International Maize and Wheat Improvement Center

About: International Maize and Wheat Improvement Center is a nonprofit organization based out in Texcoco, Mexico. It is known for research contribution in the topics: Population & Agriculture. The organization has 1976 authors who have published 4799 publications receiving 218390 citations.

Studying crossover genotype × environment interaction using linear-bilinear models and mixed models

Abstract: In agriculture and plant breeding the most important genotype × environment interaction pattern is crossover genotype × environment interaction. Procedures using linearbilinear models are used to find disjoint subsets of sites or genotypes with negligible crossover genotype × environment interaction. In terms of correlations, these subsets of sites or genotypes should be such that pairs of sites have nearly perfect positive genetic correlations. Perfect positive genetic correlation between sites is a sufficient, but not a necessary, condition for a non-COI pattern. The main objective of this study was to use the mixed model theory to confirm that the subsets of sites and genotypes formed by using the linear-bilinear models have negligible crossover genotype × environment interaction. If there is no significant crossover interaction in a subset of sites or genotypes, then the mixed model should be able to confirm this by nonrejection of the hypothesis that the covariance structure has perfect genetic correlation. Mixed model analysis of results from two multisite cultivar trials confirmed the validity of the procedures using linear-bilinear model methods for clustering sites and genotypes into noncrossover genotype × environment interaction subsets.

Differential adaptation of CIMMYT bread wheat to global high temperature environments

Abstract: and lowland Bolivia and Paraguay) and lowland dry areas (e.g., central and peninsular India, Nigeria and A good understanding of the target environment and the extent of Sudan). The most important disease constraints are Helgenotype environment (G E) interaction is essential for all cereal breeding programs. Differential adaptation of bread wheat (Triticum minthosporium Leaf Blight (HLB) caused by Bipolaris aestivum L.) to various heat-stressed environments around the world sorokiniana (Sacc.) Shoemaker and leaf rust caused wasanalyzedbycumulativeclusteranalysisoflocationsandgenotypes by Puccinia triticina Eriks. P. recondita Roberge ex in 9 yr of CIMMYT’s High Temperature Wheat Yield Trial (HTWYT). Desmaz. f. sp. tritici (Eriks. & E. Henn.) D.M. HenderThe grouping pattern of yield-testing environments could largely be son (Dubin and van Ginkel, 1990). HLB is mostly conexplained by the temperature at different growth stages and relative fined to the humid tropical areas, whereas leaf rust is humidity at booting. A clear distinction was observed between sites important to all areas (Dubin and Rajaram 1996). Adwith heat stress and more temperate locations, and the heat-stressed vanced breeding lines targeted for heat-stressed areas environments could be grouped into sites experiencing high temperaare annually distributed to international cooperators ture throughout the season and sites with more specific terminal heat through the HTWYT. stress. In addition, dry and humid heat-stressed locations tended to differentiate. The ability of individual locations to predict yield in Crop environments can be characterized in terms of different heat-stressed environments was studied by the shifted multi- the way they influence the relative performance or rank plicative model (SHMM) site clustering method, and identified loca- of genotypes. One useful method for this purpose is tions like Tandojam (Pakistan), which associated well with both heat- the SHMM, which identifies subsets of locations with stressed and temperate environments. The good ability of the January minimal internal crossover interaction (Cornelius et al., planting date in Ciudad Obregon (Mexico) to predict yield perfor- 1992; Crossa et al., 1993). However, this method requires manceinmany heat-stressedenvironmentswasalso confirmed.Geno- balanced data sets where the same locations and genotypes grouped according to their relative performance in different types are repeated over years. To analyze multienvironlocations, and specific adaptation to the various types of heat-stressed ment trials where the composition of genotypes changes environmentswasapparent. However,asubsetofgenotypes wasidenfrom year to year, DeLacy et al. (1996b) developed a tified that showed stable, and high yield across all types of environments, both heat-stressed and temperate. cumulative cluster analysis based on the incremental sum of squares (ISS) or Ward’s strategy (Ward, 1963). ISS has a strong clustering property that tends to minimize the growth of large groups (DeLacy et al., 1996a). A

