Rapid NIR determination of alkyl esters in virgin olive oil

Abstract

SUMMARY:The regulation of The European Union for olive oil and olive pomace established the limit of 35 mg·kg -1 for fatty acids ethyl ester contents in extra virgin olive oils, from grinding seasons after 2016. In this work, predictive models have been established for measuring fatty acid ethyl and methyl esters and to measure the total fatty acid alkyl esters based on near infrared spectroscopy (NIRS), and used successfully for this purpose. The correlation coefficients from the external validation exercises carried out with these predictive models ranged from 0.84 to 0.91. Different classification tests using the same models for the thresholds 35 mg·kg -1 for fatty acid ethyl esters and 75 mg·kg -1 for fatty acid alkyl esters provided success percentages from 75.0% to 95.2%. KEYWORDS: Alkyl esters; Ethyl esters; NIRS; Olive oil; Quality; Sensory defectsRESUMEN: Determinación rápida de ésteres alquílicos en aceite de oliva virgen para detección temprana de defectos sensoriales. La reglamentación de la Unión Europea para el aceite de oliva y el orujo de oliva ha establecido el límite de 35 mg·kg -1 al contenido de ésteres etílicos de ácidos grasos en los aceites de oliva virgen extra, para campañas de molienda posteriores a 2016. En este trabajo se han establecido modelos predictivos para medir los ésteres etílicos y metílicos de ácidos grasos y para la medida de los ésteres alquílicos de ácidos grasos totales basados en la espectroscopía de infrarrojo cercano (NIRS) y utilizados con éxito para este propósito. Los coeficientes de correlación de los ejercicios de validación externa realizados con estos modelos predictivos oscilaron entre 0,84 y 0,91. Diferentes pruebas de clasificación utilizando los mismos modelos con respecto a los umbrales de 35 mg·kg -1 para ésteres etílicos y 75 mg·kg -1 para ésteres alquílicos, proporcionaron porcentajes de éxito del 75,0% al 95,2%.

Identification of multiple raisins by feature fusion combined with NIR spectroscopy

“…In addition, the absorption band of linoleic acid is 5952–6757 cm -1 [ 24 ], which is largely derived from fatty acids in flesh. Since the absorption band of monounsaturated fatty acids is 5662 cm -1 [ 25 ], this is also consistent with the flesh spectra at 5662 cm -1 . In addition, it was also found that light, drying temperature and soaking dry-promoting agent solution during the production process effects on the content of coutaric and fertaric acids, quercetin-3-O-glucoside and rutin in raisins, in existing research, the traditional method favors the formation of coumaric and ferric acids, quercetin-3-O-glucoside and rutin in raisins at 60 ℃ [ 26 – 28 ].…”

Importance of some minor compounds in olive oil authenticity and quality

“…Fourier transform infrared (FTIR) spectroscopy was used in quantification of FAAEs and ratio of ethyl and methyl esters value successfully (Valli et al, 2013). The same type of application was also performed with near infrared (NIR) spectroscopy (Cayuela, 2017;Garrido-Varo, Sánchez, De la Haba, Torres, & Pérez-Marín, 2017). In addition, FTIR and UV-visible spectroscopy separately and in combined form were applied to predict FAAE and FAEE content of olive oils .…”

Beer Aroma and Quality Traits Assessment Using Artificial Intelligence

“…Even though it has been reported that ethyl ester overtones can be found between 1700 and 2300 nm [36] and alcohols may be found at around 2000 nm [37], the ML model using NIR inputs was not as accurate to predict aromas, as phenylethyl alcohol, ethyl caproate, and ethyl decanoate presented most of the outliers in the overall model (Model 1). In contrast, although Model 3 had the same number of outliers, these were fitted better in the regression line, this may be due to the relationships found in the PCA between the foam-and bubble-related parameters and the aromas, and to the form of measurement, as RoboBEER is based on a visual and volatiles (sensors) assessment, which is closer to the GC-MS principle, while NIR is based on their spectrum.…”