{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T16:35:02Z","timestamp":1773160502655,"version":"3.50.1"},"reference-count":98,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T00:00:00Z","timestamp":1662422400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ICAR-Indian Agricultural Research Institute, New Delhi, India"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A study was conducted with the goal of developing an algorithm for use in sensors to monitor available soil N. For this purpose, three different soils were selected. The soils were studied for electrical conductivity (EC) at four different moisture levels and four levels of N. The selection of moisture levels was based on optimum moisture levels between tillage moisture and field capacity. The results revealed a significant relationship between electrical conductivity and moisture level of the soil as well as between electrical conductivity and soil N content. Based on these relations, a polynomial model was developed between the EC of each selected soil sample and moisture content as well as N levels. The regression model for moisture content-based EC determination had coefficients of determination of 0.985, 0.988, and 0.981 for clay loam, sandy loam, and sandy loam soils, respectively. Similarly, the regression model for N content-based EC determination had coefficients of determination of 0.9832, 0.9, and 0.99 for clay loam, sandy loam, and sandy loam soils, respectively. An algorithm developed using a polynomial relationship between the EC of each selected soil sample at all moisture and N levels can be used to develop a sensor for site-specific N application.<\/jats:p>","DOI":"10.3390\/s22186728","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6728","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content"],"prefix":"10.3390","volume":"22","author":[{"given":"Hasan","family":"Mirzakhaninafchi","sequence":"first","affiliation":[{"name":"Department of Farm Machinery & Power Engineering, College of Agricultural Engineering and Technology (COAE&T), Punjab Agricultural University (PAU), Ludhiana 141004, India"}]},{"given":"Indra","family":"Mani","sequence":"additional","affiliation":[{"name":"Division of Agricultural Engineering, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi 110012, India"}]},{"given":"Murtaza","family":"Hasan","sequence":"additional","affiliation":[{"name":"Centre for Protected Cultivation Technology, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi 110012, India"}]},{"given":"Ali Mirzakhani","family":"Nafchi","sequence":"additional","affiliation":[{"name":"Precision Agriculture Extension, Raven Precision Agriculture Center, South Dakota State University, Brookings, SD 57007, USA"}]},{"given":"Roaf Ahmad","family":"Parray","sequence":"additional","affiliation":[{"name":"Division of Agricultural Engineering, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi 110012, India"}]},{"given":"Dinesh","family":"Kumar","sequence":"additional","affiliation":[{"name":"Division of Agronomy, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi 110012, India"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shafi, U., Mumtaz, R., Garc\u00eda-Nieto, J., Hassan, S.A., Zaidi, S.A.R., and Iqbal, N. 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