International Journal of Scientific Research and Engineering Development

Agriculture is a vital source of both food for lots of people in the world and income-generating economic activity. Changing weather conditions can dramatically alter this situation, however. The amount of rain, temperature, and humidity can all greatly affect overall crop production; soil conditions can also create variabilities that are often not in a farmer’s control. A weather/predictive model system uses historical data and machine-learning algorithms and will be able to accurately predict what kind of crops should be planted based on present weather conditions. It identifies patterns and correlations between a variety of factors that influence crop growth. It also classifies these patterns, so as a result of using the system, farmers will have better decision-making potential leading to less risk of failure and better use of their resources. While I believe that using a model like this in making decisions regarding which crops to grow is beneficial, I still need to understand how all of the variables in this group of conditions are interrelated. There is also a difference between using historical data to make these predictions versus real-time data.

Sujit Chavan,"Weather Based Crop Prediction" International Journal of Scientific Research and Engineering Development, V9(4): Page(31-39) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.