rice - Books

25.2/2000
International Rice Research Notes
August 2000
International Rice Research Institute
IRRI home page: http://www.cgiar.org/irri
Riceweb: http://www.riceweb.org
Riceworld: http://www.riceworld.org
IRRI Library: http://ricelib.irri.cgiar.org
IRRN: http://www.cgiar.org/irri/irrn.htm
Copyright International Rice Research Institute 2000
The International Rice Research Notes (IRRN) expedites communication among scientists concerned with the development of improved
technology for rice and rice-based systems. The IRRN is a mechanism to help scientists keep each other informed of current rice research
findings. The concise scientific notes are meant to encourage rice scientists to communicate with one another to obtain details on the
research reported. The IRRN is published three times a year in April, August, and December by the International Rice Research Institute.
Contents
4
MINI REVIEW
Bt rice: practical steps to sustainable
use
M.B. Cohen, F. Gould, and J.S. Bentur
Plant breeding
11 Differentiation of rice varieties cultivated in
Yunnan, China, using PCR markers corresponding to conserved motifs of disease resistance
genes
Z.H. Wang, E.S. Borromeo, P. Teng, H. Leung,
and Y.Y. Zhu
13 Genetic variability in photosynthesis and chlorophyll content of various landraces of upland rice
R.K. Agnihotri, S. Chandra, S. Sharma, and
L.M.S. Palni
15 Inheritance of aroma in four rice cultivars
(Oryza sativa L.)
Y.J. Dong, E. Tsuzuki, and H. Terao
Genetic resources
16 Variation in RFLP markers associated with rootgrowth QTLs in Indian upland rice
K.A. Steele, B.J. Moore, J.R. Witcombe, D.S. Virk, and
A.H. Price
17 Evaluation of in situ conservation of Oryza
rufipogon populations using RAPD markers
Z.-W. Xie, S. Ge, K.-Q. Wang, D.-Y. Hong, and
B.R. Lu
19 Identification of genomic constitution of three
tetraploid Oryza species through two-probe
genomic in situ hybridization
C.B. Li, D.M. Zhang, S. Ge, D.Y. Hong, and B.R. Lu
22 Collection and evaluation of hill germplasm
from Karbi Anglong and North Cachar Hill
districts of Assam, India
A. Roy and K. Das
23 WEB NOTES
2
August 2000
Pest science & management
24 Improvement of conjugation methods for
Xanthomonas oryzae pv. oryzae strain DY89031
to identify avrXa21 clones
P.K. Sharma, F.G. da Silva, Y. Shen, and P.C. Ronald
Soil, nutrient, & water management
25 Comparing management techniques to optimize
30 Efficiency of controlled-release urea and coated
fertilizer N application in rice in the Cauvery Delta
of Tamil Nadu, India
urea fertilizers in irrigated transplanted rice
in Andhra Pradesh, India
P. Stalin, T.M. Thiyagarajan, S. Ramanathan, and
M. Subramanian
K. Padmaja, R.M. Kumar, S.P. Singh, A.G.K. Murthy,
and S.V. Subbaiah
27 Optimizing chlorophyll meter threshold values for
different seasons and varieties in irrigated
lowland rice systems of the Cauvery Delta zone,
Tamil Nadu, India
M. Babu, R. Nagarajan, S.P. Ramanathan, and
V. Balasubramanian
32 Varietal response to different nitrogen
management methods in irrigated transplanted
rice ecosystem in a Vertisol, Andhra Pradesh, India
R.M. Kumar, K. Padmaja, S.V. Subbaiah, and
V. Balasubramanian
34 Assessment of chlorophyll meter-based N
28 On-farm evaluation of chlorophyll meter-based
N management in irrigated transplanted rice
in the Cauvery Delta, Tamil Nadu, India
M. Babu and R. Nagarajan, S. Mohandass,
C. Susheela, P. Muthukrishnan,
M. Subramanian, and V. Balasubramanian
application at critical growth stages of irrigated
transplanted rice
S.P. Ramanathan, R. Nagarajan, and
V. Balasubramanian
35 Chlorophyll meter threshold values for N management in wet direct-seeded irrigated rice
V. Balasubramanian, A.C. Morales, and R.T. Cruz
Crop management & physiology
38 Chlorophyll stability index (CSI): its impact on
39 Exogenous glycinebetaine reduces sodium
salt tolerance in rice
accumulation in salt-stressed rice plants
M. Madhan Mohan, S. Lakshmi Narayanan,
and S.M. Ibrahim
S. Lutts
Socioeconomics
41 Partnership in agricultural extension
G.P. Ojha
42 NEWS
44 RESEARCH HIGHLIGHTS
43 NOTES FROM THE FIELD
47 INSTRUCTIONS TO CONTRIBUTORS
About the cover
Background: healthy panicle (right) and
whitehead (left). Foreground: live yellow
stem borer larva in nontransgenic rice
(left) and dead larva in Bt rice (right).
Cover photos: Joachim Wünn (panicles),
Behzad Ghareyazie (larvae).
IRRN 25.2
Editorial Board
Michael Cohen (pest science and management),
Editor-in-Chief
Zhikang Li (plant breeding; molecular and cell
biology)
David Dawe (socioeconomics; agricultural
engineering)
Bas Bouman (soil, nutrient, and water
management; environment)
Bao-Rong Lu (genetic resources)
Shaobing Peng (crop management and
physiology)
Production Team
Katherine Lopez, Managing Editor
Editorial
Bill Hardy and Tess Rola
Design and layout
CPS design team, Grant Leceta,
and Arleen Rivera
Artwork
Grant Leceta, Juan Lazaro
Word processing
Arleen Rivera
3
MINI REVIEW
Bt rice: practical steps to
sustainable use
M.B. Cohen, Entomology and Plant Pathology Division, IRRI; F. Gould, Department of Entomology, North Carolina
State University, Raleigh, NC 27695-7634, USA; and J.S. Bentur, Department of Entomology, Directorate of Rice
Research, Rajendranagar, Hyderabad 500030, India
E-mail: [email protected]
Introduction
n 1996, maize, cotton, and potato farmers in the USA became the first farmers in the world to grow transgenic
insect-resistant cultivars. These cultivars contain genes from the bacterium Bacillus thuringiensis (Bt) that
encode insecticidal proteins known as delta-endotoxins. Delta-endotoxins have two properties that are essential
for toxins used in transgenic crops: they are highly toxic to certain insect pests, and they are generally safe for
human consumption (NRC 2000). Bt crops have been a large commercial success. In 1999, 11.7 million ha of Bt
crops were grown by farmers in 10 countries, including Australia, Canada, China, South Africa, Spain, and the USA
(James 1999).
Many laboratories around the world have transformed rice with Bt genes and have evaluated their effectiveness under greenhouse conditions (e.g., Cheng et al 1998, Datta et al 1998, Maqbool et al 1998). No Bt rice
varieties have yet been released to farmers, but field testing began at two sites in China in 1998 (Datta 1999, Ye et
al 2000). The target pests for control by Bt rice are caterpillars, most importantly the yellow stem borer (YSB,
Scirpophaga incertulas), the striped stem borer (SSB, Chilo suppressalis), and leaffolders such as Cnaphalocrocis
medinalis. It has not been possible to produce rice with high resistance to these pests through conventional
breeding, although short-duration semidwarf varieties are generally less damaged by stem borers than are traditional varieties (Khan et al 1991).
I
4
August 2000
The “high-dose/refuge” resistance management
strategy
Over the past 10 years, scientists, government regulators, environmentalists, and the private sector have vigorously debated if
and how the evolution of pest resistance to Bt crops can be delayed (e.g., Mellon and Rissler 1998, Gould 1998). There is widespread agreement that one strategy—the “high-dose/refuge” strategy—is the most promising and practical approach to prolonging the effectiveness of Bt crops. The high-dose/refuge strategy
is being enforced for Bt cotton, maize, and potato in the USA
(EPA-USDA 1999), Bt maize in Canada (CFIA 1999), and Bt cotton in Australia (ACGRA-TIMS 1997).
To understand how the high-dose/refuge strategy works,
it is necessary to examine the genetic basis of resistance. In many
cases, resistance to an insecticide is caused by a mutation in one
gene of an insect. If there are two possible forms of the gene
(alleles), i.e., R (the mutant allele, conferring resistance) and S
(the normal allele, conferring susceptibility), and each insect has
two copies of the gene, then there are three possible genetic
types (genotypes) of insects: SS, RS, and RR. Figure 1 illustrates
the response of each genotype to increasing concentrations of
an insecticide. In this example, the response of RS insects to the
insecticide is intermediate between that of the SS and RR insects,
but is more similar to that of the SS insects, indicating that the R
allele is partially recessive [as it is in many cases of resistance to
Bt toxins (Frutos et al 1999)]. To implement the high-dose/refuge
strategy, it is necessary to have a titer of toxin in the Bt cultivar
1
Note that the word “resistance” is used in two ways, which can sometimes be confusing. Cultivars
can be produced that have “resistance” to insects; and insects can evolve “resistance” to insecticides,
such as Bt toxins in transgenic plants.
IRRN 25.2
that is high enough to kill almost all of the RS insects (indicated
by the dotted line in Figure 1).
“Refuges” are non-Bt crop plants that serve to maintain Btsusceptible insects in the population. Refuges can consist of fields
planted with non-Bt plants or of non-Bt plants within fields of Bt
plants. The large number of insects with the SS genotype that
survive on the refuge plants are then available to mate with the
small number of RR insects that survive on the Bt plants (Fig. 2).
The offspring of SS × RR matings will be RS, and therefore will
not survive when they feed on high-dose Bt plants.
It might seem that a high dose of toxin in Bt cultivars would
accelerate the evolution of pest resistance rather than delay it.
The output of a simple population genetics model, however,
shows that if refuges are maintained, high-dose plants are more
durable than low-dose plants (Fig. 3).
Which spatial arrangement of refuge plants is best depends
on the biology of the pest. Mixtures of Bt and non-Bt plants within
fields can be established by sowing seed mixtures or by planting
rows of refuge plants within fields of Bt plants. Within-field mixtures are not the best type of refuge for insects that move between plants during development. This is because some of the
insects will feed on Bt and non-Bt plants, thereby “diluting” the
high-dose titer in Bt plants (Gould 1998). Most larvae of YSB and
SSB move between plants during development (Cohen et al 2000).
If separate refuge fields are established, then Bt fields must
not be too far from a refuge field, or else there might not be
random mating between the RR and SS insect genotypes. Therefore, it is important to know approximately how far the adult
pest insects will move before mating. This question is being studied at IRRI for YSB and SSB (A.M. Dirie, N.L. Cuong, F. Gould,
and M.B. Cohen, unpubl.). Based on our current knowledge of
YSB and SSB biology, it appears that maintaining separate refuge
fields within 1 km of Bt rice fields would be a suitable form of
refuge.
SS
% mortality
Genetic engineering with Bt genes is a powerful technology for protecting crops against some kinds of insects. Bt cultivars, however, have the same weakness as many other insect
control technologies: insects can evolve resistance to them,
thereby eliminating their effectiveness.1 Insects have evolved
resistance to all classes of widely used insecticides, including Bt
products that are applied as sprays (Frutos et al 1999). Insects
have also adapted to numerous resistant crop varieties produced
through conventional breeding. Notable examples in rice include
the brown planthopper, Nilaparvata lugens (Heinrichs 1986),
and the Asian rice gall midge, Orseolia oryzae (Bennett et al 2000).
The problem of insect adaptation to insecticides and resistant cultivars results in substantial costs to society, as crop failures, environmental damage, and loss of useful products. This
has stimulated extensive research on the genetic and biochemical basis of resistance, and the development of “resistance management” strategies that can extend the effectiveness of insecticides and cultivars. In this review, we describe some practical
steps that can be taken to delay the evolution of pest resistance
to Bt rice.
RR
RS
Log toxin concentration
Fig. 1. Dose-response lines indicating the mortality of three insect
genotypes at increasing concentrations of an insecticidal toxin. The
dotted line indicates the concentration required for a “high dose.” S,
allele conferring susceptibility; R, allele conferring resistance.
5
Almost all RR moths
mate with SS moths.
×
RR
SS
Very few moths
emerge. Almost all
are RR.
Many moths emerge.
Almost all are SS
(a few are RS).
All offspring are RS,
which will be killed by
high-dose plants.
Bt rice field
Non-Bt rice field
Fig. 2. How the high-dose/refuge strategy works to delay the increase in highly resistant (RR) insects in a pest population.
Frequency of R allele
A. Low-dose plants
B. High-dose plants
1.0
1.0
0.8
0.8
Without refuge
With 10% refuge
0.6
0.6
0.4
0.4
0.2
0.2
0
0
0
10
20
30
40
50
0
10
20
30
40
50
Generations after release of Bt cultivar
Fig. 3. Rate of evolution of pest resistance to Bt plants under various conditions, as simulated by a population genetics model. Settings of model
parameters are as follows: Both low-dose (panel A) and high-dose (panel B) plants kill 100% of the SS insects and 0% of the RR insects. On lowdose plants, 5% of the RS insects survive to maturity; while on high-dose plants, only 0.5% of the RS insects survive. The initial frequency of the
R allele is 10–3.
The model output indicates that if the low-dose cultivar is grown in 90% of the crop fields and the remaining fields serve as a non-Bt refuge,
resistance to the Bt toxin evolves in about 15 pest generations. Under the same conditions, the high-dose cultivar remains effective for about
45 pest generations. If no refuge is maintained, resistance evolves in less than five generations on both cultivars. In tropical irrigated areas,
there are approximately six generations of rice stem borers per year.
How can “high-dose” plants be identified?
When plants are transformed, transgenes become incorporated
into plant chromosomes at random locations. For this and other
reasons, there is great variability among independent transgenic
lines in the level of transgene expression. Because toxin titers
6
can differ substantially among plant lines that are transformed
with the same Bt gene construct (e.g., Cheng et al 1998, Datta et
al 1998, Maqbool et al 1998), many transformed lines must be
screened to identify a few that produce adequate quantities of Bt
toxin and do not have agronomic problems such as stunted growth.
August 2000
Dose-response data. Plants have a “high dose” of toxin
when they are able to kill almost all insects of the RS genotype
(Fig. 1). To make practical use of this definition, a resistant colony
of the pest must be available so that RS insects can be tested.
Unfortunately, Bt-resistant colonies of YSB or SSB have not been
developed. A high dose has also been defined as one that is 25X
higher than that required to kill 99% of homozygous susceptible
insects (EPA 1998). To make practical use of this definition, it is
necessary to have an accurate estimate of the LD99, determined
from dose-response experiments using purified Bt toxin. No rigorous estimates of the LD99 for Bt toxins against YSB or SSB have
been published. We have not been able to obtain reliable estimates of LD50 or LD99 values at IRRI due to very high variability
between experiments (R. Aguda, F. Gould, and M.B. Cohen,
unpubl.).
Plant bioassays. Another way to determine if a Bt rice line
has a high dose of toxin is to test it against a large number of
stem borer larvae and verify that very few insects survive to
maturity. A large number of test larvae is necessary because RR
insects are likely to be rare. A study of the tobacco budworm in
the USA found that the frequency of an allele conferring high
resistance to Cry1Ab and other Bt toxins was 1.5 × 10–3 (Gould et
al 1997). A population of YSB in the Philippines was found to
have a frequency of alleles conferring high resistance to Cry1Ab
of less than 3.6 × 10–3, with 95% confidence (Bentur et al 2000).
If the frequency of an allele for Bt resistance in a pest population
is 10–3 (meaning that 1 out of 1,000 copies of the resistance gene
has the R allele), then the frequency of RR insects of the population would be 10–6. If such a population were in Hardy-Weinberg
equilibrium, then the frequency of RS insects would be approximately 2 × 10–3 and that of SS insects would be about 0.998. On a
high-dose Bt cultivar that killed all of the SS insects, 99.5% of the
RS insects, and none of the RR insects, only about 10 out of 1
million insects would survive to maturity!
Typically, greenhouse evaluations of Bt rice lines use only
a few dozen or perhaps a few hundred larvae. With these small
numbers of test insects, even plants with a very low dose of toxin
will probably kill 100% of test insects, almost all of which will be
of the SS genotype. Thus, 100% larval mortality in a typical
greenhouse bioassay does not indicate that the Bt line has a
high dose of toxin, as defined in terms of the high-dose/refuge strategy.
What about field evaluations of Bt rice plants? Imagine a
100-m2 test plot of Bt rice, transplanted at 20 × 20 cm spacing,
and one seedling per hill. Such a field would contain 2,500 plants.
If every plant were artificially infested with one stem borer egg
mass at vegetative stage, and a second egg mass at booting stage,
and each egg mass contained 100 eggs, and there were no natural
infestation, then there would be 500,000 larvae in the plot during the growing season. If the plant killed all of the SS insects,
99.5% of the RS insects, and none of the RR insects, and there
were no mortality caused by natural enemies or other non-Bt factors, then about 5 insects would survive to maturity. This would
result in about 10 deadhearts or whiteheads in the entire plot. If
there were 10 panicles per plant, this would be equivalent to a
damage level of about 0.04% whiteheads. Calculations such as
these should be made when researchers evaluate the performance
of Bt rice in field tests.
Quantification of toxin titer. Comparisons with commercially released Bt cotton, maize, and potato cultivars can provide
guidance on what is a high-toxin titer dose in Bt rice. Three released cultivars in the USA are considered to have a high dose of
toxin against all target pests, based on extensive experimental
evaluation and experience in farmers’ fields (see table). The toxin
titer in these cultivars ranges from 1 to 11 µg g-1 of leaf fresh
weight or 0.1% to 0.2% of soluble leaf protein.
A Bt toxin titer of 0.2% of soluble leaf protein is well within
reach of what can be achieved with rice (e.g., Cheng et al 1998,
Characteristics of commercially available Bt cultivars.
Approximate maximum toxin titer
Crop
Potato
Cotton
Maize
Maize
Maize
Transformation event
(company)
Bt toxin
µg g–1 leaf fresh
weightb
Principal target pests
% soluble leaf
protein
nac
(Monsanto)
Events 531 and 931
(Monsanto)
Cry3A
na
0.1–0.2d
Cry1Ac
1–2
Event Bt11
(Novartis)
Event MON810
(Monsanto)
Event 176
(Novartis, Mycogen)
Cry1Ab
Does the event have a
high dose?a
Colorado potato beetle
Yes
na
Cotton bollworm
Tobacco budworm
Pink bollworm
No
Yes
Yes
3
na
European corn borer
Yes
Cry1Ab
5–11
na
European corn borer
Yes
Cry1Ab
4
European corn borer
Vegetative stage: yes
Reproductive stage: no
0.2e
a
Gould 1998, Mellon and Rissler 1998. bUS Environmental Protection Agency fact sheets (http://www.epa.gov/pesticides/biopesticides/). cna = not available. dFeldman and Stone 1997.
Koziel et al 1993.
e
IRRN 25.2
7
Datta et al 1998, Maqbool et al 1998). This toxin titer could be
considered as a guideline for the minimum titer for high-dose Bt
rice plants. For successful resistance management, it must also
be demonstrated that the high-toxin titer is maintained over the
entire period of pest attack. Toxin titer declines substantially at
reproductive stage in a maize line (Mellon and Rissler 1998) and
a rice line (Alinia et al 2000) with a cry1Ab gene under control of
the PEP C promoter. Toxin decline at later stages of plant growth
has also been observed under some environmental conditions
for Bt cotton with the CaMV 35S promoter (Fitt et al 1998).
How can refuges be maintained?
Farmers growing Bt crops in the USA must plant 4–20% of their
land to non-Bt cultivars, and these refuge fields must be within
approximately 0.8 km of their Bt fields (EPA-USDA 1999). Obviously, enforcing a similar system for small rice farmers will not be
possible in most parts of Asia. This does not mean, however, that
a functional high-dose/refuge strategy cannot be achieved for Bt
rice. In a typical village, it is unlikely that all farmers will plant Bt
rice on all their land. Bt genes will be one of many factors that
farmers will consider when choosing which rice varieties to grow.
Governments can promote the maintenance of refuges by
restricting the number and diversity of Bt cultivars that can be
released. For example, in the Indian state of Punjab, farmers grow
traditional Basmati varieties and modern semidwarf varieties.
Stem borer damage is higher in Basmati varieties, and thus the
government could authorize the release of Bt-transformed
Basmati varieties but not Bt-transformed semidwarfs.
Because of the great importance of maintaining refuges,
governments should also consider implementing a refuge system where this would be practical. Examples include large ricegrowing estates or collectives, villages with well-organized farmers’ organizations, and areas with strong extension services.
The concern is often raised that stem borer damage in nonBt fields will increase after introducing Bt rice. The implication is
that farmers will be even less likely to grow non-Bt rice because
of the increased damage, and therefore there will be even fewer
refuge fields. In fact, after the introduction of Bt rice, the level of
stem borer damage in non-Bt rice fields will probably be unchanged or will decline. Moths do not prefer to lay their eggs on
non-Bt plants (Riggin-Bucci and Gould 1997, Hellmich et al 1999),
and there is no evidence that moths can detect whether or not a
plant contains Bt toxin. In some studies, it has been found that,
after feeding begins, caterpillars move away from Bt plants faster
than from non-Bt plants (e.g., Dirie et al 2000), but very few rice
stem borer larvae crawl far enough to move from one field to
another (Cohen et al 2000).
Stem borer moths are good fliers and are well capable of
moving from one field to another (Khan et al 1991; A. Dirie, F.
Gould, and M.B. Cohen, unpubl.). Many of the moths that emerge
from fields of non-Bt rice will disperse and lay their eggs in fields
of Bt rice. In contrast, because very few moths will emerge from
8
Bt fields, very few moths will move from Bt fields to non-Bt fields.
As a consequence, the amount of stem borer damage in non-Bt
fields may decline if most fields are planted to Bt rice. This decline in damage in refuge fields, called the halo effect, has been
observed in experiments with the diamondback moth on Bt collards (Riggin-Bucci and Gould 1997) and the European corn borer
on Bt maize (Andow and Hutchinson 1998).
The importance of two-toxin Bt rice
Another practical step that governments can take to promote the
sustainable use of Bt rice is to release Bt cultivars only if they
contain two Bt toxins, both at a high dose. If insects that are able
to survive on a plant with one high-dose toxin are rare, then insects that are able to survive on plants with two high-dose toxins
will be very rare indeed. If such insects must be homozygous for
resistance alleles for two different genes, and if the frequency of
the allele for resistance of each gene is 10–3, then insects of the
genotype R1R1R2R2 will occur at a frequency of only 10–12, i.e., 1
out of 1 trillion. Because such insects will be very rare, fewer susceptible insects will be needed to ensure that resistant insects do
not mate with each other. Therefore, fewer refuge fields will be
necessary (although it is still very important to have some refuge
fields).
More than 100 Bt toxin genes have been cloned and sequenced; the toxins are highly divergent in amino acid sequence
and some biochemical properties (Frutos et al 1999). Any two Bt
toxins that are used in combination must not be too similar to
each other, otherwise, a single mutation could confer “cross-resistance” to both toxins. In most cases that have been studied,
insect resistance to Bt toxins is caused by mutations in receptor
proteins in the insect gut (Frutos et al 1999). Toxins must bind to
receptors to initiate the process that will ultimately kill the insect, and mutations in receptors can eliminate toxin binding.
