https://doi.org/10.4081/jae.2025.1710

Exploring the feasibility of near-infrared spectroscopy in analyzing and predicting the chemical and biochemical changes of chitin-amended soils

Vol. 56 No. 1 (2025)
Published: 3 February 2025
Soil property modeling, optical analysis, partial least squares regression
Abstract Views: 52
PDF: 8
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Ken Abamba Omwange
https://orcid.org/0000-0002-8268-1940
USDA-ARS Midwest Area Sugarbeet and Bean Research Unit, East Lansing, MI, United States.
Ana Chen
School of Biological and Chemical Engineering, Anhui Polytechnic University, Anhui, China.
Renfu Lu
USDA-ARS Midwest Area Sugarbeet and Bean Research Unit, East Lansing, MI, United States.
Carly Daiek
https://orcid.org/0000-0001-5593-1812
Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, MI, United States.
Julie Celini
https://orcid.org/0009-0002-3499-8430
Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, MI, United States.
Yan Liu
liuyan6@msu.edu
https://orcid.org/0000-0002-5039-6731
Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, MI, United States.

Chitin, a natural polymer, has been added to soil to enhance plant resistance to pathogens, yet its impact on soil’s chemical and biochemical properties remains unclear. Standard methods to measure these properties are often slow and labor-intensive. This study aimed to assess pH, total DNA, chitinase activity, and trpB gene DNA targeting for the identification of pathogen Streptomyces scabies in chitin-treated soil using both conventional wet chemical analysis methods and near-infrared (NIR) spectroscopy for rapid measurement. Five soil groups were treated with varying chitin levels (control, 0.2% and 2% fungus chitin, 0.2% and 2% Sigma chitin) and sampled every 9 days over 122 days. NIR reflectance spectra (900-1,685 nm) from the soil samples were acquired at each sampling time. Partial least squares regression models  were developed using preprocessing methods like Kubelka-Munk, second derivative, and smoothed data. The second derivative model for 900-1,660 nm yielded high predictive accuracy with R² values of 0.915, 0.892, and 0.810 for pH, total DNA, and trpB gene DNA respectively. This study demonstrates the potential of NIR  spectroscopy coupled with partial least squares algorithms as a rapid, cost-effective method for estimating soil biochemical properties.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Crossref
Scopus
Google Scholar
Europe PMC
Alcaraz de la Osa, R., Iparragirre, I., Ortiz, D., Saiz, J.M., 2020. The extended Kubelka–Munk theory and its application to spectroscopy. ChemTexts 6:1-14. DOI: https://doi.org/10.1007/s40828-019-0097-0
Andreo-Jimenez, B., Schilder, M.T., Nijhuis, E.H., te Beest, D.E., Bloem, J., Visser, J.H.M., et al. 2021. Chitin- and keratin-rich soil amendments suppress Rhizoctonia solani disease via changes to the soil microbial community. Appl. Environ. Microbiol. 87:e00318-21. DOI: https://doi.org/10.1128/AEM.00318-21
Baig, M.A., Qamar, S., Ali, A.A., Ahmad, J., Qureshi, M.I., 2020. Heavy metal toxicity and tolerance in crop plants. In: Naeem, M., Ansari, A., Gill, S. (eds.) Contaminants in Agriculture. Cham, Springer, pp. 201-216. DOI: https://doi.org/10.1007/978-3-030-41552-5_9
Baillères, H., Davrieux, F., Ham-Pichavant, F., 2002. Near infrared analysis as a tool for rapid screening of some major wood characteristics in a eucalyptus breeding program. Ann. Forest Sci. 59:479-490. DOI: https://doi.org/10.1051/forest:2002032
Bautista-Baños, S., Hernández-Lauzardo, A.N., Velázquez-Del Valle, M.G., Hernández-López, M., Ait Barka, E., Bosquez-Molina, E., Wilson, C.L., 2006. Chitosan as a potential natural compound to control pre and postharvest diseases of horticultural commodities. Crop Prot. 25:108-118. DOI: https://doi.org/10.1016/j.cropro.2005.03.010
