Prediksi Unsur Hara Sampel Tanah Menggunakan Near Infrared Spectroscopy
Abstract
Penentuan karakteristik dan konsentrasi unsur hara tanah perlu dilakukan metode analisa untuk perlakuan lahan serta ketepatan dosis dan jenis pemupukan dalam optimalisasi produktivitas tanaman. Metode alternatif analisis kandungan sampel secara cepat, efektif, ramah lingkungan, dan tidak merusak sampel dapat menggunakan near infrared spectroscopy (NIRS). Sampel yang digunakan berasal dari Laboratorium Tanah, P3GI. Parameter yang digunakan sebagai perkiraan kandungan yaitu pH, nitrogen (N, %), fosfat (P2O5, ppm), dan kalium (K2O, ppm). Sebanyak 64 sampel tanah digunakan untuk kalibrasi dan 30% untuk validasi. Spektrum NIRS diperoleh dari FOSS XDS rapid content analysis (400 – 2.400 nm, reflectance mode) dan pengolahan data statistik menggunakan vision software dengan model yang dibangun berdasarkan partial least square (PLS). Penelitian ini didapatkan hasil evaluasi bahwa model yang dibangun untuk memprediksi parameter pH (R2 = 0,951; r2 = 0,511; SEP = 1,428; RPD = 1,440; consistency = 22,321%; dan = 0,1776) dan nitrogen R2 = 0,767; r2 = 0,665; SEP = 0,025; RPD = 1,749; consistency = 97,745%; dan = 0,0131) performanya masih cukup baik, sedangkan lainnya masih kurang. Berdasarkan hasil evaluasi tersebut, NIRS memiliki potensi sebagai metode analisa kualitas tanah namun model yang dibangun masih perlu ditingkatkan keakuratanya.
Keywords
Full Text:
PDFReferences
Bellon-Maurel, V., & McBratney, A. (2011). Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils - critical review and research perspectives. Soil Biology and Biochemistry, 43(7), 1398–1410. https://doi.org/10.1016/j.soilbio.2011.02.019
Blanco, M., & Villarroya, I. (2002). NIR spectroscopy: a rapid-response analytical tool. TrAC - Trends in Analytical Chemistry, 21(4), 240–250. https://doi.org/10.1016/S0165-9936(02)00404-1
Bobelyn, E., Serban, A. S., Nicu, M., Lammertyn, J., Nicolai, B. M., & Saeys, W. (2010). Postharvest quality of apple predicted by NIR-spectroscopy: Study of the effect of biological variability on spectra and model performance. Postharvest Biology and Technology, 55(3), 133–143. https://doi.org/10.1016/j.postharvbio.2009.09.006
Cañasveras, J. C., Barrón, V., del Campillo, M. C., & Viscarra Rossel, R. A. (2012). Reflectance spectroscopy: a tool for predicting soil properties related to the incidence of Fe chlorosis. Spanish Journal of Agricultural Research, 10(4), 1133–1142. https://doi.org/10.5424/sjar/2012104-681-11
Cozzolino, D., Murray, I., Chree, A., & Scaife, J. R. (2005). Multivariate determination of free fatty acids and moisture in fish oils by partial least-squares regression and near-infrared spectroscopy. Lebensmittel-Wissenschaft & Technologie, LWT, 38(8), 821–828. https://doi.org/10.1016/j.lwt.2004.10.007
Debaene, G., Niedźwiecki, J., & Pecio, A. (2010). Visible and near-infrared spectrophotometer for soil analysis : preliminary results. Polish Journal of Agronomy, 3, 3–9.
Elfadl, E., Reinbrecht, C., & Claupein, W. (2010). Development of near infrared reflectance spectroscopy (NIRS) calibration model for estimation of oil content in a worldwide safflower germplasm collection. International Journal of Plant Production, 4(4), 259–270.
Guo, L., Zhao, C., Zhang, H., Chen, Y., Linderman, M., Zhang, Q., & Liu, Y. (2017). Comparisons of spatial and non-spatial models for predicting soil carbon content based on visible and near-infrared spectral technology. Geoderma, 285, 280–292. https://doi.org/10.1016/j.geoderma.2016.10.010
He, Y., Huang, M., García, A., Hernández, A., & Song, H. (2007). Prediction of soil macronutrients content using near-infrared spectroscopy. Computers and Electronics in Agriculture, 58(2), 144–153. https://doi.org/10.1016/j.compag.2007.03.011
Kooistra, L., Wehrens, R., Buydens, L. M. C., Leuven, R. S. E. W., & Nienhuis, P. H. (2001). Possibilities of soil spectroscopy for the classification of contaminated areas in river floodplains. ITC Journal, 3(4), 337–344. https://doi.org/10.1016/S0303-2434(01)85041-8
Martínez-España, R., Bueno-Crespo, A., Soto, J., Janik, L. J., & Soriano-Disla, J. M. (2018). Developing an intelligent system for the prediction of soil properties with a portable mid-infrared instrument. Biosystems Engineering, 177, 101–108. https://doi.org/10.1016/j.biosystemseng.2018.09.013
Mohamed, E. S., Saleh, A. M., Belal, A. B., & Gad, A. A. (2018). Application of near-infrared reflectance for quantitative assessment of soil properties. Egyptian Journal of Remote Sensing and Space Science, 21(1), 1–14. https://doi.org/10.1016/j.ejrs.2017.02.001
Moros, J., Martínez-Sánchez, M. J., Pérez-Sirvent, C., Garrigues, S., & de la Guardia, M. (2009). Testing of the region of murcia soils by near infrared diffuse reflectance spectroscopy and chemometrics. Talanta, 78(2), 388–398. https://doi.org/10.1016/j.talanta.2008.11.041
Mulyono, D. (2009). Pengaruh pupuk akar (NPK) dengan pupuk daun (multimikro) dan zat pengatur tumbuh (ethrel) terhadap pertumbuhan vegetatif tanaman lada. Jurnal Sains & Teknologi Lingkungan, 11(3)(November), 139–144. http://ejurnal2.bppt.go.id/index.php/JSTI/article/view/832/665
Munawar, A. A., Hörsten, D. V., Mörlein, D., Pawelzik, E., & Wegener, J. K. (2016). Rapid and non-destructive prediction of mango sweetness and acidity using near infrared spectroscopy. In Lecture Notes in Informatics (LNI). Proceedings - Series of the Gesellschaft Fur Informatik (GI), P-211, 219–222.