Biochemical tests can determine whether two Bt toxins bind to
the same receptor, and thus whether one mutation might disrupt the effectiveness of both toxins. Based on studies done by
Fiuza et al (1996) and Lee et al (1997), it is known that the following are good toxin combinations for both YSB and SSB: Cry1Aa
or Cry1Ac with Cry1C or Cry2A. Both studies also found that
Cry1Aa and Cry1Ac should not be used in combination. Recently,
it has been found that Cry1Ab with Cry1Ac would not be a good
combination for either YSB or SSB, but that Cry1Ab with Cry1C
or Cry2A would be effective (E. Alcantara, R. Aguda, D. Dean, and
M.B. Cohen, unpubl.).
Cotton producing the Cry1Ac and Cry2A toxins has been
produced by Monsanto and approved for field testing by the US
Environmental Protection Agency (http://www.epa.gov/
oppbppd1/biopesticides/reg_activ/reg_act_all_byAI.htm).
Maqbool and Christou (1999) transformed rice with genes for
the Cry1Ac and Cry2A toxins and found several lines in which the
levels of both toxins were >0.5% of soluble leaf protein. Additional laboratories are expected to produce two-toxin Bt rice soon.
August 2000
A computer model of the evolution of Bt resistance shows that
much of the long-term utility of cultivars with two toxins can be
lost if both one- and two-toxin cultivars are grown in the same
region, or if one-toxin cultivars are widely grown prior to the release of two-toxin cultivars (F. Gould, J. Van Duyn, and G.
Kennedy, unpubl.). Therefore, it is critical to develop appropriate two-toxin cultivars and not to first deploy one-toxin cultivars.
An important long-term goal is transformation of plants with combinations of a Bt toxin gene and a gene encoding an unrelated
toxin because some insect mutations can confer cross-resistance
to multiple, distantly related Bt toxins (Frutos et al 1999).
Summary and recommendations
Four practical recommendations for promoting the sustainable
use of Bt rice can be made, based on existing knowledge of the
biology of YSB and SSB and the principles of resistance management:
1. Do not release Bt varieties that do not have a high dose
of toxin. Toxin titers of 2 µg g–1 of leaf fresh weight or
0.2% of soluble leaf protein are attainable in rice, and
have been shown to act as high doses against most pests
in other crops.
2. Release only Bt cultivars that have two Bt toxin genes.
The genes should not be closely related to each other,
and both should be expressed at a high dose. Two-toxin
cultivars require smaller refuges to achieve successful
resistance management.
3. Do not release Bt-transformed versions of all popular
rice varieties. Some popular non-Bt varieties should
remain available to improve chances that some non-Bt
rice fields (refuges) will exist. Sufficient seed supplies
of non-Bt varieties should be maintained.
4. Implement a resistance monitoring program. Several
methodologies can be used to monitor pest populations for the evolution of resistance to Bt cultivars
(Andow and Hutchinson 1998). The use of “sentinel
plots,” in which insect damage is monitored in
unsprayed fields of Bt cultivars, is perhaps the most
practical for rice-growing areas. Resistance monitoring
programs can serve as an early warning system for governments and farmers and provide valuable information for improved deployment of future pest-resistant
cultivars.
More than 20 research groups in many countries have produced Bt rice. Most of the lines produced do not meet recommendation 1, and very few lines meet recommendation 2. Scientists and governments will soon be faced with decisions of whether
to release single-toxin and/or low-dose Bt rice cultivars to farmers. Their decisions should be based on long-term as well as shortterm benefits. Many farmers would benefit from growing Bt rice,
but in most areas yield increases would be modest. Stem borers
are usually low-level, chronic pests. Based on an extensive survey
IRRN 25.2
of farmers’ fields in Asia, stem borers were estimated to cause an
overall mean yield loss of 2.4% (Savary et al 2000). In areas where
stem borers are not an urgent problem, it would seem sensible
to delay the release of Bt rice until a two-toxin, high-dose cultivar
is available. In areas where stem borer damage is high, it must be
realized that low-dose and/or single-toxin cultivars might not remain effective for very long.
There are currently no proven alternatives to Bt toxins for
use in transgenic plants to control caterpillar pests. Clearly, Bt
toxins are a valuable natural resource that must be used with great
care.
References
ACGRA-TIMS (Australian Cotton Growers’ Research Association—Transgenic
and Insect Management Strategy Committee). 1997. Insect
management plan for InGard Cotton, 1997-98. Wee Waa, Australia:
ACGRA (Online: http://www.mv.pi.csiro.au/publicat/pest/
ingres97.htm)
Alinia F, Ghareyazie B, Rubia LG, Bennett J, Cohen MB. 2000. Effect of plant
age, larval age, and fertilizer treatment on resistance of a cry1Abtransformed aromatic rice to lepidopterous stem borers and foliage
feeders. J. Econ. Entomol. 93:484–493.
Andow DA, Hutchinson WD. 1998. Bt-corn resistance management. In:
Mellon M, Rissler J, editors. Now or never: serious new plans to save a
natural pest control. Cambridge, MA.: Union of Concerned Scientists. p
19–66.
Bennett J, Bentur JS, Pasalu IC, Krishnaiah K, editors. 2000. New approaches
to gall midge resistance in rice. Makati City (Philippines): International
Rice Research Institute.
Bentur JS, Andow DA, Cohen MB, Romena AM, Gould F. 2000. Frequency of
alleles conferring resistance to a Bacillus thuringiensis toxin in a
Philippine population of a rice stem borer, Scirpophaga incertulas
(Lepidoptera: Pyralidae). J. Econ. Entomol. (in press)
CFIA (Canadian Food Inspection Agency). 1999. Responsible deployment of
Bt corn technology in Ontario. Nepean, Ontario, Canada: CFIA.
(Online: http://www/cfia-acia.agr.ca/english/plaveg/pbo/old/
btweb2_e.shtml)
Cheng X, Sardana R, Kaplan H, Altosaar I. 1998. Agrobacterium-transformed
rice plants expressing synthetic cryIA(b) and cryIA(c) genes are highly
toxic to striped stem borer and yellow stem borer. Proc. Natl. Acad. Sci.
USA 95:2767–2772.
Cohen MB, Romena AM, Gould F. 2000. Dispersal by larvae of the stem
borers Scirpophaga incertulas (Lepidoptera: Pyralidae) and Chilo
suppressalis (Lepidoptera: Crambidae) in plots of transplanted rice.
Environ. Entomol. (in press)
Datta K, Vasquez A, Tu J, Torrizo L, Alam MF, Oliva N, Abrigo E, Khush GS,
Datta SK. 1998. Constitutive and tissue-specific differential expression
of the cry1Ab gene in transgenic rice plants conferring resistance to rice
insect pest. Theor. Appl. Genet. 97:20–30.
Datta SK. 1999. Transgenic rice products: roadmap for future impact.
Abstracts, General Meeting of the International Program on Rice
Biotechnology, 20-24 Sep 1999, Phuket, Thailand. NY: Rockefeller
Foundation. p 125.
Dirie AM, Cohen MB, Gould F. 2000. Larval dispersal and survival of two stem
borer (Lepidoptera: Crambidae) species on cry1Ab-transformed and
non-transgenic rice. Environ. Entomol. (in press)
EPA (US Environmental Protection Agency). 1998. FIFRA Scientific Advisory
Panel. Subpanel on Bacillus thuringiensis (Bt) plant-pesticides and
resistance management. Washington, D.C.: EPA. (Online: http://
www.epa.gov/scipoly/sap/1998/february/finalfeb.pdf)
9
EPA-USDA (US Environmental Protection Agency, US Department of
Agriculture). 1999. EPA and USDA position paper on insect resistance
management in Bt crops. Washington, D.C.: EPA. (Online: http://
www.epa.gov/oppbppd1/biopesticides/otherdocs/
bt_position_paper_618.htm)
Feldman J, Stone T. 1997. The development of a comprehensive resistance
management plan for potatoes expressing the Cry3A endotoxin. In:
Carozzi N, Koziel M, editors. Advances in insect control: the role of
transgenic plants. London: Taylor & Francis. p 49–61.
Fitt GP, Daly JC, Mares CL, Olsen K. 1998. Changing efficacy of transgenic Bt
cotton—patterns and consequences. In: Zalucki MP, Drew RAI, White
GG, editors. Proceedings of the 6th Australian Applied Entomology
Conference, Brisbane, 29 Sep–2 Oct. Vol. 1. Brisbane: University of
Queensland. p 189–196.
Fiuza L-M, Nielsen-Leroux C, Gozè E, Frutos R, Charles J-F. 1996. Binding of
Bacillus thuringiensis Cry1 toxins to the midgut brush border
membrane vesicles of Chilo suppressalis (Lepidoptera: Pyralidae):
evidence of shared binding sites. Appl. Environ. Microbiol. 62:1544–
1549.
Frutos R, Rang C, Royer M. 1999. Managing insect resistance to plants
producing Bacillus thuringiensis toxins. Crit. Rev. Biotechnol. 19:227276.
Gould FA, Anderson A, Jones D, Sumerford D, Heckel G, Lopez J, Micinski S,
Leanard R, Laster M. 1997. Initial frequency of alleles for resistance to
Bacillus thuringiensis toxins in field populations of Heliothis virescens.
Proc. Natl. Acad. Sci. USA 94:3519–3523.
Gould F. 1998. Sustainability of transgenic insecticidal cultivars: integrating
pest genetics and ecology. Annu. Rev. Entomol. 43:701–726.
Heinrichs EA. 1986. Perspectives and directions for the continued
development of insect-resistant rice varieties. Agric. Ecosyst. Environ.
18:9–36.
Hellmich RL, Higgins LS, Witkowski JF, Campbell FE, Lewis LC. 1999.
Oviposition by European corn borer (Lepidoptera: Crambidae) in
response to various transgenic corn events. J. Econ. Entomol. 92:1014–
1020.
James C. 1999. Global review of commercialized crops: 1999 (Preview).
ISAAA Briefs No. 12.
Khan ZR, Litsinger JA, Barrion AT, Villanueva FFD, Fernandez NJ, Taylor LD.
1991. World bibliography of rice stem borers, 1794-1990. Manila
(Philippines): International Rice Research Institute.
Koziel MG, Beland GL, Bowman C, Carozzi NB, Crenshaw R, Crossland L,
Dawson J, Desai N, Hill M, Kadwell S, Launis K, Lewis K, Maddox D,
McPherson K, Meghji MR, Merlin E, Rhodes R, Warren GW, Wright M,
Evola SV. 1993. Field performance of elite transgenic maize plants
expressing an insecticidal protein derived from Bacillus thuringiensis.
Bio/Technology 11:194–200.
Lee MK, Aguda R, Cohen MB, Gould FL, Dean DH. 1997. Determination of
receptor binding properties of Bacillus thuringiensis δ-endotoxins to
rice stem borer midguts. Appl. Environ. Microbiol. 63:1453–1459.
Maqbool SB, Husnain T, Riazuddin S, Masson L, Christou P. 1998. Effective
control of yellow stem borer and rice leaffolder in transgenic rice indica
varieties Basmati 370 and M7 using the novel δ-endotoxin cry2A
Bacillus thuringiensis gene. Mol. Breed. 4:501–507.
Maqbool SB, Christou P. 1999. Multiple traits of agronomic importance in
transgenic indica rice plants: analysis of transgene integration patterns,
expression levels and stability. Mol. Breed. 5:471–480.
Mellon M, Rissler J, editors. 1998. Now or never: serious new plans to save a
natural pest control. Cambridge, MA.: Union of Concerned Scientists.
NRC (National Research Council, USA). 2000. Genetically modified pestprotected plants: science and regulation. Washington, D.C.: National
Academy Press.
Riggin-Bucci TM, Gould F. 1997. Impact of intraplot mixtures of toxic and
non-toxic plants on population dynamics of diamondback moth
(Lepidoptera: Plutellidae) and its natural enemies. J. Econ. Entomol.
90:241–251.
Savary S, Willocquet L, Elazegui FS, Castilla NP, Teng PS. 2000. Rice pest
constraints in tropical Asia: quantification of yield losses due to rice
pests in a range of production situations. Plant Dis. 84:357–369.
Ye G-Y, Shu Q-Y, Yao H-W, Cui H-R, Cheng X-Y, Hu C, Xia Y-W, Gao M-W,
Altosaar I. 2000. Field evaluation of resistance of transgenic rice
containing a synthetic cryIAb gene from Bacillus thuringiensis Berliner
to two stem borers. J. Econ. Entomol. (in press)
About IRRI’s Library and
Documentation Service
Did you know...
1
Maximum of 50 pages per request
Web address: http://ricelib.irri.cgiar.org
Write to Carmelita Austria at this address:
Library and Documentation Service,
International Rice Research Institute,
MCPO Box 3127, Makati City 1271, Philippines.
E-mail address: [email protected]
2
3
10
...that IRRI has the world’s biggest rice library?
...that it provides a free photocopy service1 to rice
scientists everywhere?
...that its catalogue and rice bibliography are available on the World Wide Web for searching, 24
hours a day2?
...that IRRI Library staff are waiting right now to
receive your requests3?
We hope to be of service to you soon!
August 2000
Plant breeding
Differentiation of rice varieties cultivated in Yunnan,
China, using PCR markers corresponding to
conserved motifs of disease resistance genes
Z.H. Wang, E.S. Borromeo, P. Teng, H. Leung, Entomology and Plant Pathology Division, IRRI; and Y.Y. Zhu,
Yunnan Agricultural University, Kunming, China E-mail: [email protected]
Many disease resistance genes in plants are
found to have similar sequences that are
presumably involved in pathogen recognition and signal transduction. This sequence conservation offers opportunities
to develop markers that are indicative of
function. Using polymerase chain reaction
(PCR), primers can be designed to amplify
sequences that correspond to conserved
motifs of resistance genes. These PCR
markers, called resistance gene analog
(RGA) markers, have been used to characterize germplasm and breeding lines in
barley, wheat, and rice (Chen et al 1998).
This study tested this approach to
evaluate the diversity of a set of varieties
from Yunnan Province, China. RGA markers were applied to analyze 41 modern rice
varieties and landraces cultivated in Luxi
county in Yunnan and to test the minimal
number of primer combinations needed
to reveal the informative relationship
among varieties.
Rice genome DNA was extracted at
Yunnan Agricultural University using miniprep protocol (Zheng et al 1995). Molecular characterization was done at IRRI. The
PCR primers were designed based on conserved motifs of disease resistance genes:
leucine-rich repeats, nucleotide-binding
site, and kinase of a broad collection of
disease resistance genes (see table). Genomic DNA (20 ng) from each variety was
PCR-amplified using a primer pair as described by Chen et al (1998). Each 25 mL
reaction contains 50 mM KCl, 20 mM TrisHCl, 5 mM MgCl2, 0.2 mM of each dNTP,
60 ng of each primer, 20 ng template DNA,
and 1 unit of Taq. The reaction was conducted using the following conditions:
denature 5 min at 95 °C; 40 cycles of 1 min
at 94 °C, 1 min at 45 °C, 2 min at 72 °C;
IRRN 25.2
and a final extension of 7 min at 72 °C.
Amplified fragments were separated by 4%
polyacrylamide gel electrophoresis and silver-stained.
RGA banding patterns produced by
each of the five primers revealed a high
degree of intervarietal polymorphism. The
composite banding patterns generated
from all PCR primers were scored as binary
data and analyzed using NTSYS version 1.8
(Exeter Software, Setauket, New York).
Dice similarity coefficients were calculated
to generate a dendrogram. Statistical stability of the branches in the cluster was
estimated by bootstrap analysis with 2,000
replicates using the Winboot computer
program (Yap and Nelson 1996). A
consensus dendrogram based on markers
generated from five primer pairs is shown
in the figure.
Most of the branches had high bootstrap values, indicating the robustness of
the branching pattern. The consensus dendrogram divided the Yunnan varieties into
two groups corresponding to indicajaponica differentiation. With a few exceptions, modern and landrace varieties
tended to form separate groupings. Lower
bootstrap values were noted within the
landrace group, suggesting that diversity
within groups was higher among
landraces. The degree of relatedness was
higher among newly bred and released
varieties. This may reflect the common
pedigrees shared by improved varieties,
e.g., Chujing and Hexi series of varieties.
Three improved varieties—Chujing 14,
Gangyou 12, and Xianyou 22—appear to
be distinct from the others.
Primers used and the corresponding number of amplified and polymorphic bands generated.
Primera
Sequence (5′3′)b
Amplified
bands
Polymorphic
bands
XLRR for
XLRR rev
CCG TTG GAC AGG AAG GAG
CCC ATA GAC CGG ACT GTT
60
40
NLRR inv1
NLRR inv2
TGC TAC GTT CTC CGG G
TGA GGC CGT GAA AAA TAT
74
59
LM637
LM638
ARI GCT ARI GGI ARI CC
GGI GGI GTI GGI AAI ACI AC
55
43
S1
AS3
GGT GGG GTT GGG AAG ACA ACG IAG
IGC IAG IGG IAG ICC
51
36
Pto kin1
Pto kin2
GCA TTG GAA CAA GGT GAA
AGG GGG ACC ACC ACG TAG
51
38
a
The primer pairs, XLRR for and XLRR rev and NLRR inv1 and NLRR inv2 were designed based on leucine-rich repeat
regions of genes Xa21 and N (N. Naqvi, IRRI). The primer pairs LM637 and LM638 and S1 and AS3 were designed based
on the P-loop nucleotide-binding sites and LRR regions of genes RPS2, N, and L6. The primer pair Pto kin1 and Pto kin2
were designed based on the DNA sequence encoding for protein kinase in the tomato Pto gene conferring resistance to
Pseudomonas syringae pv. tomato.All primers were made by GIBCO. bCodes for mixed bases: I = isonine, R = A/G. Degenerate
primers were designed with isonine or more than one residue at the third codon position to fit the consensus amino acid
sequence.
11
69.5
37.2
63.2
90.3
38.5
38.0
25.0
20.0
Ai zhegu (Landrace)
Duodiangu (Landrace)
Laojingnuo (Landrace)
Baijiaolaojing (Landrace)
Yinggu (Landrace)
Huagu (Landrace)
Zhongyanggu (Landrace)
Yuelianggu (Landrace)
Chujing No. 14
Zhaogu (Landrace)
Hongzhaogu (Landrace)
Longshalingu (Landrace)
Yuenangu (Landrace)
Duodiangu (Landrace)
Niangduogu (Landrace)
Erlaojing (Landrace)
Mazhagu (Landrace)
Gangyou 12
Shanyou 22
260-1
260
Xianhuanuo (Landrace)
Gaoshanrenshuigu (Landrace)
Liming 251
Hexi 42
Zhangjing No. 8
Hexi 32
Hexi 39
Xinan 175
Dianyu No. 1
Chujing No. 9
Chujing No. 11
Chujing No. 3
88010-1
251 Xuan
Luxuan No. 1
1138
Hexi 24
Hexi 30
Hexi 22-2
Chujing No. 16
88.1
26.2
13.4
29.3
60.0
99.9
44.4
39.0
48.4
92.2
90.6
91.3
73.1
62.0
16.4
56.5
22.5
61.0
34.5
43.0
88.3
60.5
73.1
22.0
99.8
18.5
94.8
65.0
85.5
81.9
0.51
0.61
0.71
83.4
0.81
0.91
Coefficient
Dendrogram of 41 rice varieties based on polymorphic bands generated by five primer pairs. Numbers in branches indicate the percentage of
times the group of lines in a branch occurred, based on 2,000 cycles in bootstrap analysis using the Winboot program.
Similarity matrices generated by different combinations of primers using
MXCOMP program in NTSYS-pc were used
to determine the minimal primer combinations needed to obtain a good assessment of the genetic relationship among
rice varieties. Matrix comparison was conducted by pooling data in a stepwise manner (e.g., comparing the matrix produced
by five primer pairs with matrices from
combinations of two, three, and four
primer pairs). Matrix comparison showed
that the similarity matrix produced by
three primer pairs was correlated (0.87–
0.97) with that generated by five primer
pairs (data not shown). The result suggests
that using three primer pairs can provide
12
a quick assessment of genetic diversity.
Since RGA polymorphic markers
may reflect diversity in domains of resistance genes, observed varietal groups may
have different spectra of disease resistance.
There has been a growing interest in increasing the level of genetic diversity in
modern agricultural systems to sustain
productivity. This approach is based on the
premise that greater diversity in an
agroecosystem would provide greater buffering capacity against biotic and abiotic
stresses. The diversity information will be
used to test whether mixing varieties that
are agronomically similar but functionally
diverse in disease resistance would provide
enhanced protection against blast in the field.
References
Chen XM, Line RF, Leung H. 1998. Genome
scanning for conserved motifs of disease
resistance gene in rice, barley, and wheat by
high resolution electrophoresis. Theor.
Appl. Genet. 97:345–355.
Yap IV, Nelson RJ. 1996. Winboot: a program for
performing bootstrap analysis of binary data
to determine the confidence limits of
UPGMA-based dendrograms. IRRI Discuss.
Pap. Ser. 14.
Zheng KL, Subudi PK, Domingo J, Magpantay G,
Huang N. 1995. Rapid DNA isolation for
marker-assisted selection in rice breeding.
Rice Genet. Newsl. 12-255-258.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
August 2000
Genetic variability in photosynthesis and chlorophyll content
of various landraces of upland rice
R.K. Agnihotri, S. Chandra, S. Sharma, and L.M.S. Palni, G.B. Pant Institute of Himalayan Environment and Development,
Kosi-Katarmal, Almora 263643, India
After an extensive survey of the Kumaun
region in the Central Himalaya, 28 different landraces of upland rice were collected.
These landraces were studied for variation
in chlorophyll content and photosynthetic
rate and were compared with an
introduced high-yielding variety (VL 206)
released by the Vivekananda Hill
Agriculture Research Laboratory, Almora
(Indian Council of Agricultural Research),
for rainfed areas.
Landraces were grown in earthen
pots (30 cm diameter and 30 cm high) containing farmyard manure, sand, and soil
(1:1:1, v/v) during kharif (wet season) in
1998. Three sets of plants (15 plants per
set) per landrace were kept under similar
environmental conditions in the Institute
nursery at Kosi (1,150 m asl; geographical
coordinates 79° 38′ 10′′ E and 29° 38′ 15′′
N). Pots were irrigated to maintain soil
moisture (around 23–25%) for seed germination. No watering was done after germination and plants were kept under
rainfed conditions.
Observations were made before the
flowering stage (90 ± 5 d after seed sowing). Optimum photosynthetic activities
during this stage have been noted
(Chauhan et al 1996). The photosynthesis
rate was measured in flag leaves of three
uniform plants from each set, using a
closed portable photosynthetic system
model LI-6400 (LI-COR, USA). Measurements were carried out at 25 °C and at 800
mmol m–2 s–1 to avoid possible fluctuations
due to temperature and light variations.
The chlorophyll contents (chlorophyll a &
b and total) of the flag leaves of various
landraces were estimated following the
method of Holm (1954).
Photosynthesis, stomatal conductance, and chlorophyll content of various landraces of rice (±SD).
