Quantifying synergistic effects of artificial and environmental variables on potato nutrient use efficiency in China

Excessive use of fertilizer has decreased nutrient use efficiency (NUE), which leads to serious resource waste and environmental pollution. Improving potato NUE is instrumental in reducing fertilizer loss and ensuring agricultural sustainable development. Currently, potato NUE exhibits great spatial variation, and the explanatory variables of potato NUE have not been comprehensively elucidated. To address these challenges, 1850 samples and 56 corresponding explanatory variables were extracted from 19 provinces in the main potato producing areas, and the NUE models were established using random forest model, in which the uncertainty was determined by quantile regression forest model. The results indicated that the partial factor productivity (PFP) and partial nutrient balance (PNB) for nitrogen (N) and phosphorus (P) in northeast China were the highest, while the PFP and PNB for potassium (K) in the northwest were the highest. South China exhibited the lowest NUE. The prediction models had good performance, with better performance of PFP models than PNB models. The models demonstrated that the relative importance of explanatory variables was agricultural management practices (AMPs) > topography > climate > soil > crop > economy. NUE model uncertainty was higher in northwest China (Shaanxi, Gansu, Ningxia) and southwest China (Hubei). In this case, model prediction might have higher performance when constructing a model with data from each region. The findings of this study could have far-reaching implications for policymakers toward understanding the spatial variation of potato NUE. More efforts should be undertaken to investigate the effects of AMPs and topography, which are beneficial for the cleaner production of potato and environmental sustainability.