Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone

Mauro, Guido Di; Parra, Gonzalo; Santos, Diego J.; Enrico, Juan Martín; Zuil, Sebastián; Murgio, Marcos; Zbinden, Facundo; Costanzi, Jerónimo; Arias, Norma; Carrio, Alejandro; Vissani, Cristian; Fuentes, Francisco; Salvagiotti, Fernando

doi:10.1016/j.fcr.2022.108676

Cited by 9 publications

(1 citation statement)

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“…The “optimum maturity” of any location is its best adapted maturity, or the specific cultivar maturity which maximizes yield in that environment ( Mourtzinis and Conley, 2017 ). Using records of performance and maturity across MET sites, one can identify best adapted maturities, predict optimum maturity across the TPE, and delineate maturity groups ( Zhang et al., 2007 ; Mourtzinis and Conley, 2017 ; Di Mauro et al., 2022 ). For this analysis, the NUST records were combined with environmental data and used to predict optimum soybean maturities across the TPE.…”

Section: Methodsmentioning

confidence: 99%

Using agro-ecological zones to improve the representation of a multi-environment trial of soybean varieties

Gilbert,

Martin

2024

Front. Plant Sci.

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This research introduces a novel framework for enhancing soybean cultivation in North America by categorizing growing environments into distinct ecological and maturity-based zones. Using an integrated analysis of long-term climatic data and records of soybean varietal trials, this research generates a zonal environmental characterization which captures major components of the growing environment which affect the range of adaptation of soybean varieties. These findings have immediate applications for optimizing multi-environment soybean trials. This characterization allows breeders to assess the environmental representation of a multi-environmental trial of soybean varieties, and to strategize the distribution of testing and the placement of test sites accordingly. This application is demonstrated with a historical scenario of a soybean multi-environment trial, using two resource allocation models: one targeted towards improving the general adaptation of soybean varieties, which focuses on widely cultivated areas, and one targeted towards specific adaptation, which captures diverse environmental conditions. Ultimately, the study aims to improve the efficiency and impact of soybean breeding programs, leading to the development of cultivars resilient to variable and changing climates.

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