Dissecting Maize Productivity: Ideotypes Associated with Grain Yield under Drought Stress and Well-watered Conditions

Abstract: To increase maize (Zea mays L.) yields in drought-prone environments and offset predicted maize yield losses under future climates, the development of improved breeding pipelines using a multi-disciplinary approach is essential. Elucidating key growth processes will provide opportunities to improve drought breeding progress through the identification of key phenotypic traits, ideotypes, and donors. In this study, we tested a large set of tropical and subtropical maize inbreds and single cross hybrids under reproductive stage drought stress and well-watered conditions. Patterns of biomass production, senescence, and plant water status were measured throughout the crop cycle. Under drought stress, early biomass production prior to anthesis was important for inbred yield, while delayed senescence was important for hybrid yield. Under well-watered conditions, the ability to maintain a high biomass throughout the growing cycle was crucial for inbred yield, while a stay-green pattern was important for hybrid yield. While new quantitative phenotyping tools such as spectral reflectance (Normalized Difference Vegetation Index, NDVI) allowed for the characterization of growth and senescence patterns as well as yield, qualitative measurements of canopy senescence were also found to be associated with grain yield.

Transgenic Maize and the Evolution of Landrace Diversity in Mexico. The Importance of Farmers' Behavior

Abstract: The discovery of transgenic products in maize ( Zea mays ) landraces planted by small-scale Mexican farmers (Quist and Chapela, [2001][1], [2002][2]; [Christou, 2002][3]; [Editorial Note, 2002][4]) raised questions about how the commercial introduction of transgenic maize varieties might affect the

DSSAT modelling of conservation agriculture maize response to climate change in Malawi

Abstract: Adoption of conservation agriculture (CA) is increasingly being promoted as a way of adapting agricultural systems to increasing climate variability, especially for areas such as southern Africa where rainfall is projected to decrease. The DSSAT crop simulation models can be a valuable tool in evaluating the effects of CA which are viable both economically and environmentally. Our objectives were: (1) to evaluate the ability of DSSAT to predict continuous maize (Zea mays L.) yield for conventional tillage (CT) and CA systems as well as maize yield for a CA maize–cowpea (Vigna unguiculata) rotation on an Oxic rhodustalf (2) to use DSSAT to project weather effect of climate change on yield, economic returns and risk in CT and CA systems. The DSSAT model was calibrated using data from 2007–2008 season and validated against independent data sets of yield of 2008–2009 to 2011–2012 seasons. Simulations of maize yields were conducted on projected future weather data from 2010 to 2030 that was generated by RegCM4 using the A1B scenario. The DSSAT model calibration and validation showed that it could be used for decision-making to choose specific CA practices especially for no-till and crop residue retention. Long term simulations showed that maize–cowpea rotation gave 451 kg ha−1 and 1.62 kg mm−1 rain more maize grain yield and rain water productivity, respectively compared with CT. On the other hand, CT (3131–5023 kg ha−1) showed larger variation in yield than both CA systems (3863 kg ha−1 and 4905 kg ha−1). CT and CA systems gave 50% and 10% cumulative probability of obtaining yield below the minimum acceptable limit of 4000 kg ha−1 respectively suggesting that CA has lower probability of low yield than CT, thus could be preferred by risk-averse farmers in uncertain climatic conditions. Using similar reasoning, Mean-Gini Dominance analysis showed the dominancy of maize–cowpea rotation and indicated it as the most efficient management system. This study therefore suggests that CA, especially when all three principles are practiced by smallholders in the medium altitude of Lilongwe and similar areas, has the potential to adapt the maize based systems to climate change. Use of DSSAT simulation of the effects of CA was successful for no-till and crop residue retention, but poor for crop rotation. Refinement of crop rotation algorithm in DSSAT is recommended.