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Tolerance of rice germplasm to zinc deficiency
Field Crops Research 76 (2002) 123±130
Tolerance of rice germplasm to zinc de®ciency C. Quijano-Guerta*, G.J.D. Kirk, A.M. Portugal, V.I. Bartolome, G.C. McLaren International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
Abstract A database is described containing the results of screening trials for tolerance to zinc (Zn) de®ciency and other soil stresses made by IRRI and collaborators over the past 25 years. The data are scores based on visual symptoms in ®eld and greenhouse screenings and yield data from ®eld trials. The database includes search and retrieval functions. It can be downloaded from ftp://ftp.cgiar.org/icis. The data are used to explore differences in tolerance and relations with other plant and environmental variables. It is concluded that there is useful variation in tolerance to Zn de®ciency in the rice germplasm that could be exploited in breeding programs. There appears to be no yield cost associated with tolerance, and tolerant genotypes often also have tolerance to salinity and P de®ciency for reasons that are not apparent. Tolerance can be identi®ed satisfactorily by scoring for visual symptoms in early growth stages in well-managed Zn-de®cient soils. This simple procedure lends itself to large-scale screening, for example of populations for gene mapping. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Adverse soils tolerance; Germplasm; Rice; Zinc
1. Introduction Zinc (Zn) de®ciency was ®rst identi®ed as a ®eld problem in rice in 1966 (Nene, 1966). It is now widely recognized as one of the most widespread soil constraints in rice production, with as much as 50% of all lowland rice soils prone to Zn de®ciency (SillanpaÈaÈ, 1990; White and Zasoski, 1999). In a survey of 14 sites in the Philippines, Van Breemen et al. (1980) found that Zn de®ciency was most consistently associated with perennial soil wetness and with soils with weak pro®le development (Aquents in the USDA classi®cation); secondary factors were high organic matter content, high pH, and high exchangeable Mg:Ca ratio. These associations have been con®rmed in lowland rice soils across Asia, and Zn de®ciency appears to be ubiquitous in coastal saline soils. *
Corresponding author.
Increasing incidences of Zn de®ciency over the past several years have been due to various changes. These include increased crop demands on the soil's ability to supply Zn fast enough as a result of improved cultivars and management; use of urea in place of the acid fertilizer ammonium sulphate; increased use of phosphate fertilizers and the resulting P-induced Zn de®ciency; and use of alkaline irrigation water without proper drainage. We anticipate further increases in incidences with the advent of rice with Zn-dense grains for human nutrition (Graham et al., 1999; Ruel and Bouis, 1998; Welch and Graham, 1999), which will have greater Zn requirements. Zinc de®ciency can be corrected by application of Zn compounds to the soil or plants. However, there are problems with this approach. Apart from unknown long-term effects on the soil nutrient balance, Zn fertilizer is not widely available and often what is sold as Zn fertilizer is in fact something else. Thus incidences continue to increase throughout rice-producing
0378-4290/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 4 2 9 0 ( 0 2 ) 0 0 0 3 4 - 5
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C. Quijano-Guerta et al. / Field Crops Research 76 (2002) 123±130
countries in spite of widespread awareness of the problem. Development of rice cultivars that extract or metabolize Zn more ef®ciently or both is therefore a more promising strategy than fertilization. Research at the International Rice Research Institute (IRRI) over many years has shown that there is considerable variation in tolerance to Zn de®ciency in the rice germplasm. With new biotechnological tools, it should be possible to ef®ciently harness this variation to incorporate traits for Zn ef®ciency in breeding programs. This paper gives an overview of screening trials on Zn de®ciency conducted by IRRI and collaborators over the past 25 years, and describes a database containing the results of screening for Zn de®ciency and other soil stresses. The database is used to extract information about the extent of genetic variation in tolerance and its relation to other plant and environmental variables. 2. Materials and methods 2.1. Screening for Zn de®ciency tolerance at IRRI Systematic greenhouse and ®eld screening on tolerance to adverse soil conditions began at IRRI in 1974, and standard procedures were developed (IRRI, 1996). For Zn de®ciency, plants are scored from 1 (most plants without symptoms) to 9 (most plants dead) based on visual symptoms in leaves 4 weeks after transplanting. In greenhouse screening, 2-weekold seedlings are transplanted into Zn-de®cient soil in pots and rated after 4 weeks. In ®eld screening, farmers' ®elds across the Philippines with varying soil properties have been used. Tolerant and susceptible checks are planted at regular intervals with the test entries. Some 500±1500 lines have been evaluated for Zn de®ciency tolerance annually with a total of 23,000 lines up to 1998, comprising 11% of all observations for soil stresses. Lines were monitored for tolerance through generation advance. However, there has been no systematic breeding for Zn-de®ciency tolerance. The materials included breeding lines from IRRI's rice improvement program and cultivars and lines from the Genetic Resources Center (GRC) and the International Network for Genetic Evaluation of Rice (INGER).