Landrace/
introduced
variety
Landraces
Anjani
Bauran
Bauriya
Bindudhan
Chhatuli
Chhotiya
Dalbadal
Danbasmati
Dehradoonibasmati
Dudhikapkoti
Dutiau
Jhungia
Kaladur
Kaunkaun
Khudinandhani
Kururhidhan
Laldhan
Nandhani
Nauli
Patoli
Sabhawati
Sailani
Santoli
Saunji
Saurajubawan
Syaudhan
Taichin
Tilansi
Introduced variety
VL 206
IRRN 25.2
Net
photosynthesis
(mmol m–2 s–1)
Stomatal
conductance
(mmol m–2 s–1)
Chlorophyll (mg g–1)
a
b
Total
2.21 ± 0.12
4.70 ± 0.50
4.80 ± 0.03
2.53 ± 0.57
2.61 ± 0.47
2.27 ± 0.15
3.12 ± 0.50
3.35 ± 0.46
2.60 ± 0.41
3.76 ± 0.44
2.44 ± 0.38
2.46 ± 0.36
2.60 ± 0.55
2.30 ± 0.24
2.26 ± 0.08
2.73 ± 0.70
4.58 ± 0.39
2.42 ± 0.47
5.37 ± 0.45
4.15 ± 0.41
3.18 ± 0.41
5.27 ± 0.28
2.36 ± 0.12
3.64 ± 0.44
8.10 ± 0.58
6.30 ± 0.40
9.45 ± 0.44
2.29 ± 0.45
34.80 ± 3.91
127.20 ±12.60
73.50 ± 1.26
5.30 ± 5.80
53.91 ± 2.76
32.60 ± 2.30
67.70 ± 4.00
66.70 ± 1.30
56.71 ± 3.50
72.70 ± 5.48
50.20 ± 2.81
63.11 ± 2.82
88.81 ± 4.94
45.20 ± 2.87
43.40 ± 2.00
65.60 ± 2.98
116.00 ± 2.34
53.00 ± 2.60
122.80 ± 4.10
78.00 ± 1.80
59.81 ± 2.61
136.80 ±10.70
68.51 ± 5.01
116.50 ± 8.03
122.00 ± 6.07
149.00 ±10.46
230.50 ±13.90
71.10 ± 4.90
0.591 ± 0.062
0.662 ± 0.194
0.707 ± 0.174
0.338 ± 0.046
0.614 ± 0.151
0.504 ± 0.143
0.826 ± 0.202
0.879 ± 0.153
0.583 ± 0.061
0.702 ± 0.030
0.336 ± 0.057
0.913 ± 0.145
0.850 ± 0.024
1.060 ± 0.279
0.683 ± 0.050
0.500 ± 0.120
0.549 ± 0.107
0.638 ± 0.258
1.264 ± 0.040
0.878 ± 0.068
0.640 ± 0.078
0.896 ± 0.115
0.840 ± 0.103
0.502 ± 0.178
1.133 ± 0.110
0.678 ± 0.091
1.325 ± 0.123
0.731 ± 0.108
0.253 ± 0.030
0.259 ± 0.061
0.324 ± 0.067
0.146 ± 0.146
0.234 ± 0.051
0.217 ± 0.057
0.313 ± 0.075
0.339 ± 0.054
0.256 ± 0.015
0.136 ± 0.018
0.140 ± 0.012
0.452 ± 0.063
0.411 ± 0.031
0.400 ± 0.095
0.282 ± 0.007
0.208 ± 0.045
0.229 ± 0.044
0.173 ± 0.200
0.281 ± 0.031
0.189 ± 0.025
0.352 ± 0.065
0.242 ± 0.045
0.254 ± 0.086
0.214 ± 0.060
0.212 ± 0.031
0.335 ± 0.032
0.231 ± 0.056
0.314 ± 0.056
0.843 ± 0.090
0.922 ± 0.255
1.031 ± 0.240
0.484 ± 0.066
0.848 ± 0.202
0.723 ± 0.199
1.139 ± 0.277
1.218 ± 0.207
0.839 ± 0.062
0.838 ± 0.049
0.476 ± 0.070
1.365 ± 0.202
1.261 ± 0.044
1.460 ± 0.374
0.965 ± 0.058
0.708 ± 0.165
0.778 ± 0.152
0.811 ± 0.112
1.545 ± 0.070
1.061 ± 0.138
1.082 ± 0.064
1.138 ± 0.161
1.095 ± 0.173
0.716 ± 0.238
1.320 ± 0.142
1.014 ± 0.119
1.556 ± 0.179
1.046 ± 0.165
7.22 ± 0.90
161.10 ± 2.34
0.836 ± 0.154
0.384 ± 0.137
1.220 ± 0.275
13
Data on photosynthesis (see table)
reveal that various landraces differed significantly in photosynthetic rates (CO2
uptake ranged from 2.21 to 9.45 mmol
m–2 s–1) and stomatal conductance (between 34.8 and 230.5 mmol m–2 s–1). The
leaf chlorophyll content also showed significant variation among different
landraces: chlorophyll a = 0.336–1.325,
chlorophyll b = 0.136–0.452, and total
chlorophyll = 0.476–1.556 mg g–1 of fresh
weight.
Several landraces (18% of total) exhibited high photosynthetic rate (CO2 uptake >5 mmol m–2 s–1). Total chlorophyll
content was also greater (1.338–1.556 mg
g –1 ) in these landraces; 32% of the
landraces could be placed in an
intermediate group for which CO2 uptake
ranged between 3 and 5 mmol m–2 s–1. For
this intermediate group, total chlorophyll
content ranged from 0.716 to 1.218 mg
g –1. Half of the landraces showed low
photosynthesis (CO2 uptake <3 mmol
m –2 s –1). A similar trend was seen for
stomatal conductance in the landraces.
Introduced variety VL 206 exhibited physiological characteristics (photosynthesis,
stomatal conductance, and chlorophyll
content) similar to those of landraces with
high photosynthesis.
The rate of photosynthetic CO2 uptake is an important component of plant
growth (Leding and Botkin 1974). Our results indicate a positive correlation of net
photosynthesis with stomatal conductance
(P<0.01) and chlorophyll content
(P<0.02). These characteristics can thus
be used for the primary selection of appropriate landraces for a particular environment. Further, these landraces can
serve as donors of genes for introgressing
from landraces with high photosynthesis
to those with low photosynthesis through
suitable genetic approaches.
Acknowledgments
We acknowledge the financial assistance
from the International Development Research Centre (IDRC) for the Agricultural
Diversity Project.
References
Chauhan JS, Singh CV, Singh RK, Chauhan VS,
Tomar RK. 1996. Physiological
characteristics of some rainfed upland rice
cultivar. Oryza 33:103–106.
Holm G. 1954. Chlorophyll mutation in barley.
Acta Agric. 3:457.
Leding FT, Botkin DB. 1974. Photosynthetic CO2
uptake and distribution of photosynthate as
related to growth of large hemlock seedling.
Can. J. Bot. 47:519–527.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Digital Literacy for Rice Scientists
To help rice scientists take advantage of new information and communication technologies, the IRRI Training
Center has developed the Digital Literacy Course for Rice Scientists. The course aims to provide scientists with
information about what resources are available on the Internet and how they can go about accessing these resources.
The course is unique in that it focuses on the needs of rice scientists, it provides a forum for rice scientists to
share their experiences and Internet resources with other rice scientists online, and it establishes a learner-centered
knowledge network in the form of an online community centered on rice research.
The topics covered by the course include
• What is the Internet
• What is the World Wide Web and what makes it
work
• Key Internet terminology
• How to use the Internet for communication with
other scientists
• How to use Web browsers
• How to search for information efficiently and
effectively
• What are some of the good sources of information
for rice scientists available on the Internet
• How to cite Internet documents
• What training opportunities are available online
Connection to the Internet offers national scientists a
low-cost communication medium with other scientists linked
to the Internet, gives them access to the ever-growing body
of information available on and through interlinked
computers throughout the world, and provides access to
formal and informal training offered online from virtually anywhere.
14
August 2000
Inheritance of aroma in four rice cultivars (Oryza sativa L.)
Y.J. Dong, E. Tsuzuki, and H. Terao, Crop Sciences Laboratory Agricultural Faculty, Miyazaki University, Miyazaki City
8892155, Japan
We studied aroma inheritance in four rice
cultivars—Della (USA), Shiroikichi (Japan),
Hokkaido 270 (Japan), and HB1 (China).
These were crossed with nonaromatic cultivars (Koshihikari, Nipponbare) and with
each other. Four crosses each for aromatic/
nonaromatic and aromatic/aromatic were
obtained in 1998.
P1, P2, and F1 plants from all crosses
were grown in pots in the greenhouse
during the 1998-99 winter season; P1, P2,
and F2 plants were cultivated in the field
in 1999.
Ten leaves were sampled from individual plants at tillering and cut into 5-mmlong pieces, put into a capped glassware,
and stored at –20 °C before aroma evaluation. No more than 20 samples were evaluated in a single day. In this process, 1 g
was measured from each frozen leaf
sample, put into a capped test tube, and
mixed with 5 mL of 1.7% KOH solution for
10 min at 50 °C. Four to five panelists were
asked to classify the samples as either aromatic or nonaromatic by their smell.
The F 1 plants from crosses of
nonaromatic/aromatic cultivars were
nonaromatic, indicating that aroma in the
four aromatic cultivars was recessive (see
table). Segregating ratios of nonaromatic
to aromatic plants in the F2 populations
from the crosses of Della/Nipponbare (χ2
= 0.011, P>0.90), Koshihikari/Shiroikichi
(χ2 = 0.031, P = 0.75–0.90), and Hokkaido
270/Koshihikari (χ2 = 0.009, P>0.90) were
all 3:1, which indicated the inheritance of
a single recessive gene for aroma in Della,
Shiroikichi, and Hokkaido 270. In the F2
population from the cross Koshihikari/
HB1 (χ2 = 0.079, P = 0.75–0.90), the segregating ratio was 9:7, indicating that two
recessive genes control aroma in HB1.
The F1 plants from crosses between
any two aromatic cultivars (Table 1) were
aromatic; the F2 population did not segregate for aroma, which indicated that the
parents contained at least one common
aroma gene. The F2 data show that Della,
Shiroikichi, and Hokkaido 270 each contains a single recessive gene and HB1 has
two recessive genes for aroma. Accordingly, the aroma genes in Della, Shiroikichi,
and Hokkaido 270 were allelic to each
other and allelic to one of two aroma genes
in HB1.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Behavior of parent, F1, and F2 populations with regard to aroma.
Parental
leaf aroma
ratinga
Cross
Aromatic
nature of
F1 plants
Observed F2 plants
Total
Nonaromatic
Aromatic
χ2
Della/Nipponbare
+/–
–
120
90
30
Koshihikari/Shiroikichi
–/+
–
109
81
28
Hokkaido 270/Koshihikari
+/–
–
144
109
35
Koshihikari/HB1
–/+
–
182
100
82
Della/Shiroikichi
Della/HB1
Della/Hokkaido 270
Shiroikichi/HB1
+/+
+/+
+/+
+/+
+
+
+
+
81
90
24
76
0
0
0
0
81
90
24
76
a
0.011
(3:1)
0.031
(3:1)
0.009
(3:1)
0.079
(9:7)
nab
na
na
na
P
>0.90
0.75~0.90
>0.90
0.75~0.90
na
na
na
na
+ = aromatic, – = nonaromatic. b na = chi-square test does not apply.
IRRISTAT
Windows 4.0
Now available online and
on CD!
IRRISTAT is a computer program for data
management and basic statistical analysis of
experimental data. It can be run in any 32-bit
Windows operating system.
IRRISTAT has been developed primarily for
analyzing data from agricultural field trials, but
IRRN 25.2
many of the features can be used for analysis of
data from other sources.
The main modules and facilities are: Data
management with a spreadsheet, Text editor,
Analysis of variance, Regression, Genotype ×
environment interaction analysis, Quantitative trait
analysis, Single site analysis, Pattern analysis,
Graphics, and Utilities for randomization and
layout, general factorial EMS, and orthogonal
polynomial.
The software (including tutorial in zip and pdf
files) can be downloaded from the IRRI site at
http://www.cgiar.org/irri/irristat.htm
The software is also available on CD for
US$19 for highly developed countries and $5
for developing countries, with $7 for handling
costs.
Send suggestions, comments, or problems in
using the software to:
Biometrics
International Rice Research Institute
MCPO Box 3127
Makati City 1271, Philippines
or e-mail: [email protected]
To order a CD, e-mail: [email protected]
15
Genetic resources
Variation in RFLP markers associated with rootgrowth QTLs in Indian upland rice
K.A. Steele, B.J. Moore, J.R. Witcombe, and D.S.Virk, Centre of Arid Zone Studies, University of Wales,
Bangor, LL57 2UW; and A.H. Price, Department of Plant and Soil Science, University of Aberdeen,
Cruickshank Building, Aberdeen, AB24 3UU, UK E-mail: [email protected]
Kalinga III, bred at the Central Rice Research Institute in Cuttack, is an improved
variety popular in drought-prone areas of
India. It normally escapes the end-of-season drought because of its extreme earliness, but it is drought-susceptible. Sathi 3436, an improved variety from Gujarat, India, derived from landraces, has longer and
thicker roots than Kalinga III. Quantitative
trait loci (QTLs) influencing root length
and thickness in rice have been identified
in previous studies (Price and Tomos 1996,
Price et al 2000, Yadav et al 1997).
Molecular markers located near QTLs may
correlate with the same trait in different
varieties, and these markers could be used
in marker-assisted selection (MAS) to improve drought-sensitive varieties. Restriction fragment length polymorphism
(RFLP) markers on chromosomes with
root QTLs were used to compare genetic
variation within and between Indian
landraces and improved varieties.
Sixteen rice varieties were screened
with 55 RFLP probes (from chromosomes
2, 5, 7, 8, 9, and 11), 14 of which were
linked to QTLs for root growth. Four varieties were landraces and six were released
varieties derived from landraces, all widely
grown in India (see table). Other varieties
which have been used for mapping were
included: Azucena (japonica), Bala (indica,
an Aus variety), CO 39 (indica), and
Moroberekan (japonica).
DNA extraction and RFLP analysis
were carried out as described in Price et al
(2000). Five restriction enzymes were
tested and polymorphic bands were scored
for presence or absence in all 16 varieties.
Data were analyzed by cluster analysis
using SPSS (version 8). Similarity was
estimated using Jaccard’s coefficient.
Hierarchical clustering was performed on
16
the squared Euclidean distance matrix to
produce a dendrogram.
Twelve probes gave no polymorphisms while 43 probes gave 110 scorable
polymorphic bands (30 of which have been
mapped in the Bala/Azucena F6 population). Cluster analysis using all 110 polymorphic markers separated indicas from
japonicas (see figure). Average linkage and
single linkage gave similar results. Simi-
larity ranged from 82 ± 4% between
Azucena and Moroberekan to 19±4% between Azucena and Bala. The four Indian
landraces and Sathi 34-36 grouped together and were separated from the improved varieties (Sathi 34-36 and Kalinga
III had only 37 ± 5% similarity). Despite
being geographically diverse, the landraces
were similar at many marker loci and were
less diverse than improved varieties (e.g.,
Indian varieties used in molecular marker studies.
Germplasm
Desirable trait
Type
Kalinga III
Earliness, medium-tall
plants, fine grains,
good cooking quality
Released for uplands
in Orissa
IR36
High yield, stiff straw
IR64
High yield, fine grain
Sathi 34-36
High yield, stiff straw,
long roots, drought
tolerance
Drought resistance,
delayed senescence
Grain quality
Released variety for
irrigated environments
Released variety for
irrigated environments
Released variety in
Gujarat (derived from
a landrace)
Landrace
Nanisal
Vaghardha
Vandana
Vanprabha
Birsa Dhan 102
Dabra
Ratta Chawal
Pathara
High yield, earliness,
long roots, drought
resistance
High yield, earliness,
long roots, drought
resistance
Earliness, drought
resistance, long
roots
Earliness, drought
resistance
Drought resistance,
stiff straw, tall plants
Drought resistance,
earliness
Released variety for
Banswara area of
Rajasthan
Released for uplands
in India
Released for uplands
in India
Released in Bihar,
developed by selection
from a local landrace of
upland rice, Brown Gora
Landrace in western
India
Landrace in western
India
Landrace in western
India
Basis of selection
Most farmer-preferred
variety in participatory
varietal selection in
India.a,b Most widely
adopted in droughtprone uplands
High yield, multiple
resistances
High yield, multiple
resistances
Performance in
westerna India
Performance in
westerna India
Performance in onstation trials
Performance in farmers’
field trials in westerna
and easternb India
Performance in farmers’
field trials in easternb
India
Performance in farmers’
field trials in easternb
India
Observations in farmers’
fields in westerna India
Observations in farmers’
fields in westerna India
Observations in farmers’
fields in westerna India
a
Data from KRIBP (W): Krishak Bharati Co-operative Indo-British Rainfed Farming Project, West. bData from KRIBP(E):
Krishak Bharati Co-operative Indo-British Rainfed Farming Project, East.
August 2000
Dabra and Pathara shared 73 ± 4% similarity). Cluster analysis using only the 14
mapped markers linked to QTLs for root
traits gave identical first- and second-level
groups, as did analysis using only 16
mapped markers not linked to root QTLs.
A further 34 markers, covering all 12 chromosomes, were screened on the two released varieties, Kalinga III and Sathi 3436; 66% of them were polymorphic.
In the mapping population derived
from Bala/Azucena, Azucena was the donor of positive alleles for four QTLs, while
Bala was the donor for one QTL on chromosome 5. Kalinga III had the Bala-type
locus for nine markers at QTLs on chromosomes 2, 7, 9, and 11. Because most
Indian landraces had the Azucena locus in
up to five of these markers, they could be
used as donor parents for MAS to improve
Kalinga III for root growth. Dabra, Ratta
Chawal, and Sathi 34-36 had the Azucena
allele at markers C601 (chromosome 2),
RG650 (chromosome 7), and RG2 (chromosome 11).
Acknowledgment
This document is an output from a project
funded by the UK Department for Inter-
national Development (DfID) (project No.
R7080, Plant Sciences Programme) for the
benefit of developing countries. The views
expressed are not necessarily those of
DfID.
References
Price AH, Steele KA, Moore BJ, Barraclough PB,
Clarke LJ. 2000. A combined RFLP and AFLP
linkage map of upland rice (Oryza sativa L.)
used to identify QTLs for root penetration
ability. Theor. Appl. Genet. (in press)
Price AH, Tomos AD. 1996. Genetic dissection of
root growth in rice (Oryza sativa L.). II:
Mapping quantitative trait loci using
molecular markers. Theor. Appl. Genet.
95:143–152.
Yadav R, Courtois B, Huang N, McLaren G. 1997.
Mapping genes controlling root morphology
and root distribution on a double-haploid
population of rice. Theor. Appl. Genet.
96:619–632.
○
0
5
○
○
○
○
○
○
○
○
○
Rescaled combined cluster distance
10
15
○
○
20
○
○
○
○
○
○
○
25
Azucena
Moroberekan
Pathara
Sathi 34-36
Ratta Chawal
Dabra
Nanisal
IR36
Vanprabha
Birsa Dhan 102
Vaghardha
Kalinga III
Vandana
Bala
IR64
CO 39
Dendrogram showing hierarchical (average linkage, between-group) clustering of varieties based
on 110 RFLP bands.
Evaluation of in situ conservation of Oryza rufipogon
populations using RAPD markers
Z.-W. Xie, S. Ge, K.-Q. Wang, D.-Y. Hong, Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese
Academy of Sciences (CAS), Beijing 100093; and B.R. Lu, GRC, IRRI
E-mail: [email protected]
Oryza rufipogon Griff. is a perennial species widely distributed in the tropics and
subtropics of monsoon Asia. It constitutes
a valuable genetic resource for rice improvement (Chang 1984). This species
once occurred in eight provinces and autonomous regions of China but it is now
extinct in Fujian and is nearly extinct in
Hunan and Jiangxi. An intensive
biodiversity conservation program for O.
rufipogon has recently been initiated in
China, using the in situ approach, which
has been regarded as an effective method
IRRN 25.2
to maintain diversity of wild rice species
in their original habitats (Vaughan and
Chang 1992). Knowledge on genetic diversity, population structure, and dynamics of
the target O. rufipogon populations is important for strategic design and effective
management and conservation. Such information, however, is still very limited. This
study aimed to estimate the genetic diversity of O. rufipogon populations and to
confirm the in situ conservation sites for
this species using random amplified polymorphic DNA (RAPD) markers.
Six O. rufipogon populations from
in situ conservation sites in China were
investigated through field surveys during
1997-98. These populations were classified
into four groups according to their origins
(Table 1). Young and clean leaves of 15–
18 individuals were sampled from different
populations (Table 1). The method for
sample collection, leaf preservation, and
DNA extraction followed those described
by Xie et al (1999). To prevent overestimating the genetic diversity by polymorphic loci variation, 20 primers (OPB 1–20
17
of kit B of Operon Technologies Inc.) were
randomly chosen to analyze leaf samples,
regardless of the polymorphism of amplified fragments. Only one primer (OPB-06)
amplified unclear bands and was excluded
from the experiment. The other 19 primers produced strong and reproducible fragments and thus were used for further
analysis. RAPD fragments were scored as
present (1) or absent (0) for each DNA
sample to estimate genetic distance between individuals. Genetic diversity was
measured by the percent polymorphic
bands (PPB) at population and region levels. An analysis of molecular variation
(AMOVA) was used to partition variance
components among individuals of a population, among populations within a region,
and among regions. All the analyses were
performed with the RAPDistance program
(version 1.04) and WINAMOVA program
(version 1.5). An unweighted paired group
method for cluster analysis (UPGMA) using the genetic distance estimates was also
used.
A total of 241 fragments ranging
from 190 to 2,800 bp in size were scored
in 100 individuals of the six populations
studied. Each individual had a unique haplotype. PPBs for each population and region are shown in Table 2. AMOVA results
showed highly significant genetic differentiation among regions and among populations of the same regions (Table 3). Considerable variation was detected within
each of the six populations. The 100 individuals were clustered into six groups that
corresponded to the six populations in-
cluded in this study. The major portion of
the total genetic variation was identified
within rather than between populations.
These data can help in designing more strategic in situ conservation programs for O.
rufipogon in China.
China established in situ conservation sites of O. rifupogon in Dongxiang
county (populations PO2 and PO3) in
Jiangxi Province in 1992. The Dongxiang
populations are the northernmost populations in the entire distribution of this
species. The two populations are located
about 5 km from each other and have special characteristics such as cold tolerance.
Five population-specific RAPD bands were
identified in each population. The two
populations also showed some differentiation based on cluster analysis of RAPD
bands. The levels of genetic diversity of the
two populations were moderately high
among 29 Chinese O. rufipogon populations analyzed by Xie (1999). Therefore, it
is necessary to independently conserve the
two populations in situ.
Population PO5, located in
Yangtianqiao of Guangdong Province, is
particularly valuable. Individuals from this
population have been extensively used for
Table 1. Populations of Oryza rufipogon used in this study.
Group
code
GP1
GP2
GP3
GP4
Population
code
Locality
PO2
PO3
PO5
P19
P59
P47
Individuals
sampled (no.)
Dongxiang, Jiangxi Province
Dongxiang, Jiangxi Province
Yangtianqiao, Guangdong Province
Hanguang, Guangdong Province
Heping, Guangxi Province
Sanya, Hainan Province
15
15
18
18
16
18
Table 2. Number and percentage of polymorphic bands detected in each population and region.a
Primer
Bands
(no.)
