TY - JOUR
T1 - Soybean yield in relation to environmental and soil properties
AU - Faé, Giovani Stefani
AU - Kemanian, Armen R.
AU - Roth, Gregory W.
AU - White, Charles
AU - Watson, John E.
N1 - Funding Information:
This work was supported by grant GNE16-138-29994 from NESARE (University of Vermont), the Pennsylvania and National Soybean Boards, the Brazilian Agricultural Research Corporation (Embrapa) and Hatch Appropriations under Project #PEN04571 and Accession #1003346 . The authors thank the expert and invaluable support from Rodrigo Masip, Felipe Montes, Sjoerd Duiker, Delbert Voight, Brian Macafee and Zach Larson, the personnel at the Russell E. Larson Agricultural Research Farm at Rock Springs as well as that at the Southeast Agricultural Research and Extension Center in Landisville, the Agricultural Analytical Services Lab, the Soil Cluster Laboratory, and the farmers Brian Kreider, Carl Gates, Darren Grumbine, Glenn Krall, John Harrell, and William Stringer.
Funding Information:
This work was supported by grant GNE16-138-29994 from NESARE (University of Vermont), the Pennsylvania and National Soybean Boards, the Brazilian Agricultural Research Corporation (Embrapa) and Hatch Appropriations under Project #PEN04571 and Accession #1003346. The authors thank the expert and invaluable support from Rodrigo Masip, Felipe Montes, Sjoerd Duiker, Delbert Voight, Brian Macafee and Zach Larson, the personnel at the Russell E. Larson Agricultural Research Farm at Rock Springs as well as that at the Southeast Agricultural Research and Extension Center in Landisville, the Agricultural Analytical Services Lab, the Soil Cluster Laboratory, and the farmers Brian Kreider, Carl Gates, Darren Grumbine, Glenn Krall, John Harrell, and William Stringer.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/8
Y1 - 2020/8
N2 - Our goal was to identify soil, plant and climate attributes that are most closely related to soybean [Glycine max (L.) Merr.] yield variation in Pennsylvania. We studied 22 site-years over the 2016 and 2017 growing seasons in two regions. The average yields were 3.4 Mg ha-1 in 2016 (range 1.4 to 5 Mg ha-1) and 5.5 Mg ha-1 in 2017 (range 3.5 to 7.4 Mg ha-1). Solar radiation capture and water availability, both controlled by planting date, were the main predictors of soybean yield. Principal component analysis and Random Forest analysis revealed that the soil predictors of soybean yield were the content of zinc, copper, phosphorus, sulfur, potassium, as well as A horizon depth and total soil depth. The yield response to nutrients is likely a surrogate for a more complex response to animal manure additions. Soybean yield correlated positively with the ratio of soil respiration to soil organic matter, but did not correlate with the physical and biological soil metrics in the comprehensive Cornell Assessment of Soil Health (CASH). Saturated hydraulic conductivity (ksat) and root depth correlated with both soybean yield and each other. Thus, while planting date sets the maximum achievable yield, only soils having the most water and nutrient availability (manured soils with high ksat) expressed yields exceeding 7 Mg ha-1. The ksat appears to be a valuable indicator of soil condition that can be relevant well beyond its association with high soybean grain yield.
AB - Our goal was to identify soil, plant and climate attributes that are most closely related to soybean [Glycine max (L.) Merr.] yield variation in Pennsylvania. We studied 22 site-years over the 2016 and 2017 growing seasons in two regions. The average yields were 3.4 Mg ha-1 in 2016 (range 1.4 to 5 Mg ha-1) and 5.5 Mg ha-1 in 2017 (range 3.5 to 7.4 Mg ha-1). Solar radiation capture and water availability, both controlled by planting date, were the main predictors of soybean yield. Principal component analysis and Random Forest analysis revealed that the soil predictors of soybean yield were the content of zinc, copper, phosphorus, sulfur, potassium, as well as A horizon depth and total soil depth. The yield response to nutrients is likely a surrogate for a more complex response to animal manure additions. Soybean yield correlated positively with the ratio of soil respiration to soil organic matter, but did not correlate with the physical and biological soil metrics in the comprehensive Cornell Assessment of Soil Health (CASH). Saturated hydraulic conductivity (ksat) and root depth correlated with both soybean yield and each other. Thus, while planting date sets the maximum achievable yield, only soils having the most water and nutrient availability (manured soils with high ksat) expressed yields exceeding 7 Mg ha-1. The ksat appears to be a valuable indicator of soil condition that can be relevant well beyond its association with high soybean grain yield.
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U2 - 10.1016/j.eja.2020.126070
DO - 10.1016/j.eja.2020.126070
M3 - Article
AN - SCOPUS:85084733128
VL - 118
JO - European Journal of Agronomy
JF - European Journal of Agronomy
SN - 1161-0301
M1 - 126070
ER -