Systematic Reviews of Machine Learning Applications in Corn: A Literature Review

In the realm of corn cultivation, Machine learning application revolutionizes conventional farming methods by imposing advanced algorithms to analyze diverse datasets. Machine learning can be applied in projecting crop yields, detecting diseases, and controlling weeds. This method eventually enhances efficiency and crop productivity. The goal of the literature review is to analyze systematically and incorporate the existing collection of research on machine learning applications in the context of corn cultivation. The review investigates the vast range of machine learning techniques employed, their impact, and their effectiveness on different aspects of corn agriculture. The review highlights the different models that are used in different applications of machine learning in corn cultivation and its impact in the economy and environment.  This review gives valuable insights for researchers, practitioners, and policymakers aiming to integrate machine learning technology to optimize corn production by examining the present state of knowledge