Measurement and management of genotype-environment interaction (GxE) for the improvement of rainfed lowland rice yield in Cambodia

The magnitude and nature of genotype-by-environment interactions (G×E) for grain yield (GY) and days to flower (DTF) in Cambodia were examined using a random population of 34 genotypes taken from the Cambodian rice improvement program. These genotypes were evaluated in multi-environment trials (MET) conducted across three years (2000 to 2002) and eight locations in the rainfed lowlands. The G×E interaction was partitioned into components attributed to genotype-by-location (G×L), genotype-by-year (G×Y) and genotype-by-location-by-year (G×L×Y) interactions. The G×L×Y interaction was the largest component of variance for GY. The G×L interaction was also significant and comparable in size to the genotypic component (G). The G×Y interaction was small and non significant. A major factor contributing to the large G×L×Y interactions for GY was the genotypic variation for DTF in combination with environmental variation for the timing and intensity of drought. Some of the interactions for GY associated with timing of plant development and exposure to drought were repeatable across the environments enabling the identification of three-target populations of environments (TPE) for consideration in the breeding program. Four genotypes were selected for wide adaptation in the rainfed lowlands in Cambodia.

Effect of environment and genotype on bread-making quality of spring-sown spring wheat cultivars in China

Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.

Improving drought tolerance in rainfed lowland rice: An example from Thailand

A large portion of the world's poor farm in rainfed systems where the water supply is unpredictable and droughts are common. In Thailand there are approximately 6.2 million ha of rain fed lowland rice, which account for 67% of the country's total rice-growing area. This rice system is often characterised by too much and too little water in the same season. Farmers' estimates of their annual losses to drought are as high as 45% in the upper parts of the toposequence. In contrast to irrigated rice systems, gains from crop improvement of rainfed rice have been modest, in part because there has been little effort to breed and select for drought tolerance for the target rainfed environments. The crop improvement strategy being used in Thailand considers three mechanisms that influence yield in the drought prone targets: yield potential as an important mechanism for mild drought (where yield loss is less than 50%), drought escape (appropriate phenology) and drought tolerance traits of leaf water potential, sterility, flower delay and drought response index for more severe drought conditions. Genotypes are exposed to managed drought environments for selection of drought tolerant genotypes. A marker assisted selection (MAS) scheme has been developed and applied for selection of progenies in the backcrossing program. The plant breeding program uses rapid generation advance techniques that enable early yield testing in the target population of environments (TPE) through inter-station (multi-location yield testing) and on-farm trials. A farmer participatory approach has been used to identify the TPE for the breeding program. Four terrace paddy levels have been identified, upper (drought), middle (drought prone to favorable) and lower (flooded). This paper reports the change in the breeding program for the drought prone tainted lowland rice environments of North and Northeast Thailand by incorporating our knowledge on adaptation and on response of rice to drought. (c) 2005 Elsevier B.V. All rights reserved.

The effects of density on the growth and survival of different families of juvenile Penaeus japonicus Bate

Variations in the growth and survival of six families of juvenile (initial mean weight = 4.16 g) Penaeus japonicus were examined at two densities (48 and 144 individuals m(-2)) in a controlled laboratory experiment. Survival was very high throughout the experiment (95.4%), but differed significantly between densities and rearing tanks. Family, sex and family x density interaction did not significantly affect survival. Mean specific growth rate (SGR) of the shrimp was 18% faster at the low density (1.93 +/- 0.05% day(-1)) than at high density (1.64 +/- 0.03% day(-1)). However, there was a small but significant interaction between family and density indicating that growth of the families was not consistent at both densities. The inconsistent growth of the families across the two densities resulted in a change in the relative performance (ranking) of families at each density. Sex, rearing tank and rearing cage also affected growth of the shrimp. Mean SGR of the females (1.79 +/- 0.03% day(-1)) was 5% faster than males (1.70 +/- 0.03% day(-1)) when averaged across both densities. Shrimp grew significantly faster in rearing tank 3 than rearing tank 1 or 2 at both densities. Results of the present study suggest that family x density interaction could affect the efficiency of selection for growth if shrimp stocks produced from shrimp breeding programs are to be grown across a wide range of densities. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Application of DNA parentage analyses for determining relative growth rates of Penaeus japonicus families reared in commercial ponds

The ability to track large numbers of individuals and families is a key determinant of the power and precision of breeding programs, including the capacity to quantify interactions between genotypes and their environment. Until recently, most family based selective breeding programs for shrimp, and other highly fecund aquaculture species, have been restricted by the number of animals that can be physically tagged and individually selected. Advances in the development of molecular markers, such as microsatellite loci, are now providing the means to track large numbers of individuals and families in commercial production systems. In this study microsatellites, coupled with DNA parentage analyses, were used to determine the relative performance of 22 families of R japonicus reared in commercial production ponds. In the experimental design 6000 post-larvae from each of 22 families, whose maternal parents had been genotyped at 8 microsatellite loci, were stocked into each of four I ha ponds. After 6 months the ponds were harvested and a total of 6000 individuals were randomly weighed from each pond. Mean wet weight of the shrimp from one pond was significantly lower than that of the other three ponds demonstrating a possible pond effect on growth rate. The representation of families in the top 10% of each pond's weight distribution was then determined by randomly genotyping up to 300 individuals from this upper weight class. Parentage analyses based on individual genotypic data demonstrated that some families were over-represented in the top 10% in all ponds, while others were under-represented due to slower growth rates. The results also revealed some weak, but significant, male genotype x environment (G x E) interactions in the expression of shrimp growth for some families. This indicates that G x E effects may need to be factored into future R japonicus selective breeding programs. This study demonstrated the utility of DNA parentage analyses for tracking individual family performance in communally stocked shrimp pond populations and, its application to examining G x E effects on trait expression under commercial culture conditions. Crown Copyright (c) 2005 Published by Elsevier B.V. All rights reserved.