2.2. The Problem Soils Germplasm Database We have collated screening data from individual databases and logbooks in a Problem Soils Germplasm Database with the aim of: (a) providing systematic and centralized data storage and management, (b) facilitating the sharing of data within and outside IRRI, and (c) providing an analytical tool for studying the germplasm. The database is integrated with the Data Management System of the International Rice Information System (IRIS). IRIS is a network of databases containing information on pedigrees, selection histories, ®eld and greenhouse evaluations and survey results. The Problem Soils Germplasm Database comprises separate data storage and retrieval sections allowing searches to be made for individual traits or combinations of traits. To date it contains 148 studies (either an experiment, nursery or survey) with 175,000 records (individual observations for different lines): 88,000 from IRRI breeding programs, 20,000 from international nursery trials of INGER, 60,000 from GRC and 7000 from other experiments at IRRI. Eight soil stresses are distinguished in about 100,000 records, of which 9840 are for Zn de®ciency tolerance. We extracted data from the database on Zn de®ciency tolerance and other traits of lines from four stages in the IRRI rice improvement program (the hybridization block (HB), observational yield trial (OYT), replicated yield trial (RYT) and Elite nurseries) and analyzed it statistically for differences in tolerance and relations with other plant and environmental variables. 2.3. Statistical analyses The data analyzed were ordinal response variables such as Zn tolerance scores and categorical predictor variables such as location and season. Furthermore, relationships between responses and predictors need to be adjusted for other sampling strata such as years and nurseries. The second type of analysis conducted was to assess independence between different ordinal response scores, again adjusted for other sampling strata. Generalized Cochran±Mantel±Haenszel (CMH) tests (Agresti, 1990) were used for both kinds of analysis. For the ®rst type, the CMH mean score test (Qs) was computed (Stokes et al., 1995) to detect shifts
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in mean score of the response over levels of the predictors while adjusting for strata. For the second, the CMH correlation statistic (Qcs) (Stokes et al., 1995) was used. This tests for a linear association between scores of two ordinal variables that is consistent over different sampling strata. In the analyses of relationships between Zn tolerance and yield or maturity time, lines were categorized as susceptible or tolerant according to screening data and independently gathered yields or maturity times were compared using standard t-tests. 3. Results and discussion 3.1. Differences between screening procedures 3.1.1. Intra-cultivar differences Scores of the nine cultivars that have been tested most often are compared in Table 1. The scores of individual cultivars range from 1 to 9, indicating very large intra-cultivar variability. This would have been due to various causes: variation in the magnitude of the stress over space and time, especially in the ®eld screening; genotype by environment interactions; involvement of a large number of genes; and low heritability of the genes. The ®eld screening was conducted at different locations at different times with differing climatic conditions. Because Zn de®ciency is characteristically patchy in space and time as a result of its association with soil wetness and upwelling or inter¯ow of base-rich water (Van Breemen et al., 1980; Scharpenseel et al., 1983), much of the ®eld variability
125
can be attributed to spatial heterogeneity. The variability should be less severe in greenhouse trials where conditions are better controlled. It is widely observed in rice and other crops that the seed Zn content has a large effect of seedling growth and the expression of de®ciency symptoms, and that seed Zn is greatly affected by crop management as well as by cultivar differences (Graham and Rengel, 1993). Differences in management and soil conditions could therefore lead to intra-cultivar differences in Zn scores. However, the seeds of the test cultivars in all the nurseries in the studies in the database were produced under a common management regime on the IRRI farm. Differences in seed Zn due to this cause are therefore expected to be small. Therefore, differences in seed Zn re¯ect real cultivar differences. 3.1.2. Field versus greenhouse The frequency distributions of ®eld and greenhouse scores from lines in the IRRI breeding nurseries are shown in Fig. 1. The difference in mean scores (0.1) is
Table 1 Zinc-de®ciency tolerance scores of the most common IRRI cultivars in the Problem Soils Germplasm Database Cultivar
No. of observations
Minimum score
Maximum score
Standard deviation
IR42 IR36 IR38 IR20 IR8 IR26 IR46 IR44 IR54
159 152 91 47 45 43 43 35 35
1 1 3 3 3 3 3 1 3
9 9 7 9 9 9 9 9 9
1.78 1.74 1.09 1.82 1.49 1.71 1.64 1.44 1.16
Fig. 1. Distribution of Zn de®ciency tolerance scores for greenhouse and ®eld trials.
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small but signi®cant, with a greater proportion of lines being scored at least moderately susceptible (score of >7) in the greenhouse screenings. According to the CMH mean score test, with the effect of nursery controlled, the overall association between location and Zn score was signi®cant Qs 18:408 . This presumably re¯ects the greater ease with which soil and water can be managed under greenhouse conditions to produce a consistent level and pattern of stress. Also some bias would have been introduced by the order of lines tested, early generation breeding materials generally being tested ®rst in the greenhouse and then promising lines tested in the ®eld. But these effects appear to have been small. 3.1.3. Dry season versus wet season Interactions between season and scores were assessed by comparing results from dry and wet season trials in the four breeding nurseries. A set of 4243 ®eld and 5599 greenhouse results for dry and wet seasons was analyzed using the CMH mean score test controlling for the effect of nurseries. There were signi®cant differences between seasons in the ®eld data Qs 189:27 , but not in the greenhouse data Qs 2:703 ns. The absence of differences in the greenhouse data is not surprising because ``dry'' and ``wet'' season are not so tightly linked to weather conditions and the screenings tend to straddle the seasons. From the distribution of the ®eld scores, a greater percentage of tolerant scores was obtained during the dry season (Fig. 2). This is most likely because of greater solar radiation during the dry season and hence greater yield potential and therefore greater Zn demand and stress. Effects of differences in water regime can be ruled out because they should be expected to in¯uence Zn stress in the opposite direction with greater stress under wetter conditions. Greater stress under higher solar radiation is consistent with the results of Obata et al. (1997) who found that a susceptible Japanese cultivar grown under Zn de®cient conditions did not show de®ciency symptoms with shading. The effect of solar radiation is most probably through a greater plant demand for Zn. But there may also be effects on plant physiological processes affecting Zn metabolism or uptake. At any rate, the results indicate that dry season screening should produce a clearer separation of tolerance scores.
