Second-derivative laser-induced fluorescence spectroscopy combined with chemometrics for authentication of the adulteration of camellia oil

Abstract

In this study, second-derivative laser-induced fluorescence spectroscopy (SD-LIF) and its derivative intrinsic-ratiometric laser-induced fluorescence spectroscopy (IR-LIF) were developed for the qualitative and quantitative analysis of camellia oil adulterated with sunflower oil or rapeseed oil, respectively. In the qualitative analysis, three pure oils and two blended oils were successfully discriminated based on SD-LIF and linear discriminant analysis. The influence of fluorescence concentration quenching on the adulterant concentration analysis was discussed. IR-LIF was established by using 646 nm chlorophyll b fluorescence as the insensitive reference and proved to be an effective approach to reduce the possible quenching influence on the full spectrum. Then, the combination of IR-LIF and partial least squares regression was employed to determine the adulterant concentration, and the results were satisfactory. The plots of the observed versus predicted adulteration concentration values showed high linearity. Root-mean-square errors of prediction lower than 3% were achieved. Espectroscopía de fluorescencia de segunda derivada inducida por láser combinada con quimiometría para la autenticación de la adulteración de aceite de camelia RESUMEN En el presente estudio se desarrollaron la espectroscopia de fluorescencia de segunda derivada inducida por láser (SD-LIF) y su derivada, la espectroscopia de fluorescencia intrínseca-ratiométrica inducida por láser (IR-LIF), para el análisis cualitativo y cuantitativo de aceite de camelia (CO) adulterado con aceite de girasol (SO) y con aceite de canola (RO), respectivamente. En el análisis cualitativo, se discriminaron con éxito tres aceites puros y dos aceites mezclados a partir de la SD-LIF y el análisis discriminante lineal (LDA). En este sentido, se analizó la influencia que tiene la desactivación de concentración de fluorescencia en el análisis de concentración del adulterante. Mediante el uso de 646 nm de fluorescencia de clorofila b como referencia insensible se estableció la IR-LIF, comprobándose que representa una opción efectiva para reducir la posible influencia de la desactivación en todo el espectro. Luego se utilizó la combinación de la IR-LIF y la regresión de mínimos cuadrados parciales (PLSR) para determinar la concentración del adulterante, obteniéndose resultados satisfactorios. Los diagramas de los valores de la concentración de adulteración observados versus los valores pronosticados muestran una alta linealidad. Se logró obtener raíces cuadradas de errores cuadráticos medios de predicción (RMSEP) inferiores a 3%.

Toward commercial applications of LED and laser‐induced fluorescence techniques for food identity, quality, and safety monitoring: A review

“…Edible oils contain various fluorophores, including oxidation products, polyphenols, vitamin E, and chlorophyll (Botosoa & Karoui, 2022; Xu et al., 2016). Therefore, LIF and LED/IF techniques with specific excitation wavelengths were extensively used for classification (Al Riza et al., 2019; Chen et al., 2022; Kongbonga et al., 2019; Mu et al., 2013a, 2013b; Zhu et al., 2015), adulteration detection(Chen et al., 2018; Hao et al., 2019; Mu et al., 2016; ;2021 Torreblanca‐Zanca et al., 2019a), aflatoxin B 1 (AFB 1 ) contamination detection (Chen et al., 2021; He et al., 2022), and comprehensive analysis including discrimination between EVOO and other vegetable oils as well as identification of storage and thermal effect on emission of oils (Hossain et al., 2020), as shown in Figure 2.…”

“…Laser sources in the 400−500 nm range are typically considered. Some studies have collected fluorescence using right‐angle geometry (Hao et al., 2019; Torreblanca‐Zanca et al., 2019), while others have used a 45° rotation of the cuvette to reduce backscattered (Chen et al., 2018; Mu et al., 2016). Qualitative adulteration evaluation has been carried out using SVM and artificial neural networks (ANN), and some studies have conducted quantitative analyses of the adulteration level using PLSR.…”

A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends

“…Due to the presence of various common fluorophores in edible oils, the FS spectra can be overlapped when analyzing oil blends [ 46 ]. Again, chemometric means are needed to extract and optimize the FS spectra to improve prediction performance [ 47 , 48 ].…”

Rapid authentication of the geographical origin of milk using portable near‐infrared spectrometer and fuzzy uncorrelated discriminant transformation

“…Recently, some researchers reported that chemical analysis techniques were widely applied to detect the composition and adulteration of food such as laser-induced fluorescence spectroscopy (LIFS; Chen, Geng, Chen, Lu, & Chen, 2018), gas chromatography-mass spectrometry (GC-MS; Lv, Huang, Aheto, Mu, & Tian, 2018), and hyperspectral imaging (HSI) technique (Huang, Zhao, Chen, & Zhang, 2013). Differential scanning calorimetry (DSC) coupled with machine-learning tools were used to detect adulteration of raw bovine milk (Farah et al, 2021).…”