Santana Monique Carvalho de, Ferreira Marcia Miguel Castro, Pallone Juliana Azevedo Lima
1Department of Food Science, Faculty of Food Engineering, University of Campinas, Campinas, SP 13083-862 Brazil.
2Department of Physical Chemistry, Institute of Chemistry, University of Campinas, Campinas, SP 13084-971 Brazil.
J Food Sci Technol. 2020 Apr;57(4):1233-1241. doi: 10.1007/s13197-019-04154-1. Epub 2019 Nov 18.
Powdered soft drinks (PSDs), fortified with antioxidants such as ascorbic acid (AA), are normally controlled by titration or chromatographic methods. This study evaluated the feasibility of using near-infrared spectroscopy (NIRS) and multivariate analysis to predict AA contents in PSDs as an alternative not-destructive method. The AA content of sixty-seven samples of commercial fortified grape and passion fruit PSDs was analyzed by the standard method (titration) and showed significant variance between flavors within the same brand. In addition, 75% of the samples required from 0.3 to 10.2 more cups of grape than passion fruit flavor to supply the AA Reference Nutrient Intake for children and adults. Spectral and reference data sets were split into calibration and validation sets. Partial least squares regression models were built and validated for the determination of AA in both PSDs. The model's basic statistics for grape flavor PSDs (RMSEC = 0.49 mg g, R = 0.84; RMSECV = 0.67 mg g, R = 0.70; RMSEP = 0.50 mg g, R = 0.84), and that for passion fruit flavor PSDs (RMSEC = 0.24 mg g, R = 0.95; RMSECV = 0.56 mg g, R = 0.76; RMSEP de 0.57 mg g, R = 0.72) indicated that NIRS-PLS methodology produced reasonable results. The limits of detection and quantification obtained showed that the method is useful to detect and quantify AA in the studied samples. A new set of grape drinks was used for external prediction and the RMSEP was 0.62 mg g, R was 0.72. Based on the results, NIRS-multivariate analysis proved to be useful for quality control of AA in commercialized grape and passion fruit in PSDs and a faster, objective and environmentally friendly method alternative to standard methods.
添加了抗坏血酸（AA）等抗氧化剂的粉状软饮料（PSD）通常采用滴定法或色谱法进行检测。本研究评估了使用近红外光谱（NIRS）和多变量分析来预测PSD中AA含量作为一种无损替代方法的可行性。采用标准方法（滴定法）分析了67个市售强化葡萄味和百香果味PSD样品的AA含量，结果显示同一品牌内不同口味之间存在显著差异。此外，75%的样品供应儿童和成人AA参考营养素摄入量所需的葡萄味饮料比百香果味饮料多0.3至10.2杯。光谱数据集和参考数据集被分为校准集和验证集。建立了偏最小二乘回归模型并对两种PSD中的AA进行了测定和验证。葡萄味PSD模型的基本统计数据（RMSEC = 0.49 mg/g，R = 0.84；RMSECV = 0.67 mg/g，R = 0.70；RMSEP = 0.50 mg/g，R = 0.84）以及百香果味PSD模型的基本统计数据（RMSEC = 0.24 mg/g，R = 0.95；RMSECV = 0.56 mg/g，R = 0.76；RMSEP = 0.57 mg/g，R = 0.72）表明，NIRS-PLS方法产生了合理的结果。所获得的检测限和定量限表明该方法可用于检测和定量所研究样品中的AA。使用一组新的葡萄味饮料进行外部预测，RMSEP为0.62 mg/g，R为0.72。基于这些结果，NIRS多变量分析被证明可用于商业化葡萄味和百香果味PSD中AA的质量控制，是一种比标准方法更快、更客观且环保的替代方法。