Fig. 2. Distribution of ®eld Zn de®ciency scores for dry and wet season trials, IRRI, 1976±1998.
3.2. Tolerance in lines bred at IRRI Although there has been no systematic selection for tolerance to soil stresses in the rice improvement program at IRRI, there may have been inadvertent selection for Zn de®ciency tolerance because the soil in parts of the IRRI farm is Zn de®cient. According to observation most elite lines developed at IRRI have at least moderate tolerance to Zn de®ciency (Neue et al., 1990). However, this observation has not been rigorously tested. Fig. 3 compares the frequency distribution of scores of elite lines with those of other nurseries in the general rice improvement program at IRRI. The CMH mean score test (4238 samples) showed signi®cant association between nurseries and tolerance scores Qs 113:478 with a greater percentage of tolerant scores among the elite lines (82% versus 72% for the sum of the other nurseries). Comparing the distribution of scores in the individual nurseries, the distribution for the hybridization block, which
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Fig. 3. Comparison of Zn de®ciency scores distribution for different IRRI breeding nurseries: HB: hybridization block, OYT: observational yield trial, RYT: replicated yield trial, and Elite: elite nurseries.
contains parent cultivars and lines and has been subjected to the least selection pressure from conditions on the IRRI farm, has the greatest mean score and greatest proportion of sensitive scores. This is consistent with a gradual improvement in tolerance from the hybridization block to the elite nursery as a result of selection pressure. 3.3. Relations between tolerance and yield Given the ubiquity of Zn de®ciency in lowland rice, Zn de®ciency tolerance could contribute substantially to a cultivar's adaptability across regions if it does not cause yield reductions in the absence of the stress. The most widely grown irrigated lowland cultivarÐIR 64Ðand recently released Philippine cultivars that are being widely adoptedÐPSB Rc 10, PSB Rc 18 and PSB Rc 28Ðare at least moderately tolerant of Zn de®ciency, though they were bred for other traits.
Table 2 shows the mean yields under non-Zn-de®cient conditions of Zn-de®ciency tolerant and susceptible lines. The yield data were obtained from independent ®eld trials on lines from the various breeding nurseries. The lines were classi®ed as tolerant or susceptible based on their mean scores over years. The mean yields of 28 tolerant and 34 susceptible lines from the RYT nursery scored under ®eld conditions were not signi®cantly different t 0:9316 ns. However, the yields of 118 tolerant and 374 susceptible RYT lines scored in the greenhouse were signi®cantly different. The RYT nursery contains cultivars that have attained yield stability and, being replicated, the yield data are reliable. Data for other nurseries in the database had statistically signi®cant differences between tolerant and susceptible lines, but in all cases the tolerant lines had higher yields. There is insuf®cient data on cultivar yields in the database to test whether the differences in tolerance
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Table 2 Comparison of mean yields under non-Zn-de®cient conditions of Zn-de®ciency tolerant (score of 1±3 averaged over the years) and susceptible (score of 7±9) lines from different IRRI breeding nurseries, 1976±1998 Nursery
No. of lines
a
Hybridization block Observational yield triala Replicated yield triala Replicated yield trialb
21 1133 492 62
a
Greenhouse scores.
b
Field scores. Signi®cance at 5% level using the t-test.
*
**
Mean yield (kg ha 1)
Difference
Susceptible
Tolerant
4564 4027 4138 5480
6355 4118 5614 5787
1791* 91 ns 1476** 307 ns
Signi®cance at 1% level using the t-test.
scores, measured by visual symptoms during the vegetative growth stages, translate into differences in yield under Zn stress. In other crops correlations between vegetative Zn ef®ciency and grain yield are
often poor because unrelated genes acting on growth during the reproductive stages are also important (Graham and Rengel, 1993). At any rate, in a survey involving 411 rice lines in 46 tests at 11 Zn-de®cient
Fig. 4. Relationship between Zn de®ciency scores and salinity scores for greenhouse studies, IRRI, 1976±1998.
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sites in the Philippines, Neue et al. (1990) reported an average yield advantage of 2.6 t ha 1 for lines rated tolerant when compared with susceptible. 3.4. Relation to maturity time Giordano and Mortvedt (1974) observed a positive relationship between Zn de®ciency tolerance and maturity time in a small number of US rice cultivars, and hypothesized that tolerance was conveyed by slower growth and consequently smaller daily Zn requirement in longer-duration cultivars. We tested this relationship by analyzing data for lines from RYT nurseries for which maturity times were available. The t-test of 67 observations showed a signi®cant difference in mean maturity of Zn tolerant and susceptible lines t 2:1927 . However, contrary to Giordano and Mortvedt's ®ndings, the tolerant group (based on mean scores over years as in Section 3.2) had a shorter mean
129
maturity (105 days) than the susceptible (122 days). It is likely that the early maturing cultivars are able to capture Zn when the Zn is most available in the soil early in the season. Concentrations of water-soluble Zn in the soil are largest at the start of soil ¯ooding and decrease over time (Ponnamperuma, 1985). 3.5. Relation to other stress tolerances 3.5.1. Salinity Problem soils tend to have multiple mineral de®ciencies and toxicities, and multiple tolerances are required. In saline rice soils, Zn and P de®ciencies are more or less universally present. We consider here how widespread Zn de®ciency tolerance is in salinitytolerant germplasm. There has been a large effort in breeding for tolerance to coastal saline soils at IRRI in recent years, and the Problem Soils Germplasm Database contains
Fig. 5. Relationship between Zn de®ciency scores and P de®ciency scores for greenhouse studies, IRRI, 1976±1998.
