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.

Pan bread and dry white Chinese noodle quality in Chinese winter wheats

Abstract: Improvements in pan bread quality and Chinese dry white noodle (DWCN) quality are the major breeding objectives in the north China winter wheat region. Eighty-one wheat cultivars and advanced lines were sown in two locations in the 2000–2001 season to evaluate the quality of winter wheat germplasm and investigate the association between pan bread quality and DWCN quality. Significant variability was observed for grain, pan bread, and DWCN quality attributes. Six cultivars and lines showed very good pan bread quality, 23 showed excellent DWCN quality in both locations, and the cultivars Yumai 34 and Sunstate showed superior quality for both food products. Protein content and grain hardness were significantly associated with pan bread quality, while the gluten quality-related parameters SDS-sedimentation value, Farinograph stability, and Extensograph maximum resistance, were significantly associated with pan bread quality score, and accounted for 59.3–72.3% of its variation. Yellow colour (b, CIE Lab) showed a strong negative association with pan bread and DWCN quality largely due to the strong and negative association between yellow colour and gluten strength parameters in this germplasm pool. Flour ash content and polyphenol oxidase (PPO) had a negative moderate effect on noodle colour, while protein content and grain hardness were negatively associated with noodle colour, appearance, and smoothness. The association between SDS-sedimentation volume, Farinograph stability, and Extensograph maximum resistance and DWCN score fitted a quadratic regression model, accounting for 31.0%, 39.0%, and 47.0% of the DWCN score, respectively. The starch pasting parameters, peak viscosity and paste breakdown, contributed positively to DWCN quality, with r = 0.57 and 0.55, respectively. Quality requirements for pan bread and DWCN differ in colour, gluten strength, and pasting viscosity. It is suggested that PPO, yellow pigment, SDS sedimentation volume, and peak viscosity are parameters that could be used to screen for DWCN quality in the early generations of a wheat-breeding program.

Diallel Analysis of Grain Iron and Zinc Density in Southern African-Adapted Maize Inbreds

Abstract: Iron and zinc deficiencies in humans are prevalent in areas where maize (Zea mays L.) constitutes a significant portion of the human diet, such as sub Saharan Africa. This study determined the breeding potential for increasing grain Fe and Zn density to increase Fe and Zn intakes among maize-consuming populations. Fourteen southern African-adapted white-grained maize inbred lines were crossed in a diallel. The F 1 hybrids made among seven high and seven low Fe and Zn concentration lines were evaluated in six locations, two replications per location, throughout Zimbabwe in 1999-2000. There were five high productivity sites and one low-N site, typical of the low-input production conditions of small-scale farmers in Zimbabwe. Grain Fe and Zn concentrations were analyzed with an inductively coupled argon plasma emission spectrometer. Variation among genotypes was highly significant for flour Fe and Zn concentration and per kernel Fe and Zn content. General combining ability (GCA) effects for flour Fe and Zn concentration were significantly more important than specific combining ability (SCA) effects in high yielding environments, indicating that per se line evaluation could identify promising lines. Under low N conditions, one low Fe-Zn parent line had a significant positive GCA effect for flour Fe concentration, with no effect on flour Zn concentration. In inbred trials, this line was among the low Fe-Zn lines, though in hybrid combination it emerged as a highly promising line. Therefore, test-cross performance and per se line evaluation should be used to identify iron- and zinc-rich materials for low-N environments.

Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data

Abstract: Modern agriculture uses hyperspectral cameras to obtain hundreds of reflectance data measured at discrete narrow bands to cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra, depending on the camera. This information is used to construct vegetation indices (VI) (e.g., green normalized difference vegetation index or GNDVI, simple ratio or SRa, etc.) which are used for the prediction of primary traits (e.g., biomass). However, these indices only use some bands and are cultivar-specific; therefore they lose considerable information and are not robust for all cultivars. This study proposes models that use all available bands as predictors to increase prediction accuracy; we compared these approaches with eight conventional vegetation indexes (VIs) constructed using only some bands. The data set we used comes from CIMMYT’s global wheat program and comprises 1170 genotypes evaluated for grain yield (ton/ha) in five environments (Drought, Irrigated, EarlyHeat, Melgas and Reduced Irrigated); the reflectance data were measured in 250 discrete narrow bands ranging between 392 and 851 nm. The proposed models for the simultaneous analysis of all the bands were ordinal least square (OLS), Bayes B, principal components with Bayes B, functional B-spline, functional Fourier and functional partial least square. The results of these models were compared with the OLS performed using as predictors each of the eight VIs individually and combined. We found that using all bands simultaneously increased prediction accuracy more than using VI alone. The Splines and Fourier models had the best prediction accuracy for each of the nine time-points under study. Combining image data collected at different time-points led to a small increase in prediction accuracy relative to models that use data from a single time-point. Also, using bands with heritabilities larger than 0.5 only in Drought as predictor variables showed improvements in prediction accuracy.

Examining the Role of Collective Action in an Informal Seed System: A Case Study from the Central Valleys of Oaxaca, Mexico

Abstract: This paper explores social arrangements associated with seed transactions among small-scale maize farmers in the Central Valleys of Oaxaca, Mexico, where no formal seed supply system exists. We test the hypothesis that individual farmers have strong incentives to participate in some form of collective action to ensure their access to seed. Six communities were studied, three of them in detail, using in-depth, semistructured interviews with key informants; focus group discussions; and a tracer study that followed seed flows among farmers. Farmers mostly saved seed and only occasionally acquired seed from outside sources. We found no evidence of a specialized social organization based on collective action to mediate seed flows. Seed transactions are infrequent, bilateral, and ad hoc, although trust is an important component, as it ensures reliable information about the seed is provided. Implications of these findings are discussed, especially for genetic diversity if the current supply system breaks down.