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.

Efficiency of selective genotyping for genetic analysis of complex traits and potential applications in crop improvement

Abstract: Selective genotyping of individuals from the two tails of the phenotypic distribution of a population provides a cost efficient alternative to analysis of the entire population for genetic mapping. Past applications of this approach have been confounded by the small size of entire and tail populations, and insufficient marker density, which result in a high probability of false positives in the detection of quantitative trait loci (QTL). We studied the effect of these factors on the power of QTL detection by simulation of mapping experiments using population sizes of up to 3,000 individuals and tail population sizes of various proportions, and marker densities up to one marker per centiMorgan using complex genetic models including QTL linkage and epistasis. The results indicate that QTL mapping based on selective genotyping is more powerful than simple interval mapping but less powerful than inclusive composite interval mapping. Selective genotyping can be used, along with pooled DNA analysis, to replace genotyping the entire population, for mapping QTL with relatively small effects, as well as linked and interacting QTL. Using diverse germplasm including all available genetics and breeding materials, it is theoretically possible to develop an “all-in-one plate” approach where one 384-well plate could be designed to map almost all agronomic traits of importance in a crop species. Selective genotyping can also be used for genomewide association mapping where it can be integrated with selective phenotyping approaches. We also propose a breeding-to-genetics approach, which starts with identification of extreme phenotypes from segregating populations generated from multiple parental lines and is followed by rapid discovery of individual genes and combinations of gene effects together with simultaneous manipulation in breeding programs.

Right-Sizing Stem-Rust Research

Abstract: Stem rust caused by Puccinia graminis f. sp. tritici is a potentially devastating fungal disease that can kill wheat plants and small grain cereals but more typically reduces foliage, root growth, and grain yields [e.g., ( 1 , 2 )]. After years of success in keeping the disease at bay, new virulent races (collectively referred to as “Ug99”) have emerged, with the potential to infect much of the world's wheat ( 3 ). Despite, or because of, the success of past research, these programs saw an eventual rundown in support ( 4 ). We estimate global wheat losses over the past 50 years absent investments in research to limit impacts of stem rust and discuss how this can inform decisions about “right-sizing” research investments.

Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

Abstract: Hyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and biochemical processes in plants. Genomic selection models utilize genome-wide marker or pedigree information to predict the genetic values of breeding lines. In this study, we propose a multi-kernel GBLUP approach to genomic selection that uses genomic marker-, pedigree-, and hyperspectral reflectance-derived relationship matrices to model the genetic main effects and genotype × environment (G × E) interactions across environments within a bread wheat (Triticum aestivum L.) breeding program. We utilized an airplane equipped with a hyperspectral camera to phenotype five differentially managed treatments of the yield trials conducted by the Bread Wheat Improvement Program of the International Maize and Wheat Improvement Center (CIMMYT) at Ciudad Obregon, Mexico over four breeding cycles. We observed that single-kernel models using hyperspectral reflectance-derived relationship matrices performed similarly or superior to marker- and pedigree-based genomic selection models when predicting within and across environments. Multi-kernel models combining marker/pedigree information with hyperspectral reflectance phentoypes had the highest prediction accuracies; however, improvements in accuracy over marker- and pedigree-based models were marginal when correcting for days to heading. Our results demonstrate the potential of using hyperspectral imaging to predict grain yield within a multi-environment context and also support further studies on the integration of hyperspectral reflectance phenotyping into breeding programs.

Agricultural Extension, Collective Action and Innovation Systems: Lessons on Network Brokering from Peru and Mexico

Abstract: Purpose: New approaches to extension service delivery are needed that stimulate increased agricultural production, contribute to collective action and which also foster the emergence of agricultural innovation systems. Research in Peru and Mexico explores some of these new approaches. Design/methodology/approach: In both countries, a qualitative value chain mapping methodol- ogy was used to explore the challenges of providing extension provision to resource-poor farmers in ways that stimulate collective action and agricultural innovation systems. Findings: In Peru, collective action and the development of an agriculture innovation system required the network broker activities of initially a non-governmental organization (NGO) and then increasingly trusted local farmers known as Kamayoq. In Mexico, collective action took place in the context of a linear transfer-of-technology approach focused on access to improved maize seed and there was no evidence of the emergence of innovation networks. Practical implications: Different extension modalities can foster collective action but this in itself is not enough to encourage innovation. Extension needs to focus on combining collective action with networking amongst sets of heterogeneous value chain actors. Originality/value: The Peruvian and Mexican case studies demonstrate that the debate about the modalities of pluralistic and diversified extension systems has obscured the reality that the development community still has some way to go to achieve comprehensively the paradigm shift from a linear transfer-of-technology approach to one that supports the emergence of agricultural innovation systems.