Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Citrus peels are rich in bioactive compounds such as vitamin C and extraction of vitamin C is a good strategy for citrus peel recycling. It is essential to evaluate the levels of vitamin C in citrus peels before reuse. In this study, a near-infrared (NIR)-based method was proposed to quantify the vi...

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Veröffentlicht in:Molecules (Basel, Switzerland) Jg. 28; H. 4; S. 1681
Hauptverfasser: Zhang, Weiqing, Lin, Mei, He, Hongju, Wang, Yuling, Wang, Jingru, Liu, Hongjie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 01.02.2023
MDPI
Schlagworte:
Algorithms
Analysis
Antioxidants
Ascorbic Acid
Chromatography
Citrus
Citrus fruits
citrus peel
Composition
determination
Ethanol
Health aspects
Least-Squares Analysis
linear algorithm
Mean square errors
Measurement
Methods
Near infrared spectroscopy
near-infrared (NIR)
Normal distribution
Nutritional aspects
Spectroscopy, Near-Infrared - methods
Spectrum analysis
Vitamin C
Vitamins
China
Asia
linear algorithm
near-infrared (NIR)
determination
citrus peel
vitamin C
ISSN:1420-3049, 1420-3049
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Zusammenfassung:Citrus peels are rich in bioactive compounds such as vitamin C and extraction of vitamin C is a good strategy for citrus peel recycling. It is essential to evaluate the levels of vitamin C in citrus peels before reuse. In this study, a near-infrared (NIR)-based method was proposed to quantify the vitamin C content of citrus peels in a rapid way. The spectra of 249 citrus peels in the 912–1667 nm range were acquired, preprocessed, and then related to measured vitamin C values using the linear partial least squares (PLS) algorithm, indicating that normalization correction (NC) was more suitable for spectral preprocessing and NC-PLS model built with full NC spectra (375 wavelengths) showed a better performance in predicting vitamin C. To accelerate the predictive process, wavelength selection was conducted, and 15 optimal wavelengths were finally selected from NC spectra using the stepwise regression (SR) method, to predict vitamin C using the multiple linear regression (MLR) algorithm. The results showed that SR-NC-MLR model had the best predictive ability with correlation coefficients (rP) of 0.949 and root mean square error (RMSEP) of 14.814 mg/100 mg in prediction set, comparable to the NC-PLS model in predicting vitamin C. External validation was implemented using 40 independent citrus peels samples to validate the suitability of the SR-NC-MLR model, obtaining a good correlation (R2 = 0.9558) between predicted and measured vitamin C contents. In conclusion, it was reasonable and feasible to achieve the rapid estimation of vitamin C in citrus peels using NIR spectra coupled with MLR algorithm.
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These authors contributed equally to this work.
ISSN:1420-3049
1420-3049
DOI:10.3390/molecules28041681