Novel, Rapid Identification, and Quantification of Adulterants in Extra Virgin Olive Oil Using Near-Infrared Spectroscopy and Chemometrics

Lipids ◽  
2015 ◽  
Vol 50 (7) ◽  
pp. 705-718 ◽  
Author(s):  
Hormoz Azizian ◽  
Magdi M. Mossoba ◽  
Ali Reza Fardin-Kia ◽  
Pierluigi Delmonte ◽  
Sanjeewa R. Karunathilaka ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Rapid Identification ◽  
Identification And Quantification

Near infrared Spectroscopy for discrimination between Extra Virgin Olive Oil and Lampante Olive Oil.

2015 ◽  
Author(s):  
Irina Torres Rodríguez ◽  
Maria-Teresa Sánchez ◽  
Maria-José de la Haba ◽  
DOLORES CATALINA PÉREZ MARÍN ◽  
JOSÉ EMILIO GUERRERO GINEL ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil

scholarly journals Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1042
Author(s):  
Silvia Grassi ◽  
Olusola Samuel Jolayemi ◽  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Giacomo Squeo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Green Technology ◽  
Soluble Solids ◽  
Integrating Sphere ◽  
Total Phenolic ◽  
Handheld Device ◽  
Quality Design

Poorly emphasized aspects for a sustainable olive oil system are chemical analysis replacement and quality design of the final product. In this context, near infrared spectroscopy (NIRS) can play a pivotal role. Thus, this study aims at comparing performances of different NIRS systems for the prediction of moisture, oil content, soluble solids, total phenolic content, and antioxidant activity of intact olive drupes. The results obtained by a Fourier transform (FT)-NIR spectrometer, equipped with both an integrating sphere and a fiber optic probe, and a Vis/NIR handheld device are discussed. Almost all the partial least squares regression models were encouraging in predicting the quality parameters (0.64 < R2pred < 0.84), with small and comparable biases (p > 0.05). The pair-wise comparison between the standard deviations demonstrated that the FT-NIR models were always similar except for moisture (p < 0.05), whereas a slightly lower performance of the Vis/NIR models was assessed. Summarizing, while on-line or in-line applications of the FT-NIR optical probe should be promoted in oil mills in order to quickly classify the drupes for a better quality design of the olive oil, the portable and cheaper Vis/NIR device could be useful for preliminary quality evaluation of olive drupes directly in the field.

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