OPB-01
OPB-02
OPB-03
OPB-04
OPB-05
OPB-07
OPB-08
OPB-09
OPB-10
OPB-11
OPB-12
OPB-13
OPB-14
OPB-15
OPB-16
OPB-17
OPB-18
OPB-19
OPB-20
14
12
15
15
15
12
14
10
10
13
12
13
8
12
6
18
12
14
16
Total
PPB
241
–
a
Polymorphic bands (no.)
PO2
PO3
GP1
PO5
P19
3
3
6
4
2
4
4
2
5
4
5
4
0
4
1
3
5
5
4
6
3
5
5
3
5
4
2
4
7
3
3
2
5
1
6
5
4
5
6
3
7
6
3
5
6
3
6
8
6
5
2
6
1
7
5
7
6
5
6
9
3
1
3
5
3
5
7
6
5
2
5
2
9
4
6
5
8
7
7
4
3
4
7
3
4
6
6
6
3
7
2
9
4
4
6
72
29.88
78
32.37
98
41.08
91
37.76
100
41.49
GP2
8
8
11
5
4
6
9
4
5
7
8
9
4
9
3
12
5
8
7
132
54.77
P59
GP3
P47
GP4
Total
2
6
3
5
3
5
4
4
4
5
2
3
1
3
3
6
5
2
2
2
6
3
5
3
5
4
4
4
5
2
3
1
3
3
6
5
2
2
5
9
5
4
8
6
7
4
5
5
4
5
3
5
3
6
4
5
9
5
9
5
4
8
6
7
4
5
5
4
5
3
5
3
6
4
5
9
9
12
12
13
12
10
13
9
9
12
8
10
7
10
6
15
10
11
11
102
42.32
102
42.32
68
28.22
68
28.22
200
82.99
Population codes = PO2, PO3, PO5, P19, P59, and P47; group codes = GP1, GP2, GP3, and GP4. PPB = percent polymorphic bands.
18
August 2000
Table 3. Analysis of molecular variance (AMOVA) for 100 individuals of Oryza rufipogon from four different regions.
Source of
variation
Global
Between regions
Populations/region
Individuals/population
Within regions
Between populations
Within populations
Among regions
Among regions
Within regions
df
SSD
MSD
Variance
component
% total
variance
P value
Bartlett’s
statistic
3
2
94
5.175
2.256
8.799
1.725
1.128
0.094
0.024
0.063
0.094
13.40
34.73
51.87
<0.001
<0.001
<0.001
2.638
2.608
5
94
7.431
8.799
1.486
0.094
0.084
0.094
47.20
52.80
<0.001
<0.001
3
96
5.175
11.054
1.725
0.115
0.067
0.115
36.73
63.27
<0.001
<0.001
SSD = sum of squared deviation, MSD = mean square deviation.
rice breeding since 1980. Some high-quality and high-yielding new rice varieties have
been produced using O. rufipogon from
this population as a parent in crossing programs. Considering its high genetic diversity as revealed by RAPD analysis (PPB =
38.15), this population needs to be conserved in situ.
Population P19, found in Hanguang,
Guangdong Province, is one of the northern marginal populations in China. It has
a much higher genetic diversity (PPB =
40.16%) than many of the 29 other populations studied by Xie (1999) and therefore
is also a key population that needs to be
conserved in situ.
One of the southernmost populations of O. rufipogon in China is population P47, located in Sanya of Hainan Prov-
ince. It occurs in a large pond near the sea
and grows in brackish water. Because of
the importance of maintaining some populations with special characteristics such as
salinity tolerance, this population should
be conserved in situ. In addition, the genetic diversity (PPB = 46.18%) of this
population is the highest among the 29
populations studied.
Population P59 occurs on the upper
reaches of a river in Heping, Guangxi Province, and is isolated from other O.
rufipogon populations. RAPD analysis and
previous analysis of data from 29 other
populations showed that this population
has a relatively low genetic diversity (PPB
= 25.70) and no special characters. Therefore, this population could be maintained
under ex situ conservation.
References
Chang TT. 1984. Conservation of rice genetic
resources: luxury or necessity? Science
224:251–256.
Vaughan DA, Chang TT. 1992. In situ conservation
of rice genetic resources. Econ. Bot.
46:368–383.
Xie ZW. 1999. Population genetics and
conservation strategy of natural populations
of Oryza rufipogon Griff. in China. PhD
dissertation, Institute of Botany, Chinese
Academy of Sciences, Beijing. p 36–57.
Xie ZW, Ge S, Hong DY. 1999. Preparation of DNA
from silica gel dried mini-amount of leaves
of Oryza rufipogon Griff. for RAPD study
and total DNA bank construction. Acta Bot.
Sin. 41:884–890.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Identification of genomic constitution of three tetraploid
Oryza species through two-probe genomic in situ
hybridization
C.B. Li, D.M. Zhang, S. Ge, and D.Y. Hong, Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese
Academy of Sciences, Beijing 100093, China; and B.R. Lu, GRC, IRRI E-mail: [email protected]
Two tetraploid Oryza species, O. minuta
and O. punctata (with diploid and tetraploid types), are reported to contain the
BBCC genomes based on the analysis of
meiotic chromosome pairing at metaphase
I of interspecific F1 hybrids. O. officinalis
and O. eichingeri have diploid and tetraploid forms. The genomic constitution of
IRRN 25.2
tetraploid forms is still unclear. The genomic constitution of O. malampuzhaensis
(treated as a synonym of O. officinalis by
Vaughan 1989) was tentatively designated
as BBCC, but no sound cytological data
have been provided to support this designation.
Genome analysis based on observation of chromosome pairing has been
largely challenged because chromosome
pairing is known to be influenced by several factors including environmental and
genetic ones, which have led to inaccurate
measures of genomic affinities in some
19
cases. It is therefore necessary to adopt
more reliable and powerful methods to
detect and confirm the genomic constitution of these tetraploid wild rice species.
Total genomic in situ hybridization (GISH)
uses total genomic DNA of an analyzer
(genomically known species) as a probe
to detect chromosomal homology of the
analyzer with a genome of an unknown
target species. It provides a more direct
approach for genomic studies at the chromosome and DNA levels. This study aimed
to determine the genomic constitution of
the tetraploid O. malampuzhaensis (IRGC
80764), O. minuta, and O. punctata by
two-probe GISH technology using total
genomic DNA of three diploid wild rice
species—O. eichingeri, O. officinalis, and
O. punctata—as probes.
Six wild rice species with different
ploidy levels and origins were used in this
study (Table 1). Diploid species were used
as analyzers, from which genomic probes
were prepared, with the tetraploid species
as target species. Somatic chromosomes
of target species were prepared by
enzymatic maceration and an air-dry
method as described by Fukui and Iijima
(1991) and Fukui et al (1994) with modifications. A precooled wet slide covered with
polylysine was placed on ice; then a macerated root tip was placed on it with a drop
of cold fixative (acetic acid: absolute ethanol = 1:3) at 0 °C and smeared with sharp
tweezers. The in situ hybridization and
probe detection methods followed those
of Leitch et al (1994). Chromosome
samples were treated in turn with 100 mg
mL–1 Dnase-free Rnase, 1 mg mL–1 proteinase K, 20% acetamide, and 4% (w/v)
paraformaldehyde; then dehydrated
through a graded ethanol series (70%,
90%, and 100%); and air-dried. Total DNA
from the C- and B-genome species was labeled by nick translation with bio-14-dATP
(GIBCO BRL Cat. No. 19524-016) and DIG11-dUTP (Boehringer Mannheim,
1093088), respectively. The hybridization
mixture consisted of 50% deionized
formamide, 2 × SSC, 10% (w/v) dextran
sulfate, 0.1% (w/v) SDS, 0.25 mg mL–1
sheared salmon sperm DNA (about 100
20
bp), and the probes (3–5 ng mL–1 for each
probe). Table 2 shows the probes in the
hybridization mixture and the stringency
at which posthybridization washes were
carried out. Detection of the biotin-labeled
probe was achieved by using avidin-FITC
and of the digoxigenin-labeled probe by
using anti-digoxigenin rhodamine
conjugate. Results of the two-probe GISH
were observed with a fluorescence
microscope and photographs were taken
with Kodak Ektachrome 400 film.
Results clearly showed that the
tetraploid O. malampuzhaensis (IRGC
80764) was an allotetraploid and its genomic constitution was BBCC (Figs. 1a &
1b). This taxon was collected from India
and provided by the International Rice
Genebank (IRG). We carefully examined
the specimen of IRGC 80764 deposited at
IRRI and found that O. malampuzhaensis
was different from O. officinalis in many
characters, particularly panicle characters.
Results also confirmed that the genomic
constitutions of O. punctata and O.
minuta were BBCC (Figs. 2a,b & 3a,b). The
identification of the BBCC genomes in the
latter two species further confirmed the
reliability of the genomic determination of
O. malampuzhaensis as BBCC.
Although containing the same
BBCC genomes, these species showed
considerable differences in their karyotypes. One pair of satellite chromosomes
belonging to the BB genome was clearly
identified in the tetraploid O.
malampuzhaensis (Figs. 1a & 1b), but no
such satellite chromosomes were found in
either O. minuta or O. punctata. Eight
visible hybridization sites, which showed
co-hybridization signals on both BB and CC
genomes, were located on the chromosomes of the BB genome of the tetraploid
O. punctata (Fig. 3a). The average chromosome length of the CC genome is larger
than that of the BB genome in O. minuta
(Figs. 2a & 2b) but not in O. punctata
(Figs. 3a & 3b) and the tetraploid O.
malampuzhaensis (Figs. 1a & 1b). The ratio of the total chromosome length between the BB and CC genomes was determined as 1:1.5 in O. minuta, 1:0.9 in O.
Table 1.Wild rice species and accessions used in the study with their ploidy level and origin.a
Species
O. officinalis
O. eichingeri
O. punctata
O. punctata
O. minuta
O. malampuzhaensis
a
b
Accession
number
Zhou-198
IRGC 101422b
IRGC 103896
IRGC 105137
IRGC 101082
IRGC 80764
2n
24
24
24
48
48
48
Genomic
constitution
Country
CC
CC
BB
BBCC
BBCC
Unknown
China
Uganda
Tanzania
Zaire
Philippines
India
All living materials are maintained in the greenhouse of the Beijing Institute of Botany, Chinese Academy of Sciences.
IRGC = International Rice Genebank Collection stored at IRRI.
Table 2. Probes in the hybridization mixture and the posthybridization wash stringency.
Species
Probe
O. minuta (BBCC)
DIG-CCb (O. eichingeri)
BIO-BBc (O. punctata)
O. punctata (BBCC)
DIG-CC (O. eichingeri)
BIO-BB (O. punctata)
O. malampuzhaensis (4x)
DIG-BB (O. punctata)
BIO-CC (O. officinalis)
Stringency (%)a
Stringent washes
50% formamide in
0.1 × SSC at 42 °C for
10 min
20% formamide in
0.1 × SSC at 42 °C for
10 min
20% formamide in
2 × SSC at 42 °C for
10 min
99
82–87
60–63
a
Calculated by using the equation described by Meinkoth and Wahl (1984). bDIG-CC = total DNA of CC genome labeled
with digoxigenin. cBIO-BB = total DNA of BB genome labeled with biotin.
August 2000
Figs. 1-3. Metaphase of Oryza malampuzhaensis, O. minuta, and O. punctata after in situ hybridization with the B- and C-genome species
and counterstained with DAPI (blue). Figures 1a and 1b show results of O. malampuzhaensis probed with labeled B genome (diploid O.
punctata) and C genome (O. officinalis) DNA. The 24 chromosomes with strong violet signals belong to the BB genome (Fig. 1a) and the
other 24 with strong green-blue signals are the C-genome chromosomes (Fig. 1b). Arrows indicate a pair of satellite chromosomes.
Figures 2a and 2b show a metaphase of O. minuta hybridized by the B- and C-genome DNA. The chromosomes with green-blue signal
belong to the BB genome (Fig. 2a) and the other chromosomes showing violet color belong to the CC genome (Fig. 2b). Figures 3a and
3b show results of tetraploid O. punctata probed with B- and C-genome (O. eichingeri) DNA. The 24 chromosomes with violet color
belong to the CC genome (Fig. 3a) and the other 24 chromosomes with green-blue color belong to the BB genome (Fig. 3b). The arrows
indicate hybridization signals of the C-genome probe on the B-genome chromosomes (Fig. 3a). Scale bar = 5 mm.
IRRN 25.2
21
punctata, and 1:1 in O. malampuzhaensis.
These ratios strongly suggest differences in
BBCC genomes in the three rice species.
Possible causes for differences in genomes
might be the different sources/origins of
the BB and CC genomes for the different
species. It is also possible that
chromosome differentiation within species
occurred after the formation of these species. The former is more likely the mechanism that causes differences in BBCC genomes in the three tetraploid wild rice
species.
This study also shows that the twoprobe GISH can give a high resolution in
identifying chromosomes of different genomes of an allopolyploid species on the
same chromosome spread. The method
has a great potential to be used for further
genomic studies in the genus Oryza.
References
Fukui K, Iijima K. 1991. Somatic chromosome
map of rice by imaging methods. Theor.
Appl. Genet. 81:589–596.
Fukui K, Ohmido N, Khush GS. 1994. Variability in
rDNA loci in genus Oryza detected through
fluorescence in situ hybridization. Theor.
Appl. Genet. 87:893–899.
Leitch AR, Schwarzacher T, Jackson D, Leitch IJ.
1994. Hybridization, a practical guide. UK:
BIOs Scientific Publishers Limited.
Meinkoth J, Wahl G. 1984. Hybridization of
nucleic acids immobilized on solid support.
Anal. Biochem. 138:267–284.
Vaughan DA. 1989. The genus Oryza L. Current
status of taxonomy. IRRI Res. Pap. Ser. 138.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Collection and evaluation of hill germplasm from Karbi
Anglong and North Cachar Hill districts of Assam, India
A. Roy and K. Das, Regional Agricultural Research Station (RARS), Assam Agricultural University, Diphu 782460, Assam,
India
In Karbi Anglong and North Cachar Hill
districts of Assam, India, local tribes grow
several hill rice cultivars on the hilly slopes
as jhum (shifting cultivation practiced
through slash-and-burn method) and on
terraces. These cultivars are highly adaptable to local agroecological conditions and
are grown at the onset of monsoon (AprilMay) with minimum or even zero-tillage
operation as a direct-seeded rainfed crop.
They require less inputs and management
practices and possess enormous variability for various quantitative and qualitative
traits. Rice is mostly grown as a mixed crop
with various crops such as sesame, maize,
cotton, colocasia, chili, ginger, turmeric,
and others in this region. These local cultivars, however, face extinction due to recent trends in agricultural development.
Hence, the collection and evaluation of
these varieties for various quantitative and
qualitative traits are important for breeding and conservation programs. This study
reports on the collection and evaluation
of hill rice germplasm from Assam.
Seventy-six rice hill cultivars were
collected from 36 sampling sites in the two
districts. The farmers’ field was considered
as a unit area. Random samples from populations and biased samples of elite materi-
als were collected. Germplasm samples
were also collected from threshing yards
and farm stores (Pandravada et al 1996).
Each sample was given an accession number; source and date of collection were also
recorded.
The collected germplasm was
grown in a randomized block design with
three replications during summer 1998 at
RARS in Assam (25° 50′ N latitude, 90° 30′
E longitude, and an altitude of 180 m asl).
Cultivars were evaluated for 13 yield and
yield-attributing traits (see table). A wide
range of mean values depicted sufficient
variability among cultivars for all the traits.
Variability parameters of hill rice cultivars from Karbi Anglong and North Cachar Hill districts, Assam, India.a
Character
Days to 50%
flowering
Days to maturity
Plant height (cm)
Tillers plant–1 (no.)
Leaf length (cm)
Flag leaf length (cm)
Leaf breadth (cm)
Flag leaf breadth (cm)
Panicle length (cm)
Spikelets panicle–1 (no.)
Grains panicle–1 (no.)
100-grain weight (g)
Yield plant–1 (g)
a
Range
Mean ± SE
GCV (%)
PCV (%)
Heritability
(%)
GA (%)
of mean
81.0 –145.0
101.36 ± 1.46
12.5
12.7
95.8
25.1
113.5 –162.5
88.8 –161.8
3.4 – 12.5
40.6 – 73.7
21.8 – 49.2
1.2 – 2.2
1.0 – 1.9
19.7 – 31.8
81.8 –293.0
51.5 –243.2
1.2 – 3.0
5.0 – 35.4
126.86 ± 1.35
127.62 ± 1.69
8.45 ± 0.26
57.54 ± 0.96
34.30 ± 0.64
1.66 ± 0.03
1.42 ± 0.03
25.60 ± 0.30
181.77 ± 5.24
131.47 ± 4.96
1.84 ± 0.04
15.26 ± 0.92
9.2
11.3
26.6
13.9
15.9
13.5
14.5
9.7
24.3
32.1
20.6
52.5
9.3
12.0
28.5
14.8
17.0
15.9
16.4
10.6
26.7
34.5
20.8
53.2
98.3
89.2
87.2
87.2
87.1
71.4
77.8
84.1
83.0
86.5
98.4
97.4
18.9
22.0
51.2
26.7
30.5
23.4
26.3
18.3
45.6
61.5
42.0
106.8
SE = standard error, GCV = genotypic coefficient of variation, PCV = phenotypic coefficient of variation, and GA = genetic advance.
22
August 2000
A high genotypic coefficient of variation
(GCV) and phenotypic coefficient of variation (PCV) were recorded for grain yield
per plant (52.2% and 53.2%, respectively),
indicating maximum variability among
genotypes for this trait. Moderate GCV and
PCV values (20% and 50%) were recorded
for grains per panicle, tillers per plant, and
100-grain weight. The remaining traits
showed relatively low GCV and PCV estimates. Heritability estimates were high for
all traits studied, ranging from 71.4% in leaf
breadth to 98.4% in 100-grain weight. High
estimates of heritability revealed reliability for phenotypic selection for all traits.
Genetic advance (GA) as a percentage of mean was high for yield per plant
(106.8%), grains per panicle (61.5%), tillers
per plant (51.2%), and spikelets per panicle
(45.6%). The remaining traits exhibited
relatively low GA. High heritability coupled
with high GA was observed in yield per
plant, grains per panicle, tillers per plant,
and spikelets per panicle. This indicated
the predominance of additive gene effects
in the inheritance of these traits and revealed relatively high feasibility for phenotypic selection. Similar observations were
also reported (Kihupi and Dote 1989, Deb
Choudhury and Das 1998).
In this work, sufficient variability was
observed among cultivars for all traits studied. Hence, these cultivars may serve as an
important source of genetic variability for
developing suitable rice varieties for the
region. Moreover, these cultivars are likely
to possess drought resistance/tolerance
and can be used for future breeding programs.
References
Deb Choudhary PK, Das PK. 1998.Genetic
variability, correlation and path coefficient
analysis in deepwater rice. Ann. Agric. Res.
19(2):120–124.
Kihupi AN, Dote AL. 1989. Genotypic and
environmental variability in selected rice
characters. Oryza 26(2):129–134.
Pandravada SR, Sivraj N, Murthy KRK. 1996.
Collection of rice germplasm from Adilabad
District, Andhra Pradesh, India. Indian J.
Plant Genet. Resour. 9(2):255–259.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Badan Pusat Statistik (Indonesian
Central Bureau of Statistics)
http://www.bps.go.id
High Wire Press
http://highwire.stanford.edu
High Wire Press, the “Internet imprint of the Stanford
University libraries,” offers free access to full text
articles from dozens of scientific journals. Journals
with free access that are of interest to rice scientists
include Proceedings of the National Academy of
Sciences of the USA, Plant Cell, Plant Physiology,
and Microbiology and Molecular Biology Reviews.
Although current issues of most journals are not
available for free, many journals offer free access
to back issues 1 month or 1 year after publication.
The site also provides information on obtaining faster
Web access for users outside of the USA and Canada.
IRRN 25.2
This is the Web site for the Indonesian Central Bureau of Statistics (Badan Pusat Statistik, BPS, in Indonesian). It presents statistical information at both
national and provincial levels organized into different subjects, including population, employment,
wages, agriculture, foreign trade, consumer and
wholesale price indices, consumption expenditures,
and many other topics. For example, one can find
data on rice production for the past several years.
The statistics are accompanied by explanations of
concepts, definitions, methodologies, publications,
and tables. More detailed information at the provincial level can be obtained through links to the
homepages of individual provinces.
Other interesting sites to explore that are linked
to the BPS Web page include those of Indonesian
government agencies, international organizations,
statistical agencies in other countries, and other
members of the statistics community within Indonesia. A search engine is provided to make browsing
the BPS site easier.
There is also a page devoted to explaining how
BPS was established, the functions of the institution,
and how it undertakes data collection, storage, and
management.
23
Pest science & management
Improvement of conjugation methods for
Xanthomonas oryzae pv. oryzae strain DY89031
to identify avrXa21 clones
P.K. Sharma, Department of Microbiology, CCS Haryana Agricultural University, Hisar, India 125004; F.G.
da Silva, Y. Shen, and P.C. Ronald, Department of Plant Pathology, University of California–Davis, CA
95616, USA
E-mail: [email protected]
Xanthomonas oryzae pv. oryzae (Xoo), a
Gram-negative bacterium, causes bacterial
blight, a destructive disease of rice. Xoo
strain PXO99A (race 6), an avirulent strain
on plants carrying the Xa21 gene, is hypothesized to carry the avrXa21 gene. Attempts to identify avrXa21 by transferring
genomic library clones (plasmid or
cosmid) of Xoo strain PXO99A to Xoo strain
DY89031 (virulent on plants carrying the
Xa21 gene) were not successful because
strain DY89031 was not a good recipient
strain. The conjugation methods developed for Xoo strain PXO99A failed to transfer cosmid pHM1 and plasmid pUFRO27
clones to Xoo strain DY89031, thus delaying identification of avrXa21. In this report, conjugation methods described by
Choi and Leach (1994) and Simon et al
(1989) were modified to give a high frequency of conjugation in Xoo strain
DY89031.
Xoo strain DY89031 was streaked on
peptone sucrose agar (PSA) plates that
were incubated at 30 °C for 3–4 d. Cells
were scraped from plates and resuspended
in 100 mL of nutrient broth (NB) to give
O.D.600 = 0.25–0.3. Cells were incubated
for 5–6 h on a rotary shaker (150 rpm) at
30 °C to O.D.600 = 0.5–0.6. Donors Escherichia coli S17-1 (pUFRO27) for biparental
mating and E. coli DH10B (pUFRO27) for
triparental mating containing different-size
inserts were grown in NB at 37 °C for 4 h
to give O.D.600 = 0.5. Helper E. coli DH10B
(pRK2013) was grown in NB at 37 °C for 4
h to O.D.600 = 0.5. For biparental matings,
1.5 mL of Xoo strain DY89031 was mixed
with 0.1 mL of donor, while for triparental
matings, 1.35 mL of Xoo strain DY89031
was mixed with 0.15 mL of helper and 0.1
mL of donor in an eppendorf tube. The
mating mixture was centrifuged for 2 min
at 8,000 rpm. The pellet was resuspended
in 40 mL of sterilized distilled water, spot24
ted on well-dried PSA plates, and allowed
to dry in the laminar flow chamber. After
incubation at 30 °C for 48 h, the mating
mixture spots were resuspended in 0.2 mL
sterilized distilled water and were spread
on PSA plates containing kanamycin (25
mg mL–1) and cephalexin (20 mg mL–1).
