Application of ML in Agriculture
INTRODUCTION Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy . pre-harvesting machine learning is used to capture the parameters of soil, seeds quality , fertilizer application, pruning, genetic and environmental conditions and irrigation . Focusing on each component it is important to minimize the overall losses in production. How Is Machine Learning Used in Agriculture? Machine learning (ML) has already begun to play an important role in making agriculture more efficient and effective. Precision ag relies on the gathering, processing, and analysis of data for more efficient agricultural production. On the modern farm, you can collect data with the use of advanced technology, such as: autonomous vehicles, variable rate technology, GPS-based soil sampling, automated har...