Nanni, M. R., & Demattê, J. A. M. (2006). Spectral reflectance methodology in comparison to traditional soil analysis. Soil Science Society of America Journal, 70(2), 393–407. https://doi.org/10.2136/sssaj2003.0285
Niederberger, J., Todt, B., Boča, A., Nitschke, R., Kohler, M., Kühn, P., & Bauhus, J. (2015). Use of near-infrared spectroscopy to assess phosphorus fractions of different plant availability in forest soils. Biogeosciences, 12(11), 3415–3428. https://doi.org/10.5194/bg-12-3415-2015
Nircal 5.5 Manual. (2013). Nircal Manual. In Buchi Labortechnik AG, CH Flawil.
Peltre, C., Thuriès, L., Barthès, B., Brunet, D., Morvan, T., Nicolardot, B., Parnaudeau, V., & Houot, S. (2011). Near infrared reflectance spectroscopy: a tool to characterize the composition of different types of exogenous organic matter and their behaviour in soil. Soil Biology and Biochemistry, 43(1), 197–205. https://doi.org/10.1016/j.soilbio.2010.09.036
Pinheiro, É. F. M., Ceddia, M. B., Clingensmith, C. M., Grunwald, S., & Vasques, G. M. (2017). Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the Central Amazon. Remote Sensing, 9(4), 1–22. https://doi.org/10.3390/rs9040293
Saeys, W., Mouazen, A. M., & Ramon, H. (2005). Potential for onsite and online analysis of pig manure using visible and near infrared reflectance spectroscopy. Biosystems Engineering, 91(4), 393–402. https://doi.org/10.1016/j.biosystemseng.2005.05.001
Soriano-Disla, J. M., Janik, L. J., Forrester, S. T., Grocke, S. F., Fitzpatrick, R. W., & McLaughlin, M. J. (2019). The use of mid-infrared diffuse reflectance spectroscopy for acid sulfate soil analysis. Science of the Total Environment, 646, 1489–1502. https://doi.org/10.1016/j.scitotenv.2018.07.383
Vaknin, Y., Ghanim, M., Samra, S., Dvash, L., Hendelsman, E., Eisikowitch, D., & Samocha, Y. (2011). Predicting Jatropha curcas seed-oil content, oil composition and protein content using near-infrared spectroscopy-a quick and non-destructive method. Industrial Crops and Products, 34(1), 1029–1034. https://doi.org/10.1016/j.indcrop.2011.03.011
Viscarra Rossel, R. A., Rizzo, R., Demattê, J. A. M., & Behrens, T. (2010). Spatial modeling of a soil fertility index using visible-near-infrared spectra and terrain attributes. Soil Science Society of America Journal, 74(4), 1293–1300. https://doi.org/10.2136/sssaj2009.0130
Wang, K., Zhao, Y., Yang, Z., Lin, Z., Tan, Z., Du, L., & Liu, C. (2018). Concentration and characterization of groundwater colloids from the northwest edge of Sichuan basin, China. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 537, 85–91. https://doi.org/10.1016/j.colsurfa.2017.08.032
Waruru, B. K., Shepherd, K. D., Ndegwa, G. M., & Sila, A. M. (2016). Estimation of wet aggregation indices using soil properties and diffuse reflectance near infrared spectroscopy: An application of classification and regression tree analysis. Biosystems Engineering, 152, 148–164. https://doi.org/10.1016/j.biosystemseng.2016.08.003
Xiao, S., & He, Y. (2019). Application of near-infrared spectroscopy and multiple spectral algorithms to explore the effect of soil particle sizes on soil nitrogen detection. Molecules, 24(13). https://doi.org/10.3390/molecules24132486
Yamani, A. (2012). Analisis kadar hara makro tanah pada hutan lindung gunung sebatung di Kabupaten Kotabaru. Jurnal Hutan Tropis, 12(2), 181–187.
Yarce, C. J., & Rojas, G. (2012). Near infrared spectroscopy for the analysis of macro and micro nutrients in sugarcane leaves. Zuckerindustrie, 137(11), 707–710. https://doi.org/10.36961/si13611
DOI: https://doi.org/10.54256/isrj.v3i1.88
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 Opal Priya Wening, Risvan Kuswurjanto
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Editorial Office:
Pusat Penelitian Perkebunan Gula Indonesia
Jl.Pahlawan Nomor 25 Pasuruan 67126, Indonesia
Telp:+62 0343 421086 ; Fax: +62 0343 421178
Email: p3gipasuruanok@gmail.com; web perusahaan:http://www.p3gi.co.id
Indonesian Sugar Research Journal (ISRJ) is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.