Determining soil organic carbon concentration in agricultural fields using a handheld spectroradiometer: Implication for soil fertility measurement

Authors

  • ElKamil Tola Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia
  • Khalid A. Al-Gaadi 1. Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia; 2. Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia
  • Rangaswamy Madugundu Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia
  • Ahmed G. Kayad Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia
  • Ahmed A. Alameen Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia
  • Haroon F. Edrees Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia
  • Mohamed K. Edrris Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia

DOI:

https://doi.org/10.25165/ijabe.v11i6.4061

Keywords:

soil fertility, organic carbon, modeling, spectroscopy, reflectance

Abstract

The soil organic carbon (SOC) plays a vital role in plant growth and development, and therefore is considered as one of the most important indicators of soil quality. This study was carried out in the central region of Saudi Arabia to explore the potential of spectroscopy in determining the SOC concentration in low-fertility soils. Spectral reflectance data were collected, under the controlled laboratory conditions on 39 air-dried 2.0 mm sieved soil samples, using a handheld spectroradiometer of a wavelength range between 350 nm and 2500 nm in the direct contact probe mode. The concentration of the SOC was determined using the Walkley and Black (W&B) and the UV-VIS spectrophotometric methods. The increase in the concentration of SOC was associated with a decrease in the corresponding spectral reflectance. Regression analysis showed linear relationships with high significant correlation between the spectral reflectance and the SOC measured by both the UV-VIS (Model-1: R2=0.46, p=0.00015 and RMSE=6.6 g/kg) and the W&B (Model-2: R2=0.48, p=8.92E-05 and RMSE= 2.8 g/kg) methods. For these models, two wavebands with wavelengths of 2167 nm (Model-1) and 1359 nm (Model-2) were identified as the most sensitive bands to the SOC concentration. The cross-validation confirmed the validity of Model-1 with R2, p and RMSE values of 0.50, 0.0099 and 6.6 g/kg, respectively. The validation results of the Model-2 showed values of R2, p and RMSE of 0.72, 0.00023 and 4.0 g/kg, respectively. Results of this study revealed the possibility and the potential of using the spectral reflectance technique in predicting the concentration of SOC. Keywords: soil fertility, organic carbon, modeling, spectroscopy, reflectance DOI: 10.25165/j.ijabe.20181106.4061 Citation: Tola E, Al-Gaadi K A, Madugundu R, Kayad A G, Alameen A A, Edrees H F, et al. Determining soil organic carbon concentration in agricultural fields using a handheld spectroradiometer: Implication for soil fertility measurement. Int J Agric & Biol Eng, 2018; 11(6): 13–19.

Author Biography

ElKamil Tola, Precision Agriculture Research Chair, King Saud University, Riyadh 11451, Saudi Arabia

Associate Professor, Precision Agriculture Research Chair King Saud University

References

Chan K Y, Oates A, Liu D L, Li G D, Pragnell R, Poile G,et al. A farmer’s guide to increasing soil organic carbon under pastures. Industry & Investment NSW, Wagga, Wagga, NSW. 2010. ISBN: 978 1 74256 010 6.

Buringh P. Organic carbon in soils of the world. In: Woodwell G M (Ed.). The Role of Terrestrial Vegetation in the Global Carbon Cycle: Measurement by Remote Sensing; John Wiley & Sons Ltd. 1984. pp. 91–109.

Liu X, Herbert S J, Hashemi A M, Zhang X, Ding G. Effects of agricultural management on soil organic matter and carbon transformation – A review. ENVIRON., Plant Soil Environ., 2000; 52: 531–543.

Magdoff F, van Es H. Organic matter: What it is and why it’s so important. In: Building Soils for Better Crops: Sustainable soil management. Sustainable Agriculture Research and Education (SARE),

USDA, USA, 2009. pp. 9–21.

Lal R. Soil carbon dynamics in cropland and rangeland. Environmental Pollution, 2002; 116: 353–362.

Brown D J, Shepherd K D, Walsh M G, Mays M D, Reinsch T G. Global soil characterization with VNIR diffuse reflectance spectroscopy. Geoderma, 2006; 132: 273–290.

Baharom S N A, Shibusawa S, Kodaira M, Kanda R. Multiple-depth mapping of soil properties using a visible and near infrared real-time soil sensor for a paddy field. Engineering in Agriculture, Environment and Food, 2015; 8: 13–17.

