摘要：Integration of AI and ML technologies in the agricultural supply chain(ASC) is revolutionalizing, the domain by bringing in robust monitoring and pre-diction as well as quick decision-making abilities. A comprehensive literature analysis of the applications of artificial intelligence methods and machine learn-ing algorithms in the agricultural supply chain is demonstrated in this study. In order to solve compli-cated challenges confronted by various areas of the agricultural supply chain, this literature analysis ad-dresses different significant works that machine learning and artificial intelligence methods are used. Different AIand ML applications were suggested for the following areas of agriculture belonging to dif-ferent phases:(i) crop yield prediction, prediction of soil properties and irrigation management;(ii)weather prediction, disease detection and weed de-tection,(i) demand management and production planning,(iv)transportation, storage, inventory and retailing. In order to remain unbiased and objective, different studies from different journals were ana-lyzed for each phase. It is observed that the majority ofthese studies focus on crop yield and soil proper-ties prediction. It is also inferred that artificial neural networks, support vector machines, utilization of un-manned aerial vehicles, and remote sensors are fairly popular in the agriculture discipline.
