Identifying the drivers and predicting the outcome of conservation agriculture globally
Conservation agriculture (CA) is a potentially viable system for sustainable intensification
across diverse agroecological and socio-economic landscapes. This analysis applied
machine-learning techniques to a wealth of published data to create a predictive model of
the agronomic outcome of CA relative to conventional practice (CP) based on 21 variables.
The impact of different management scenarios were modeled by manipulating model input
values for residue retention and N application rate, CA duration, and the ratio of CA to CP …
across diverse agroecological and socio-economic landscapes. This analysis applied
machine-learning techniques to a wealth of published data to create a predictive model of
the agronomic outcome of CA relative to conventional practice (CP) based on 21 variables.
The impact of different management scenarios were modeled by manipulating model input
values for residue retention and N application rate, CA duration, and the ratio of CA to CP …
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