Mid-Infrared Reflectance Spectroscopy for Estimation of Soil Properties of Alfisols from Eastern India

Kuntal M. Hati, Nishant K. Sinha, Monoranjan Mohanty, Pramod Jha, Sunil Londhe, Andrew Sila, Erick Towett, Ranjeet S. Chaudhary, Somasundaram Jayaraman, Mounisamy Vassanda Coumar, Jyoti K. Thakur, Pradip Dey, Keith Shepherd, Pankaj Muchhala, Elvis Weullow, Muneshwar Singh, Shiv K. Dhyani, Chandrashekhar Biradar, Javed Rizvi, Ashok K. Patra and Suresh K. Chaudhari
Additional contact information
Kuntal M. Hati: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Nishant K. Sinha: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Monoranjan Mohanty: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Pramod Jha: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Sunil Londhe: CIFOR-ICRAF, New Delhi 110001, India
Andrew Sila: World Agroforestry (ICRAF), Nairobi 999070, Kenya
Erick Towett: World Agroforestry (ICRAF), Nairobi 999070, Kenya
Ranjeet S. Chaudhary: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Somasundaram Jayaraman: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Mounisamy Vassanda Coumar: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Jyoti K. Thakur: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Pradip Dey: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Keith Shepherd: World Agroforestry (ICRAF), Nairobi 999070, Kenya
Pankaj Muchhala: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Elvis Weullow: World Agroforestry (ICRAF), Nairobi 999070, Kenya
Muneshwar Singh: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Shiv K. Dhyani: CIFOR-ICRAF, New Delhi 110001, India
Chandrashekhar Biradar: CIFOR-ICRAF, New Delhi 110001, India
Javed Rizvi: CIFOR-ICRAF, New Delhi 110001, India
Ashok K. Patra: ICAR-Indian Institute of Soil Science, Nabibagh, Berasia Road, Bhopal 462038, India
Suresh K. Chaudhari: Indian Council of Agricultural Research, New Delhi 110001, India

Sustainability, 2022, vol. 14, issue 9, 1-17

Abstract: Mid-infrared (MIR) spectroscopy is emerging as one of the most promising technologies, as it is a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. This study was conducted to evaluate the potential of mid-infrared spectroscopy for the rapid and nondestructive measurement of some important soil properties of Alfisols. A total of 336 georeferenced soil samples fromthe 0–15 cm soil layer of Alfisols that were collected from the eastern Indian states of Odisha and Jharkhand were used. The partial least-squares regression (PLSR), random forest, and support vector machine regression techniques were compared for the calibration of the spectral data with the wet chemistry soil data. The PLSR-based predictive models performed better than the other two regression techniques for all the soil properties, except for the electrical conductivity (EC). Good predictions with independent validation datasets were obtained for the clay and sand percentages and for the soil organic carbon (SOC) content, while satisfactory predictions were achieved for the silt percentage and the pH value. However, the performance of the predictive models was poor in the case of the EC and the extractable nutrients, such as the available phosphorus and potassium contents of the soil. Specific regions of the MIR spectra that contributed to the prediction of the soil SOC, the pH, and the clay and sand percentages were identified. The study demonstrates the potential of the MIR spectroscopic technique in the simultaneous estimation of the SOC content, the sand, clay, and silt percentages, and the pH of Alfisols from eastern India.

Keywords: mid-infrared spectroscopy; soil properties; alfisols; partial least squares; support vector machine; random forest (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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