基于可见光谱结合神经网络算法快速鉴别特级初榨橄榄油  

Application of Generalized Regression Neural Network With Ultraviolet-Visible Spectrometry Methods for Detection of Extra Virgin Olive Oil

作　　者：袁媛[1] 张晋[2] YUAN Yuan;ZHANG Jin(Department of Engineering Management,Sichuan College of Architectural Technology,Deyang 618000,China;College of Information Science and Engineering,Shanxi Agricultural University,Taigu 030801,China)

机构地区：[1]四川建筑职业技术学院,四川德阳618000 [2]山西农业大学信息科学与工程学院,山西太谷030801

出　　处：《光谱学与光谱分析》2024年第10期2973-2980,共8页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(61972268)资助。

摘　　要：随着中国经济的不断繁荣,人民对物质生活水平提出了更高的要求,预防疾病、改善身体功能的食品成为当前消费市场的“热点”。油脂能提供人体所必需的能量,食用油是人类获取油脂的主要途径之一,而高品质植物油含有对人体健康更有益的物质,例如单不饱和脂肪酸、多酚、角鲨烯、维生素E等营养物质。由于采用物理冷榨工艺,特级初榨橄榄油几乎保留了其橄榄果中所有的营养物质,油酸含量高达70%。因此,虽然作为一种“舶来品”,特级初榨橄榄油进入中国市场后一直是植物油市场中的“宠儿”,其价格也明显高于市场上的普通植物油。在利益的驱动下,特级初榨橄榄油的制假贩假现象屡禁不止,制假贩假的手段也不断更新迭代,从而造成国内橄榄油市场假冒伪劣产品屡禁不止,掺假的油品不仅会对消费者的生命财产造成伤害,而且也会影响合法经营者的生产和销售,扰乱销售市场,破坏市场秩序,影响民众对特级初榨橄榄油的认可度。为实现特级初榨橄榄油掺伪量的快速、准确、低成本地检测,提出一种基于广义回归神经网络结合紫外可见光谱实现植物油定性定量分析方法。广义回归神经网络在学习速度和非线性映射能力上表现出色,且扩散因子是其网络的唯一优化参数,不需要反向传播和反复迭代。与其他检测技术相比,紫外可见光谱技术在检测周期、稳定性、低维护成本等方面具有压倒性优势。通过两种方法的联用在植物油定性鉴别中实现了100%的判别,在特级初榨橄榄油掺伪定量检测中实现了判定系数R2优于0.98875,均方根误差RMSE优于0.03833的结果。研究结果表明,该模型在植物油种类鉴别及特级初榨橄榄油掺伪定量检测中表现出优秀的预测能力。With the continuous prosperity of China's economy,people have put forward higher requirements for material living standards.Food that prevents diseases and improves physical function has become a“hot spot”in the consumer market.Oil can provide energy for the human body.Edible oil is one of the major ways for human beings to get oil,and high-quality vegetable oil contains substances that are more beneficial to human health,such as monounsaturated fatty acids,polyphenols,squalene,vitamin E,and other nutrients.Because of the physical cold pressing process,extra virgin olive oil keeps almost all the nutrients in its olive fruit,and the oleic acid content is as high as 70%.Therefore,although an“imported product”,extra virgin olive oil has been a“favorite”in the vegetable oil market since it entered the Chinese market,and its price is also significantly higher than ordinary vegetable oil on the market.Driven by interests,the phenomenon of making and selling fake super virgin olive oil has been repeatedly banned,and the means of making and selling fake olive oil have been constantly updated and iterated,resulting in the repeated prohibition of fake and inferior products in the domestic olive oil market.Adulterated oil products will not only harm the lives and property of consumers but also affect the production and sales of legitimate operators,disrupt the sales market,destroy the market order,and affect the public's recognition of super virgin olive oil.The adulteration of vegetable oil is one of the urgent problems facing food safety at present.To realize the rapid,accurate,and low-cost identification and detection of the adulteration of vegetable oil and extra virgin olive oil,a method for qualitative and quantitative analysis of vegetable oil based on a generalized regression neural network and UV-Vis spectrum is proposed.Because the generalized regression neural network performs well in learning speed and nonlinear mapping ability,and the diffusion factor is the only optimization parameter of the networ

关 键 词：定性定量 植物油 特级初榨橄榄油 紫外可见光谱 广义回归神经网络 

分 类 号：TS225.1[轻工技术与工程—粮食、油脂及植物蛋白工程]