Transconjugants appearing after 72 h were
purified on the same medium and stored
in 10% glycerol in microtiter plates for inoculation experiments.
Conjugation frequency was improved 1,000-fold by manipulating growth
conditions, growth stage of the recipient,
and proportion of donor, recipient, and
helper in the mating mixture (see table).
Using this modified protocol, 80–95% of
the clones of the pUFRO27 library were
able to undergo conjugation in contrast to
published protocols with a 1–5% success
rate. Thus, using the modified protocol,
400–500 matings can be performed in 1
wk and 6,000 clones (with average insert
size between 6 and 8 kb) can be transferred
in 12–15 wk. Recipient cells in the early
exponential phase were a better candidate
for conjugation compared with cells in the
late exponential phase. Dominance of Xoo
(O.D.600 > 0.8–1.0) in the mating mixture
inhibited the conjugation. A minimum
threshold number of E. coli (O.D.600 = 0.3–
0.4) was required for efficient conjugation.
A regulatory mechanism such as quorum
sensing appears to be involved in XooE.coli conjugations. Such a phenomenon
has been described for conjugation in
Agrobacterium tumefaciens (Piper et al
1993). Finally, the modification of conjugation protocols for Xoo strain DY89031
and the use of a plasmid library with small
inserts (9–12 kb) have facilitated the identification of clones carrying the avrXa21
gene.
References
Choi SH, Leach JE. 1994. Genetic manipulations
of Xanthomonas oryzae pv. oryzae. Int.
Rice Res. Newsl. 19:131–132.
Piper KR, Beck von Bodman S, Farrand SK. 1993.
Conjugation factor of Agrobacterium
tumefaciens regulates Ti plasmid transfer by
autoinduction. Nature 362:448–450.
Simon R, Quandt J, Klipp W. 1989. New derivatives
for transposon Tn5 suitable for mobilization
of replicons, generation of operon fusions
and induction of genes in gram negative
bacteria. Gene 80:161–169.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Conjugation frequency of Xanthomonas oryzae pv. oryzae strain DY89031 with pUFRO27
library clones.
Conjugation frequency
Insert size (kb)
Mating typea
Modified method
Previous methodb
Vector pUFRO27
(No insert)
0.4
2.6
5.6
7.2
10.6
12.0
Vector pUFRO27
(No insert)
2.7
5.9
12.0
a
BP
1.80 × 10–6
2.5 × 10–8
BP
BP
BP
BP
BP
BP
1.65 × 10–6
1.08 × 10–6
1.02 × 10–6
1.05 × 10–6
1.06 × 10–6
0.96 × 10–6
1.3 × 10–8
1.9 × 10–8
1.0 × 10–10
–c
–
–
TP
TP
TP
TP
1.04 × 10–6
1.50 × 10–7
1.20 × 10–7
1.10 × 10–7
1.2 × 10–8
>10–10
–
–
BP = biparental mating, TP = triparental mating. bChoi and Leach (1994). c = no conjugation.
August 2000
Soil, nutrient, & water management
Part 2. All notes published under this section constitute part of the outputs of the second CREMNET (Crop and Resource
Management Network) India Workshop-cum-Group Meeting held at the Soil and Water Management Research Institute in
Thanjavur, India, on 24–27 August 1999. The workshop was organized by the Directorate of Rice Research (DRR), India, and
CREMNET-IRRI with the theme Innovative nitrogen and other crop management techniques for intensive rice systems
of South Asia.
Comparing management techniques to optimize
fertilizer N application in rice in the Cauvery Delta
of Tamil Nadu, India
P. Stalin, T.M. Thiyagarajan, Department of Soil Science and Agricultural Chemistry, Tamil Nadu
Agricultural University, Coimbatore; S. Ramanathan and M. Subramanian, Tamil Nadu Rice Research
Institute (TNRRI), Aduthurai, India
With the present levels of fertilizer N use
efficiency (NUE) (<40%) in rice, it is estimated that an increase of about 300% in N
use will be required to achieve an average
yield of 8 t ha–1 by 2025 (Cassman and
Pingali 1995). Many fertilizer application
methods and fertilizer types can help optimize N use in rice. In this paper, the following techniques and fertilizer types were
evaluated on an Udorthentic Chromustert
soil at TNRRI in the Cauvery Delta, during
the 1997 and 1998 dry seasons (DS): the
model Manage-N to optimize dose and timing of N application (Thiyagarajan et al
1994), the chlorophyll or SPAD meter to
dose topdressing of N (Peng et al 1996,
Balasubramanian et al 1999), controlledrelease fertilizers (Shoji and Gandeza
1992), and a soil test crop response-based
N application (STCR-N) developed in India.
In 1997, an on-station trial was conducted to compare seven N treatments: (1)
zero-N control; (2) STCR-N for a yield target
of 8 t ha–1 (167 kg N ha–1 applied in four
equal splits: basal, 15, 30, and 45 d after
transplanting, DAT); (3) Manage-N (168 kg
N ha–1 applied in four equal splits at 13
DAT, 23 DAT, panicle initiation, and flowering); (4) SPAD-guided N application
without basal application; (5) same as 4 but
with 20 kg N ha–1 basal; (6) resin-coated
controlled-release urea (CRU) with 4.5%
coating at 60% of STCR-N recommendation applied as a single dose at the last puddling; and (7) same as 6 but with CRU with
6% coating. In all but the CRU treatments,
the fertilizer N used was prilled urea. The
IRRN 25.2
model Manage-N was calibrated on data
from 1996 DS experiments to generate fertilizer N recommendations. In the SPADN treatment, SPAD readings were taken
weekly from 14 DAT until flowering. Nitrogen was applied when SPAD readings
dropped below 35 (Peng et al 1996,
Balasubramanian et al 1999). In 1998, both
on-station and on-farm verification trials
using the same N treatments as in 1997
except for treatments 1 (zero N) and 5
(SPAD with basal N application) were conducted (four locations). Instead of the control zero-N treatment, a treatment using
the current farmers’ practice was used. On
the research farm, all treatments were replicated three times in a randomized complete block design. Each farm formed a
replication in on-farm trials. In both 1997
and 1998, irrigated transplanted rice cv
ADT36 was used. Nitrogen use efficiency
was expressed as agronomic N efficiency
(AEN) and as partial factor productivity for
applied N (PFP-N).
Results in 1997 showed that the
SPAD-guided treatment had a significantly
lower grain yield than the Manage-N and
STCR-N methods (Table 1). This may be
due to the relatively low amount of N
applied (75 kg N ha–1), suggesting that the
SPAD threshold value for ADT36 needs to
be increased to maximize grain yield and
NUE. There was no substantial increase in
yield with an additional basal application
of 20 kg N ha–1. With CRU application, grain
yields obtained were on a par with the
SPAD treatment but were significantly
lower than yields under the Manage-N and
STCR-N methods (Table 1). The high single
dose of CRU-N (100 kg N ha–1) as basal ap-
Table 1.Total N applied, N uptake, grain yield, and N use efficiency of irrigated transplanted
rice (cv ADT36) under various N sources and N management practices in an on-station trial
at TNRRI, Aduthurai, Tamil Nadu, India, 1997 dry season.a
N treatment
Control
STCR-N for 8 t ha–1
yield targetd
Manage-Ne
SPAD-35 N
SPAD-35 N + 20
kg N ha–1 basal
CRU 4.5%f
CRU 6.0%f
CDg (.05)
AENb
PFP-Nc
3.5 c
5.7 a
–
13.1
–
34.0
144.7 a
114.3 c
109.1 c
5.9 a
5.0 b
5.1 b
14.3
20.3
16.5
35.1
66.8
53.3
106.0 c
109.9 c
4.9 b
5.0 b
9.6
14.2
15.6
0.34
49.0
50.3
Total N applied
(kg ha–1)
Total N uptake
(kg ha–1)
0.0
167.2
60.3 d
124.2 b
168.0
75.0
95.0
100.3
100.3
Grain yield
(t ha–1)
a
Means followed by the same letter are not significantly different at LSD (5% level). bAEN = additional grain yield over
control per kg N applied. cPFP-N = total grain yield divided by total N applied. dApplied in four equal splits: basal, 15, 30, and
45 d after transplanting (DAT). eApplied in four equal splits at 13 DAT, 23 DAT, panicle initiation, and flowering. fApplied as
a single dose at last puddling. gCD = critical difference, STCR = soil test crop response, CRU = controlled-release urea.
25
plication resulted in luxurious vegetative
growth, which led to higher pest incidence
and lower yields. This suggested that the
N rate for STCR is high and that using 60%
of it as a single basal application of CRU
may be too high for the soil of our
experiment. In the STCR-N and Manage-N
treatments, the target yield of 8 t ha–1 was
not reached, which indicates the need to
refine these techniques further to achieve
target yields with high NUE.
The NUE values (AEN and PFP-N)
were highest for the SPAD method, which
could be attributed to improved timing of
N application. Although the SPAD method
did not have the highest yield, it had the
highest NUE because of less N application
(75 kg ha–1). SPAD-guided N management
may be an attractive option for resourcepoor farmers. NUE values were low in the
STCR-N and Manage-N methods in spite
of high yields. It is therefore important to
further improve the STCR-N and ManageN methods to achieve higher NUE values
consistent with high yields. N uptake was
highest in the Manage-N method, probably
due to better timing of split N applications
based on the model. The STCR-N method
gave the second highest N uptake. All other
N treatments gave similar N uptake values
(106–114 kg N ha–1), which were significantly superior to that of the control.
Results of the 1998 on-station trial
showed that the Manage-N method
produced the highest yield (Table 2). All
other treatments produced the same
yields, which were significantly higher than
the yield of the local recommendation (125
kg N ha–1). As in 1997, the target yield of 8
t ha–1 was not reached in the STCR-N and
Manage-N treatments. In on-farm trials,
Table 2. Total N, applied N, and grain yield of irrigated transplanted rice (cv ADT36) under
various N sources and N management practices in on-station and on-farm trials at TNRRI,
Aduthurai,Tamil Nadu, India, 1998 dry season.a
On-station trial
On-farm trial (mean of 4 farms)
N treatment
Total N applied
(kg ha–1)
Local N recommendation
(farmers’ practice)
STCR-N for 8 t ha–1
yield targetb
Manage-Nc
SPAD-35 N
CRU 4.5%d
CRU 6.0%d
CDe (.05)
Grain yield
(t ha–1)
Total N applied
(kg ha–1)
Grain yield
(t ha–1)
125.0
4.3 c
121.4
5.5
163.1
4.6 b
124.4
5.7
168.0
105.0
97.9
97.9
5.2 a
4.7 b
4.6 b
4.7 b
0.22
125.0
101.3
74.6
74.6
6.3
5.4
6.1
6.4
–
a
Means followed by the same letter are not significantly different at LSD (5% level). bApplied in four equal splits: basal, 15,
30, and 45 d after transplanting (DAT). cApplied in four equal splits at 13 DAT, 23 DAT, panicle initiation, and flowering.
d
Applied as a single dose at last puddling. eCD = critical difference.
mean grain yield with the Manage-N treatment was similar to that with 75 kg N ha–1
as CRU 6%. The CRU 6% treatment provided the N needs of the crop throughout
its growth period, probably similar to that
provided by four equal split applications
of N in the Manage-N treatment. On the
other hand, the SPAD treatment produced
lower yields than the other treatments,
suggesting a need to adjust the SPAD
threshold to a higher value to optimize rice
yields.
Our results showed that the
Manage-N and STCR-N methods produced
high grain yields with low NUE values;
further refinement of these methods is
needed to improve yields and NUE. The
SPAD method has to be evaluated with a
higher SPAD threshold value (e.g., 37) to
see whether high grain yields can be
obtained in the Cauvery Delta. The N rate
that will be applied as a single basal dose
of CRU before planting requires further
study.
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation of
knowledge-intensive nitrogen management
technologies for rice systems. Nutr. Cycl.
Agroecosyst. 53:59-69.
Cassman KG, Pingali PL. 1995. Extrapolating trends
from long-term experiments to farmers’ fields:
the case of irrigated rice systems in Asia. In:
Barnett V, Payne R, Steiner R, editors.
Agricultural sustainability: economic,
environmental and statistical considerations.
New York: Wiley. p 64-84.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas RM,
Cassman KG. 1996. Increased N-use efficiency
using a chlorophyll meter on high-yielding
irrigated rice. Field Crops Res. 47:243-252.
Shoji S, Gandeza AT, editors. 1992. Controlledrelease fertilizers with polyolefin resin coating.
Sendai (Japan): Tohoku University and Konno
Printing Co. Ltd.
Thiyagarajan TM, Sivasamy R, ten Berge HFM. 1994.
Time course of leaf nitrogen concentration
required to attain target yields in transplanted
rice. In: ten Berge HFM, Wopereis MCS, Shin
JC, editors. Nitrogen economy of irrigated rice:
field and simulation studies – SARP Research
Proceedings, April 1994. Wageningen (The
Netherlands): DLO Research Institute for
Agrobiology and Soil Fertility, and Manila
(Philippines): IRRI. p 267-282.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Information support system for rice crop management
TropRice is an information support system of best-bet practices designed to provide practical field-level guides for rice crop management in the
tropics. It aims to help users make informed decisions related to rice production.
It is not a single system for the world. It contains some generic information, but some is site- or region-specific. TropRice is intended to be a
template that could be modified for different environments. As improved systems on component technologies become available, they will replace
or be linked to the system.
TropRice is an ongoing project intended for intermediary technology transfer agents and farmers who have no
access to information on how to grow rice.
Web site: http://www.cgiar.org/irri/TropRice
26
August 2000
Optimizing chlorophyll meter threshold values for different
seasons and varieties in irrigated lowland rice systems
of the Cauvery Delta zone, Tamil Nadu, India
M. Babu, R. Nagarajan, and S.P. Ramanathan, Soil and Water Management Research Institute (SWMRI), Thanjavur 613501,
Tamil Nadu, India; and V. Balasubramanian, IRRI
Innovative tools such as the chlorophyll or
SPAD meter offer a new strategy for
optimizing fertilizer nitrogen (N)
application in rice (Peng et al 1996,
Balasubramanian et al 1999). A simple and
portable device, the SPAD meter provides
a nondestructive and accurate measurement of rice leaf N status in situ in the field.
It thus helps assess the N topdressing requirements of rice crops. Earlier studies
indicated that critical SPAD values could
be established for different varieties and
growing seasons, depending on local growing conditions (Balasubramanian et al 1999).
This study was conducted to determine the
critical values for optimizing grain yield and
N use efficiency for different rice varieties
and growing seasons in the Cauvery Delta
of Tamil Nadu.
On-station trials were conducted at
the experimental farms of SWMRI in
Thanjavur (representing the New Cauvery
Delta area) during the 1996, 1997, and 1998
dry seasons [DS (kuruvai): June to
September] and 1997-98 first wet season
[WS-I (samba): August to January] and
second wet season [WS-II (thaladi):
October to February]. Different SPAD
threshold levels (29, 31, 33, 35, 37, and 39)
were evaluated along with the local N
recommendation of 125 (dry season) or
150 (wet season) kg N ha–1 and a zero-N
control. Treatments were arranged in a
randomized complete block design with
three replications. Rice varieties used for
different seasons and locations are given
in the table.
SPAD readings were taken weekly
in all treatments starting from 14 d after
transplanting (DAT) until first flowering,
using the youngest fully expanded leaf of
10 randomly selected plants from each
plot. For the SPAD-N treatments, N was
applied whenever the SPAD reading fell
below the set critical threshold value. DurIRRN 25.2
ing the DS, N was applied each time at the
rate of 30 kg N ha–1 at early to maximum
tillering stage, 45 kg N ha–1 at maximum
tillering to panicle initiation (PI) stage, and
30 kg N ha–1 at PI to flowering stage; for
the wet season, it was reduced to 20, 30,
and 20 kg N ha–1, respectively, for the three
growth stages. Phosphorus (P) and
potassium (K) were applied at 23 kg P and
40 kg K ha–1 during the dry season, and at
27 kg P and 48 kg K ha–1 during the wet
season. A full dose of P and 50% of K were
incorporated into the soil at last puddling
and the remaining K was topdressed at PI.
Zinc at 10 kg ha–1 was also applied along
with P and K at last puddling in Zn-deficient soils.
Two indicators of N use efficiency
were used in this study: agronomic
efficiency of applied N (AEN) and partial
factor productivity of N (PFP-N).
The 1996 DS trials showed that cv
ADT36 and IR50 produced significantly
higher grain yields at a SPAD threshold
value of 35 compared with 29, 31, and 33
(see table). No significant difference in
grain yields, however, was observed
between SPAD 35 and 39 in ADT36, and
among SPAD 33, 35, and 37 in IR50 during
the 1997 DS. In both varieties, grain yield
was highest at SPAD 39, but it was not
significantly different from that of SPAD 35
in ADT36 and SPAD 35 and 37 in IR50. In
the 1998 DS, grain yields were significantly
lower at SPAD 35 than those at SPAD 37,
which were on a par with SPAD 39 in varieties ADT36 and ADT42. These results indicate that a SPAD threshold of 35 to 37
will optimize grain yield and N use efficiency for the three test varieties. The respective AEN values for SPAD 35 and 37
were 49 and 31 in 1997 and 80 and 51 in
1998.
During the 1996 WS-I and WS-II,
yields were relatively low and crop re-
sponse to N was poor (see table). In WS-I,
White Ponni had the highest yield with 3.9
t ha–1 at SPAD 35, but it was not significantly different from that of SPAD 31 and
33. Similarly, in WS-II, grain yields of cv
TRY1 were not significantly different at
SPAD 29, 31, 33, and 35. The AEN values
were 14 for White Ponni and 10–11 for
TRY1 at SPAD thresholds of 31–35. In the
1997 WS-I and WS-II, when higher SPAD
values were used, grain yields of both varieties did not vary significantly at SPAD 35,
37, and 39. The AEN values were 13–14
for White Ponni and 15–22 for TRY1 at
yields of 3.6–4.2 t ha–1. In 1998, rice variety ASD19 produced grain yields of 4.1 t
ha–1 at SPAD 37 and 39; in WS-I, corresponding AEN values were 26 and 21. The
yield of cv ADT38 in WS-II was significantly
higher at SPAD 39 than at 37 or 35; corresponding AEN values were 20, 23, and 27.
These results indicated that a SPAD threshold value of 37 will optimize grain yield and
fertilizer use efficiency of modern varieties grown during the wet season.
In conclusion, critical SPAD values
vary between 35 and 37 depending on
season and rice variety. For modern
varieties, a SPAD threshold value of 35–37
is optimum during the DS (kuruvai), while
SPAD 37 is suitable for the WS (samba and
thaladi).
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation
of knowledge-intensive nitrogen
management technologies for rice systems.
Nutr. Cycl. Agroecosyst. 53:59–69.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas
RM, Cassman KG. 1996. Increased N-use
efficiency using a chlorophyll meter on
high-yielding irrigated rice. Field Crops Res.
47:243–252.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
27
Mean grain yield and N use efficiency of irrigated transplanted rice varieties under different SPAD threshold levels, SWMRI farm,Thanjavur
(New Cauvery Delta area),Tamil Nadu, India, 1996-98 dry and wet seasons.a
SPAD threshold
level/season/variety
1996
1997
1998
DS (kuruvai)
Rice variety: ADT36
Control
Control
Control
SPAD 29
SPAD 33
SPAD 33
SPAD 31
SPAD 35
SPAD 35
SPAD 33
SPAD 37
SPAD 37
SPAD 35
SPAD 39
SPAD 39
IR50
IR50
ADT42
Control
Control
Control
SPAD 29
SPAD 33
SPAD 33
SPAD 31
SPAD 35
SPAD 35
SPAD 33
SPAD 37
SPAD 37
SPAD 35
SPAD 39
SPAD 39
LSD 0.05
WS-I (samba)
W. Ponni
W. Ponni
ASD19
Control
Control
Control
SPAD 29
SPAD 33
SPAD 33
SPAD 31
SPAD 35
SPAD 35
SPAD 33
SPAD 37
SPAD 37
SPAD 35
SPAD 39
SPAD 39
WS-II (thaladi)
TRY1
TRY1
ADT38
Control
Control
Control
SPAD 29
SPAD 33
SPAD 33
SPAD 31
SPAD 35
SPAD 35
SPAD 33
SPAD 37
SPAD 37
SPAD 35
SPAD 39
SPAD 39
LSD 0.05
a
Grain yield (t ha–1)
1996
1997
1998
N applied (kg ha–1)
1996
1997
1998
1996
AEN (kg grain kg–1 N)
1997
1998
4.1 b
3.7 b
3.8 b
4.0 b
5.7 a
2.8 d
4.2 c
5.3 ab
5.2 b
6.1 a
2.7 d
4.0 c
6.2 b
7.0 a
7.1 a
0
0
0
0
45
0
30
60
75
120
0
25
45
85
110
–
–
–
–
36
–
45
49
31
27
–
53
80
51
41
3.3 b
3.6 b
3.4 b
3.5 b
5.1 a
480
3.2 c
5.3 b
6.2 ab
6.0 ab
6.6 a
467
2.8 d
4.1 c
6.6 b
7.3 a
7.3 a
501
0
0
0
30
75
0
75
75
75
120
0
35
55
75
125
–
–
–
6
24
–
15
26
24
20
–
35
68
60
36
2.2 d
3.0 c
3.5 ab
3.6 ab
3.9 a
2.1 d
3.5 bc
3.8 ab
3.8 ab
4.3 a
2.0 d
3.2 c
3.5 c
4.1 b
4.1 b
0
50
100
100
120
0
90
130
140
160
0
50
70
80
100
–
17
14
14
14
–
16
14
13
14
–
23
21
26
21
2.1 d
2.9 c
2.9 c
3.2 bc
3.0 bc
2.0 d
3.1 c
3.6 b
4.0 ab
4.0 ab
558
2.0 d
3.1 c
3.9 bc
4.3 b
4.8 a
923
0
30
80
100
100
400
0
50
70
120
130
0
50
70
100
140
–
25
10
11
10
–
21
22
16
15
–
22
27
23
20
In a column, means followed by the same letter are not significantly different at the 5% level by DMRT. AEN = additional grain yield over control per kilogram N applied.
On-farm evaluation of chlorophyll meter-based
N management in irrigated transplanted rice
in the Cauvery Delta, Tamil Nadu, India
M. Babu and R. Nagarajan, TNRRI, Aduthurai 612101, Tamil Nadu; S. Mohandass, C. Susheela, P. Muthukrishnan, and
M. Subramanian, SWMRI, Thanjavur 613501, Tamil Nadu, India; and V. Balasubramanian, IRRI
Judicious use of nitrogen (N) fertilizer in
rice requires synchronizing N fertilizer applications with plant needs. Predicting
plant N requirement through soil testing
has not proven valuable for rice because
of dynamic changes in native N supply and
difficulty in predicting climatic variables
that control soil N mineralization and crop
growth. The chlorophyll meter is a simple,
portable device that accurately measures
leaf N status of rice plants in situ. It could
help improve grain yield and N use efficiency (Peng et al 1996, Balasubramanian
et al 1999).