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56,000 records relating to salinity tolerance. There are 4247 records for lines tested for both salinity and Zn de®ciency tolerance in the greenhouse. Fig. 4 compares the frequency distributions of scores for salinity and Zn de®ciency tolerances in these lines. The association between salinity and Zn de®ciency scores, controlling for the effect of nursery, was signi®cant according to the CMH correlation test Qcs 33:033 . Apparently many of the saline tolerant and moderately tolerant lines are also tolerant or moderately tolerant of Zn de®ciency. We do not have an explanation for this. It seems unlikely that plant responses to salinity and Zn de®ciency are mechanistically related. 3.5.2. P de®ciency A similar analysis was made for P de®ciency tolerance in a set of 1061 lines from greenhouse screenings (Fig. 5). The distribution of scores showed that lines tolerant of Zn de®ciency often possess at least moderate tolerance to P de®ciency, and vice versa. The relationship between the distributions was signi®cant according to the CMH correlation test Qcs 41:121 . As for the relation with salinity tolerance, we do not have an explanation for this association. 4. Conclusions Although tolerance to Zn de®ciency is a complex trait, interacting with environmental factors in a complex way, our analysis of the database shows that there is useful variation in tolerance in the rice germplasm that could be exploited in breeding programs. There appears to be no yield cost associated with tolerance, and tolerant genotypes may have adaptation to more than one soil stress. Tolerance can be identi®ed satisfactorily by scoring for visual symptoms in early growth stages in well-managed Zn-de®cient soils. This simple and ef®cient screening procedure lends itself to large-scale screening, for example of mutant or other populations to map the genes responsible for tolerance. However, this procedure does not distinguish between the various components of Zn ef®ciency in the plant, related to acquisition from the soil, metabolism in the plant and partitioning to the
grain. Information on these aspects is required in selecting for Zn-dense grains. References Agresti, A., 1990. Categorical Data Analysis. Wiley, New York. Giordano, P.M., Mortvedt, J.J., 1974. Response of several rice cultures to Zn. Agron. J. 66, 220±223. Graham, R.D., Rengel, Z., 1993. Genotype variation in zinc uptake and utilization. In: Robson, A.D. (Ed.), Zinc in Soils and Plants. Kluwer Academic Publisher, Dordrecht, The Netherlands, pp. 107±118. Graham, R.D., Senadhira, D., Beebe, S., Iglesias, C., Monastereio, I., 1999. Breeding for micronutrient density in edible portions of staple food crops: conventional approaches. Field Crops Res. 60, 57±80. IRRI, 1996. Standard Evaluation System Manual. International Rice Research Institute, Manila, Philippines, p. 35. Nene, Y.L., 1966. Symptoms, cause and control of Khaira disease of paddy. Bull. Ind. Phytopathol. Soc. 3, 97±101. Neue, H.U., Lantin, R.S., Cayton, M.T.C., Autor, N.U., 1990. Screening of rices for adverse soils tolerance. In: El Bassam, N., Dambroth, M., Loughman, B.C. (Eds.), Genetic Aspects of Plant Nutrition. Kluwer Academic Publisher, Dordrecht, The Netherlands, pp. 523±531. Obata, H., Shimoyama, A., Umebayashi, M., 1997. Effect of shading on zinc de®ciency symptoms in rice. Soil Sci. Plant Nutr. 43, 933±936. Ponnamperuma, F.N., 1985. Chemical kinetics of wetland rice soils relative to soil fertility. In: Wetland Soils: Characterization, Classi®cation, and Utilization. International Rice Research Institute, Los BanÄos, Laguna, Philippines, pp. 71±89. Ruel, M.T., Bouis, H.E., 1998. Plant breeding: a long term strategy for the control of Zn de®ciency in vulnerable populations. Am. J. Clin. Nutr. 68 (2(S)), 488±494. Scharpenseel, H.W., Eichwald, E., Haupenthal, C., Neue, H.U., 1983. Zinc de®ciency in a soil toposequence, grown to rice, at Tiaong, Quezon Province, Philippines. Catena 10, 115±132. SillanpaÈaÈ, M., 1990. Micronutrients Assessment at the Country Level: An International study. FAO Soils Bulletin No. 63. Food and Agricultural Organization of the United Nations, Rome, Italy. Stokes, M.E., Davis, C.S., Koch, G.G., 1995. Categorical data analysis using the SAS System. SAS Institute, Cary, NC. Van Breemen, N., Quijano, C.C., Sen, L.N., 1980. Zinc de®ciency in wetland rice along a toposequence of hydromorphic soils in the Philippines. I. Soil conditions and hydrology. Plant Soil 57, 203±214. Welch, R., Graham, R.D., 1999. A new paradigm for world agriculture: meeting human needs. Productive, sustainable and nutritious. Field Crops Res. 60, 1±10. White, J.G., Zasoski, R.J., 1999. Mapping soil micronutrients. Field Crops Res. 60, 11±24.
