International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 184 - Number 24 |
Year of Publication: 2022 |
Authors: Kalyani M., Rachana R.S., Bhargavi K., Malashree R., Sindhu S., Praveena K.S. |
10.5120/ijca2022922277 |
Kalyani M., Rachana R.S., Bhargavi K., Malashree R., Sindhu S., Praveena K.S. . A Study on Crop Yield Prediction using Machine Learning Techniques. International Journal of Computer Applications. 184, 24 ( Aug 2022), 5-11. DOI=10.5120/ijca2022922277
Machine learning is a powerful technique for identifying crop yields, also detecting which seeds to sow in the planting time. By studying the agricultural region, the system needs to address agricultural challenges by analyzing the agricultural region based on soil qualities and guiding farmer just on best crop to plant, allowing them to boost productivity and reduce losses. Many techniques were used to classify and predict the best suited crop for the soil. This survey provides the details on the study of different crop yield prediction techniques based on different parameters such as weather data in the past, soil parameters, and agriculture yield of previous year.