Blanco, M., Villarroya, I., 2002. NIR spectroscopy: A rapid-response analytical tool. TrAC-Trend. Anal. Chem. 21:240-250. DOI: https://doi.org/10.1016/S0165-9936(02)00404-1
Brady, N.C., Weil, R.R., 2008. The nature and properties of soils, 14th ed. Upper Saddle River, Pearson Prentice Hall.
Cardenas, G., Cuellar, J.D., Casals, P., 1997. Chitin and tosil chitin applications as nematocides. Bol. Soc. Chil. Quim. 42:535-546.
Chae, D.H., De Jin, R., Hwangbo, H., Kim, Y.W., Kim, Y.C., Park, R.D., et al., 2006. Control of late blight (Phytophthora capsici) in pepper plant with a compost containing multitude of chitinase-producing bacteria. BioControl 51:339-351. DOI: https://doi.org/10.1007/s10526-005-2934-x
Chandrashekara, K.N., Manivannan, S., Chandrashekara, C., Chakravarthi, M., 2012. Biological control of plant disease management. In: Singh, V.K., Singh, Y., Singh, A. (eds.), Eco-friendly Innovative Approaches in Plant Disease Management. International Book Publishers and Distributers, Dehradun, chapter 10.
Chang, C.-W., Laird, D.A., Mausbach, M.J., Hurburgh, C.R., 2001. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties. Soil Sci. Soc. Am. J. 65:480-490. d DOI: https://doi.org/10.2136/sssaj2001.652480x
Chysirichote, T., Reiji, T., Asami, K., Ohtaguchi, K., 2014. Quantification of the glucosamine content in the filamentous fungus Monascus ruber cultured on solid surfaces. J. Basic Microbiol. 54:350-357. d DOI: https://doi.org/10.1002/jobm.201200350
El Hadrami, A., Adam, L.R., El Hadrami, I., Daayf, F., 2010. Chitosan in plant protection. Mar. Drugs 8:968-987. DOI: https://doi.org/10.3390/md8040968
Forouzangohar, M., Kookana, R.S., Forrester, S.T., Smernik, R.J., Chittleborough, D.J., 2008. Midinfrared spectroscopy and chemometrics to predict diuron sorption coefficients in soils. Environ. Sci. Technol. 42:3283-3288. DOI: https://doi.org/10.1021/es702750d
Ghehsareh, A.M., Samadi, N. 2012. Effect of soil acidification on growth indices and microelements uptake by greenhouse cucumber. Afr. J. Agricultural Res. 7:1659-1665. DOI: https://doi.org/10.5897/AJAR11.1714
Herrera-Estrella, A., Chet, I., 1999. Chitinases in biological control. EXS 87:171-184. DOI: https://doi.org/10.1007/978-3-0348-8757-1_12
Hummel, J.W., Sudduth, K.A., Hollinger, S.E., 2001. Soil moisture and organic matter prediction of surface and subsurface soils using an NIR soil sensor. Comput. Electron. Agr. 32:149-165. DOI: https://doi.org/10.1016/S0168-1699(01)00163-6
Jabeen, F., Qazi, J.I., 2014. Potential of bacterial chitinases and exopolysaccharides for enhancing shelf life of food commodities at varying conditions. Int. Res. J. Environ. Sci. 3:87-93.
Kokalis-Burelle, N., 2001. Chitin amendments for suppression of plant parasitic nematodes and fungal pathogens. Phytopathology 91:S168-S168.
Krishnan, P., Alexander, J.D., Butler, B.J., Hummel, J.W., 1980. Reflectance technique for predicting soil organic matter. Soil Sci. Soc. Am. J. 44:1282-1285. DOI: https://doi.org/10.2136/sssaj1980.03615995004400060030x
Kumar, V., Singh, K., Shah, M.P., Singh, A.K., Kumar, A., Kumar, Y., 2021. Application of omics technologies for microbial community structure and function analysis in contaminated environment. In: Shah, M.P., Sarkar, A., Mandal, S. (eds.) Wastewater treatment: cutting-edge molecular tools, techniques and applied aspects. Amsterdam, Elsevier, pp. 1-40. DOI: https://doi.org/10.1016/B978-0-12-821881-5.00001-5
Kumar, V., Thakur, I.S., Singh, A.K., Shah, M.P., 2020. Application of metagenomics in remediation of contaminated sites and environmental restoration. In: Shah, M.P., Rodriguez-Couto, S., Sevinç Şengör, S. (eds.) Emerging technologies in environmental bioremediation. Amsterdam, Elsevier, pp. 197-232. DOI: https://doi.org/10.1016/B978-0-12-819860-5.00008-0