28
The SPAD-guided N technique was
evaluated in farmers’ fields in the new and
old Cauvery Delta areas of Tamil Nadu,
India, during the 1996-98 wet and dry seasons (DS, kuruvai: June to September; WSI, samba: August to December/January;
WS-II, thaladi: October to February). Trials were conducted by TNRRI and SWMRI
to compare grain yield and N use efficiency
of irrigated transplanted rice under different N management practices. Three N
treatments—zero-N control, local N recommendation, and SPAD-guided N—were
evaluated in the 1996-97 trials. A fourth
treatment of SPAD-guided N with a basal
application of 20 kg N ha–1 was included
in the 1997-98 trials. Each farm had one
replication in the old area and two in the
new area.
Soils of the experimental fields in
the new Cauvery Delta belong to two series—Madukkhur (Alfisol) and Pattukkottai
(Alfisol)—while those of the old Cauvery
Delta constitute three major series—Kalathur
(Udorthentic Chromustert), Adanur (Entic
Chromustert), and Padugai (Typic
August 2000
Table 1. Total N applied, grain yield, and N use efficiency of irrigated transplanted rice under different N management practices in the new
Cauvery Delta area of Tamil Nadu, India, 1996-98 cropping seasons.a
WS-I (samba)b
DS (kuruvai)
Treatment
I996-97
Control
Local N recommendation
SPAD-based N
1997-98
Control
Local N recommendation
SPAD-based N
Basal + SPAD-N
N
applied
(kg ha–1)
Grain
yield
(t ha–1)
AENc
2 farms (2 reps each)
5.3 b
–
6.4 a
8.8
7.1 a
29.0
6 farms (2 reps each)
0
2.9 b
–
125 (3)
3.9 a
7.6
75 (3)
4.1 a
13.5
107 (4)
4.4 a
15.9
0
125 (3)
60 (2)
N
applied
(kg ha–1)
Grain
yield
(t ha–1)
7 farms (2 reps each)
0
3.4 b
150 (4)
4.8 a
56 (2)
4.6 a
3 farms (2 reps each)
0
2.7 b
150 (4)
3.8 a
72 (3)
3.5 a
92 (4)
3.4 a
WS-II (thaladi)
AEN
–
9.7
20.7
–
7.3
11.3
8.0
N
applied
(kg ha–1)
Grain
yield
(t ha–1)
AEN
3 farms (2 reps each)
0
3.4 b
–
150 (4)
5.1 a
11.7
60 (2)
5.1 a
32.0
3 farms (2 reps each)
0
2.5 b
–
150 (4)
3.4 a
5.6
55 (2)
3.1 a
10.6
65 (3)
3.0 a
6.4
a
All treatments received 22-42-10 kg ha–1 of P, K, and Zn in the dry season and 26-50-10 kg ha–1 of P, K, and Zn in the wet season. Means followed by a common letter are not significantly
different at the 5% level by DMRT. Number in parentheses refers to number of split N applications. bFlood affected yields during 1997-98. cAEN = additional grain yield over control
per kilogram N applied.
Ustifluent). The number of on-farm trials
conducted during each season is given in
Tables 1 and 2.
In SPAD-guided N treatments, leaf
N status was monitored weekly starting
from 14 d after transplanting (DAT) until
first flowering. Measurements were obtained from the youngest fully expanded
leaf of 10 randomly selected plants from
each plot. Whenever the average SPAD
reading fell below the critical value of 35,
N fertilizer was applied immediately.
During the DS, the amount of N applied
each time was 30 kg N ha–1 from early to
maximum tillering stage (14–28 DAT), 45
kg N ha–1 from maximum tillering to
panicle initiation (PI) stage (29–48 DAT),
and 30 kg N ha–1 from PI to flowering (49
DAT to flowering); it was reduced to 2030-20 kg N ha–1 for corresponding stages
in the WS. All treatments received a basal
application of 22-40-10 kg ha–1 of phosphorus (P), potassium (K), and zinc (Zn) in the
DS and 26-50-10 kg ha–1 of P, K, and Zn in
the WS. Zinc was applied only to Zn-deficient soils.
Grain yield was determined from
three 5-m2 sample areas from each plot at
14% moisture content. The agronomic efficiency of applied N (AEN) was calculated
as additional grain yield over the control
per kilogram N applied.
Trial results indicated no significant
differences in crop response to N treatIRRN 25.2
Table 2.Total N applied, grain yield, and N use efficiency of irrigated transplanted rice under
different N management practices in the old Cauvery Delta area of Tamil Nadu, India, 199698.a
Treatment
N applied (kg ha–1)
Grain yield (t ha–1)
AENb
1996-98 dry seasonc
1996 DS (mean of 5 farms)
Control
Local N recommendation
SPAD-35 N
0
125 (3)
105 (3)
5.1 c
5.8 b
6.7 a
–
5.3
14.6
1997 DS (mean of 12 farms)
Control
Local N recommendation
SPAD-35 N
Basal + SPAD-35 N
0
125 (3)
67 (2)
88 (3)
4.9 c
7.1 b
8.3 a
7.7 a
–
21.5
50.5
31.9
1998 DS (mean of 7 farms)
Control
Local N recommendation
SPAD-35 N
Basal + SPAD-35 N
0
125 (3)
61 (2)
67 (3)
4.0 b
6.1 a
6.1 a
5.8 a
–
16.5
36.4
27.3
1997-98 wet seasond
WS-1: samba (mean of 9 farms)
Control
Local N recommendation
SPAD-N
Basal + SPAD-N
0
150 (4)
69 (3)
89 (4)
4.3 b
7.4 b
7.4 a
7.3 a
–
20.9
45.2
33.7
WS-II: thaladi (mean of 6 farms)
Control
Local N recommendation
SPAD-N
Basal + SPAD-N
0
150 (4)
70 (3)
90 (4)
3.4 c
5.5 ab
5.7 a
5.4 ab
–
13.9
32.1
21.7
a
Means followed by a common letter are not significantly different at the 5% level by DMRT. Number in parentheses refers
to number of split N applications. bAEN = additional grain yield over control per kilogram N applied. cAll treatments
received 22-42-10 kg ha–1 of P, K, and Zn. dAll treatments received 26-50-10 kg ha–1 of P, K, and Zn.
ments in various soil series in both zones;
hence, data across soil series were pooled
for analysis and interpretation. In farms of
the new Cauvery Delta, grain yields were
generally higher for all seasons in 1996-97
than in 1997-98 (Table 1) due to heavy rain29
fall and flooding at critical crop growth
stages in 1997-98. In both good and bad
years, the SPAD-guided N treatment recorded a significantly higher grain yield
than the control, but it was on a par with
the local N recommendation in all three
cropping seasons. The AEN values of the
SPAD treatment were 1.5–2.5 times that
of the local N recommendation (Table 1).
Savings in fertilizer rates of 50–65 kg N
ha–1 were recorded during the DS; 78–95
kg N ha–1 were saved during the WS. Data
also indicated that no basal N application
is required for the SPAD method in soils
of the new Cauvery Delta because there
was no substantial increase in grain yield
with a basal application of 20 kg N ha–1.
In farms of the old Cauvery Delta,
the crop response to different N
treatments was similar to that observed in
the new Cauvery Delta (Table 2). Likewise,
AEN values followed the same trend. Grain
yield was highest for the SPAD method, but
it was on a par with the local N recommendation and SPAD method with a basal application of 20 kg N ha–1. The data again
indicated that basal N application is not advantageous for various soil types in the old
Cauvery Delta. An average savings of 80 kg
ha–1 for N fertilizer was obtained in both
the DS and WS.
These results clearly demonstrated
the advantage of using the chlorophyll
meter technique to fine-tune N recommendations for various seasons in the Cauvery
Delta. There is a potential to save 50–95
kg N ha–1 if refined N recommendations
are used. This study focused on using a
single SPAD threshold value to assess N
needs of rice crops. Further research is
ongoing to determine the effect of using a
range of SPAD values (e.g., 32–34, 35–37,
38–40, etc.) for synchronizing N application with crop demand in rice.
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation
of knowledge-intensive nitrogen
management technologies for rice systems.
Nutr. Cycl. Agroecosyst. 53:59-69.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas
RM, Cassman KG. 1996. Increased N-use
efficiency using a chlorophyll meter on
high-yielding irrigated rice. Field Crops Res.
47:243-252.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Efficiency of controlled-release urea and coated urea
fertilizers in irrigated transplanted rice
in Andhra Pradesh, India
K. Padmaja, R.M. Kumar, S.P. Singh, A.G.K. Murthy, and S.V. Subbaiah, Directorate of Rice Research (DRR), Hyderabad
500030, Andhra Pradesh, India
Nitrogen (N) is one of the major nutrients
applied to rice. The recovery of N from N
applied to wetland rice, however, seldom
exceeds 40% (De Datta and Buresh 1989).
Thus, new methods or strategies are
needed to improve the agronomic and
economic efficiency of N fertilizers in rice
that would also minimize fertilizer-related
environmental pollution. Some of the
promising N management techniques
include split application, subsurface
placement, and the use of slow-release and
coated urea fertilizers (Mohanty et al 1999).
We evaluated the relative efficiency
of selected controlled-release urea (CRU)
and coated urea fertilizers compared with
a single basal application of prilled urea on
irrigated transplanted rice (cv Ajaya) at the
DRR farm, Andhra Pradesh, India. Field
trials were conducted during the monsoon
(kharif: July to October 1997) and winter
30
(rabi: November 1997 to March 1998)
seasons on a typic Vertisol soil (pH in water
8.3, cation exchange capacity (CEC) 45
cmol P+ kg–1, organic carbon 5.5 g kg–1,
available KMnO4-extractable N 150 kg
ha–1, Olsen P 30.4 kg ha–1, and NH4Ac-extractable K 244.5 kg ha–1). Treatments were
four types of fertilizer N and a no-N control (Table 1) arranged in a randomized
complete block design with three replications.
Types of fertilizer N used were CRU
with 4.5% and 6% coating, gypsum-coated
urea (GCU), neem-coated urea (NCU), and
commonly available prilled urea (PU).
CRU, a free-flowing granular fertilizer
coated with polyurethane and wax, had
43% N, 1.3% biuret, 120 ppm free
ammonia, 0.08% moisture, and 1.8%
conditioner. All fertilizers were broadcast
in a single dose of 86 kg N ha–1 just before
planting. Phosphorus (P) as single superphosphate and potassium (K) as muriate
of potash were applied to all plots at locally recommended rates of 27 kg P and
32 kg K ha–1.
Among different fertilizers, CRU 6%
produced the highest grain yields, whereas
a single basal application of PU had the
lowest yields in both seasons (Table 1).
Grain yields obtained with CRU 6% were
38% and 27% higher than those obtained
with PU in the monsoon and winter
seasons, respectively. In the monsoon
season, yield of CRU 6% was significantly
higher than that of CRU 4.5%, but, during
winter, there was no significant difference
in grain yield of the two CRU fertilizers.
Grain yields produced by GCU and NCU
were similar but significantly lower than
those of the two CRUs in the monsoon
season. During the winter season, howAugust 2000
Table 1. Effect of controlled-release and coated urea fertilizers on grain yield and N use efficiency of rice (cv Ajaya) in two seasons, 1997-98,
Andhra Pradesh, India.a
Grain yield (t ha–1)
Treatment
N uptake (kg ha–1)
N recovery efficiency (%)
AEN
PFP-N
b
Monsoon Winter Mean
crop
crop
Control
CRU 4.5%
CRU 6.0%
GCU
NCU
Prilled urea
CD (5%)
2.3 e
4.7 c
6.0 a
5.4 b
5.2 b
3.7 d
0.35
2.1 d
5.5 a
5.7 a
5.2 b
5.1 b
4.1 c
0.48
2.2
5.1
5.9
5.3
5.1
3.9
–
Monsoon Winter
crop
crop
51.5 e
101.5 c
142.1 a
115.9 b
105.2 c
77.9 d
8.34
Mean Monsoon Winter Mean Monsoon Winter Mean Monsoon Winter
crop
crop
crop
crop
crop
crop
45.9 d 48.7
84.6 b 93.0
92.2 a 117.1
93.4 a 104.6
94.1 a 99.6
53.0 c 65.5
5.78
–
58.1
105.3
74.9
58.7
30.7
–
–
45.0
53.8
55.2
56.0
8.2
–
–
51.6
79.6
65.1
57.4
19.5
–
–
39.6
42.0
35.8
34.7
23.9
–
–
29.3
45.2
38.2
35.4
18.3
–
–
34.5
43.6
37.0
35.1
21.1
–
–
54.2
70.4
63.4
60.6
43.5
–
Mean
–
63.7
66.2
59.9
61.2
48.0
–
–
59.1
68.2
61.6
60.9
45.8
–
a
In a column, means followed by the same letter are not significantly different at CD 5% probability level. bN rate for all sources was 86 kg ha–1. GCU = gypsum-coated urea, NCU = neem
oil-coated urea, CRU = controlled-release urea, AEN = additional grain yield over control per kilogram N applied, PFP-N = total grain yield per kilogram N applied, CD = critical
difference.
Table 2. Economic analysis of using coated fertilizers.
Treatment
Mean yield
(t ha–1)
Gross value
(Rs ha–1)a
Additional
labor costb
(Rs ha–1)
Net value
(Rs ha–1)
Net value to
investment
(Rs Rs–1)
Additional value
to investment
(Rs Rs–1)
Additional
value
(%)
CRU 4.5%
CRU 6.0%
GCU
NCU
PU
5.1
5.9
5.3
5.1
3.9
25,400
29,350
26,500
25,650
19,500
1,120
1,900
1,340
1,170
–
24,280
27,450
25,160
24,480
19,500
33.1
37.1
34.0
33.1
26.6
6.5
10.5
7.4
6.5
–
24.4
39.5
27.8
24.4
–
a
US$1 = Rs 42.00. Cost of PU = Rs 8.60 kg–1, cost of rough rice = Rs 5.00 kg–1. bAdditional labor cost for harvest and postharvest processing of additional produce.
ever, grain yields of CRU 4.5%, GCU, and
NCU were on a par and the performance
of CRU 6% was significantly superior to that
of GCU and NCU.
Agronomic efficiency of applied N
(AEN) and partial factor productivity for
applied N (PFP-N) (Peng et al 1996) were
43.6 and 68.2 for CRU 6%, respectively.
Mean AEN values ranged from 34.5 to 37.0
and the PFP-N ranged from 59.1 to 68.2
for other coated fertilizers. The single basal
application of PU was the least efficient
(AEN = 21.1, PFP-N = 45.8). Total N uptake
was highest in CRU 6% with 117 kg N ha–1
and lowest in the single basal application
of PU (55 kg N ha–1).
Financial returns to investment in
fertilizers were computed for different
fertilizer types. When prices of CRUs and
modified urea were assumed to be equal
to that of commonly available PU (Rs 8.6
per kg N as PU), the analysis indicated a
24–40% additional net value for money
invested in CRUs and modified urea
IRRN 25.2
(Table 2). This means that, if these fertilizers are priced at less than 124–140% of the
price of PU, they will be competitive in the
market. Mean values over several seasons
and sites must be considered to achieve
the economic advantage and comparative
pricing of CRU fertilizers.
These results revealed that CRU 6%
was better than all other coated fertilizers
in rice yield, N use efficiency, and plant N
uptake. CRU 4.5% was comparable with
other coated fertilizers (GCU and NCU). If
appropriately priced, CRU fertilizers will be
economically competitive with the
commonly available PU, and may become
an important source of N fertilizer for rice
with a high N use efficiency.
References
De Datta SK, Buresh RJ. 1989. Integrated nitrogen
management in irrigated rice. Adv. Soil Sci.
10:143-169.
Mohanty SK, Singh U, Balasubramanian V, Jha KP.
1999. Nitrogen deep-placement technologies for productivity, profitability, and
environmental quality of rainfed lowland
rice systems. Nutr. Cycl. Agroecosyst.
53:43-57.
Peng S, Garcia FV, Gines HC, Laza RC, Samson MI,
Sanico AL, Visperas RM, Cassman KG. 1996.
Nitrogen use efficiency of irrigated tropical
rice established by broadcast wet-seeding
and transplanting. Fert. Res. 45:123-134.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
New handbook and CD
on nutrient deficiencies
The Handbook and CD titled Rice:
nutrient deficiencies and nutrient
management will soon be available.
For more information about this
publication, e-mail:
[email protected] or
[email protected]
31
Varietal response to different nitrogen management methods
in an irrigated transplanted rice ecosystem in a Vertisol,
Andhra Pradesh, India
R.M. Kumar, K. Padmaja, S.V. Subbaiah, Directorate of Rice Research (DRR), Hyderabad 500030, Andhra Pradesh, India;
and V. Balasubramanian, IRRI
Nitrogen (N) fertilizer is a major input for
rice. Only 30–40% of applied N is used by
the crop, however, due to losses through
volatilization, denitrification, leaching, and
runoff (De Datta and Buresh 1989). Deep
placement of urea, split N application,
preplanting incorporation of coated and
controlled-release urea (CRU), and the
chlorophyll meter and leaf color chart techniques are some N management strategies
that could reduce N losses and improve
fertilizer use efficiency in rice (Katyal et al
1985, Kumar et al 1989, Peng et al 1996,
Balasubramanian et al 1999). Since rice
varieties differ in N use efficiency (NUE),
this study was conducted to determine
their response to selected N management
techniques.
Field trials were conducted at the
DRR farm, Andhra Pradesh, India, during
the 1997 monsoon (kharif, July to October)
and 1997-98 winter (rabi, November to
February/March) seasons. The soil at the
experimental site is a typic Vertisol, with a
pH of 8.3, cation exchange capacity (CEC)
45 cmol P+ kg–1, organic carbon 5.5 g kg–1,
available (KMnO4-extractable) N 150 kg
ha–1, Olsen P 30.4 kg ha–1, and NH4Ac-extractable K 244.5 kg ha–1.
Five N treatments were evaluated:
zero-N control, controlled-release urea
with 4.5% and 6% coating, chlorophyll
meter-guided N, and prilled urea (PU) applied in two equal splits. The CRU fertilizers had 43% N, 1.3% biuret, 120 ppm free
ammonia, 0.08% moisture, and 1.8% conditioner. The two CRUs were broadcast at
the rate of 86 kg N ha–1 and incorporated
into the soil just before planting. PU (100
kg N ha–1) was applied in two equal splits:
50% basal and 50% topdressing at the maximum tillering stage.
32
Three rice varieties were used: Rasi
(short duration, 105 d, and yield potential
of 6.5 t ha–1), Ajaya (medium duration, 135
d, and yield potential of 7.5 t ha–1), and
Pusa Basmati (improved aromatic variety,
145 d, and yield potential of 4.5 t ha–1). All
varieties were transplanted at 20 × 10-cm
spacing. The two-factor factorial was
organized in a randomized block design
with three replications.
In all treatments, chlorophyll meter
readings were taken weekly starting from
14 d after transplanting (DAT) until first
flowering using the youngest fully
expanded leaf of 10 randomly selected
plants in each plot. For the SPAD method,
N was applied when measured mean SPAD
values fell below the threshold of 35 for
each of the three varieties. The amount of
N applied in the SPAD treatment varied
with season and crop growth stages. The
rate per application was 20, 30, and 20 kg
N ha–1 in the monsoon season and 30, 35,
and 20 kg N ha–1 in the winter season at
the early (14–28 DAT), rapid (29–48 DAT),
and late growth stages (49 DAT-first
flowering), respectively. Phosphorus (P)
and potassium (K) were applied in all plots
at locally recommended rates of 27 kg P
and 32 kg K ha–1. Locally recommended
practices were used for all other field
operations and crop care.
In the SPAD treatments, the total
amount of N applied to varieties Ajaya and
Rasi was 70 kg ha–1 in the monsoon and 75
kg ha–1 in winter. A lower amount was applied to Pusa Basmati—50 kg ha–1 in the
monsoon and 65 kg ha–1 in winter. For
short-duration Rasi, CRU 6% and SPAD-35
N gave higher grain yields than other
treatments in both seasons (Table 1). Yield
performances of CRU 4.5% and CRU 6%
were comparable in the winter season. The
mean increase in grain yield over PU-2
splits was 26% for SPAD-35 N, 24% for CRU
6%, and 7% for CRU 4.5%. The mean
agronomic efficiency of applied N (AEN)
and partial factor productivity for N (PFPN) were highest in the SPAD-35 N
treatment, followed closely by CRU 6%
(Table 1). Plant N uptake was highest
(111.8 kg N ha–1) in Rasi fertilized with CRU
6%; it had an N recovery of 87.4%.
The response of medium-duration
Ajaya to N application was better than that
of the other two varieties in both seasons
(Table 1). Application of CRU 6% produced
a mean grain yield over two seasons of 6.3
t ha–1, compared with 5.9 t ha–1 for SPAD35 N, 5.7 t ha–1 for CRU 4.5%, and 5.6 t
ha–1 for PU-2 splits. In the monsoon season, CRU 6% gave the highest grain yield,
which was on a par with CRU 4.5% but significantly superior to the other treatments.
In the winter season, grain yields of CRU 6%
and SPAD-35 N (6.8 t ha–1 each) were significantly higher than those of PU-2 splits
and CRU 4.5% (5.9 t ha–1 each). The AEN
and PFP-N values of these treatments
showed a similar trend (Table 1). Mean
AEN and PFP-N values over two seasons
were highest in the SPAD-35 N treatment,
followed closely by CRU 6%. Plant N uptake, however, was highest in CRU 6%
(110.0 kg N ha–1), followed by the SPAD35 N treatment (93.5 kg N ha–1).
The aromatic rice variety Pusa
Basmati was the least responsive to various
N treatments. The CRU 6% and SPAD-35
N treatments produced the highest grain
yield in the monsoon and winter,
respectively, followed by PU-2 splits. The
single application of CRU 4.5% was less
efficient than the other methods.
August 2000
Table 1. Response of three rice varieties to different N management methods in irrigated transplanted rice at the DRR farm, Andhra
Pradesh, India, 1997-98.a
Grain yield (t ha–1)
Total N uptake (kg ha–1)
Recovery (%)b
AENc
PFP-Nd
Treatment
1997
kharif
Rasi
Control
1.9 c
CRU 4.5%
3.5 b
CRU 6%
4.3 a
SPAD-35 N
4.8 a
PU-2 splits
3.3 b
Mean
3.6
Ajaya
Control
2.4 c
CRU 4.5%
5.5 ab
CRU 6%
5.7 a
SPAD-35 N
5.0 b
PU-2 splits
5.4 ab
Mean
4.8
Pusa Basmati
Control
1.4 c
CRU 4.5%
2.6 b
CRU 6%
3.3 a
SPAD-35 N
2.6 b
PU-2 splits
2.6 b
Mean
2.5
CDe (5%)
Varieties
0.2
Treatments
0.3
Varieties × treatments
1997-98
rabi
Mean
1997
kharif
2.0 c
5.5 ab
5.9 a
5.8 a
5.1 b
4.9
2.0
4.5
5.1
5.3
4.2
4.2
2.2 c
5.9 b
6.8 a
6.8 a
5.9 b
5.5
2.6 c
3.6 b
4.0 b
4.5 a
3.8 b
3.7
0.2
0.3
0.6
1997-98
rabi
Mean
37.1 e
79.3 c
91.4 a
83.7 b
61.6 d
70.6
36.2e
97.8 d
132.3 a
125.5 b
114.3 c
101.2
36.6
88.6
111.8
104.6
87.9
85.9
–
49.1
63.1
66.5
24.5
50.8
–
71.6
111.7
119.0
78.1
95.1
–
60.3
87.4
92.8
51.3
73.0
–
18.3
27.4
40.4
13.5
24.9
–
40.5
44.7
50.3
30.5
41.5
–
29.4
36.1
45.3
22.0
33.2
–
40.8
50.0
68.1
32.8
47.9
–
64.2
68.4
77.5
50.9
65.2
–
52.5
59.2
72.8
41.8
56.6
2.3
5.7
6.3
5.9
5.6
5.1
37.6 d
93.5 b
103.5 a
87.0 c
88.1 c
81.9
28.2 d
80.1 c
116.5 a
100.0 b
79.9 c
80.9
32.9
86.8
110.0
93.5
84.0
81.4
–
65.0
76.6
70.6
50.5
65.7
–
60.3
102.7
95.7
51.7
77.6
–
62.7
89.6
83.2
51.1
71.6
–
36.3
39.3
37.7
29.0
35.6
–
43.0
53.3
60.9
37.5
48.7
–
39.7
46.3
49.3
33.3
42.1
–
63.7
66.7
71.4
53.5
63.8
–
68.4
78.6
90.0
59.3
74.1
–
66.1
72.7
80.7
56.4
69.0
2.0
3.1
3.7
3.6
3.2
3.1
25.7 d
64.5 c
75.0 a
70.0 b
60.7 c
59.2
32.4 d
95.2 a
88.4 b
88.8 b
74.0 c
75.7
29.0
79.8
81.7
79.4
67.4
67.5
–
45.1
57.3
88.6
35.0
56.5
–
73.0
65.1
86.8
41.6
66.6
–
59.1
61.2
87.7
38.3
61.6
–
14.7
22.3
25.0
12.6
18.6
–
11.7
16.6
30.2
12.5
17.8
–
13.2
19.5
27.6
12.6
18.2
–
30.5
38.1
52.2
26.2
36.8
–
41.7
46.6
69.8
38.3
49.1
–
36.1
42.4
61.0
32.3
43.0
1.8
2.3
2.4
3.1
4.0
5.4
0.5
1997 1997-98 Mean 1997 1997-98 Mean
kharif
rabi
kharif
rabi
1997 1997-98
kharif
rabi
Mean
Treatment means within each variety followed by the same letter are not significantly different at CD 5% probability level. bRecovery efficiency: (Σ r = ∆ plant N uptake/N applied). cAEN
= additional grain yield over control per kilogram N applied. dPFP-N = total grain yield per kilogram N applied. eCD = critical difference.
a
The interaction between rice cultivars and N treatments was significant for
grain yield in both seasons. The highest
grain yield of 6.8 t ha–1 was recorded in
Ajaya given CRU 6% and SPAD-35 N
treatments during the winter season. The
N recovery (mean of two seasons) was
highest in SPAD-35 N, followed by CRU 6%
in all three cultivars; this was probably due
to the congruence of N supply with crop
demand.
The highest SPAD values were
observed at the maximum tillering stage
for all varieties (Table 2). SPAD values
recorded at critical crop growth stages
were higher for CRU 6% and SPAD-35 N
treatments than for PU-2 splits. The higher
SPAD values indicate a higher foliar N
concentration that led to higher grain
yield, plant N uptake, fertilizer N recovery,
and efficiency with CRU 6% and SPAD-35
N treatments. The highest total N uptake
by all varieties recorded in the CRU 6%
treatment indicated that this controlledrelease fertilizer maintained a steady N
IRRN 25.2
Table 2. SPAD values at critical growth stages of three rice varieties as influenced by various
N treatments, DRR farm, Andhra Pradesh, India, 1997-98 cropping seasons.
Maximum tillering
Treatment
Rasi
Control
CRU 4.5%
CRU 6%
SPAD-35 N
PU-2 splits
PU-basal
Ajaya
Control
CRU 4.5%
CRU 6%
SPAD-35 N
PU-2 splits
PU-basal
Pusa Basmati
Control
CRU 4.5%
CRU 6%
SPAD-35 N
PU-2 splits
PU-basal
Panicle initiation
Heading
1997
kharif
1997-98
rabi
Mean
1997
kharif
1997-98
rabi
Mean
1997
kharif
1997-98
rabi
Mean
30.6
44.6
39.7
38.7
39.3
39.5
32.1
38.4
38.2
40.2
38.9
35.9
31.3
41.5
39.0
39.5
39.1
37.7
31.6
36.8
39.9
38.1
37.4
35.6
32.0
37.5
40.3
39.0
37.0
33.1
31.8
37.2
40.1
38.6
37.2
34.4
29.7
34.1
36.2
34.7
29.7
29.7
28.3
33.2
35.7
34.0
28.8
28.8
29.0
33.7
36.0
34.4
29.3
29.3
31.0
40.3
41.1
38.0
38.8
39.8
32.3
38.2
41.1
38.7
39.8
38.6
31.6
39.3
41.1
38.4
39.3
39.2
30.5
32.2
35.5
35.5
33.6
32.9
29.0
31.8
35.0
40.6
32.3
33.5
29.8
32.0
35.3
38.1
33.0
33.2
30.8
32.4
35.6
34.0
32.7
30.1
30.1
32.5
33.2
34.7
30.9
30.0
30.5 ␣
32.5 ␣
34.4 ␣
34.4 ␣
31.8␣
30.5
33.0
42.8
42.8
43.1
40.4
41.1
32.0
39.5
42.1
37.4
34.9
41.1
32.5
41.2
42.4
40.3
37.7
41.1
33.0
37.4
38.8
36.0
36.8
35.7
31.3
36.2
38.0
41.3
35.9
33.8
32.2
36.8
38.4
38.7
36.3
34.8
34.0
37.9
36.1
37.1
38.2
36.0
33.2
35.3
37.4
38.7
33.2
30.4
33.6 ␣
36.6 ␣
36.8␣
37.9 ␣
35.7␣
33.2
33
supply to the crop throughout the growth
period.
These observations confirm that the
use of CRU 6% fertilizer and the
chlorophyll meter technique (SPAD-N)
produces high grain yields with high N
uptake and efficiency. CRU 6% also
appeared to be better than CRU 4.5%,
probably due to its slower N release profile.
If CRU could be priced competitively with
the commonly available PU, it could
become the preferred N fertilizer for rice.
Real-time N management using the chlorophyll meter and PU represents an attractive alternative for improving grain yields
and N use efficiency in rice.
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation
of knowledge-intensive nitrogen management technologies for rice systems. Nutr.
Cycl. Agroecosyst. 53:59-69.
De Datta SK, Buresh RJ. 1989. Integrated nitrogen
management in irrigated rice. Adv. Soil Sci.
10:143-169.
Katyal JC, Singh B, Sharma VK, Grasswell ET. 1985.
Efficiency of some modified urea fertilizer
for lowland rice grown on a permeable soil.
Fert. Res. 6:279-290.
Kumar V, Shrotriya GC, Kaore SV, editors. 1989.
Soil fertility and fertilizer use. Vol. III. Urea
supergranules for increasing nitrogen use
efficiency. New Delhi (India): Indian
Farmers Fertilizer Cooperative. 143 p.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas
RM, Cassman KG. 1996. Increased N-use
efficiency using a chlorophyll meter on
high-yielding irrigated rice. Field Crops Res.
47:243-252.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Assessment of chlorophyll meter-based N application at
critical growth stages of irrigated transplanted rice
S.P. Ramanathan and R. Nagarajan, SWMRI, Thanjavur, India; and V. Balasubramanian, IRRI
Synchronizing nitrogen (N) application
with crop demand and soil N supply is one
strategy for improving N use efficiency
(NUE) in rice. Using a variable N rate application based on observed chlorophyll
meter readings at critical growth stages
may help optimize grain yield and NUE at
the same time. The chlorophyll or SPAD
meter can accurately measure leaf chlorophyll content that is related to leaf N status. It could help develop need-based N
fertilization in rice (Peng et al 1996). One
disadvantage of the SPAD technique, however, is the need for weekly observations
to monitor crop N status, which could
sometimes lead to many (3–6) split N applications (Balasubramanian et al 1999).
Field experiments were conducted
during the 1997-98 dry (DS, kuruvai: June
to September) and wet (WS-II, thaladi:
October to February) seasons at the
SWMRI farm in Thanjavur, India. The objective was to determine whether chlorophyll meter readings taken only at critical
crop growth stages—early tillering, active
tillering, panicle initiation, and 10% flowering—were sufficient, and to apply variable rates of N based on a range of SPAD
threshold values (Table 1) rather than on
a single critical SPAD value. The effect of
variable rate N application, based on a
range of chlorophyll meter readings, on
34
grain yield and NUE was measured in these
trials. Treatments included different ranges
of SPAD threshold values: <32, 33–35, and
36–38. Rice varieties ADT42 (115 d) and
ADT38 (135 d) were used during the DS
and WS-II, respectively. Treatments were
arranged in a completely randomized
block design with seven replications.
SPAD readings were taken in all
treatments at critical crop growth stages
using the youngest fully expanded leaf of
10 randomly selected plants from each
plot. Whenever average SPAD readings fell
within a set range of threshold values, N
was applied immediately based on the variable rates specified in Table 1. Plant N status was allowed to fall to the specific range
of SPAD values for each treatment before
N was applied.
Grain yield (t ha–1) was determined at
14% moisture content from three 5-m2
sample areas taken from each plot. The NUE
is expressed as the partial factor productivity
of applied N (PFP-N).
Grain yields were low in both the
1997-98 DS and WS due to heavy flooding
at critical crop growth stages. Among the
SPAD threshold ranges used in the DS, the
36–38 range gave the highest grain yield
(4.9 t ha–1), but it was not significantly different from that of SPAD <32 (4.7 t ha–1)
or 33–35 (4.6 ha–1) (Table 2). The NUE as
expressed by the PFP-N value was 125 for
SPAD <32, 92 for SPAD 33–36, and 54 for
SPAD 36–38. The data seem to indicate
that a SPAD threshold range of 36–38
could be optimum for DS rice crops. Further research is ongoing to confirm these
results.
In the WS, the highest grain yield
was obtained from SPAD 36–38; this was
not significantly different from that of
SPAD 33–35, but significantly different
from that of SPAD <32 (Table 2). More N
Table 1. Amount of N applied (kg ha–1) based on range of SPAD threshold values observed at
critical crop growth stages.
Range of SPAD
threshold values
<32
33–35
36–38
a
Early tillering
(14 DAT)a
Active tillering
(28 DAT)
Panicle initiation
(42 DAT)
Flowering
(56 DAT)
30
30
20
50
40
30
50
40
30
30
30
20
DAT = d after transplanting.
August 2000
Table 2. Effect of variable rate N application based on range of SPAD values observed at
critical crop growth stages on yield and N use efficiency of irrigated transplanted rice at the
SWMRI farm,Thanjavur, India, 1997-98 dry (DS) and wet seasons (WS).a
Range of
SPAD threshold
values
Total N applied
(kg ha–1)
DS
<32
33–35
36–38
SEc
LSDc (5%)
38
50
92
WS
58
70
104
PFP-Nb
Grain yield
(t ha–1)
DS
WS
4.7 a
4.6 a
4.9 a
347
nsc
3.3 b
3.7 ab
4.0 a
DS
125
92
54
202
530
WS
57
53
38
a
P, K, and Zn were applied to all treatments at the rate of 22-42-10 kg ha–1 in the DS and 26-50-10 kg ha–1 in the WS. bPFPN = total grain yield per kilogram N applied. cns = not significant. cSE = standard error, LSD = least significant difference.
(104 kg ha-1), however, was required at this
range to produce a yield of 4.0 t ha-1, which
resulted in a low PFP-N value of 38. SPAD
<32 produced the lowest yield with a to-
tween N topdressing in this treatment.
These observations suggested that, for
grain yield and NUE, a SPAD threshold
range of 33–35 could be optimum for the
WS rice in the new Cauvery Delta zone.
tal N use of 58 kg ha-1 (PFP-N = 57). Waiting for SPAD values to fall below 32 before
applying N fertilizer may have starved
plants for N during the long intervals be-
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation
of knowledge-intensive nitrogen management technologies for rice systems. Nutr.
Cycl. Agroecosyst. 53:59-69.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas
RM, Cassman KG. 1996. Increased N-use
efficiency using a chlorophyll meter on
high-yielding irrigated rice. Field Crops Res.
47:243-252.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Chlorophyll meter threshold values for N management
in wet direct-seeded irrigated rice
V. Balasubramanian and A.C. Morales, IRRI; and R.T. Cruz, Philippine Rice Research Institute (PhilRice), Maligaya, Nueva
Ecija, Philippines
Asian rice farmers are increasingly adopting wet seeding as an alternative method
to transplanting for economic and technical reasons. High-density, excessive early
vegetative growth and low foliar N concentration (Schnier et al 1990, Peng et al
1996b) characterize wet direct-seeded rice
(W-DSR). These characteristics will have an
impact on the critical leaf N concentration
required for high grain yields in W-DSR.
The chlorophyll or SPAD meter
offers a new strategy for synchronizing N
application with actual crop demand in rice
(Peng et al 1996a, Balasubramanian et al
1999). Earlier studies indicated that the
SPAD threshold or critical value of 35
established for transplanted rice invariably
overestimated the N requirement of and
reduced the N use efficiency (NUE) in WDSR (IRRI-CREMNET 1996). This study was
undertaken to establish specific SPAD
threshold values for maximizing both grain
yield and NUE in W-DSR in the Philippines.
In collaboration with PhilRice, we
conducted on-farm trials at Maligaya in the
IRRN 25.2
1996 dry (DS) and wet seasons (WS) and
in the 1997 DS (DS: December/JanuaryApril; WS: July-October). The objective was
to compare the grain yield and NUE of
irrigated W-DSR under different N
management practices. In the 1996 trials,
the SPAD method with a single SPAD
threshold of 35 was compared with the
farmers’ practice and a zero-N control. The
farmers’ practice consisted of 150 kg ha–1
N application in two or three splits in the
DS and 90 kg N ha–1 in the WS. In the 1997
DS, different SPAD threshold levels (29, 32,
and 35) were evaluated along with a fixed
N application rate of 120 kg ha–1 in two or
three splits and a zero-N control. Treatments were arranged in a randomized
complete block design with each farm as a
replication. The mean amount of P and K
applied was 13 kg P ha–1 and 25 kg K ha–1
in the 1996 DS, 17 kg P ha–1 and 28 kg K
ha–1 in the 1996 WS, and 26 kg P ha–1 and
50 kg K ha–1 in the 1997 DS.
SPAD readings were taken in all
treatments weekly starting from 21 d after
seeding (DAS) until first flowering, using
the youngest fully expanded leaf of 10
randomly selected plants from each plot.
For the SPAD-N treatments, N was applied
whenever the mean SPAD reading fell
below the chosen threshold values. The N
rates applied were 30, 45, and 30 kg ha–1
in the DS and 20, 30, and 20 kg ha–1 in the
WS during the early (21–35 DAS), rapid
(36–56 DAS), and late (57 DAS-flowering)
growth stages, respectively. The P and K
rates applied followed the local farmers’
practice.
Grain yield was expressed in kg
ha–1 at 14% moisture content. Two indicators of N use efficiency were used in this
study: agronomic efficiency of applied N
(AEN) and partial factor productivity of N
(PFP-N).
In the 1996 DS, grain yields and
efficiency values (AEN and PFP-N) were
high for 3-N splits in broadcast and 2-N
splits in row-seeded rice (Table 1). In spite
of the high yields, SPAD-35 N was the least
efficient due to a high N rate of 213 kg
35
Table 1. Comparison of the chlorophyll meter method and fixed-schedule N application in
irrigated direct-seeded rice, Maligaya, Nueva Ecija, Philippines, 1996 dry (DS) and wet seasons
(WS).a
Treatmentb
N used (kg ha–1)
Yield (t ha–1)
AENc
PFP-Nd
1996 DS: 13 kg P ha–1 & 25 kg K ha–1 (10 farms)
Control, B
–
–
SPAD-35 N, B
213
7
2-N splits, B
150
2
3-N splits, B
150
3
2-N splits, R
150
2
2.9 c
6.0 a
5.2 b
5.8 a
6.0 a
–
15 b
15 b
19 a
19 a
–
28
34
38
40
1996 WS: 17 kg P ha–1 & 28 kg K ha–1 (9 farms)
Control, B
–
–
SPAD-32 N, B
57
4
2-N splits, B
90
2
3-N splits, B
90
3
2-N splits, R
90
2
2.5 c
3.9 a
3.4 b
3.7 ab
3.8 ab
–
14 ab
11 b
14 ab
16 a
–
36
38
42
42
Splits (no.)
a
In a column, means followed by the same letter are not different at 5% probability by DMRT. bB = broadcast-sown rice, R
= row-seeded rice. cAEN = agronomic efficiency of applied N (grain yield over control per kilogram N applied). dPFP-N =
partial factor productivity for N (total grain yield per kilogram N applied).
SPAD value
40
T1
T2
T3
T4
T5
35
30
25
20
15
MT (35 DAS)
PI (56 DAS)
Plant growth stage
FL (77 DAS)
Mean SPAD values at critical crop growth stages (MT, PI, FL) of B-WSR and R-WSR (cv IR64),
Maligaya, Nueva Ecija, 1996 dry season (mean of 10 farms).
Table 2. Comparison between chlorophyll meter method with three thresholds and fixedschedule N application in irrigated direct-seeded rice, Maligaya, Nueva Ecija, Philippines,
1997 dry season.a
Treatment
N used (kg ha–1)
Splits (no.)
Broadcast-sown rice: 26 kg P ha–1 & 50 kg K ha–1 (10 farms)
Control
–
–
SPAD-29 N
100
4
SPAD-32 N
137
4–5
SPAD-35 N
180
6
2-N splits
120
2
3-N splits
120
3
Row-seeded rice: 26 kg P ha–1 & 50 kg K ha–1 (10 farms)
Control
–
–
SPAD-29 N
57
4
SPAD-32 N
114
4–5
SPAD-35 N
165
6
2-N splits
120
2
3-N splits
120
3
Yield (t ha–1)
AENb
PFP-Nc
4.4 c
6.8 ab
6.8 ab
6.5 b
6.5 b
6.9 a
–
25 a
18 b
12 c
18 b
21 b
–
68
50
36
54
58
4.7 c
6.1 b
6.8 a
6.6 ab
6.7 a
6.7 ab
–
25 a
19 ab
11 b
16 b
16 b
–
107
60
40
56
55
a
In a column, means followed by the same letter are not different at 5% probability by DMRT. bAEN = agronomic efficiency
of applied N (grain yield over control per kg N applied). cPFP-N = partial factor productivity for N (total grain yield per kg
N applied).
36
ha–1 applied in seven splits. In the 1996 WS,
SPAD-32 N gave the highest grain yield,
which was on a par with 3-N splits for
broadcast and 2-N splits for row-seeded
rice. All three methods were equally
efficient in N use.
In the DS, SPAD readings at
maximum tillering, panicle initiation, and
first flowering varied between 31–32 for
3-N splits in broadcast and 2-N splits in rowseeded rice and 32–33 for the SPAD
method (see figure). The trend was similar
in the WS (data not shown). This indicated
that the SPAD threshold value for W-DSR
appears to be around 32 for both DS and
WS.
In broadcast rice, SPAD-29 N, SPAD32 N, and the 3-N splits gave significantly
higher grain yields than the other
treatments (Table 2). The AEN was highest
in SPAD-29 N. Again, SPAD-35 N was the
least efficient. This suggested that, for highdensity (~800 productive tillers m–2)
broadcast-sown rice, the SPAD critical
value is around 29.
In row-seeded rice, SPAD-32 N
produced the highest grain yield with an
AEN of 19. Despite having the highest AEN,
SPAD-29 N had the lowest grain yield
among fertilized plots. The 2-N or 3-N splits
gave similar grain yields and AEN values.
The SPAD-35 N was the least efficient due
to the high N requirement (165 kg N ha–1)
for moderate yields. For the high-density
(662 panicles m–2) row-seeded rice, a SPAD
threshold of 32 maximized both grain yield
and NUE, which were similar to those of
2-N splits.
In conclusion, the SPAD threshold of
35, considered optimum for transplanted
rice, overestimated the N requirement and
drastically reduced the NUE of broadcast
and row-seeded rice.
A SPAD threshold of 29 for highdensity broadcast rice (800 panicles m–2)
and 32 for high-density row-seeded rice
(650 panicles m–2) appears to maximize
both grain yield and NUE.
The 3-N splits (at 21, 35, and 49
DAS) for broadcast rice and 2-N splits (at
21 and 42 DAS) for row-seeded rice produced high grain yields with high NUE that
August 2000
were similar to those of the SPAD technique with optimum threshold values for
the respective sowing methods.
Thus, the adequacy of farmers’
current N fertilization practices or local
recommendations can be verified by the
SPAD technique and adjusted, if necessary,
to optimize rice productivity.
References
Balasubramanian V, Morales AC, Cruz RT,
Abdulrachman S. 1999. On-farm adaptation
of knowledge-intensive nitrogen management technologies for rice systems. Nutr.
Cycl. Agroecosyst. 53:59-69.
IRRI-CREMNET (International Rice Research
Institute – Crop and Resource Management
Network). 1996. CREMNET annual report
for 1994-95. Manila (Philippines): IRRI.
Peng S, Garcia FV, Laza RC, Sanico AL, Visperas
RM, Cassman KG. 1996a. Increased N-use
efficiency using a chlorophyll meter on
high-yielding irrigated rice. Field Crops Res.
47:243-252.
Peng S, Garcia FV, Gines HC, Laza RC, Samson MI,
Sanico Al, Visperas RM, Cassman KG. 1996b.
Nitrogen use efficiency of irrigated tropical
rice established by broadcast wet-seeding
and transplanting. Fert. Res. 45:123-134.
Schnier HF, Dingkuhn M, De Datta SK, Marqueses
EP, Farolina JE. 1990. Nitrogen-15 balance in
transplanted and direct-seeded flooded rice
as affected by different methods of urea
application. Biol. Fertil. Soils 10:89-96.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
The leaf color chart (LCC)
Leaf color is generally used as a visual and subjective indicator of the rice crop’s need for nitrogen (N) fertilizer. Leaf color intensity is directly
related to leaf chlorophyll content and leaf N status.
Here is a tool that can help farmers improve their decision-making process in N management. The leaf color chart is a simple, easy-to-use,
and inexpensive guide that can help farmers determine the right time of N application to the rice crop by measuring leaf color intensity.
It is an ideal tool to optimize N use at reasonably high yield levels, irrespective of N source applied—organic, biological, or chemical
fertilizers.
The tool was developed from a Japanese prototype by the Crop and Resource Management Network (CREMNET) at IRRI and the Philippine
Rice Research Institute (PhilRice).
Features
• Made of high-quality plastic material
• Consists of six color shades ranging from light yellowish green (no.1) to dark green (no.6). Color strips fabricated with veins resembling those of rice leaves
Advantages
• Inexpensive, simple, easy to use
• Helps avoid too much N application
• Reduces lodging problem and pest and disease incidence
• Environment-friendly
• Savings in fertilizer use range from 0 to 53 kg N ha–1 in flooded rice
Limitations
Several factors influence LCC readings: varietal group, plant or tiller density, solar radiation differences between seasons, status of nutrients other than N in soil and plant, and biotic and abiotic stresses that induce discoloration of leaves.
