Soil Health Analysis for Crop Suggestions using Machine Learning
| Author(s) | : | Pratiksha Yadav, Prof. Prashant Ahire |
| Institution | : | Computer Engineering, Dr. D. Y. Patil Institute of Technology |
| Published In | : | Vol. 6, Issue 12 — December 2019 |
| Page No. | : | 70-73 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Indian economy is depending on agriculture. Agriculture is the main source of income for most of thepopulation. So farmers are always curious about yield prediction. Many factors are responsible like soil, weather, rain,fertilizers and pesticides to increase yield production. Agriculture being a soil-based industry, an increase in yield canonly be attained by ensuring that the soil provides a balanced and an adequate supply of nutrients. Soil testing is pivotalin understanding the deficiencies in soil and avoiding nutrient imbalance. This survey and study focuses on the differentsoil types, crop types and soil test reports. Soils are complex mixtures of air, water, minerals, organic matter, andcountless organisms that are the decaying remains of once-living things. We can say soil is an important ingredient ofagriculture. There are several types of soils and each type of soil can have different kinds of features and different kindsof crops grow on different types of soils. We must know which type of crop is go better in our soil. We can apply machinelearning techniques to classify soil and to predict the crop suitable.
Pratiksha Yadav, Prof. Prashant Ahire, “Soil Health Analysis for Crop Suggestions using Machine Learning”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 6, Issue 12, pp. 70-73, December 2019.








