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Determination of Organic Matter and pH Value of the Soil Using Deep Learning Techniques


R. Kavitha, M. Kavitha and P. Subha
Abstract

Tamil Nadu net cultivated land is 48.92 lakhs ha in which 58% land are under irrigation and rest are rain-fed. The productivity of rice, maize, sugarcane, cotton, and grams compared to the other countries are very less. The productivity of vegetables in India is 11.2 tonnes/ha and fruits are 16.2 tonnes from the document on Tamil Nadu Vision 2023. This motivated to develop a system that identifies the organic content of the soil. So there needs a technology to estimate or predict the organic matter of the soil before cultivation of any crop that ends up in good crop yield with better productivity. To estimate the soil organic content and pH value present in the soil, Shortwave Infra Red (SWIR) and Visible-Near Infrared (VNIR) bands ranges between 400-2500 nm are used. The work is to elaborate on soil organic and pH estimation using remote sensing (RS) techniques. SOM provides important functions including nutrient preservation, water holding capacity. It acts as a key pointer for soil quality. Soil pH is measure of acidity and alkalinity present in the soil, on a scale read from 0 to 14. The comprehensive study on soil spectroscopy needs to be investigated. The soil images are captured using UAV using hyperspectral sensor camera for the chosen study site. The estimated organic contents of the soil benefits the farmers to improve the crop yield which results in the increase of their productivity.

Volume 12 | 07-Special Issue

Pages: 1187-1195

DOI: 10.5373/JARDCS/V12SP7/20202219