Tolerance of rice germplasm to zinc de®ciency C. Quijano-Guerta*, G.J.D. Kirk, A.M. Portugal, V.I. Bartolome, G.C. McLaren International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
Abstract A database is described containing the results of screening trials for tolerance to zinc (Zn) de®ciency and other soil stresses made by IRRI and collaborators over the past 25 years. The data are scores based on visual symptoms in ®eld and greenhouse screenings and yield data from ®eld trials. The database includes search and retrieval functions. It can be downloaded from ftp://ftp.cgiar.org/icis. The data are used to explore differences in tolerance and relations with other plant and environmental variables. It is concluded that there is useful variation in tolerance to Zn de®ciency in the rice germplasm that could be exploited in breeding programs. There appears to be no yield cost associated with tolerance, and tolerant genotypes often also have tolerance to salinity and P de®ciency for reasons that are not apparent. Tolerance can be identi®ed satisfactorily by scoring for visual symptoms in early growth stages in well-managed Zn-de®cient soils. This simple procedure lends itself to large-scale screening, for example of populations for gene mapping. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Adverse soils tolerance; Germplasm; Rice; Zinc
1. Introduction Zinc (Zn) de®ciency was ®rst identi®ed as a ®eld problem in rice in 1966 (Nene, 1966). It is now widely recognized as one of the most widespread soil constraints in rice production, with as much as 50% of all lowland rice soils prone to Zn de®ciency (SillanpaÈaÈ, 1990; White and Zasoski, 1999). In a survey of 14 sites in the Philippines, Van Breemen et al. (1980) found that Zn de®ciency was most consistently associated with perennial soil wetness and with soils with weak pro®le development (Aquents in the USDA classi®cation); secondary factors were high organic matter content, high pH, and high exchangeable Mg:Ca ratio. These associations have been con®rmed in lowland rice soils across Asia, and Zn de®ciency appears to be ubiquitous in coastal saline soils. *
Corresponding author.
Increasing incidences of Zn de®ciency over the past several years have been due to various changes. These include increased crop demands on the soil's ability to supply Zn fast enough as a result of improved cultivars and management; use of urea in place of the acid fertilizer ammonium sulphate; increased use of phosphate fertilizers and the resulting P-induced Zn de®ciency; and use of alkaline irrigation water without proper drainage. We anticipate further increases in incidences with the advent of rice with Zn-dense grains for human nutrition (Graham et al., 1999; Ruel and Bouis, 1998; Welch and Graham, 1999), which will have greater Zn requirements. Zinc de®ciency can be corrected by application of Zn compounds to the soil or plants. However, there are problems with this approach. Apart from unknown long-term effects on the soil nutrient balance, Zn fertilizer is not widely available and often what is sold as Zn fertilizer is in fact something else. Thus incidences continue to increase throughout rice-producing
0378-4290/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 4 2 9 0 ( 0 2 ) 0 0 0 3 4 - 5
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C. Quijano-Guerta et al. / Field Crops Research 76 (2002) 123±130
countries in spite of widespread awareness of the problem. Development of rice cultivars that extract or metabolize Zn more ef®ciently or both is therefore a more promising strategy than fertilization. Research at the International Rice Research Institute (IRRI) over many years has shown that there is considerable variation in tolerance to Zn de®ciency in the rice germplasm. With new biotechnological tools, it should be possible to ef®ciently harness this variation to incorporate traits for Zn ef®ciency in breeding programs. This paper gives an overview of screening trials on Zn de®ciency conducted by IRRI and collaborators over the past 25 years, and describes a database containing the results of screening for Zn de®ciency and other soil stresses. The database is used to extract information about the extent of genetic variation in tolerance and its relation to other plant and environmental variables. 2. Materials and methods 2.1. Screening for Zn de®ciency tolerance at IRRI Systematic greenhouse and ®eld screening on tolerance to adverse soil conditions began at IRRI in 1974, and standard procedures were developed (IRRI, 1996). For Zn de®ciency, plants are scored from 1 (most plants without symptoms) to 9 (most plants dead) based on visual symptoms in leaves 4 weeks after transplanting. In greenhouse screening, 2-weekold seedlings are transplanted into Zn-de®cient soil in pots and rated after 4 weeks. In ®eld screening, farmers' ®elds across the Philippines with varying soil properties have been used. Tolerant and susceptible checks are planted at regular intervals with the test entries. Some 500±1500 lines have been evaluated for Zn de®ciency tolerance annually with a total of 23,000 lines up to 1998, comprising 11% of all observations for soil stresses. Lines were monitored for tolerance through generation advance. However, there has been no systematic breeding for Zn-de®ciency tolerance. The materials included breeding lines from IRRI's rice improvement program and cultivars and lines from the Genetic Resources Center (GRC) and the International Network for Genetic Evaluation of Rice (INGER).
