Variables ambientales y de manejo que definen el rendimiento de soja (Glycine max (L.) Merr.) en el noreste argentino
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2021
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La región noreste de Argentina (NEA) forma parte del Gran Chaco, una de las regiones a nivel global con las mayores tasas de desforestación en los últimos años a causa de la expansión de la frontera agrícola. Esta nueva superficie productiva está mayormente destinada al cultivo de soja. A pesar de la importancia económica del cultivo de soja para esta región, son escasos los estudios orientados a proveer mejoras para un manejo sustentable de los sistemas de producción. Los objetivos del trabajo fueron (i) identificar variables de manejo y del ambiente claves para el rendimiento de soja, y cuantificar su impacto, y (ii) explorar interacciones entre el grupo de madurez (GM) del genotipo y otras variables de manejo y ambientales. Se realizaron 112 ensayos multi-ambientales (EMAs) en campos de productores durante 11 campañas productivas consecutivas (2008/09 a 2018/19) donde en cada uno se incluyeron 14 a 19 genotipos comerciales dentro del rango de GM V a VIIII.
En primer lugar se analizó un solo genotipo sembrado en 106 EMAs para identificar las variables de manejo y ambiente que tengan buen poder predictivo para el rendimiento de soja, que varió entre 435 y 5117 kg.ha-1. Las variables ambientales más relevantes fueron, en orden de importancia, lluvias desde 30 días antes de la siembra a madurez fisiológica (R7), años desde el inicio de la agricultura, evapotranspiración de referencia desde siembra a R7, y número de períodos de 2 días con temperatura máxima mayor a 35°C desde inicio de floración (R1) a R7. En base a la importancia relativa (IR), la fecha de siembra fue la variable de manejo más importante (IR = 0,99), seguida por la disponibilidad de fósforo del suelo (IR = 0,59). En el segundo análisis, se encontró que la elección del genotipo también tuvo un importante efecto significativo. Hubo una interacción entre el GM y la fecha de siembra, se encontró una mayor reducción del rendimiento por el atraso de la fecha de siembra en GM VIII, seguido de GM VII, mostrando los GM VI y V las menores mermas. Las mayores diferencias de rendimiento entre GM fueron observadas en ambientes con elevado contenido de materia orgánica del suelo (rango desde 1,64 a 4,05%). Los resultados mostraron variables de manejo específicas para optimizar el manejo de los sistemas de producción de soja en la región NEA. Las reducciones en rendimiento provocadas por los años desde el inicio de la agricultura y por disminuciones en la materia orgánica del suelo sugieren un deterioro de la calidad de los ambientes de la región, y la necesidad del desarrollo de nuevas alternativas productivas para detener estas tendencias.
Northeastern Argentina is part of the Gran Chaco, one of the global regions with the highest recent rates of agricultural expansion due to soybean production. In this region, studies that provide options for sustainable soybean management are scarce. The objectives of this study were (i) to identify and to quantify key management and environmental soybean yield predictors, and (ii) to explore interactions among management and environmental factors with maturity group selection. Commercial genotypes were evaluated in 112 multi-environment on-farm trials (METs) during 11 consecutive years (from 2008/09 to 2018/19), where 14 to 19 commercial genotypes within the range of MG V to VIIII were included in each one. We first analyzed a single genotype sown in 106 METs to identify management and environmental variables that have good predictive power for soybean yield, which ranged from 435 to 5117 kg.ha-1. Relevant environmental variables were, in order of importance, rainfall from 30 days before sowing to physiological maturity (R7), years after land conversion to agriculture, reference evapotranspiration from sowing to R7, and the number of 2-day periods with maximum temperatures above 35°C from beginning of flowering to R7. Sowing date was the most important management variable, followed by phosphorous availability. In the second analysis, it was found that genotype selection also had a strong significant effect. There was an interaction between the MG and the sowing date, a greater reduction in yield was found due to delays in the sowing date in MG VIII, followed by MG VII, with MG VI and V showing the lowest losses. The greatest differences in yield between MG were observed in environments with a high content of soil organic matter (range from 1,64 to 4,05%). These results illustrate specific management variables to guide farmers and advisors to optimize regional soybean cropping systems. The negative yield effect promoted by years after land conversion and reductions in soil organic matter suggest a decline in the environmental quality of the region and the need for new production alternatives to halt these trends
Northeastern Argentina is part of the Gran Chaco, one of the global regions with the highest recent rates of agricultural expansion due to soybean production. In this region, studies that provide options for sustainable soybean management are scarce. The objectives of this study were (i) to identify and to quantify key management and environmental soybean yield predictors, and (ii) to explore interactions among management and environmental factors with maturity group selection. Commercial genotypes were evaluated in 112 multi-environment on-farm trials (METs) during 11 consecutive years (from 2008/09 to 2018/19), where 14 to 19 commercial genotypes within the range of MG V to VIIII were included in each one. We first analyzed a single genotype sown in 106 METs to identify management and environmental variables that have good predictive power for soybean yield, which ranged from 435 to 5117 kg.ha-1. Relevant environmental variables were, in order of importance, rainfall from 30 days before sowing to physiological maturity (R7), years after land conversion to agriculture, reference evapotranspiration from sowing to R7, and the number of 2-day periods with maximum temperatures above 35°C from beginning of flowering to R7. Sowing date was the most important management variable, followed by phosphorous availability. In the second analysis, it was found that genotype selection also had a strong significant effect. There was an interaction between the MG and the sowing date, a greater reduction in yield was found due to delays in the sowing date in MG VIII, followed by MG VII, with MG VI and V showing the lowest losses. The greatest differences in yield between MG were observed in environments with a high content of soil organic matter (range from 1,64 to 4,05%). These results illustrate specific management variables to guide farmers and advisors to optimize regional soybean cropping systems. The negative yield effect promoted by years after land conversion and reductions in soil organic matter suggest a decline in the environmental quality of the region and the need for new production alternatives to halt these trends
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Soja, Argentina, Rendimiento de cultivos, Fecha de siembra, Factores ambientales, Grupo de madurez