Exploring long-term variety performance trials to improve environment-specific genotype x management recommendations: A case-study for winter wheat

• Autor(a) principal: Munaro, L. B. [UNESP]
• Data de Publicação: 2020
• Outros Autores: Hefley, T. J., DeWolf, E., Haley, S., Fritz, A. K., Zhang, G., Haag, L. A., Schlegel, A. J., Edwards, J. T., Marburger, D., Alderman, P., Jones-Diamond, S. M., Johnson, J., Lingenfelser, J. E., Uneda-Trevisoli, S. H. [UNESP], Lollato, R. P.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.fcr.2020.107848; http://hdl.handle.net/11449/197130
• topic: G x E x M; Long-term data; Exploratory analysis; Conditional inference trees; Management practices

The complex and interactive effects of genotype (G), environment (E), and management (M) can be a barrier to the development of sound agronomic recommendations. We hypothesize that long-term variety performance trials (VPT) can be used to understand these effects and improve regional recommendations. Our objective was to explore long-term VPT data to improve management and variety-selection recommendations using winter wheat (Triticum aestivum L.) in the U.S. central Great Plains as a case-study. Data of grain yield, variety, and trial management were collected from 748 wheat VPT conducted in the states of Colorado, Kansas, and Oklahoma over nineteen harvest years (2000-2018) and 92 locations, resulting in 97,996 yield observations. Using 30-yr cumulative annual precipitation and growing degrees days, we partitioned the study region into 11 contiguous sub-regions, which we refer to as growing adaptation regions (GAR). We used variance component analysis, gradient boosted trees, and conditional inference trees to explore the management and variety trait effects within each GAR. For the variety trait analysis, the VPT dataset was reduced to account for varieties for which 17 agronomic traits and 11 disease/insect reaction ratings were available (65,264 yield observations). GAR accounted for 46 % of the total variation in grain yield, M for 32 %, residuals (including interactions) for 13 %, year for 7 %, and G for 2 %. Conditional inference trees identified interactions among management practices and their effects on yield within each GAR. For instance, water regime was the most important practice influencing wheat yield in the semi-arid western portion of the study region, followed by sowing date and fungicide. In dryland trials, there was typically an interaction between fungicide, sowing date, and tillage system, depending on GAR. Other management practices (e.g. dual-purpose management, crop rotation, and tillage practice) also significantly affected yield, depending on GAR. The main variety trait associated with increased yields depended on region and management combination. For instance, drought tolerance was the most important trait in dryland trials while stripe rust tolerance was more relevant in irrigated trials in the semi-arid region. In this research, we demonstrated an approach that uses widely available long-term VPT data to improve management and variety selection recommendations and can be used in other regions and crops for which long-term VPT data are available.