2.2. The Problem Soils Germplasm Database We have collated screening data from individual databases and logbooks in a Problem Soils Germplasm Database with the aim of: (a) providing systematic and centralized data storage and management, (b) facilitating the sharing of data within and outside IRRI, and (c) providing an analytical tool for studying the germplasm. The database is integrated with the Data Management System of the International Rice Information System (IRIS). IRIS is a network of databases containing information on pedigrees, selection histories, ®eld and greenhouse evaluations and survey results. The Problem Soils Germplasm Database comprises separate data storage and retrieval sections allowing searches to be made for individual traits or combinations of traits. To date it contains 148 studies (either an experiment, nursery or survey) with 175,000 records (individual observations for different lines): 88,000 from IRRI breeding programs, 20,000 from international nursery trials of INGER, 60,000 from GRC and 7000 from other experiments at IRRI. Eight soil stresses are distinguished in about 100,000 records, of which 9840 are for Zn de®ciency tolerance. We extracted data from the database on Zn de®ciency tolerance and other traits of lines from four stages in the IRRI rice improvement program (the hybridization block (HB), observational yield trial (OYT), replicated yield trial (RYT) and Elite nurseries) and analyzed it statistically for differences in tolerance and relations with other plant and environmental variables. 2.3. Statistical analyses The data analyzed were ordinal response variables such as Zn tolerance scores and categorical predictor variables such as location and season. Furthermore, relationships between responses and predictors need to be adjusted for other sampling strata such as years and nurseries. The second type of analysis conducted was to assess independence between different ordinal response scores, again adjusted for other sampling strata. Generalized Cochran±Mantel±Haenszel (CMH) tests (Agresti, 1990) were used for both kinds of analysis. For the ®rst type, the CMH mean score test (Qs) was computed (Stokes et al., 1995) to detect shifts
C. Quijano-Guerta et al. / Field Crops Research 76 (2002) 123±130
in mean score of the response over levels of the predictors while adjusting for strata. For the second, the CMH correlation statistic (Qcs) (Stokes et al., 1995) was used. This tests for a linear association between scores of two ordinal variables that is consistent over different sampling strata. In the analyses of relationships between Zn tolerance and yield or maturity time, lines were categorized as susceptible or tolerant according to screening data and independently gathered yields or maturity times were compared using standard t-tests. 3. Results and discussion 3.1. Differences between screening procedures 3.1.1. Intra-cultivar differences Scores of the nine cultivars that have been tested most often are compared in Table 1. The scores of individual cultivars range from 1 to 9, indicating very large intra-cultivar variability. This would have been due to various causes: variation in the magnitude of the stress over space and time, especially in the ®eld screening; genotype by environment interactions; involvement of a large number of genes; and low heritability of the genes. The ®eld screening was conducted at different locations at different times with differing climatic conditions. Because Zn de®ciency is characteristically patchy in space and time as a result of its association with soil wetness and upwelling or inter¯ow of base-rich water (Van Breemen et al., 1980; Scharpenseel et al., 1983), much of the ®eld variability
125
can be attributed to spatial heterogeneity. The variability should be less severe in greenhouse trials where conditions are better controlled. It is widely observed in rice and other crops that the seed Zn content has a large effect of seedling growth and the expression of de®ciency symptoms, and that seed Zn is greatly affected by crop management as well as by cultivar differences (Graham and Rengel, 1993). Differences in management and soil conditions could therefore lead to intra-cultivar differences in Zn scores. However, the seeds of the test cultivars in all the nurseries in the studies in the database were produced under a common management regime on the IRRI farm. Differences in seed Zn due to this cause are therefore expected to be small. Therefore, differences in seed Zn re¯ect real cultivar differences. 3.1.2. Field versus greenhouse The frequency distributions of ®eld and greenhouse scores from lines in the IRRI breeding nurseries are shown in Fig. 1. The difference in mean scores (0.1) is
Table 1 Zinc-de®ciency tolerance scores of the most common IRRI cultivars in the Problem Soils Germplasm Database Cultivar
No. of observations
Minimum score
Maximum score
Standard deviation
IR42 IR36 IR38 IR20 IR8 IR26 IR46 IR44 IR54
159 152 91 47 45 43 43 35 35
1 1 3 3 3 3 3 1 3
9 9 7 9 9 9 9 9 9
1.78 1.74 1.09 1.82 1.49 1.71 1.64 1.44 1.16
Fig. 1. Distribution of Zn de®ciency tolerance scores for greenhouse and ®eld trials.
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small but signi®cant, with a greater proportion of lines being scored at least moderately susceptible (score of >7) in the greenhouse screenings. According to the CMH mean score test, with the effect of nursery controlled, the overall association between location and Zn score was signi®cant Qs 18:408 . This presumably re¯ects the greater ease with which soil and water can be managed under greenhouse conditions to produce a consistent level and pattern of stress. Also some bias would have been introduced by the order of lines tested, early generation breeding materials generally being tested ®rst in the greenhouse and then promising lines tested in the ®eld. But these effects appear to have been small. 3.1.3. Dry season versus wet season Interactions between season and scores were assessed by comparing results from dry and wet season trials in the four breeding nurseries. A set of 4243 ®eld and 5599 greenhouse results for dry and wet seasons was analyzed using the CMH mean score test controlling for the effect of nurseries. There were signi®cant differences between seasons in the ®eld data Qs 189:27 , but not in the greenhouse data Qs 2:703 ns. The absence of differences in the greenhouse data is not surprising because ``dry'' and ``wet'' season are not so tightly linked to weather conditions and the screenings tend to straddle the seasons. From the distribution of the ®eld scores, a greater percentage of tolerant scores was obtained during the dry season (Fig. 2). This is most likely because of greater solar radiation during the dry season and hence greater yield potential and therefore greater Zn demand and stress. Effects of differences in water regime can be ruled out because they should be expected to in¯uence Zn stress in the opposite direction with greater stress under wetter conditions. Greater stress under higher solar radiation is consistent with the results of Obata et al. (1997) who found that a susceptible Japanese cultivar grown under Zn de®cient conditions did not show de®ciency symptoms with shading. The effect of solar radiation is most probably through a greater plant demand for Zn. But there may also be effects on plant physiological processes affecting Zn metabolism or uptake. At any rate, the results indicate that dry season screening should produce a clearer separation of tolerance scores.
