Machine Learning in Agriculture: Identifying Patterns to Improve Crop Performances

Category: Technology

A data-intensive approach is absolutely necessary for agribusinesses to stay relevant in today’s competitive landscape. Machine learning in agriculture can help in analysing large data sets and enable producers, field managers to make better decisions, improve crop performance and mitigate food safety concerns. With machine learning-based agricultural practices, making crop quality evaluations, yield estimates, disease predictions, etc becomes easier for agribusinesses. The global agriculture industry is at a critical juncture. According to the Food and Agriculture Organization of the United Nations, around 660 million people may be facing hunger in 2030. There is an urgent need to redefine our agricultural practices in order to meet the food demands of a rising population. The best way to do this is by assessing information and finding out patterns in every aspect of food production.