• Mahantesh Mathapati
• Jyoti Metan
• Kavita Baragani

One of the sectors that contributes most to our nation's GDP is agriculture. But still, the farmers don't get the worth price of the crops. It mostly happens due to improper irrigation or inappropriate crop selection, or also sometimes the crop yield is less than that of expected. The population of the world is always expanding, hence adequate crop production is required. India is a country based mostly on agriculture, and the increase of agricultural profits and agro-industrial goods support its budget. Monitoring crop development and yield estimates is crucial for a nation's commercial expansion. In agriculture, estimating yield is a crucial issue. Crop harvest estimates have a continuous impact on national and global economy and play a crucial role in the nutrition administration and nutrition security. Every farmer cares about how much output he can reasonably be expected to produce. With the aid of this estimate, farmers will be able to select crops that are suitable for their farm in terms of temperature, humidity, soil pH, season, and fertiliser. Sections of nutrients, such as nitrogen (N), phosphorus (P), and potassium (K), as well as the crop's location and zone, run parallel to it. In order to create a traditional JK model, all of these record features will be taken into consideration when training the records using numerous suitable machine-learning methods. The organization's goal is to be precise and accurate in estimating crop harvest and to provide the final user with the relevant, essential manure fraction based on the plot's full of atmospheric and soil elements, which will increase crop harvest and farmer income.

yield prediction, fertilizer, Support Vector Machine (SVM)algorithm, regression algorithm

"PREDICTING YIELD OF CROP AND DETECTING FERTILIZER EFFICIENCY USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d650-d655, April-2024, Available :http://www.jetir.org/papers/JETIR2404383.pdf

"PREDICTING YIELD OF CROP AND DETECTING FERTILIZER EFFICIENCY USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd650-d655, April-2024, Available at : http://www.jetir.org/papers/JETIR2404383.pdf