Fig. 2. Distribution of ®eld Zn de®ciency scores for dry and wet season trials, IRRI, 1976±1998.
3.2. Tolerance in lines bred at IRRI Although there has been no systematic selection for tolerance to soil stresses in the rice improvement program at IRRI, there may have been inadvertent selection for Zn de®ciency tolerance because the soil in parts of the IRRI farm is Zn de®cient. According to observation most elite lines developed at IRRI have at least moderate tolerance to Zn de®ciency (Neue et al., 1990). However, this observation has not been rigorously tested. Fig. 3 compares the frequency distribution of scores of elite lines with those of other nurseries in the general rice improvement program at IRRI. The CMH mean score test (4238 samples) showed signi®cant association between nurseries and tolerance scores Qs 113:478 with a greater percentage of tolerant scores among the elite lines (82% versus 72% for the sum of the other nurseries). Comparing the distribution of scores in the individual nurseries, the distribution for the hybridization block, which
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Fig. 3. Comparison of Zn de®ciency scores distribution for different IRRI breeding nurseries: HB: hybridization block, OYT: observational yield trial, RYT: replicated yield trial, and Elite: elite nurseries.
contains parent cultivars and lines and has been subjected to the least selection pressure from conditions on the IRRI farm, has the greatest mean score and greatest proportion of sensitive scores. This is consistent with a gradual improvement in tolerance from the hybridization block to the elite nursery as a result of selection pressure. 3.3. Relations between tolerance and yield Given the ubiquity of Zn de®ciency in lowland rice, Zn de®ciency tolerance could contribute substantially to a cultivar's adaptability across regions if it does not cause yield reductions in the absence of the stress. The most widely grown irrigated lowland cultivarÐIR 64Ðand recently released Philippine cultivars that are being widely adoptedÐPSB Rc 10, PSB Rc 18 and PSB Rc 28Ðare at least moderately tolerant of Zn de®ciency, though they were bred for other traits.
Table 2 shows the mean yields under non-Zn-de®cient conditions of Zn-de®ciency tolerant and susceptible lines. The yield data were obtained from independent ®eld trials on lines from the various breeding nurseries. The lines were classi®ed as tolerant or susceptible based on their mean scores over years. The mean yields of 28 tolerant and 34 susceptible lines from the RYT nursery scored under ®eld conditions were not signi®cantly different t 0:9316 ns. However, the yields of 118 tolerant and 374 susceptible RYT lines scored in the greenhouse were signi®cantly different. The RYT nursery contains cultivars that have attained yield stability and, being replicated, the yield data are reliable. Data for other nurseries in the database had statistically signi®cant differences between tolerant and susceptible lines, but in all cases the tolerant lines had higher yields. There is insuf®cient data on cultivar yields in the database to test whether the differences in tolerance
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Table 2 Comparison of mean yields under non-Zn-de®cient conditions of Zn-de®ciency tolerant (score of 1±3 averaged over the years) and susceptible (score of 7±9) lines from different IRRI breeding nurseries, 1976±1998 Nursery
No. of lines
a
Hybridization block Observational yield triala Replicated yield triala Replicated yield trialb
21 1133 492 62
a
Greenhouse scores.
b
Field scores. Signi®cance at 5% level using the t-test.
*
**
Mean yield (kg ha 1)
Difference
Susceptible
Tolerant
4564 4027 4138 5480
6355 4118 5614 5787
1791* 91 ns 1476** 307 ns
Signi®cance at 1% level using the t-test.
scores, measured by visual symptoms during the vegetative growth stages, translate into differences in yield under Zn stress. In other crops correlations between vegetative Zn ef®ciency and grain yield are
often poor because unrelated genes acting on growth during the reproductive stages are also important (Graham and Rengel, 1993). At any rate, in a survey involving 411 rice lines in 46 tests at 11 Zn-de®cient
Fig. 4. Relationship between Zn de®ciency scores and salinity scores for greenhouse studies, IRRI, 1976±1998.
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sites in the Philippines, Neue et al. (1990) reported an average yield advantage of 2.6 t ha 1 for lines rated tolerant when compared with susceptible. 3.4. Relation to maturity time Giordano and Mortvedt (1974) observed a positive relationship between Zn de®ciency tolerance and maturity time in a small number of US rice cultivars, and hypothesized that tolerance was conveyed by slower growth and consequently smaller daily Zn requirement in longer-duration cultivars. We tested this relationship by analyzing data for lines from RYT nurseries for which maturity times were available. The t-test of 67 observations showed a signi®cant difference in mean maturity of Zn tolerant and susceptible lines t 2:1927 . However, contrary to Giordano and Mortvedt's ®ndings, the tolerant group (based on mean scores over years as in Section 3.2) had a shorter mean
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maturity (105 days) than the susceptible (122 days). It is likely that the early maturing cultivars are able to capture Zn when the Zn is most available in the soil early in the season. Concentrations of water-soluble Zn in the soil are largest at the start of soil ¯ooding and decrease over time (Ponnamperuma, 1985). 3.5. Relation to other stress tolerances 3.5.1. Salinity Problem soils tend to have multiple mineral de®ciencies and toxicities, and multiple tolerances are required. In saline rice soils, Zn and P de®ciencies are more or less universally present. We consider here how widespread Zn de®ciency tolerance is in salinitytolerant germplasm. There has been a large effort in breeding for tolerance to coastal saline soils at IRRI in recent years, and the Problem Soils Germplasm Database contains
Fig. 5. Relationship between Zn de®ciency scores and P de®ciency scores for greenhouse studies, IRRI, 1976±1998.