Van Maarschalkerweerd M, Husted S. Recent developments in fast spectroscopy for plant mineral analysis. Frontiers in Plant Science, 2015; 6: 1–14.

Aitkenhead M J, Gaskin G J, Lafouge N, Hawes C. Phylis: A low-cost portable visible range spectrometer for soil and plants. Sensors (Basel, Switzerland), 2017; 17(1): 1–14.

Ingleby H R, Crowe T G. Reflectance models for predicting organic carbon in Saskatchewan soils. Canadian Agricultural Engineering, 2000; 42: 57–63.

Jiang Q, Chen Y, Guo L, Fei T, Qi K. Estimating soil organic carbon of cropland soil at different levels of soil moisture using VIS-NIR spectroscopy. Remote Sens., 2016; 8: 1–16.

Mouazen A M, Kuang B, de Baerdemaeker J, Ramon H. Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy. Geoderma, 2010; 158: 23–31.

Gholizadeh A, Carmon N, Klement A, Ben-Dor E, Boruvka L. Agricultural soil spectral response and properties assessment: effects of measurement protocol and data mining technique. Remote Sens., 2017; 9: 1–14.

Stevens A, van Wesemael B, Bartholomeus H, Rossillon D, Tychon B, Ben-Dor E. Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils. Geoderma, 2008; 144: 395–404.

Summers D, Lewis M, Ostendorf B, Chittleborough D. Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties. Ecological Indicators, 2011; 11: 123–131.

Sallam A Sh. Evaluation of some soils in Najd plateau (Central Region, Saudi Arabia. J. Saudi Soc. Agric. Sci., 2002; 1: 21–40.

Combs S M, Nathan M V. Soil organic matter. In: North Central Regional Research Publication No. 221 (Revised) Recommended Chemical Soil Test Procedures for the North Central Region, 1998. pp. 53–58.

Kiss K, Szalai Z, Jakab G, Madarász B, Zboray N. Characterization of soil organic substances by UV-Vis spectrophotometry in some soils of hungary. In: Hartemink A E, McSweeney K (Ed.). Soil Carbon. Progress in Soil Science. Springer International Publishing Switzerland, 2014. pp. 127–136.

Peng X, Shi T, Song A, Chen Y, Gao W. Estimating soil organic carbon using VIS/NIR spectroscopy with SVMR and SPA methods. Remote Sens., 2014; 6: 2699–2717.

Gupta I C, Yaduvanshi N P S, Gupta S K. Standard methods for analysis of soil-plant and water. Scientific publishers, India, 2012. 224.

Wang C, Feng M, Yang W, Ding G, Xiao L, Li G, et al. Extraction of sensitive bands for monitoring the winter wheat (Triticum aestivum) growth status and yields based on the spectral reflectance. PLoS ONE, 2017; 12: 1–16.

Ngo T H. The steps to follow in a multiple regression Analysis. Proceedings of the SAS Global Forum, 22–25 April, 2012, Orlando, Florida, USA, 2012.

Ting H, Jing W, Li Z, Ye C. Spectral features of soil organic matter. Geo-spatial Information Science, 2009; 12: 33–40.

Stout F, Kalivas J H, Héberger K. Wavelength selection for multivariate calibration using tikhonov regularization. Applied Spectroscopy, 2007; 61: 85–95.

Bartholomeus H M, Schaepman M E, Kooistra L, Stevens A, Hoogmoed W B, Spaargaren O S P. Spectral reflectance based indices for soil organic carbon quantification. Geoderma, 2008; 145: 28–36.

Daniel K, Tripathi N K, Honda K, Apisit E. Analysis of spectral reflectance and absorption patterns of soil organic matter. The proceedings of the 22nd Asian Conference on Remote Sensing, 5-9 November 2001, Singapore.

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Published

2018-12-08

How to Cite

Tola, E., Al-Gaadi, K. A., Madugundu, R., Kayad, A. G., Alameen, A. A., Edrees, H. F., & Edrris, M. K. (2018). Determining soil organic carbon concentration in agricultural fields using a handheld spectroradiometer: Implication for soil fertility measurement. International Journal of Agricultural and Biological Engineering, 11(6), 13–19. https://doi.org/10.25165/ijabe.v11i6.4061

Issue

Vol. 11 No. 6 (2018): IJABE

Section

Applied Science, Engineering and Technology

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