Tan Huizhen, Liu Yang, Tang Hui, Fan Wei, Jiang Liwen, Li Pao
Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region, Shaoguan University, Shaoguan 512005, China.
College of Food Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Foods. 2024 Nov 29;13(23):3856. doi: 10.3390/foods13233856.
Unscrupulous merchants sell the mold-damaged (CRP) after removing the mold. In this study, an accurate and non-destructive strategy was developed for the discrimination of mold-damaged CRPs using portable near-infrared (NIR) spectroscopy and chemometrics. The outer surface and inner surface spectra were obtained without destroying CRPs. The discrimination models were established using partial least squares-discriminant analysis (PLS-DA) and wavelength selection strategy was used to further improve the discrimination ability. The predictive ability of models was assessed using the test set and an independent test set obtained one month later. The results demonstrate that the models of the outer surface outperform those of the inner surface. With multiplicative scatter correction (MSC)-PLS-DA, 100% accuracies were obtained in test and independent test sets. Furthermore, the wavelength selection strategy simplified the models with 100% discrimination accuracy. In addition, the randomization test (RT)-PLS-DA model developed in this study combines both the benefits of high accuracy and robustness, which can be applied for the accurate discrimination of mold-damaged CRPs.
无良商家会在去除霉菌后出售发霉损坏的（CRP）。在本研究中，开发了一种准确且无损的策略，利用便携式近红外（NIR）光谱和化学计量学来鉴别发霉损坏的CRP。在不破坏CRP的情况下获取其外表面和内表面光谱。使用偏最小二乘判别分析（PLS-DA）建立判别模型，并采用波长选择策略进一步提高判别能力。使用测试集和一个月后获得的独立测试集评估模型的预测能力。结果表明，外表面模型优于内表面模型。通过多元散射校正（MSC）-PLS-DA，在测试集和独立测试集中均获得了100%的准确率。此外，波长选择策略简化了模型，判别准确率为100%。此外，本研究中开发的随机化测试（RT）-PLS-DA模型兼具高精度和稳健性的优点，可用于准确鉴别发霉损坏的CRP。
