João Vasco Silva

TL;DR: In this article, a comprehensive database consisting of 5228 on-farm trials located in three major maize production regions of China was used for this purpose, and the objective of the study was to decompose maize yield gaps under different nitrogen (N) application rates and soil quality conditions across irrigated and rainfed cropping systems in China.

TL;DR: In this article, a site in Northern Rwanda (representative of the cool humid climatic zone which accounts for most of the spring wheat production of SSA) and analysed the determinants of wheat productivity and profitability for 130 smallholder farms during two consecutive short rainy seasons, namely 2017A and 2018A.

TL;DR: In this paper , a framework for yield gap decomposition accounting for the main genotype, management, and environmental factors explaining crop yield in intensive rice irrigated systems was developed, and context-specific opportunities to narrow yield gaps were identified to target sustainable intensification of rice production in the region.

TL;DR: In this article, a theoretical framework combining concepts of production ecology and methods of frontier analysis was developed to decompose yield gaps into efficiency, resource and technology yield gaps for the major crops in each case study using crop-specific input-output data for a large number of individual farms.

TL;DR: In this paper , the performance of different machine learning methods to explain on-farm wheat yield variability in the Northwestern Indo-Gangetic Plains of India was evaluated using a suite of fine-tuned machine learning models (ridge and lasso regression, classification and regression trees, k-nearest neighbor, support vector machines, gradient boosting, extreme gradient boosting and random forest).