Similar Items: Integrating APSIM model with machine learning to predict wheat yield spatial distribution
- Developing automated machine learning approach for fast and robust crop yield prediction using a fusion of remote sensing, soil, and weather dataset
- Advanced Prediction of Rice Yield Gaps Under Climate Uncertainty Using Machine Learning Techniques in Eastern India
- Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
- Predicting climate smart agriculture (CSA) practices using machine learning: A prime exploratory survey
- Predicting aflatoxin risk in maize using machine learning and satellite data in East and Southern Africa
- Deep learning methods improve genomic prediction of wheat breeding
Author: Kheir, A.M.S.
Author: Mkuhlani, S.
- Crop–livestock integration in smallholder farming systems of Goromonzi and Murehwa, Zimbabwe
- Integrating a crop model with a greenhouse gas calculator to identify low carbon agricultural intensification options for smallholder farmers in rural South Africa
- Editorial: modelling approaches for climate variability and change mitigation and adaptation in resource constrained farming systems
- Yield stability assessment under climate change using crop modelling frameworks V1
- Soybean water-limited yields, optimum maize sowing time & variety recommendations summary for the Zambezi River Basin (including the Chinyanja triangle)
- Lessons from integrated seasonal forecast-crop modelling in Africa: a systematic review