National Institute for Research and Development of Isotopic and Molecular Technologies, Donat, 67-103, 400293 Cluj-Napoca, Romania.
National Institute for Research and Development of Isotopic and Molecular Technologies, Donat, 67-103, 400293 Cluj-Napoca, Romania.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 May 15;293:122433. doi: 10.1016/j.saa.2023.122433. Epub 2023 Feb 3.
The development of new approaches for honey recognition, based on spectroscopic techniques, presents a huge market potential especially because of the fast development of portable equipment. As an emerging approach, the association between Raman spectroscopy and Artificial Intelligence (i.e. Machine Learning algorithms) for food and beverages recognition starts to prove its efficiency, becoming an important candidate for the development of a practical application. Through this study, new recognition models for the rapid and efficient botanical differentiation of investigated honey varieties were developed, allowing the correct prediction of each type in a percentage better than 81%. The performances of the constructed models were expressed in terms of precision, sensitivity, and specificity. Moreover, through this approach, the detection of honey mixtures was possible to be made and an estimative percentage of the mixture components was obtained. Thus, the applicative potential of this new approach for honey recognition as well as a qualitative and quantitative estimation of the honey mixture was demonstrated.
基于光谱技术的新型蜂蜜识别方法的发展具有巨大的市场潜力，尤其是因为便携式设备的快速发展。作为一种新兴方法，拉曼光谱与人工智能（即机器学习算法）在食品和饮料识别方面的结合开始证明其效率，成为开发实际应用的重要候选方法。通过这项研究，开发了新的识别模型，用于快速高效地对所研究的蜂蜜品种进行植物学区分，使得对每种类型的正确预测百分比超过 81%。所构建模型的性能通过精度、灵敏度和特异性来表示。此外，通过这种方法，可以检测蜂蜜混合物，并获得混合物成分的估计百分比。因此，该新型蜂蜜识别方法的应用潜力以及对蜂蜜混合物的定性和定量估计得到了证明。
