Federal University of Rio Grande do Norte, Department of Chemical Engineering, 59072-970 Natal, RN, Brazil.
Federal University of Rio Grande do Norte, Institute of Chemistry, PPGQ, Biological Chemistry and Chemometrics, 59072-970 Natal, RN, Brazil.
Food Chem. 2016 Jan 1;190:1-4. doi: 10.1016/j.foodchem.2015.05.063. Epub 2015 May 16.
The aim of this work was to develop an analytical method to predict total anthocyanins content (TAC) and total phenolic compounds (TPC) in intact wax jambu fruit [Syzygium malaccense (L.) Merryl et Perry] using near-infrared spectroscopy (NIRS) and partial least squares (PLS). The estimation accuracy was based on parameters such as root mean square error of prediction (RMSEP), correlation coefficients [calibration (rc) and prediction (rp) set] and ratio of performance to deviation (RPD). TAC, rp = 0.98, RMSEP = 9.0 mg L(-1) and RPD = 5.19 were attained using second derivative pre-treatment. TPC, rp = 0.94, RMSEP = 22.18 (mg gallic acid equivalents (GAE)/100g) and RPD = 3.27 (excellent accuracy) were also obtained using second derivative pre-treatment. These findings suggest that the NIRS and PLS algorithms can be used to determine TCA and TPC in intact wax jambu fruit.
本工作旨在利用近红外光谱（NIRS）和偏最小二乘法（PLS）建立一种分析方法，用于预测完整番荔枝果实（Syzygium malaccense（L.）Merryl et Perry）中的总花色苷含量（TAC）和总酚类化合物含量（TPC）。预测精度的评估参数包括预测均方根误差（RMSEP）、校准集和预测集相关系数（rc 和 rp）和表现偏差比（RPD）。使用二阶导数预处理后，TAC 的 rp = 0.98，RMSEP = 9.0mg/L，RPD = 5.19。同样使用二阶导数预处理，TPC 的 rp = 0.94，RMSEP = 22.18（mg 没食子酸当量（GAE）/100g），RPD = 3.27（准确度优秀）。这些结果表明，NIRS 和 PLS 算法可用于测定完整番荔枝果实中的 TCA 和 TPC。
