Fig. 5: BRT analysis identifies the relative importance of 12 predictors that drive the effects of CCs on yield and SOC. | npj Sustainable Agriculture

Fig. 5: BRT analysis identifies the relative importance of 12 predictors that drive the effects of CCs on yield and SOC.

From: Optimizing cover cropping application for sustainable crop production

Fig. 5: BRT analysis identifies the relative importance of 12 predictors that drive the effects of CCs on yield and SOC.The alternative text for this image may have been generated using AI.

a, b Variable importance for the effects of CCs on SOC at 0–30 cm depth with legume CCs (a) and non-legume CCs (b). d, e Variable importance of the effects of CCs on yield with legume CCs (d) and non-legume CCs (e). c, f The relationship between the model’s predicted and measured response ratios for SOC at 0–30 cm depth (c) and yield (f). The red and yellow lines in c, f represent the fitted function of legume and non-legume CCs, respectively, and the dashed gray line is the 1:1 line. The figure is drawn using the R project.

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