Machine Learning Techniques for Crop, Fertilizer Prediction and Disease Detection
T Sai Lalith Prasad, P Yuvaraj, B Bala Shiva, T Gnaneshwar
Agriculture is an important part of a country's economy, but with the population growing, weather
patterns changing, and resources dwindling, the food demands of today's world are becoming more
challenging to meet. Smart farming, or precision agriculture, is a modern solution to these challenges. It
utilizes technology, especially machine learning (ML), to help farmers make better decisions about their
crops. ML allows machines to learn and get better with time without having to be directly programmed.
This paper examines how ML is being used in farming for such important questions as: Which crops
should one grow in that particular area? What fertilizer does the soil prefer? How does one detect
diseases and treat them? In this regard, new farming techniques also make it easy to harvest crops,
thus not requiring much human labor.ML is not technology; it's changing the way farmers work. For
instance, consider a farmer who used to decide how to manage his crops with the help of years of
experience. Now, they can make much more accurate data-driven decisions through ML. Farmers
can use the sensors and drones to check how healthy their crops are in real-time, then problems can
easily be identified, and solutions would be implemented rapidly. This means that not only time is
saved but also assists the farmer in being more productive, with guesswork reduced. The use of ML in
agriculture makes agriculture become more sustainable. By using resources like water, fertilizer, and
pesticides more efficiently, farmers can minimize waste and lower their environmental footprint. This
is important because the climate is changing and it is not easy to predict weather patterns anymore.
Smart farming practices help in creating a more resilient agricultural system, one that can adapt to
changing conditions and continue to produce food for future generations. In the end, ML is not just
about increasing productivity but making farming more efficient, environmentally friendly, and secure
for everyone.
