Estimating Macronutrient Content of Paddy Soil Based on Near-Infrared Spectroscopy Technology Using Multiple Linear Regression

Authors

  • Jonni Firdaus Agricultural Engineering Science Study Program, IPB University, Bogor, Indonesia/ National Research and Innovation Agency Republic of Indonesia, Jakarta, Indonesia
  • Usman Ahmad Department of Mechanical and Biosystem Engineering, IPB University, Bogor, Indonesia
  • I Wayan Budiastra Department of Mechanical and Biosystem Engineering, IPB University, Bogor, Indonesia
  • I Dewa Made Subrata Department of Mechanical and Biosystem Engineering, IPB University, Bogor, Indonesia

DOI:

https://doi.org/10.46604/aiti.2023.12683

Keywords:

fertility, near-infrared spectroscopy, nitrogen, phosphorus, potassium

Abstract

This study investigates the feasibility of employing near-infrared (NIR) spectroscopy with multiple linear regression (MLR) to estimate macronutrients in paddy soil compared with partial least squares (PLS) and principal component regression (PCR). Seventy-nine soil samples from West Java Province, Indonesia, are subject to conventional nutrient analysis and NIR spectroscopy (1000-2500 nm). The reflectance data undergoes various pretreatment techniques, and MLR models are calibrated using the forward method to achieve correlations exceeding 0.90. The best model calibrations are selected based on high correlation coefficients, determination coefficients, RPD, and low RMSE values. Meanwhile, the comparison of performance MLR is made with the PLS and PCR models. Results indicate that simple MLR models perform less than PLS for all nutrients, better than PCR for nitrogen, and below PCR for phosphorus and potassium. However, MLR reliably estimates soil nitrogen, phosphorus, and potassium content with ratio of performance to deviation (RPD) exceeding 2.0. This study demonstrates the potential of MLR for precise macronutrient estimation in paddy soil.

References

M. A. Munnaf and A. M. Mouazen, “Development of a Soil Fertility Index Using On-Line Vis-NIR Spectroscopy,” Computers and Electronics in Agriculture, vol. 188, article no. 106341, September 2021.

J. M. Johnson, E. Vandamme, K. Senthilkumar, A. Sila, K. D. Shepherd, and K. Saito, “Near-Infrared, Mid-Infrared or Combined Diffuse Reflectance Spectroscopy for Assessing Soil Fertility in Rice Fields in Sub-Saharan Africa,” Geoderma, vol. 354, article no. 113840, November 2019.

Devianti, Sufardi, R. Bulan, and A. Sitorus, “Vis-NIR Spectra Combined with Machine Learning for Predicting Soil Nutrients in Cropland from Aceh Province, Indonesia,” Case Studies in Chemical and Environmental Engineering, vol. 6, article no. 100268, December 2022.

S. Alomar, S. A. Mireei, A. Hemmat, A. A. Masoumi, and H. Khademi, “Comparison of Vis/SWNIR and NIR Spectrometers Combined with Different Multivariate Techniques for Estimating Soil Fertility Parameters of Calcareous Topsoil in an Arid Climate,” Biosystems Engineering, vol. 201, pp. 50-66, January 2021.

M. Pusch, A. Samuel-Rosa, P. S. G. Magalhães, and L. R. do Amaral, “Covariates in Sample Planning Optimization for Digital Soil Fertility Mapping in Agricultural Areas,” Geoderma, vol. 429, article no. 116252, January 2023.

S. Srisomkiew, M. Kawahigashi, P. Limtong, and O. Yuttum, “Digital Soil Assessment of Soil Fertility for Thai Jasmine Rice in the Thung Kula Ronghai Region, Thailand,” Geoderma, vol. 409, article no. 115597, March 2022.

Y. Wang, H. Huang, and X. Chen, “Predicting Organic Matter Content, Total Nitrogen and pH Value of Lime Concretion Black Soil Based on Visible and Near Infrared Spectroscopy,” Eurasian Soil Science, vol. 54, no. 11, pp. 1681-1688, November 2021.

G. Zheng, A. Wang, C. Zhao, M. Xu, C. Jiao, and R. Zeng, “Evolution of Paddy Soil Fertility in a Millennium Chronosequence Based on Imaging Spectroscopy,” Geoderma, vol. 429, article no. 116258, January 2023.

B. G. Barthès, E. Kouakoua, M. Clairotte, J. Lallemand, L. Chapuis-Lardy, M. Rabenarivo, et al., “Performance Comparison Between a Miniaturized and a Conventional Near Infrared Reflectance (NIR) Spectrometer for Characterizing Soil Carbon and Nitrogen,” Geoderma, vol. 338, pp. 422-429, March 2019.

F. B. de Santana and K. Daly, “A Comparative Study of MIR and NIR Spectral Models Using Ball-Milled and Sieved Soil for the Prediction of a Range Soil Physical and Chemical Parameters,” Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, vol. 279, article no. 121441, October 2022.

U. J. dos Santos, J. A. de Melo Dematte, R. S. C. Menezes, A. C. Dotto, C. C. B. Guimarães, B. J. R. Alves, et al., “Predicting Carbon and Nitrogen by Visible Near-Infrared (Vis-NIR) and Mid-Infrared (MIR) Spectroscopy in Soils of Northeast Brazil,” Geoderma Regional, vol. 23, article no. e00333, December 2020.

