A study on prediction of soil properties content based on machine learning models
Charu Gitey, Dr. Kamlesh Namdev
The Indian economy is dependent on the agricultural sector. Although focused on industrialization, agriculture remains an important sector of the Indian economy, both in terms of contribution to gross domestic product (GDP) and jobs for millions of people across the country. One of the key factors for productive agriculture is soil. The purpose of the work is to predict the type of terrain using data mining classification methods. Agricultural properties and soil ownership play a crucial role in agricultural decision-making. Now-a-days there is a need to study the nutrient status in lower horizons of the soil. Soil testing has played historical role in evaluating soil fertility maintenance and in sustainable agriculture. Soil testing shall also play its crucial role in precision agriculture. At present there is a need to develop basic inventory as per soil test basis and necessary information has to be built into the system for translating the results of soil test to achieve the crop production goal in new era. To achieve this goal Machine Learning approach is used for predicting the soil properties.
Charu Gitey, Dr. Kamlesh Namdev. A study on prediction of soil properties content based on machine learning models. International Journal of Advanced Engineering and Technology, Volume 3, Issue 3, 2019, Pages 42-46