Machine Learning in Agriculture: Applications and Techniques

Recently we have discussed the emerging concept of smart farming that makes agriculture more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is Machine Learning -- the scientific field that gives machines the ability to learn without being strictly programmed. It has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data intensive processes in agricultural operational environments. Let's discover how agriculture can benefit from Machine Learning at every stage: Our favorite, this application is so logical and yet so unexpected, because mostly you read about harvest prediction or ambient conditions management at later stages. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste.