Lu Xiaonan, Wang Jun, Al-Qadiri Hamzah M, Ross Carolyn F, Powers Joseph R, Tang Juming, Rasco Barbara A
School of Food Science, Washington State University, P.O. Box 646376, Pullman, WA 99163, USA.
College of Food Science and Engineering, Northwest A&F University, Yangling 712100, PR China.
Food Chem. 2011 Nov 15;129(2):637-644. doi: 10.1016/j.foodchem.2011.04.105. Epub 2011 May 5.
Total phenolic content (TPC) and total antioxidant capacity (TAC) of four onion varieties (red, white, yellow and sweet) and shallot from selected locations (Washington, Idaho, Oregon, Texas and Georgia) were determined using Fourier transform infrared (FT-IR) spectroscopy (4000-400cm). The Folin-Ciocalteu (F-C) assay was used to quantify TPC and three assays were used to determine TAC, including 2,2-diphenyl-picrylhydrazyl (DPPH) assay, Trolox equivalent antioxidant capacity (TEAC) assay and ferric reducing antioxidant power (FRAP) assay. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was conducted on onion and shallot extracts (n=200) and their corresponding F-C, DPPH, TEAC and FRAP values were employed to obtain four independent calibration models for predicting TPC and TAC for the extracts. Spectra from an extra 19 independent extracts were used as an external validation set for prediction. A correlation of r>0.95 was obtained between FT-IR predicted and reference values (by F-C, DPPH, TEAC and FRAP assay) with standard errors of calibration (SEC) and standard errors of cross-validation (SECV) less than 2.85, 0.35 and 0.45μmolTrolox/g FW of extracts for TEAC, FRAP and DPPH assay, respectively; and 0.36mggallic acid/g FW of extracts for the F-C assay. In addition, cluster analysis (principal component analysis (PCA)) and discriminant function analysis (DFA) could differentiate varieties of onions and shallot based upon infrared spectral features. Loading plots for the various chemometrics models indicated that hydroxyl and phenolic functional groups were most closely correlated with antioxidant capacity. The use of mid-infrared spectroscopy to predict the total antioxidant capacity of vegetables provides a rapid and precise alternative to traditional wet chemistry analysis.
采用傅里叶变换红外（FT-IR）光谱法（4000 - 400cm）测定了来自选定地点（华盛顿、爱达荷州、俄勒冈州、得克萨斯州和佐治亚州）的四个洋葱品种（红皮、白皮、黄皮和甜洋葱）以及青葱的总酚含量（TPC）和总抗氧化能力（TAC）。采用福林 - 西奥尔特（F-C）法对TPC进行定量，并使用三种方法测定TAC，包括2,2 - 二苯基 - 苦味酰基肼（DPPH）法、Trolox等效抗氧化能力（TEAC）法和铁还原抗氧化能力（FRAP）法。对洋葱和青葱提取物（n = 200）进行了带有交叉验证（留一法）的偏最小二乘回归（PLSR），并利用其相应的F-C、DPPH、TEAC和FRAP值获得了四个独立的校准模型，用于预测提取物的TPC和TAC。另外19个独立提取物的光谱用作外部验证集进行预测。FT-IR预测值与参考值（通过F-C、DPPH、TEAC和FRAP测定）之间的相关性r > 0.95，校准标准误差（SEC）和交叉验证标准误差（SECV）分别小于TEAC、FRAP和DPPH测定中提取物的2.85、0.35和0.45μmol Trolox/g FW；以及F-C测定中提取物的0.36mg没食子酸/g FW。此外，聚类分析（主成分分析（PCA））和判别函数分析（DFA）可以根据红外光谱特征区分洋葱和青葱的品种。各种化学计量学模型的载荷图表明，羟基和酚类官能团与抗氧化能力的相关性最为密切。使用中红外光谱法预测蔬菜的总抗氧化能力为传统湿化学分析提供了一种快速、精确的替代方法。
