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Monthly metabolic changes and PLS prediction of carotenoid content of citrus fruit by combined Fourier transform infrared spectroscopy and quantitative HPLC analysis
- Monthly metabolic changes and PLS prediction of carotenoid content of citrus fruit by combined Fourier transform infrared spectroscopy and quantitative HPLC analysis
- Kim, SW[Kim, Suk Weon]; Ahn, MS[Ahn, Myung Suk]; Kwon, YK[Kwon, Yong Kook]; Song, SY[Song, Seung Yeob]; Kim, JK[Kim, Jae Kwang]; Ha, SH[Ha, Sun-Hwa]; Kim, IJ[Kim, In-Jung]; Liu, JR[Liu, Jang R.]
- DGIST Authors
- Liu, JR[Liu, Jang R.]
- Issue Date
- Plant Biotechnology Reports, 9(4), 247-258
- Article Type
- Carotenoids; Citrus; Citrus Fruit; Citrus Unshiu; Fourier Transform Infrared Spectroscopy; Metabolic Change; PCA; PLS Regression
- This work examined the potential of Fourier transform infrared spectroscopy (FT-IR) spectroscopy and high-performance liquid chromatography (HPLC) analysis in evaluating metabolic changes during ripening of citrus fruit. Further, the feasibility of prediction modeling of carotenoid content by multivariate statistical analysis combined with FT-IR spectral and HPLC data was examined without additional HPLC analysis. FT-IR spectra of citrus (Citrus unshiu Marc. cv. Miyagawa) fruit peels and flesh were measured at monthly intervals of fruit development. Quantification of carotenoids from the fruit was confirmed by quantitative HPLC analysis. The most remarkable evolution of FT-IR spectral decrease during ripening of fruit was found in the amide region (1500–1700 cm−1), whereas there was an increase in the carbohydrate region (1000–1200 cm−1). The evolution of different FT-IR spectral bands was related to fruit constituents, including organic acids, carbohydrates, carotenoids, and phenolic compounds. Significant qualitative changes in the carotenoid pattern included an increase in β-cryptoxanthin and decrease in lutein content during citrus fruit development. The content of antheraxanthin (R2 = 0.9117), β-carotene (R2 = 0.8816), β-cryptoxanthin (R2 = 0.8856), and violaxanthin (R2 = 0.7305) from peels of citrus fruit could be predicted from FT-IR spectral data using partial least square (PLS) regression modeling. Considering the results of PLS-discriminant analysis (PLS-DA) of FT-IR spectral data and PLS regression modeling of carotenoid content, FT-IR in combination with multivariate analysis enables not only discrimination of metabolic variation during fruit development, but also prediction of carotenoid content from citrus fruit. © 2015, Korean Society for Plant Biotechnology and Springer Japan.
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