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Machine learning (ML) and big data analytics have emerged as transformative technologies in the agricultural sector, offering innovative solutions to enhance productivity, sustainability, and profitability. This abstract provides an overview of how ML and big data are revolutionizing traditional farming practices by leveraging advanced algorithms and data analytics. It discusses the potential of ML and big data in optimizing crop yield and quality, promoting sustainable practices, enabling precision agriculture, and addressing crop diseases through advanced predictive modelling. The abstract emphasizes the potential of ML and big data to reshape the future of agriculture, fostering resilience and prosperity for farmers and stakeholders worldwide. The application of machine learning in the field of agriculture and its correlation with weather patterns delves into various ways in which machine learning techniques can be used to analyze and predict the impact of weather conditions on agricultural productivity. The paper discusses specific machine learning algorithms and models that have been successfully applied in this domain, providing insights into the potential benefits and challenges of integrating machine learning into agricultural practices.
N et al. (Tue,) studied this question.
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