Liu, Y., Liao, W., Chen, S., 2008. Co-production of lactic acid and chitin using a pelletized filamentous fungus Rhizopus oryzae cultured on cull potatoes and glucose. J. Appl. Microbiol. 105:1521-1528. DOI: https://doi.org/10.1111/j.1365-2672.2008.03913.x
Nakatsu, C.H., Torsvik, V., Øvreås, L., 2000. Soil community analysis using DGGE of 16S rDNA polymerase chain reaction products. Soil Sci. Soc. Am. J. 64:1382-1388. DOI: https://doi.org/10.2136/sssaj2000.6441382x
Omwange, K.A., Al Riza, D.F., Sen, N., Shiigi, T., Kuramoto, M., Ogawa, Y., Kondo, N., Suzuki, T., 2020. Fish freshness monitoring using UV-fluorescence imaging on Japanese dace (Tribolodon hakonensis) fisheye. J. Food Eng. 287:110111. DOI: https://doi.org/10.1016/j.jfoodeng.2020.110111
Pearce, R.B., Ride, J.P., 1982. Chitin and related compounds as elicitors of the lignification response in wounded wheat leaves. Physiol. Plant Pathol. 20:119-123. DOI: https://doi.org/10.1016/0048-4059(82)90030-3
Peng, X., Shi, T., Song, A., Chen, Y., Gao, W., 2014. Estimating soil organic carbon using VIS/NIR spectroscopy with SVMR and SPA methods. Remote Sens. (Basel) 6:2699-2717. DOI: https://doi.org/10.3390/rs6042699
Poulsen, P.H.B., Møller, J., Magid, J., 2008. Determination of a relationship between chitinase activity and microbial diversity in chitin amended compost. Bioresource Technol. 99:4355-4359. DOI: https://doi.org/10.1016/j.biortech.2007.08.042
Reddy, M.V.B., Arul, J., Angers, P., Couture, L., 1999. Chitosan treatment of wheat seeds induces resistance to Fusarium graminearum and improves seed quality. J. Agr. Food Chem. 47:1208-1216. DOI: https://doi.org/10.1021/jf981225k
Wang, Y., Huang, T., Liu, J., Lin, Z., Li, S., Wang, R., Ge, Y., 2015. Soil pH value, organic matter and macronutrients contents prediction using optical diffuse reflectance spectroscopy. Comput. Electron. Agr. 111:69-77. DOI: https://doi.org/10.1016/j.compag.2014.11.019
Xu, R., Falardeau, J., Avis, T.J., Tambong, J.T., 2016. HybProbes-based real-time PCR assay for specific identification of Streptomyces scabies and Streptomyces europaeiscabiei, the potato common scab pathogens. Lett. Appl.Microbiol. 62:153-159. DOI: https://doi.org/10.1111/lam.12522
Xuemei, L., Jianshe, L., 2014. Using short wave visible-near infrared reflectance spectroscopy to predict soil properties and content. Spectrosc. Lett. 47:729-739. DOI: https://doi.org/10.1080/00387010.2013.840315
Yin, H., Zhao, X., Du, Y., 2010. Oligochitosan: A plant diseases vaccine-A review. Carbohyd. Polym. 82:1-8. DOI: https://doi.org/10.1016/j.carbpol.2010.03.066
Zeng, D., Mei, X., Wu, J., 2010. Study and preparation of an environmentally friendly corn seed coating agent. J. Plant Protect. Res. 50:21-214. DOI: https://doi.org/10.2478/v10045-010-0036-y
Zeng, D., Shi, Y., 2009. Preparation and application of a novel environmentally friendly organic seed coating for rice. J. Sci. Food Agr. 89:2181-2185. DOI: https://doi.org/10.1002/jsfa.3700

Supporting Agencies

United States Department of Agriculture, Agricultural Research Service
Ana Chen, School of Biological and Chemical Engineering, Anhui Polytechnic University, Anhui

Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, MI, USA

How to Cite

Omwange, K. A. (2025) “Exploring the feasibility of near-infrared spectroscopy in analyzing and predicting the chemical and biochemical changes of chitin-amended soils”, Journal of Agricultural Engineering, 56(1). doi: 10.4081/jae.2025.1710.
Copyright (c) 2025 the Author(s) Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.