info:ar-repo/semantics/artículo
Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
Fecha
2022-10Autor
Di Mauro, Guido
Parra, Gonzalo
Santos, Diego Jose
Enrico, Juan Martin
Zuil, Sebastian
Murgio, Marcos
Zbinden, Facundo
Costanzi, Jerónimo
Arias, Norma Monica
Carrio, Alejandro Javier
Vissani, Cristian Angel
Fuentes, Francisco Horacio
Salvagiotti, Fernando
Resumen
Soybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.