Narrowing crop yield gaps in Ethiopia under current and future climate: A model-based exploration of intensification options and their trade-offs with the water balance

Implementation and application of APSIM for crop modelling in Ethiopia: A comprehensive review

“…Of the fourteen research articles reviewed in this paper, ten were done on maize, two on wheat, two on sorghum, and one on both maize and wheat simultaneously. Among the wheat across different locally grown early, medium, and late-growing cultivars such as Hartog [ 18 ], HAR-2501 (Hawi) [ 19 ], Hawi, and Digelu cultivars [ 20 ] were used for APSIM wheat calibration and validation. For sorghum model calibration and validation, locally available cultivars Gigrite [ 21 ], Meko, and Jigurti [ 22 ] were used.…”

Assessing the growth dynamics of alfalfa varieties (Medicago sativa cv. Bilensoy 80 and Nimet) response to varied carbon dioxide (CO2) concentrations

“…Climate is one of the most crucial aspects of agricultural output [ [1] , [2] , [3] ]. Climate patterns are altering as a consequence of a rise in greenhouse gas levels in the atmosphere [ 4 , 5 ].…”

Integrating APSIM model with machine learning to predict wheat yield spatial distribution

“…New technology will transform farming and agribusiness, making it more profitable (Popescu et al, 2022). Crop models have been widely used in cropping system simulations for a variety of purposes, including agricultural water management (Kheir et al, 2021), food security and nutrition, and genotype × environment × management (G × E × M) interactions (Cooper et al, 2021), and narrowing yield gaps (Asseng et al, 2018;Getnet et al, 2022). Crop models have recently demonstrated the ability to predict genetic yield potential despite significant difficulties (Guarin et al, 2022).…”