Using the LCC
• Start taking LCC readings from 14 days after transplanting or 21 days after seeding. Take the last reading when the crop starts to
flower.
• Select at least 10 disease-free rice plants or hills in a field with uniform population.
• Under the shade, compare the color of the youngest fully expanded leaf of the selected plant or hill with the color strips of the chart.
• If more than five leaves read below a set critical value, apply 23 kg N ha–1 (if wet season) or 35 kg ha–1 (if dry season). The suggested
critical values are 4 for transplanted rice (TPR) and 3 for high-density wet-seeded rice (WSR).
• Repeat the process every 7–10 days or at critical growth stages (early tillering, active tillering, panicle initiation, and first flowering)
and apply N as needed.
The LCC is being introduced and distributed to farmers by field researchers
and extension staff of government and nongovernment organizations and privatesector agencies in different countries.
For comments and inquiries, contact
The CREMNET Coordinator
International Rice Research Institute
MCPO Box 3127, Makati City 1271
Philippines
E-mail: [email protected]
Fax: (63-2) 891-1292/845-0606
IRRN 25.2
37
Crop management & physiology
Chlorophyll stability index (CSI): its impact
on salt tolerance in rice
M. Madhan Mohan, S. Lakshmi Narayanan, and S.M. Ibrahim, Department of Agricultural Botany,
Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai 625104, India
Salinity is a major constraint to successful
agriculture in the arid and semiarid tropics. High-yielding varieties do not perform
well under salt stress conditions. Thus,
there is a need to develop special varieties
that can perform well under saline conditions. The area with potential saline soil is
about 20 million ha, and about 7 million
ha are severely affected by salinity. This
constitutes a major part of problem soils
in India. Irregular monsoon and irrigation
in red soil cause salinity problems in large
areas.
The chlorophyll stability index (CSI)
is an indication of the stress tolerance capacity of plants. A high CSI value means
that the stress did not have much effect
on chlorophyll content of plants. A higher
CSI helps plants to withstand stress
through better availability of chlorophyll.
This leads to increased photosynthetic
rate, more dry matter production, and
higher productivity. This indicates how
well chlorophyll can perform under stress.
This study was carried out to estimate the CSI of salt tolerance in rice using
three salt-tolerant varieties (CSR10, TRY1,
and CO 43) and four salt-susceptible varieties (IR20, White Ponni [WP], ADT36, and
Jaya) along with their hybrids in two soil
types (normal and salt-affected soil). Each
treatment was replicated five times in pot
cultures using a completely randomized
design.
The field experiment was conducted in normal soil on the college farm.
Salt-affected soil (sodic) was taken from a
farmer’s field at Elanthakulam (25 km
away) and transferred to pots for further
study. Soil samples were randomly collected from a depth of 30 cm from both
the college farm and Elanthakulam and
their nutrient status analyzed (Table 1).
CSI in the leaf was estimated using
a spectrometer following the method of
Koleyoreas (1958). It was calculated as the
difference in light transmission percentage
between treated and untreated leaf
samples (see formula).
Treated sample = 1,000 mg of leaf sample kept in a test tube containing
water at 55 °C for 1 h
Untreated/
= 1,000 mg of leaf sample kept in a test tube
(control)
containing water at room temperature
CSI
= OD at 652 nm of treated sample × 100
OD at 652 nm of control
Table 1. Soil properties of the experimental field.
Character
Normal soil
Texture
pH (1:2.5 soil:water suspension)
Electrical conductivity
(dS m–1) (1:2.5 soil:water suspension)
Sandy clay loam
7.2
Sandy clay loam
8.9
0.4
1.5 (soil)
2.5 (irrigation water)
Saline soil
Table 2. Effect of salt stress on CSI (%).
Variety/hybrid
CSR10
TRY1
CO 43
IR20
WP
ADT36
Jaya
IR20/CSR10
IR20/TRY1
IR20/CO 43
WP/CSR10
WP/TRY1
WP/CO 43
ADT36/CSR10
ADT36/TRY1
ADT36/CO 43
Jaya/CSR10
Jaya/TRY1
Jaya/CO 43
SEa
CDb
a
38
Experimental results are presented
in Table 2. Under normal soil conditions,
all varieties and their hybrids showed good
levels of CSI. Salt-tolerant cultivars CO 43,
TRY1, and CSR10 registered higher CSI
values, whereas susceptible varieties
Normal soil
Saline soil
74.4
82.8
83.3
72.9
74.5
73.5
71.2
73.3
75.6
75.2
74.2
76.6
78.5
73.3
77.7
78.1
72.5
75.7
77.8
0.156
0.311
71.9
80.3
82.0
68.9
69.5
68.2
67.8
74.7
74.3
79.8
75.8
75.4
69.8
70.9
70.7
81.9
70.6
71.3
73.7
0.3
0.598
% decrease (–)/
increase (+)
–3.36
–3.02
–1.56
–5.49
–6.71
–7.21
–4.78
+1.91
–1.72
+6.12
+2.16
–1.57
–11.08
–3.27
–9.01
+4.87
–2.62
–5.81
–5.27
SE = standard error, bCD = critical difference.
August 2000
ADT36, WP, IR20, and Jaya showed lower
values under saline conditions. This means
that under stress conditions, chlorophyll
content was affected to a greater extent in
susceptible varieties than in tolerant varieties. Hybrids IR20/CO 43, ADT 36/CO 43,
WP/CSR10, and IR20/CSR10, however, per-
formed better under saline conditions than
under normal conditions.
All hybrids were generally found to
be more tolerant compared with their
more susceptible parents (Table 2). This
suggests that salt tolerance is a dominant
trait. It is possible to incorporate salt tolerance through hybridization between tol-
erant and susceptible parents. Increased
salt tolerance in hybrids is a consequence
of increased seedling vigor.
Reference
Koleyoreas SA. 1958. A new method for
determining drought resistance. Plant
Physiol. 33:22.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
Exogenous glycinebetaine reduces sodium accumulation
in salt-stressed rice plants
S. Lutts, Laboratoire de Cytogénétique, Université Catholique de Louvain, 5 (Bte 13), Place Croix du Sud, 1348 Louvainla-Neuve, Belgium
Glycinebetaine (GB) is a compatible organic solute produced by several plant species to cope with salt or water stress. This
compound is involved in osmotic adjustment as well as in protecting several cellular structures. It is well established that rice
is unable to synthesize this compound because it lacks choline monooxygenase
(CMO), which is involved in the synthesis
of betaine aldehyde, the immediate precursor of GB. It has also been reported that
exogenous GB protects rice from salt stress
by maintaining photosystem II integrity
and relative water content (Harinasut et al
1996). Its effect on sodium nutrition in saltstressed rice, however, was never reported.
In a phytotron experiment, a saltsensitive rice cultivar—I Kong Pao—maintained on nutrient solution (Yoshida et al
1976; renewed each week) was subjected
to various NaCl doses (0, 30, 50, and 100
mM), with or without simultaneous exposure to 1 mM GB (Sigma Chemical). Plants
were exposed to salt stress at the seedling
stage (20 d old; 100 plants per treatment)
on 25-L tanks in a complete randomized
block. Ten surviving plants were collected
each week during a subsequent 1-mo experiment. Relative growth rate was quantified on a dry-weight basis and ion concentration was determined after digestion
of organic matter with nitric acid by an in-
ductively coupled argon plasma emission
spectrophotometer.
The presence of GB in nutrient solution had no deleterious effect on unstressed plants, but it clearly improved
surviving plant percentages and growing
abilities of salt-treated ones (see table). At
the highest NaCl dose (100 mM), exogenous GB affords protection only during
the 2 wk of exposure to salinity. The positive effect of exogenous GB was associated
with reduced sodium accumulation and
with the maintenance of potassium concentration in all parts of salinized plants as
shown in the figure for plants exposed to
various NaCl doses during 2 wk. Exog-
Surviving percentagesa (S%) and relative growth rates (RGR, expressed on a dry-weight basis in g g–1 d–1 × 10–3) of plants of salt-sensitive
cultivar I Kong Pao exposed during 4 wk to various NaCl doses (0, 30, 50, and 100 mM) on nutrient solution in the presence (+) or absence
(–) of 1 mM GB.
Parameter
S%
Shoot RGR
(in g g–1 d–1 × 10–3)
Root RGR
(in g g–1 d–1 × 10–3)
Duration of
exposure (wk)
1
2
3
4
1
2
3
4
1
2
3
4
0 mM
30 mM
–GB
+GB
–GB
100 a
100 a
98 a
100 a
113.4 a
98.8 a
95.1 a
77.5 b
86.0 a
77.9 a
68.9 b
72.3 b
100 a
99 a
100 a
100 a
108.9 a
102.4 a
86.4 b
80.3 b
83.7 a
80.8 a
71.2 b
68.6 b
100 a
83 b
71 c
65 c
85.2 b
77.7 b
50.2 c
38.2 c
80.1 a
63.9 b
65.5 b
49.7 c
50 mM
+GB
–GB
100 a
86 b
86 b
75 c
100.7 a
97.1 a
81.9 b
69.3 c
75.4 a
71.3 b
66.2 b
68.5 b
71 c
70 c
54 d
38 e
55.5 c
17.5 e
*
*
44.4 d
39.7 d
10.4 f
*
100 mM
+GB
85 b
87 b
73 c
62 d
71.6 b
35.2 c
22.3 d
28.9 d
58.6 c
55.7 c
21.6 e
12.6 f
–GB
+GB
72 c
51 d
32 e
7f
49.0 c
15.6 e
*
*
40.3 d
11.6 f
*
*
83 b
78 b
45 e
12 f
58.3 c
29.6 d
*
*
53.8 c
38.4 d
22.8 e
*
a
Values followed by the same letter are not significantly different at P = 0.05 (χ2 test); * = not significantly different from 0.
IRRN 25.2
39
enous GB had no effect on calcium and
magnesium nutrition of stressed plants,
whatever the NaCl dose (detailed data not
shown). These results suggest that GB may
have a positive impact on both absorption
and translocation of monovalent cations in
salt-stressed rice and that its synthesis by
transferring gene coding for CMO may
constitute an interesting goal for genetic
engineering in this species.
Na concentration (mmol g–1 DW)
1.5
Sodium
Na concentration (mmol g–1 DW)
1.4
Potassium
1.2
1.0
1.0
0.8
0.6
0.5
0.4
root - GB
root + GB
shoot - GB
shoot + GB
0.2
0.0
0.0
0
References
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
50
75
100
0
25
50
75
100
NaCl concentration (mM)
Harinasut P, Tsutsui K, Takebe T, Nomura M,
Takebe T, Kishitani S. 1996. Exogenous
glycinebetaine accumulation and increased
salt-tolerance in rice seedlings. Biosci.
Biotechnol. Biochem. 60:366–368.
Yoshida S, Forno OA, Cock JH, Gomez KA. 1976.
Laboratory manual for physiological studies
of rice. Manila (Philippines): International
Rice Research Institute.
○
25
Sodium and potassium concentrations in roots and shoots of rice plants (cv I Kong Pao) exposed
during 2 wk to a nutrient solution containing various NaCl doses (0, 30, 50, and 100 mM) in the
presence (+) or absence (–) of 1 mM GB. Each value is the mean of at least four replicates and
vertical bars are S.E.
○
Instructional videos available
The Leaf Color Chart (LCC) (8:20 min)
Farmers generally observe the color of rice leaves to determine a rice crop’s need for nitrogen fertilizer. Dark green rice leaves mean a
high nitrogen content, while pale green rice leaves necessitate the application of more nitrogen fertilizer.
Mere observation, however, holds no absolute guarantee of measurement accuracy. Thus, to better help farmers determine their
rice crops’ need for nitrogen, the leaf color chart (LCC) was developed.
The Leaf Color Chart (LCC) instructional video was produced to familiarize farmers and extension workers with the proper use of
this new and affordable farming implement.
Portable Chlorophyll Meter for Nitrogen Management in Rice (13:30 min)
In agriculture, excess nitrates can actually be highly damaging to crops and the environment. There is thus a need to efficiently manage
the application of nitrogen fertilizers on rice crops.
The Portable Chlorophyll Meter for Nitrogen Management in Rice introduces the features and use of the chlorophyll or SPAD
meter, which is capable of measuring the relative nitrogen content in plant leaves through a simple, quick, and nondestructive procedure.
Go breAk inTo the Code (13:30 min)
Genetic engineering need not be a property of the scientific few. This is what IRRI had in
mind when it produced Go breAk inTo the Code: to make the general public grasp and
understand the seemingly complicated science through a visually stunning, fast-paced, and
entertaining presentation of the genetic code, DNA sequencing, and plant biotechnology.
The video also gives the public a glimpse as to how IRRI scientists are redesigning the
rice plant—that most important food staple––using biotechnology tools.
These instructional videos are available in English, in the 3/4-inch u-matic and VHS
formats, and in the NTSC, SECAM, or PAL systems.
For more information about the videos, contact
Marketing and Distribution
Communication and Publications Services
IRRI, MCPO Box 3127, Makati City 1271
Philippines
E-mail: [email protected]
40
August 2000
Socioeconomics
Partnership in agricultural extension
S
i
i
G.P. Ojha, Ministry of Agriculture, Kathmandu, Nepal
Partnership has been recognized as a
strategy for attaining effectiveness and efficiency in agricultural research and development. Research and evaluation studies
on this theme, however, are not adequate
(Carney 1998).
A study was conducted in Chitwan,
Nepal, to assess the effectiveness of partnership between and among government
(GO), nongovernment (NGO), and private
(PO) organizations. Through informal
discussion and peer ratings, the District Agriculture Development Office (DADO) was
selected as the GO, the Rural
Reconstruction Nepal (RRN) as the NGO,
and four private entrepreneurs (Inter
Nepal Agrovet, Beera Agrovet, Narayani
Agrovet, and Kisan Seva Agrovet) dealing
with agricultural inputs as POs. Identified
partners, together with farmers, selected
the research problem and technologies
related to the crop variety that farmers preferred—rice, hybrid maize, and sunflower.
The partners divided responsibilities and
agreed to work together through a memorandum of understanding.
During the implementation phase,
partners reviewed the performance of the
past month and developed programs for
the ensuing months. After the implementation of the project in seven villages for
21 mo, data obtained from a complete
enumeration of 123 adopters and 17
extension workers were used to assess the
effectiveness of three individual
organizations (GO, NGO, and PO) and four
partnership (GO+NGO, GO+PO,
NGO+PO, and GO+NGO+PO) patterns.
The study showed that partnership
was more effective than nonpartnership in
terms of crop variety use by farmers. Mean
adoption was 8.4% for partnership and
4.3% for individual organizations. Five
reasons explained the differences in effectiveness of institutions. Institutions under
partnership performed their given responsibilities at a higher rate through compleIRRN 25.2
E-mail: [email protected]
mentation, provision of more resources
(manpower and materials), and more professional use of agents’ time. Other factors
that contributed to effectiveness were peer
pressure and mutual benefits.
The study also showed additional
differences in collaborative efforts. Among
partnerships, GO+PO and GO+NGO were
more effective than other forms of
partnerships (Table 1). The reasons for
this include mutual understanding of each
other’s responsibilities, closely located offices at research sites, more frequent
participation in monthly joint meetings,
and a positive attitude toward each other.
Among these patterns, GO+NGO+PO had
the lowest adoption rate. The reasons were
higher transaction costs and lower
participation level in activities by the NGO
due to project phaseout and staff
reduction. This resulted in fewer farmers
being motivated. Consequently, demand
for inputs is lower. The PO’s participation
was low because of low demand for inputs.
Partnership was found to be technology-specific. Technology was classified
as either high-cost or low-cost. Hybrid seed
and associated technology were considered as a high-cost technology, whereas
use of open-pollinated variety and associated technology was a low-cost technology.
Among the effective patterns, adoption of
high-cost technologies took place under
GO+PO partnership. With GO+NGO partnership, low-cost and locally available
agricultural technologies were adopted
(Table 2).
Similarly, partnerships were specific
to farmer circumstances. Except for the
GO+NGO pattern, mean farm size of
adopters was larger than the mean farm
size of nonadopters. Significant differences, however, were observed only with
PO, GO+PO, and GO+NGO+PO patterns.
Among the effective partnerships, GO+PO
mostly reached large landholders, while
the GO+NGO partnership preferred small
farmers (Table 3).
Table 1. Effectiveness of seven institutional patterns.
Pattern
GO
NGO
PO
GO+NGO
GO+PO
NGO+PO
GO+NGO+PO
Adopter
farmers
(no.)
Households
(no.)
7
17
5
22
52
14
6
154
287
209
271
311
198
326
Adoption
(%)
4.6
5.9
2.4
8.1
16.7
7.1
1.8
Table 2. Adopter farmers and technology types, by pattern.
Pattern
GO
NGO
PO
GO+NGO
GO+PO
NGO+PO
GO+NGO+PO
Adopter farmers
(no.)
7
17
5
22
52
14
6
Low-cost technology
(%)
100.0
100.0
40.0
90.9
11.5
85.7
83.3
High-cost technology
(%)
0.0
0.0
60.0
9.1
88.5
14.3
16.7
41
Table 3. Differences in farm size between adopter and nonadopter farmers, by pattern.
Mean farm size (ha)
Pattern
GO
NGO
PO
GO+NGO
GO+PO
NGO+PO
GO+NGO+PO
a
Adopter
Nonadopter
Differences
1.17
0.51
2.40
0.89
1.23
1.08
2.02
0.69
0.37
0.77
1.04
0.76
0.58
0.62
0.48
0.14
1.63
– 0.15
0.47
0.50
1.40
t valuea
0.1250
0.1852
0.0087**
0.6110
0.0470*
0.0856
0.0497*
** = significant at 0.01 level, * = significant at 0.05 level.
This study showed that partnership
is an effective strategy but is specific to
circumstances. Results suggest that
partnership should not be generalized to
be equally effective in all situations.
Therefore, efforts should be made to
develop partnership according to the local
context.
Reference
Carney D. 1998. Changing public and private roles
in agricultural services. London: Overseas
Development Institute.
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
○
NEWS
International Rice Symposium
Honors Chandler at Cornell
Dr. Robert F. Chandler Jr., IRRI’s founding director, who died in March 1999 at the age of
91, was honored in a major scientific gathering held at Cornell University in Ithaca, New
York, on 15-17 June 2000.
The Symposium, Rice Research and Production in the 21st Century, recognized his
lifetime contributions to agricultural science. More than 150 scientists involved in rice
research attended the international symposium.
Dr. Chandler, considered by many as a visionary, was a scientist of conviction and wisdom. His impact on international agricultural research is still widely felt today, particularly in Asia and in rice research. According to Dr. Ronald Cantrell,
current IRRI director general, “If it were not for visionaries such as Bob Chandler, there may have never been a CGIAR and
the makeup and strength of the national agricultural research systems—or NARS—as we see today in Asia and other regions
of the world would be quite different.”
Dr. Chandler was at IRRI’s helm until 1972. Dr. Chandler wrote An Adventure in Applied Science: A History of the
International Rice Research Institute. Before the Rockefeller Foundation hired him to establish IRRI, he was a professor at
Cornell University. He later served as Dean of Agriculture, then President, of the University of New Hampshire.
In 1972, Dr. Chandler became the founding director general of the Asian Vegetable Research and Development
Center (AVRDC) based in Taiwan, China. He remained active in international agricultural research even after his retirement
in 1975.
In addition to honoring Dr. Chandler, the symposium focused on rice genetics and production in the context of
international agricultural research management. Among the speakers was Dr. Norman Borlaug, who received the 1970
Nobel Peace Prize for developing high-yielding wheat varieties that, along with the IRRI rice semidwarfs, triggered the
Green Revolution.
Sessions focused on “Intensive Rice Production Systems: Implications and Opportunities” and “Developments in
Genetics: Future Opportunities in Rice.”
The symposium was sponsored by the Office for Research, the International Agriculture Program of the College of
Agriculture and Life Sciences of Cornell University; and the Cornell International Institute for Food, Agriculture and
Development. Financial assistance was provided by a grant from the Rockefeller Foundation.
A 2-day reunion of former and current IRRI scientists, scholars, and dependents followed the symposium.
Source: IRRI hotline and Rice News of PlanetRice.net (http://www.planetrice.net)
42
August 2000
NOTES FROM THE FIELD
Does wild rice Oryza minuta
exist in Thailand?
Dayun Tao, Food Crops Research
Institute,Yunnan Academy of Agricultural
Sciences, Kunming 650205, People’s
Republic of China; and Prapa Scripichitt,
Agronomy Department, Kasetsart
University, P.O. Box 1097, Bangkok
10903,Thailand
It is generally believed that Oryza minuta
is distributed only in the Philippines, Papua
New Guinea, and Indonesia (Irian Jaya).
Recently, Japanese scientists reported collecting this species from northern Thailand
(Sato et al 1996, see map in Fig. 1), and a
Thai scientist, Dr. Songkran Chitrakon,
claims that the species belongs to O.
officinalis because of its tall stature.
To confirm the existence of O.
minuta in Thailand, one accession of O.
minuta (GS No. 8173), supplied by Dr.
Songkran of the Pathumthani Rice Research Center, Thailand, was planted in a
greenhouse at Kasetsart University. Three
plants reached flowering stage. Among
these, one was a typical O. officinalis with
tall stature (152 cm), rhizomes, and equally
long branches at the panicle base. The
lower half of these branches had no
spikelets, which is a character of O.
officinalis (Fig. 2). The other two plants
were typical O. minuta, having short
stature (77.5 cm), a panicle base lacking a whorl of branches, spikelets inserted in the entire length of panicle
branches, and less spikelets (Fig. 2).
Plants were nonrhizomatous, creeping,
and stoloniferous. Results suggest that
O. minuta exists in Thailand and O.
officinalis and O. minuta grow sympatrically in Sukhothai because O.
officinalis was collected at the same site.
If this is true, Sukhothai is another
sympatric site for O. officinalis and O.
minuta. To confirm this conclusion, the
site should be investigated and the
chromosome number of plants should
be checked.
a
b
Fig. 2. Panicles of (a) Oryza minuta and (b) O.
officinalis (GS No. 8173).
Reference
Sato YI, Morishima H, Shimamoto Y. 1996.
Roles of in situ conservation of wild rice
for ecosystem sustainability. In: Seminar
on the 80th Anniversary of Pathumthani
Rice Research Center; 13-14 Nov 1996,
Pathumthani Rice Research Center;
Pathumthani, Thailand. p 155–175.
Job openings
at IRRI
IRRI has openings for the
following internationally recruited
staff:
1. Public Awareness Editor/Writer
2. Molecular Geneticist/Molecular
Taxonomist
China
For more information and full
position descriptions, visit
http://irriwww.irri.cgiar.org/
IRRIHome/irsemp.htm or contact
Vietnam
Myanmar
Chiang Mai
Laos
20° N
Uttaradit
Sukhothai
Thailand
Ayutthaya
Bangkok
COLLECTION SITE
15° N
Cambodia
100° E
105° E
Gene Hettel
Chair, Selection Committee
IRRI
[email protected]
For Public Awareness Editor/Writer
(application deadline: 15 October
2000)
Michael Cohen
Chair, Selection Committee
IRRI
[email protected]
For Molecular Geneticist/Molecular
Taxonomist
(application deadline: 31 October
2000)
Fig. 1. Collection site of Oryza minuta population (after Sato et al 1996).
IRRN 25.2
43