Department of Biotechnology Chemistry and Pharmacy, University of Siena, via A. Moro 2, 53100 Siena, Italy.
Center for Colloid and Surface Science (CSGI), via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
Molecules. 2021 May 21;26(11):3068. doi: 10.3390/molecules26113068.
The intake of tomato glycoalkaloids can exert beneficial effects on human health. For this reason, methods for a rapid quantification of these compounds are required. Most of the methods for α-tomatine and dehydrotomatine quantification are based on chromatographic techniques. However, these techniques require complex and time-consuming sample pre-treatments. In this work, HPLC-ESI-QqQ-MS/MS was used as reference method. Subsequently, multiple linear regression (MLR) and partial least squares regression (PLSR) were employed to create two calibration models for the prediction of the tomatine content from thermogravimetric (TGA) and attenuated total reflectance (ATR) infrared spectroscopy (IR) analyses. These two fast techniques were proven to be suitable and effective in alkaloid quantification (R = 0.998 and 0.840, respectively), achieving low errors (0.11 and 0.27%, respectively) with the reference technique.
摄入番茄糖苷生物碱对人体健康有益。出于这个原因，需要快速定量这些化合物的方法。大多数用于α-茄碱和脱氢茄碱定量的方法都是基于色谱技术。然而，这些技术需要复杂且耗时的样品预处理。在这项工作中，HPLC-ESI-QqQ-MS/MS 被用作参考方法。随后，采用多元线性回归（MLR）和偏最小二乘回归（PLSR）分别建立了基于热重分析（TGA）和衰减全反射（ATR）红外光谱（IR）分析预测茄碱含量的两个校准模型。这两种快速技术被证明适合且有效地用于生物碱定量（分别为 R = 0.998 和 0.840），与参考技术相比，误差较低（分别为 0.11%和 0.27%）。
