Rapid detection of walnut and pumpkin oil adulteration using Raman spectroscopy and partial least square methodology

被引:12
作者
Becze, Anca [1 ]
Simedru, Dorina [1 ]
机构
[1] ICIA Cluj Napoca Subsidiary, Res Inst Analyt Instrumentat, INCDO INOE2000, Cluj Napoca 400293, Romania
关键词
adulteration; partial least square methodology; Raman; pumpkin oil; walnut oils; spectroscopy; rapid detection; FATTY-ACID-COMPOSITION; VIRGIN OLIVE OIL; INFRARED-SPECTROSCOPY; VEGETABLE-OIL; SEED OIL; DIFFERENTIATION; AUTHENTICATION; CHEMOMETRICS; PARAMETERS;
D O I
10.15835/nbha48312024
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
The purpose of this study is to develop a statistical method, based on Raman spectroscopy results, to quickly identify the adulteration of pumpkin and walnut oils. For this purpose, pure pumpkin and walnut oils from Cluj County, Romania were studied with Raman techniques. They were adulterated with sunflower oil at 14 levels of concentration, ranging from 2.5 to 50%. The areas under the significant peaks were quantified and compared. A statistical method using the partial least square methodology was developed and used as a prediction tool in order to establish the adulteration percentage for pumpkin and walnut oils. 4 components were used to model the equation, the peak areas from similar to 1264, similar to 1300, similar to 1441 and respectively similar to 1659 cm-1. The final model equations take into account only the peak areas that had a high impact on the prediction values, statistically proven using the p-value. The level of prediction obtained with the final model equation was A 95%.
引用
收藏
页码:1426 / 1438
页数:13
相关论文
共 42 条
[41]   The effects of pumpkin seed oil supplementation on arterial hemodynamics, stiffness and cardiac autonomic function in postmenopausal women [J].
Wong, Alexei ;
Viola, Danielle ;
Bergen, Douglas ;
Caulfield, Eileen ;
Mehrabani, Javad ;
Figueroa, Arturo .
COMPLEMENTARY THERAPIES IN CLINICAL PRACTICE, 2019, 37 :23-26
[42]   Detection of flaxseed oil multiple adulteration by near-infrared spectroscopy and nonlinear one class partial least squares discriminant analysis [J].
Yuan, Zhe ;
Zhang, Liangxiao ;
Wang, Du ;
Jiang, Jun ;
Harrington, Peter de B. ;
Mao, Jin ;
Zhang, Qi ;
Li, Peiwu .
LWT-FOOD SCIENCE AND TECHNOLOGY, 2020, 125