International Journal of Technology and Applied Science

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Agriculture Crop Recommendation Based on Productivity and Season

Author(s) N Sangeetha, M Sindhu, G Sreenath, T Surendra, B. Javeed Basha
Country India
Abstract Machine learning plays a vital role in all industries. Machine getting to know makes work less difficult and more particular. Agriculture is a major supply of employment in Tamil Nadu. Agricultural manufacturing suffers due to environmental modifications. Factors inclusive of humidity, rainfall, sunlight, soil type and temperature immediately have an effect on the crop. Agriculture calls for right expertise to cultivate. The data used to put it on the market Agrifacts is created the use of agricultural metrics and elements. Agricultural factors and parameters generate facts to reap facts approximately agricultural data. The growth of the sector of facts technology is generating some strengths in agricultural technological know-how Aids to better offer farmers with agricultural facts. In the existing situation, the utility of modern-day technological strategies in agriculture is timely. Machine learning strategies create a properly-described version using statistics and assist us make predictions. It can clear up agricultural troubles such as crop forecasting, crop cycle, water demand, fertilizer call for and conservation. Due to the various motives of the climatic environment, it is important to have a effective generation that permits the vegetation to grow and the farmers to supply and maintain them. This will assist farmers to produce greater inside the destiny. Through information mining, a recommendation device can be supplied to the farmer to help him inside the conservation of his crops. To put into effect this approach, it is recommended that the crop grows in its factors and factors and their amount. Data analytics paves the manner the manner for the evolution of useful mining from agricultural databases. The crop statistics set turned into analyzed and crops had been endorsed based on productivity and season. Using diverse gadget mastering strategies, we are able to predict crops and create a model from the records furnished. This will permit destiny farmers to provide higher plants. Through data mining, agricultural manufacturing is increased by recommending vegetation to farmers. It is suggested to apply crops in this strategy deliberating their length and weather. Data analysis opens the door to the development of valuable extraction from agricultural databases. Analysis of the crop statistics set ended in a advice based on crop productiveness and developing season.
Keywords Accurate, Agriculture, Impact, Crop harvesting, Intelligence, prediction.
Field Engineering
Published In Volume 17, Issue 4, April 2026
Published On 2026-04-05
Cite This Agriculture Crop Recommendation Based on Productivity and Season - N Sangeetha, M Sindhu, G Sreenath, T Surendra, B. Javeed Basha - IJTAS Volume 17, Issue 4, April 2026.
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