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Estimation of Glucosinolates and Anthocyanins in Kale Leaves Grown in a Plant Factory Using Spectral Reflectance

Milon Chowdhury, Ngo Viet Duc, Md Nafiul Islam, Mohammod Ali, Sumaiya Islam, Kamal Rasool, Sang Un Park, Sun‐Ok Chung

2021Horticulturae23 citationsDOIOpen Access PDF

Abstract

The spectral reflectance technique for the quantification of the functional components was applied in different studies for different crops, but related research on kale leaves is limited. This study was conducted to estimate the glucosinolate and anthocyanin components of kale leaves cultivated in a plant factory based on diffuse reflectance spectroscopy through regression methods. Kale was grown in a plant factory under different treatments. After specific periods of transplantation, leaf samples were collected, and reflectance spectra were measured immediately from nine different points on each leaf. The same leaf samples were freeze-dried and stored for analysis of the functional components. Regression procedures, such as principal component regression (PCR), partial least squares regression (PLSR), and stepwise multiple linear regression (SMLR), were applied to relate the functional components with the spectral data. In the laboratory analysis, progoitrin and glucobrassicin, as well as cyanidin and malvidin, were found to be dominating components in glucosinolates and anthocyanins, respectively. From the overall analysis, the SMLR model showed better performance, and the identified wavelengths for estimating the glucosinolates and anthocyanins were in the early near-infrared (NIR) region. Specifically, reflectance at 742, 761, 787, 796, 805, 833, 855, 932, 947, and 1000 nm showed a strong correlation.

Topics & Concepts

Partial least squares regressionAnthocyaninGlucosinolateChemistryLinear regressionReflectivityFood scienceHorticultureBotanyPrincipal component analysisPrincipal component regressionBrassicaBiologyMathematicsPhysicsOpticsStatisticsPhytochemicals and Antioxidant ActivitiesSpectroscopy and Chemometric AnalysesGenomics, phytochemicals, and oxidative stress
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