Pattern analysis on grain yield performance of Chinese and CIMMYT spring wheat cultivars sown in China and CIMMYT

Understanding the relationships among testing environments is essential for better targeting cultivars to production environments. To identify patterns of cultivar, environment, cultivar-by-environment interactions, and opportunities for indirect selection for grain yield, a set of 25 spring wheat cultivars from China and the International Maize and Wheat Improvement Center (CIMMYT) was evaluated in nine environments in China and four management environments at CIMMYT in Cd. Obregon, Mexico, during two wheat seasons. Genetic background and original environment were the main factors influencing grain yield performance of the cultivars. Baviacora M 92, Xinchun 2 and Xinchun 6 showed relatively more stable and higher grain yields, whereas highly photoperiod sensitive cultivars Xinkehan 9, Kefeng 6 and Longmai 19 proved consistently inferior across environments, except in Harbin and Keshan, the two high latitude environments. Longmai 26, also from high latitude environments in the northeastern Heilongjiang province, was however probably not as photoperiodicly sensitive as other cultivars; from that region, and produced much higher grain yield and expressed a broader adaptation. None of the environments reported major diseases. Pattern analyses revealed that photoperiod response and planting option on beds were the two main factors underlying the observed interactions for grain yield. The production environment of planting on the flat in Mexico grouped together with Huhhot and Urumqi in both wheat seasons, indicating an indirect response to selection for grain yield in this CIMMYT managed environment could benefit the two Chinese environments. Both the environment of planting on the flat with Chinese Hejin and Yongning, and the three CIMMYT enviromnents planting on raised beds with Chinese Yongning grouped together only in one season, showing that repeatability may not be stable in this case.

Analysis of line x environment interactions for yield in navy beans. 2. Pattern analysis of lines and environment within years

Seven years of multi-environment yield trials of navy bean (Phaseolus vulgaris L.) grown in Queensland were examined. As is common with plant breeding evaluation trials, test entries and locations varied between years. Grain yield data were analysed for each year using cluster and ordination analyses (pattern analyses). These methods facilitate descriptions of genotype performance across environments and the discrimination among genotypes provided by the environments. The observed trends for genotypic yield performance across environments were partly consistent with agronomic and disease reactions at specific environments and also partly explainable by breeding and selection history. In some cases, similarities in discrimination among environments were related to geographic proximity, in others management practices, and in others similarities occurred between geographically widely separated environments which differed in management practices. One location was identified as having atypical line discrimination. The analysis indicated that the number of test locations was below requirements for adequate representation of line x environment interaction. The pattern analyses methods used were an effective aid in describing the patterns in data for each year and illustrated the variations in adaptive patterns from year to year. The study has implications for assessing the number and location of test sites for plant breeding multi-environment trials, and for the understanding of genetic traits contributing to line x environment interactions.

Milling quality and protein properties of autumn-sown Chinese wheats evaluated through multi-location trials

Eight milling quality and protein properties of autumn-sown Chinese wheats were investigated using 59 cultivars and advanced lines grown in 14 locations in China from 1995 to 1998. Wide ranges of variability for all traits were observed across genotypes and locations. Genotype, location, year, and their interactions all significantly influenced most of the quality parameters. Kernel hardness, Zeleny sedimentation value, and mixograph development time were predominantly influenced by the effects of genotype. Genotype, location and genotype x location interaction were all important sources of variation for thousand kernel weight, test weight, protein content, and falling number, whereas genotype x location interaction had the largest effect on flour yield. Most of the genotypes were characterized by weak gluten strength with Zeleny sedimentation values less than 40 ml and mixograph development time shorter than 3 min. Eight groups of genotypes were recognized based on the average quality performance, grain hardness and gluten strength were the two parameters that determined the grouping, with contributions from protein content. Genotypes such as Zhongyou 16 and Annong 8903 displayed good milling quality, high grain hardness, protein content and strong gluten strength with high sedimentation value and long mixograph development time. Genotypes such as Lumai 15 and Yumai 18 were characterized by low grain hardness, protein content and weak gluten strength. Genotypes such as Yannong 15 and Chuanmai 24 were characterized by strong gluten strength with high sedimentation value and long mixograph development time, but low grain hardness and protein content lower than 12.3%. Genotypes such as Jingdong 6 and Xi'an 8 had weak gluten strength, but with high grain hardness and protein content higher than 12.2%. Five groups of locations were identified, and protein content and gluten strength were the two parameters that determined the grouping. Beijing, Shijiazhuang, Nanyang, Zhumadian and Nanjing produced wheats with medium to strong gluten strength and medium protein content, although there was still a large variation for most of the traits investigated between the locations. Wheat produced in Yantai was characterized by strong gluten strength, but with low protein content. Jinan, Anyang and Linfen locations produced wheats with medium to weak gluten strength and medium to high protein content. Wheats produced in Yangling, Zhenzhou, and Chengdu were characterized by weak gluten strength with medium to low protein content, whereas wheats produced in Xuzhou and Wuhan were characterized by weak gluten strength with low protein content. Industrial grain quality could be substantially improved through integrating knowledge of geographic genotype distribution with key location variables that affected end-use quality.