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Associations among Twenty Years of International Bread Wheat Yield Evaluation Environments

Richard TrethowanWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF MexicoM. van GinkelWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF MexicoKarim AmmarWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF MexicoJosé CrossaBiometrics and Statistics Unit CIMMYT Apdo. Postal 6‐641 06600 Mexico DF MexicoThomas PayneWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF MexicoB. ÇukadarMonsanto Corporation RR3 Box 331C Harbstadt IN USAS. RajaramWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF MexicoEduardo Osorio-HernándezWheat Program International Maize and Wheat Improvement Center (CIMMYT) Apdo. Postal 6‐641 06600 Mexico DF Mexico
2003en
ABI

Аннотация

Understanding the way different environments differentiate cultivars for yield allows the plant breeder to optimize choice of parents, germplasm screening, yield testing, and resource use within the target region. To determine the associations among yield testing environments, wheat ( Triticum aestivum L.) yield data from 963 replicated trials sown across a 20‐yr period were analyzed by means of pattern analysis and the shifted multiplicative model (SHMM) to group sites within and across years. Pattern analysis identified four primary clusters of sites and four representative locations within these clusters were identified by squared Euclidean distances. Group‐1 represented primarily Mediterranean and West Asian locations and South American sites. Group‐2 was comprised of generally warmer sites in southern and eastern Asia. Group‐3 comprised higher rainfall locations in South America and eastern Africa and Group‐4 represented cooler sites in South America and West Asia. The respective key locations for each of the four groups were Sakha, Egypt; Quezaltenango, Guatemala; Londrina, Brazil; and Pirsabak, Pakistan. The four key sites were then used to examine site clusters within each year by SHMM. The sites at Pirsabak and Sakha associated best across all global wheat‐growing regions where a combined total of 700 of 1117 (62%) possible clusters with other global wheat locations were realized. This compared with 52% for Quezaltenango and 38% for Londrina. Factors with a primary influence on site clustering were cropping season moisture availability and temperature. Genotype performance at Pirsabak and Sakha can be used to enhance genetic progress in a range of related wheat growing environments thereby improving the effectiveness of global wheat breeding.

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