Primary assessment of macronutrients in durian (CV Monthong) leaves using near infrared spectroscopy with wavelength selection

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dc.contributor.authorPhanomsophon, Thitima
dc.contributor.authorJaisue, Natthapon
dc.contributor.authorWorphet, Akarawhat
dc.contributor.authorTawinteung, Nukoon
dc.contributor.authorKhurnpoon, Lampan
dc.contributor.authorLapcharoensuk, Ravipat
dc.contributor.authorKrusong, Warawut
dc.contributor.authorPornchaloempong, Pimpen
dc.contributor.authorSirisomboon, Panmanas
dc.contributor.authorInagaki, Tetsuya
dc.contributor.authorMa, Te
dc.contributor.authorTsuchikawa, Satoru
dc.date.accessioned2026-08-06T10:45:28Z
dc.date.available2026-08-06T10:45:28Z
dc.date.issued2024-01-05
dc.description.abstractFarmers would be able to regulate fertilization and produce quality durian if they knew the nutrient concentration in durian leaves. A long period of time for traditional nutritional content determination is needed. Therefore, near-infrared spectroscopy is a good method for nondestructive and quick nutrient content evaluation. The leaf sample matrices (fresh leaves, dried ground leaves, and dried ground leaf pellets) were scanned by Fourier transform near-infrared (FT-NIR) with a wavelength of 12,500–3,600 cm<sup>−1</sup>. Regression models were developed using partial least squares (PLS) with full wavelength, short wavelength, and selected wavelength by successive projections algorithm (SPA). In this study, the model for N and K concentration was acceptable and the prediction was considered good but for P content not had succeeded. As a result, the PLS-SPA model using fresh leaf samples for evaluating N content in durian leaves exhibited performance of r<sup>2</sup> = 0.852, SEP = 0.14%, RPD = 2.63 and bias = −0.020%. The PLS-SPA model using dried ground leaf samples for evaluating K content in durian leaves exhibited performance of r<sup>2</sup> = 0.820, SEP = 0.13%, RPD = 2.36 and bias = 0.006%. This research found that it is possible to apply NIR waves to predict N and K concentrations in durian leaves. It is not necessary to predict directly from the wavelengths associated with -N or -K bonds. Instead, NIR can measure them indirectly from the bonding of proteins, which are products formed by N and K. In addition, selecting the wavelength that is related to the value to be measured can produce results that are not significantly different from using full or short wavelengths. These models can assist farmers in rapidly predicting N and K content in durian leaves for immediate fertilizer adjustment.
dc.identifier.citationSpectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, 304, 2024
dc.identifier.doi10.1016/j.saa.2023.123398
dc.identifier.issn13861425
dc.identifier.other2-s2.0-85171335877
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15473
dc.sourceSpectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
dc.subjectDurian leaf
dc.subjectNear infrared spectroscopy
dc.subjectPrimary macronutrients
dc.subjectSuccessive projections algorithm
dc.titlePrimary assessment of macronutrients in durian (CV Monthong) leaves using near infrared spectroscopy with wavelength selection
dc.typeArticle

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