A. A. Munawar, Y. Yunus, Devianti, and P. Satriyo, “Calibration Models Database of Near Infrared Spectroscopy to Predict Agricultural Soil Fertility Properties,” Data in Brief, vol. 30, article no. 105469, June 2020.

A. Pudełko and M. Chodak, “Estimation of Total Nitrogen and Organic Carbon Contents in Mine Soils with NIR Reflectance Spectroscopy and Various Chemometric Methods,” Geoderma, vol. 368, article no. 114306, June 2020.

R. Reda, T. Saffaj, B. Ilham, O. Saidi, K. Issam, L. Brahim, et al., “A Comparative Study Between a New Method and Other Machine Learning Algorithms for Soil Organic Carbon and Total Nitrogen Prediction Using Near Infrared Spectroscopy,” Chemometrics and Intelligent Laboratory Systems, vol. 195, article no. 103873, December 2019.

P. Zhou, Y. Zhang, W. Yang, M. Li, Z. Liu, and X. Liu, “Development and Performance Test of an In-Situ Soil Total Nitrogen-Soil Moisture Detector Based on Near-Infrared Spectroscopy,” Computers and Electronics in Agriculture, vol. 160, pp. 51-58, May 2019.

W. Ng, Husnain, L. Anggria, A. F. Siregar, W. Hartatik, Y. Sulaeman, et al., “Developing a Soil Spectral Library Using a Low-Cost NIR Spectrometer for Precision Fertilization in Indonesia,” Geoderma Regional, vol. 22, article no. e00319, September 2020.

R. Reda, T. Saffaj, S. E. Itqiq, I. Bouzida, O. Saidi, K. Yaakoubi, et al., “Predicting Soil Phosphorus and Studying the Effect of Texture on the Prediction Accuracy Using Machine Learning Combined with Near-Infrared Spectroscopy,” Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, vol. 242, article no. 118736, December 2020.

H. T. Cai, J. Liu, J. Y. Chen, K. H. Zhou, J. Pi, and L. R. Xia, “Soil Nutrient Information Extraction Model Based on Transfer Learning and Near Infrared Spectroscopy,” Alexandria Engineering Journal, vol. 60, no. 3, pp. 2741-2746, June 2021.

Y. Tang, E. Jones, and B. Minasny, “Evaluating Low-Cost Portable Near Infrared Sensors for Rapid Analysis of Soils from South Eastern Australia,” Geoderma Regional, vol. 20, article no. e00240, March 2020.

P. Berzaghi, J. H. Cherney, and M. D. Casler, “Prediction Performance of Portable Near Infrared Reflectance Instruments Using Preprocessed Dried, Ground Forage Samples,” Computers and Electronics in Agriculture, vol. 182, article no. 106013, March 2021.

Z. Li, J. Song, Y. Ma, Y. Yu, X. He, Y. Guo, et al., “Identification of Aged-Rice Adulteration Based on Near-Infrared Spectroscopy Combined with Partial Least Squares Regression and Characteristic Wavelength Variables,” Food Chemistry: X, vol. 17, article no. 100539, March 2023.

Q. Wang, H. Zhang, F. Li, C. Gu, Y. Qiao, and S. Huang, “Assessment of Calibration Methods for Nitrogen Estimation in Wet and Dry Soil Samples with Different Wavelength Ranges Using Near-Infrared Spectroscopy,” Computers and Electronics in Agriculture, vol. 186, article no. 106181, July 2021.

A. Cambou, B. G. Barthès, P. Moulin, L. Chauvin, E. Faye, D. Masse, et al., “Prediction of Soil Carbon and Nitrogen Contents Using Visible and Near Infrared Diffuse Reflectance Spectroscopy in Varying Salt-Affected Soils in Sine Saloum (Senegal),” Catena, vol. 212, article no. 106075, May 2022.

Z. Patonai, R. Kicsiny, and G. Géczi, “Multiple Linear Regression Based Model for the Indoor Temperature of Mobile Containers,” Heliyon, vol. 8, no. 12, article no. e12098, December 2022.

BBSDLP, Semi-Detailed Soil Map of Bogor Regency, West Java Province. Bogor, Indonesia: Center for Agricultural Land Resources, Agency for Agricultural Research and Development, 2016.

BBSDLP, Semi-Detailed Soil Map of Sukabumi Regency, West Java Province. Bogor, Indonesia: Center for Agricultural Land Resources, Agency for Agricultural Research and Development, 2016.

BBSDLP, Semi-Detailed Soil Map of Indramayu Regency, West Java Province. Bogor, Indonesia: Center for Agricultural Land Resources, Agency for Agricultural Research and Development, 2017.

BBSDLP, Semi-Detailed Soil Map of Subang Regency, West Java Province. Bogor, Indonesia: Center for Agricultural Land Resources, Agency for Agricultural Research and Development, 2017.

B. Miloš, A. Bensa, and B. Japundžić-Palenkić, “Evaluation of Vis-NIR Preprocessing Combined with PLS Regression for Estimation Soil Organic Carbon, Cation Exchange Capacity and Clay from Eastern Croatia,” Geoderma Regional, vol. 30, article no. e00558, September 2022.

Downloads

Published

2023-12-29

How to Cite

[1]
Jonni Firdaus, Usman Ahmad, I Wayan Budiastra, and I Dewa Made Subrata, “Estimating Macronutrient Content of Paddy Soil Based on Near-Infrared Spectroscopy Technology Using Multiple Linear Regression”, Adv. technol. innov., vol. 9, no. 1, pp. 50–64, Dec. 2023.

Issue

Section

Articles