IJASEIT

International Journal on Advanced Science, Engineering and Information Technology, Vol. 13 (2023) No. 2, pages: 572-577, DOI:10.18517/ijaseit.13.2.17663

Smart Agriculture: Soil Aggregate Stability Classification for Damaged Crops in India

M. Meenakshi, R. Naresh

Abstract

Soil health is the most important element in a stable farm environment in soil-based agriculture. Soil aggregate stabilization is man-datory for soil characteristics influencing crop yield and stability. The study was conducted on Tamilnadu delta areas where the alluvial and black soil types for rabi and Kharif crops are used, and soil parameters are analyzed. This study aims to provide an overview of the mechanisms and aggregate-forming agents using ensemble methods. It is difficult to assess and analyze the aggregate stability. However, the most popular farming methods used in commercial crop yields, including artificial fertilizers and monocul-tures, can weaken the soil throughout the term, resulting in a sequence of issues that necessitate using many more man-made inputs, which contribute to global warming. The soil type's qualities and functions in predicting the crop type that can be grown under spe-cific soil conditions. Remote monitoring of soil parameters can change agricultural practices and boost productivity. We suggest a process in this article for classifying soil based on micro and macro-nutrients and predicting the form of the crop that can be grown in that type of soil. The results obtained were compared to the standardized maximum point for specific crops, and crop inputs var-ied depending on the variations. Several ensemble methods have been used, such as the bagging meta-estimator, Ada Boost, and XGB. On the held-out dataset, the bagging models estimated an accuracy of 98 percent, showing the technological viability of differ-ent soil types.