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56,000 records relating to salinity tolerance. There are 4247 records for lines tested for both salinity and Zn de®ciency tolerance in the greenhouse. Fig. 4 compares the frequency distributions of scores for salinity and Zn de®ciency tolerances in these lines. The association between salinity and Zn de®ciency scores, controlling for the effect of nursery, was signi®cant according to the CMH correlation test Qcs 33:033 . Apparently many of the saline tolerant and moderately tolerant lines are also tolerant or moderately tolerant of Zn de®ciency. We do not have an explanation for this. It seems unlikely that plant responses to salinity and Zn de®ciency are mechanistically related. 3.5.2. P de®ciency A similar analysis was made for P de®ciency tolerance in a set of 1061 lines from greenhouse screenings (Fig. 5). The distribution of scores showed that lines tolerant of Zn de®ciency often possess at least moderate tolerance to P de®ciency, and vice versa. The relationship between the distributions was signi®cant according to the CMH correlation test Qcs 41:121 . As for the relation with salinity tolerance, we do not have an explanation for this association. 4. Conclusions Although tolerance to Zn de®ciency is a complex trait, interacting with environmental factors in a complex way, our analysis of the database shows that there is useful variation in tolerance in the rice germplasm that could be exploited in breeding programs. There appears to be no yield cost associated with tolerance, and tolerant genotypes may have adaptation to more than one soil stress. Tolerance can be identi®ed satisfactorily by scoring for visual symptoms in early growth stages in well-managed Zn-de®cient soils. This simple and ef®cient screening procedure lends itself to large-scale screening, for example of mutant or other populations to map the genes responsible for tolerance. However, this procedure does not distinguish between the various components of Zn ef®ciency in the plant, related to acquisition from the soil, metabolism in the plant and partitioning to the
grain. Information on these aspects is required in selecting for Zn-dense grains. References Agresti, A., 1990. Categorical Data Analysis. Wiley, New York. Giordano, P.M., Mortvedt, J.J., 1974. Response of several rice cultures to Zn. Agron. J. 66, 220±223. Graham, R.D., Rengel, Z., 1993. Genotype variation in zinc uptake and utilization. In: Robson, A.D. (Ed.), Zinc in Soils and Plants. Kluwer Academic Publisher, Dordrecht, The Netherlands, pp. 107±118. Graham, R.D., Senadhira, D., Beebe, S., Iglesias, C., Monastereio, I., 1999. Breeding for micronutrient density in edible portions of staple food crops: conventional approaches. Field Crops Res. 60, 57±80. IRRI, 1996. Standard Evaluation System Manual. International Rice Research Institute, Manila, Philippines, p. 35. Nene, Y.L., 1966. Symptoms, cause and control of Khaira disease of paddy. Bull. Ind. Phytopathol. Soc. 3, 97±101. Neue, H.U., Lantin, R.S., Cayton, M.T.C., Autor, N.U., 1990. Screening of rices for adverse soils tolerance. In: El Bassam, N., Dambroth, M., Loughman, B.C. (Eds.), Genetic Aspects of Plant Nutrition. Kluwer Academic Publisher, Dordrecht, The Netherlands, pp. 523±531. Obata, H., Shimoyama, A., Umebayashi, M., 1997. Effect of shading on zinc de®ciency symptoms in rice. Soil Sci. Plant Nutr. 43, 933±936. Ponnamperuma, F.N., 1985. Chemical kinetics of wetland rice soils relative to soil fertility. In: Wetland Soils: Characterization, Classi®cation, and Utilization. International Rice Research Institute, Los BanÄos, Laguna, Philippines, pp. 71±89. Ruel, M.T., Bouis, H.E., 1998. Plant breeding: a long term strategy for the control of Zn de®ciency in vulnerable populations. Am. J. Clin. Nutr. 68 (2(S)), 488±494. Scharpenseel, H.W., Eichwald, E., Haupenthal, C., Neue, H.U., 1983. Zinc de®ciency in a soil toposequence, grown to rice, at Tiaong, Quezon Province, Philippines. Catena 10, 115±132. SillanpaÈaÈ, M., 1990. Micronutrients Assessment at the Country Level: An International study. FAO Soils Bulletin No. 63. Food and Agricultural Organization of the United Nations, Rome, Italy. Stokes, M.E., Davis, C.S., Koch, G.G., 1995. Categorical data analysis using the SAS System. SAS Institute, Cary, NC. Van Breemen, N., Quijano, C.C., Sen, L.N., 1980. Zinc de®ciency in wetland rice along a toposequence of hydromorphic soils in the Philippines. I. Soil conditions and hydrology. Plant Soil 57, 203±214. Welch, R., Graham, R.D., 1999. A new paradigm for world agriculture: meeting human needs. Productive, sustainable and nutritious. Field Crops Res. 60, 1±10. White, J.G., Zasoski, R.J., 1999. Mapping soil micronutrients. Field Crops Res. 60, 11±24.