Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have introduced a favorable opportunity in the response to climate change. This review aims to highlight the use of artificial intelligence and machine learning for crop improvement under current climate change condition. These technologies have many opportunities and are very useful in the actualization of climate policies and decision without limitations on various parameters like improvement in spatial detail of climate models and the allocation of resources for crop improvement. These algorithms identify stipulations in extensive datasets and thus enhance foretelling of several climate parameters including frequency of extreme weather, rate of sea level rise and other climate issues. AI systems and ML systems also participate in environmental impact assessments such as the measurement of deforestation, loss of biodiversity, and carbon emissions. AI is essential to precision agriculture, optimizing resource allocation and boosting crop yields. AI and ML is very useful for the identification of climate smart genotypes, hence help in crop improvement. The prospects of AI and ML adoption into the climate science domain are bright. For global climate science objectives to be realized, AI and ML integration should be harnessed through different disciplines, appropriate data ecosystem and ethical standards. 

Keywords

artificial intelligence (AI), machine learning (ML), crop improvement, datasets, environmental impact, crop yield