Enhancing Crop Productivity using Machine Learning

Abstract

Amid mounting concerns about food security and climate change, the agriculture industry has begun to incorporate artificial intelligence (AI) into its operations. While there are numerous potential AI benefits, there is a lack of understanding of the goals that drive AI adoption and its consequences. This study tries to close the gap by looking at the fundamental themes surrounding AI in agriculture via the prism of dynamic capabilities. We do text mining of news stories from 2014 to 2019 in Asia, Africa, Europe, and North America using centered resonance analysis to see how AI is addressing major farming concerns. The findings reveal that AI is being used largely to boost productivity and efficiency, with labor shortages and environmental sustainability The results show active AI adoption in North America and Europe, as well as expanding initiatives in Asia and Africa, at the regional level.