研究目的
Investigating the carotenoid composition in cassava genotypes to classify them based on their pro-vitamin A activity and other health-related features using UV-visible spectrophotometry, HPLC, and chemometric analysis.
研究成果
The analytical approach effectively discriminated cassava genotypes based on carotenoid content, with yellow-fleshed roots high in cis-β-carotene and lutein, cream-fleshed roots low in pigments, and red-fleshed roots rich in lycopene. This supports the use of UV-Vis, HPLC, and chemometrics for classifying genotypes to aid in breeding programs for improved nutrition and health benefits.
研究不足
The study is limited to ten cassava genotypes from one region, which may not represent global diversity. The analytical methods, while efficient, rely on specific equipment and may have sensitivity constraints. The chemometric models, though accurate, could be improved with larger datasets or additional validation.
1：Experimental Design and Method Selection:
The study used UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography (RP-HPLC) for metabolomics characterization of carotenoids in cassava roots, combined with chemometric analysis including principal component analysis (PCA), cluster analysis, fold-change analysis, volcano plot, PLS-DA, and random forest for data modeling and classification.
2：Sample Selection and Data Sources:
Ten cassava genotypes from the EPAGRI germplasm bank in southern Brazil were selected based on economic and social importance, classified by root flesh color (cream, yellow, red). Samples were analyzed in triplicate.
3：List of Experimental Equipment and Materials:
Equipment includes Ultra-Turrax homogenizer (Janke & Kunkel IKA - T25 basic), UV-visible spectrophotometer (Gold Spectrum lab 53 UV-Vis spectrophotometer, BEL photonics), liquid chromatograph (LC-10A Shimadzu) with C18 reversed-phase column (Vydac 201TP54) and pre-column, spectrophotometric detector. Materials include organic solvents (acetone, petroleum ether), standard carotenoid compounds (Sigma-Aldrich), and R software for data analysis.
4：Experimental Procedures and Operational Workflow:
Carotenoids were extracted from fresh roots using acetone and petroleum ether with homogenization. Absorbance was measured from 200 to 700 nm. HPLC injections (10μl) were performed with methanol:acetonitrile elution at 1 ml/min, detection at 450 nm. Data were processed with baseline correction, normalization, smoothing, and analyzed using ANOVA, Tukey's test, PCA, clustering, fold-change, volcano plot, PLS-DA, and random forest.
5：Data Analysis Methods:
Statistical analysis included ANOVA and Tukey's test for mean comparison. Chemometric methods involved PCA, hierarchical clustering, fold-change analysis, volcano plot with t-test, PLS-DA, and random forest using R language (v. 3.1.1) with packages ChemoSpec, HyperSpec, and ggplot2.
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