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.

Household energy choice and consumption intensity: Empirical evidence from Bhutan

Abstract: This paper uses data from three Bhutan Living Standard surveys (BLSS 2003, BLSS 2007, and BLSS 2012) to examine the trends and patterns of household energy consumption, and identify and analyze the factors that influence household energy choices, consumption intensity and the per capita household expenditure on energy sources in Bhutan. During the last decade significant numbers of Bhutanese households have switched to cleaner energy sources. Empirical results show that a household׳s choice of cleaner energy sources is driven by income level and household wealth, the age, gender and education of the household heads, access to electricity, and location. Education and income have a differential role on the choice of clean or dirty fuel; wealthier and more educated households use and rely more on clean sources of energy like electricity and liquid petroleum gas while poorer households use and rely on dirty fuel such as fuelwood and kerosene. The study shows that female-headed households are more likely to choose cleaner fuels and, above all, the availability of a clean and cost-effective source of energy within proximity to the household is an important factor in the adoption of clean energy. Several models using a variety of alternative independent variables, such as proxies for education and wealth, were estimated and confirmed the robustness of the results.

Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models

Abstract: In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects.

Detection of the apomictic mode of reproduction in maize.Tripsacum hybrids using maize RFLP markers

Abstract: Polyploid plants in the genus Tripsacum, a wild relative of maize, reproduce through gametophytic apomixis of the diplosporous type, an asexual mode of reproduction through seed. Moving gene(s) responsible for the apomictic trait into crop plants would open new areas in plant breeding and agriculture. Efforts to transfer apomixis from Tripsacum into maize at CIMMYT resulted in numerou intergeneric F1 hybrids obtained from various Tripsacum species. A bulk-segregant analysis was carried out to identify molecular markers linked to diplospory in T. dactyloides. This was possible because of numerous genome similarities among related species in the Andropogoneae. On the basis of maize RFLP probes, three restriction fragments co-segregating with diplospory were identified in one maize-Tripsacum dactyloides F1 population that segregated 1∶1 for the mode of reproduction. The markers were also found to be linked in the maize RFLP map, on the distal end of the long arm of chromosome 6. These results support a simple inheritance of diplospory in Tripsacum. Manipulation of the mode of reproduction in maize-Tripsacum backcross generations, and implications for the transfer of apomixis into maize, are discussed.

Quality (End-Use) Improvement in Wheat: Compositional, Genetic, and Environmental Factors

Abstract: Wheat provides nutrients and the raw materials for industrialized food production. Recent global economic trends and increases in urban population growth have led to an increased demand for wheat-based convenience foods (fast, ready-to-eat, frozen foods, etc.) and for new wheat-based products. These factors have resulted in a greater emphasis than ever on the end-use quality of wheat. This paper reviews grain compositional aspects influencing the processing and quality attributes of the main foods produced with wheat, as well as the breeding strategies and methodologies used to achieve germplasm with desirable end-use quality. Common wheat (Triticum aestivum) is used in bread (leavened, flat, and steamed), noodles, biscuits, and cakes. Durum wheat (T. turgidum L. var. durum) is used globally in alimentary pasta and regional foods (flat breads, couscous, and burghoul) in North Africa and West Asia. Grain characteristics (grain hardness, protein content/quality, enzymatic activity, etc.) play a mod...

Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants.

Abstract: Although long-term genetic gain has been achieved through increasing use of modern breeding methods and technologies, the rate of genetic gain needs to be accelerated to meet humanity's demand for agricultural products. In this regard, genomic selection (GS) has been considered most promising for genetic improvement of the complex traits controlled by many genes each with minor effects. Livestock scientists pioneered GS application largely due to livestock's significantly higher individual values and the greater reduction in generation interval that can be achieved in GS. Large-scale application of GS in plants can be achieved by refining field management to improve heritability estimation and prediction accuracy and developing optimum GS models with the consideration of genotype-by-environment interaction and non-additive effects, along with significant cost reduction. Moreover, it would be more effective to integrate GS with other breeding tools and platforms for accelerating the breeding process and thereby further enhancing genetic gain. In addition, establishing an open-source breeding network and developing transdisciplinary approaches would be essential in enhancing breeding efficiency for small- and medium-sized enterprises and agricultural research systems in developing countries. New strategies centered on GS for enhancing genetic gain need to be developed.