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

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.

Quantitative Analysis of UV-B Radiation Interception and Bioactive Compound Contents in Kale by Leaf Position According to Growth Progress

“…The annual production of TPC and TFC in plant factories could be estimated using the content per plant at various growth stages without neighboring shading, which could determine the optimal harvest time ( Yoon et al, 2019 ). Chowdhury et al (2021) reported that health-promoting components, specifically glucosinolates and anthocyanin, in kale grown in a plant factory can be estimated through spectral reflectance. Similar to these studies, the annual production of UV-B-induced bioactive compounds can be estimated through UV-B radiation interception analysis.…”

Characterization of Polyphenol Composition and Starch and Protein Structure in Brown Rice Flour, Black Rice Flour and Their Mixtures

“…The best correlation is registered in the case of area A# 9 (695 nm), for which the values of R 2 were in the range of 0.9905 to 0.9977, the values of ER(%) were in the range of 3.0616–5.1745% and the predictive power of the model ranged from 5.37% to 8.31%. The literature indicates the presence of anthocyanins around 627 nm [ 39 ], but the model did not assign a compound to the A#6, probably due to its low values of the areas associated with the Gaussian distributions ( Table 4 ). The concentration of protocatechuic acid significantly correlates ( p < 0.00007) with the area A#2 assigned to the wavelength 429 nm, with values of 0.9970, 5.2081% and 5.5689% for the R 2 , ER (%) and predictive power, respectively.…”

“…The literature indicates the presence of anthocyanins around 627 nm [ 39 ], but the model did not assign a compound to the A#6, probably due to its low values of the areas associated with the Gaussian distributions ( Table 4 ).…”

Spectral Reflectance Indexes Reveal Differences in the Physiological Status of Brassica oleracea with Contrasting Glucosinolate Content under Biotic Stress

“…In our experiments we have found that high and low GSL content populations differed in their spectral patterns. Following [ 18 ], the absorbance at 425 nm is correlated to total GSL content in Brassica napus , while [ 19 ] found that the spectral reflectance in several bands between 742 and 1000 nm is strongly correlated to individual GSL content in kale ( B. oleracea ). Other differences in the spectral reflectance between populations with contrasting GSL content reflect differences in their vigor, photosynthesis, or water content.…”