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

Thitima Phanomsophon; Natthapon Jaisue; Akarawhat Worphet; Nukoon Tawinteung; Lampan Khurnpoon; Ravipat Lapcharoensuk; Warawut Krusong; Pimpen Pornchaloempong; Panmanas Sirisomboon; Tetsuya Inagaki; Te Ma; Satoru Tsuchikawa

doi:10.1016/j.saa.2023.123398

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

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Jan 5:304:123398. doi: 10.1016/j.saa.2023.123398. Epub 2023 Sep 11.

Affiliations

¹ Department of Agricultural Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
² Department of Plant Production Technology, School of Agricultural Technology, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
³ Department of Agricultural Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand. Electronic address: ravipat.la@kmitl.ac.th.
⁴ Division of Fermentation Technology, School of Food Industry, King Mongkut's Institute of Technology Ladkrabang, Bangkok. Thailand.
⁵ Department of Food Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
⁶ Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan.
⁷ Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan. Electronic address: st3842@agr.nagoya-u.ac.jp.

PMID: 37714103
DOI: 10.1016/j.saa.2023.123398

Abstract

Farmers 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^-1. 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 r² = 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 r² = 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.

Keywords: Durian leaf; Near infrared spectroscopy; Primary macronutrients; Successive projections algorithm.