Kim Young-Jun, Lee Hyong Joo, Shin Han-Seung, Shin Youngjae
Department of Agricultural Biotechnology, Seoul National University, Seoul, 151-921, Republic of Korea.
Phytochem Anal. 2014 Sep-Oct;25(5):445-52. doi: 10.1002/pca.2514. Epub 2014 Apr 1.
Turmeric has been widely used in curry powders as the main spice. Conventional chemical analysis such as high-performance liquid chromatography (HPLC) may take several hours to extract curcuminoids and prepare samples in many turmeric processing industries.
This study was conducted to evaluate curcuminoids in turmeric powder using near-infrared reflectance spectroscopy (NIRS).
All spectral acquisition ranged from 1100 to 2500 nm and a chemometrics analysis using partial least-squares (PLS) regression was performed to quantify the contents of individual curcuminoids. The HPLC was carried out (n = 129) to develop a PLS model based on the reference values.
High correlation coefficient (R(2) > 0.93) and low standard error of cross-validation (SECV < 0.20 g/100 g) and standard error of prediction (SEP < 0.13 g/100 g) values were obtained for precision and accuracy. In addition, the ratio of prediction to deviation (RPD > 2.65) values was also calculated.
Our results indicate that NIRS could be utilised as a control procedure or as an alternative rapid and effective quantification method.
姜黄作为主要香料已被广泛用于咖喱粉中。在许多姜黄加工行业中,诸如高效液相色谱法(HPLC)之类的传统化学分析可能需要数小时来提取姜黄素并制备样品。
本研究旨在使用近红外反射光谱法(NIRS)评估姜黄粉中的姜黄素。
所有光谱采集范围为1100至2500nm,并使用偏最小二乘法(PLS)回归进行化学计量学分析,以量化各个姜黄素的含量。进行了HPLC分析(n = 129)以基于参考值建立PLS模型。
获得了高精度和高准确度的相关系数(R²> 0.93)、低交叉验证标准误差(SECV <0.20 g/100 g)和预测标准误差(SEP <0.13 g/100 g)值。此外,还计算了预测偏差比(RPD> 2.65)值。
我们的结果表明,NIRS可作为一种控制程序或作为一种快速有效的替代定量方法。