Sowing date, genotype choice, and water environment control soybean yields in central Argentina

Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed-effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse-textured Hapludolls and under low-rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.Fil: Vitantonio Mazzini, Lucas Nicolás. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaFil: Gómez, Damián. Don Mario; ArgentinaFil: Gambin, Brenda Laura. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; ArgentinaFil: Di Mauro, Guido. Don Mario; ArgentinaFil: Iglesias, Rodrigo. Don Mario; ArgentinaFil: Costanzi, Jerónimo. Don Mario; ArgentinaFil: Jobbágy, Esteban G.. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Borras, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentin

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

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.EEA ParanáFil: Di Mauro, Guido. Grupo Don Mario (Buenos Aires); ArgentinaFil: Parra, Gonzalo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Santos, Diego Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Grupo Manejo de Cultivos, Suelos y Agua. ArgentinaFil: Zuil, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Murgio, Marcos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Zbinden, Facundo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Costanzi, Jerónimo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Arias, Norma Monica. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Carrio, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Vissani, Cristian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Fuentes, Francisco Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin