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Article Abstract
Challenges such as a downward trend in cultivation and post-harvest losses lead to increased gap in cocoa bean supply and demand. This review deals with the recent AI models used in farming, processing, and supply chain of cocoa beans. Farming models viz. XAI-CROP, Random Forest, and Gradient Boosting can detect cocoa diseases, recommend appropriate pesticides, enable targeted crop spraying, count the number of pods on cocoa trees, and indicate cocoa pod ripeness. Processing models involving AI viz. Artificial Neural Network, Bootstrap Forest fermentation, and Particle Swarm Optimisation were explored for their efficiency in technological steps viz drying, roasting, conching, and tempering to obtain high-quality chocolates. The supply chain models used AI such as Decision Tree, Multi-level Perception and Long Short-Term memory for cold storage, traceability, and deforestation prediction. AI can thus be used to standardise the quality of produce by optimal resource utilisation leading to minimal impact on the environment.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12408427 | PMC |
| http://dx.doi.org/10.1007/s10068-025-01848-5 | DOI Listing |
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