domain: sdv sde

text:
Eliot Patrick Botosoa

Romdhane Karoui
email: romdhane.karoui@univ-artois.fr

3D Front Face fluorescence Spectroscopy as a tool for monitoring the oxidation level of edible vegetable oil during storage at 60 °C

Keywords: Vegetable oil, Thermo-oxidation, Fluorescence spectroscopy, excitation-emission matrix, PARAFAC. -

Fluorescence landscapes with excitation wavelengths varying between 280 and 400 nm, and emission wavelengths in the range of 300 -650 nm were scanned directly on oil samples throughout storage in capped and uncapped flasks for 15 days at 60 °C. PARAFAC analysis of the fluorescence landscapes showed the presence of three fluorophores in the edible oils, which are strongly dependent on the storage conditions. The fluorescence spectra were resolved into excitation and emission profiles of the pure fluorescent compounds, which are ascribed to be oxidation products and vitamin E. The complexity of edible oil data sets was suitable for PARAFAC modeling. Problems with scattering were encountered, the use of missing values was tackled before obtaining a validated model with a criterion of similarity measurements of splits reaching the 83.8 % and this allowed us to start getting through the model of interpretation.

Introduction

World trends in oil crop production, yield, and growing area over the last 30 years exhibited an increase of 240 %, 82 %, and 48 %, respectively (El-Hamidi & Zaher, 2018).

Consequently, the food industry will be faced with challenges to set up reliable and robust methods in the evaluation of edible oils quality during the process and/or storage. Several chemical reactions contribute to the chemical, physical and sensorial aging of edible oils.

During heating, edible oils undergo degradation and their functional and organoleptic features are significantly modified. The heating induces chemical reactions such as oxidation, polymerization, hydrolysis and cis/trans isomerization, which have a huge impact not only on the nutritional value of oils but may also generate toxic compounds damaging to health [START_REF] Schaich | Challenges in elucidating lipid oxidation mechanisms -When, where and how do products arise?[END_REF]. Oxidation stability is considered one of the most important quality indicators of edible vegetable oils. It determines their usefulness in technological processes as well as shelf life. Several methods enable to determine the oxidative stability of oils. The most reliable one is the aging test at ambient temperature that requires a long time (several months). Therefore, methods that allow the determination of oil stability in the shortest possible time are valuable such as Schaal oven test, swift test or AOM (Active Oxygen Method), Rancimat test, Oxidograph, Oxipress, and Rapidoxy. The Schaal oven test is one of the most frequently used accelerated shelf life of edible oils. This accelerated oxidation test consists of storing oil samples at a constant and controlled temperature at ~ 60 °C [START_REF] Warner | Flavor and oxidative stability of soybean, sunflower and low erucic acid[END_REF]. The increase in temperature acts as a gesture and allows oxidation reactions, as well as measuring their evolution, both organoleptically (color, smell, taste) and by chemical analyses. The Schaal oven test has some advantages such as its simplicity and its standardization among the methods referenced in the AOCS database. The oxidation, thermal stability, chemical composition, and quality of edible oils under various conditions have been previously investigated by applying different techniques such as infrared and Raman spectroscopy [START_REF] Saleem | Raman spectroscopy-based characterization of canola oil[END_REF], 1D and 2D NMR [START_REF] Cordella | A multiway chemometric and kinetic study for evaluating the thermal stability of edible oils by 1 H NMR analysis: Comparison of methods[END_REF]Dugo et al., 2015), differential scanning calorimetry [START_REF] Qi | Differential scanning calorimetry study -Assessing the influence of composition of vegetable oils on oxidation[END_REF] and front face fluorescence spectroscopy (FFFS) [START_REF] Cordella | A multiway chemometric and kinetic study for evaluating the thermal stability of edible oils by 1 H NMR analysis: Comparison of methods[END_REF][START_REF] Ali | Phenolic profile and thermal stability of monovarietal extra virgin olive olive oils based on synchronous fluorescence spectroscopy[END_REF]. Despite of the current progress in the development of these analytical methods; sensory evaluation, chemical analyses (determination of free acidity, acid value, peroxide value, p-anisidine value, totox, thiobarbituric acid (TBA), iodine value) and chromatographic techniques remained the reference methods used in the different regulations such as AFNOR, ISO, and AOCS recommended practice, in edible oil quality control applied during process and storage. These methods are often time-consuming, and require qualified operators.

Moreover, chemical analyses and the use of liquid chromatography are incompatible with a reagent and/or organic solvent-free strategy. Indeed, these analyses are performed to get informations from the use of different markers for monitoring the edible oil oxidation state.

Each marker provides partial information of the whole phenomenon, but is unable to predict by itself the future stability of the edible oil [START_REF] Cuvelier | Stabilité des huiles alimentaires au cours de leur stockage[END_REF]. In real-world application, these limitations present some constraints from industrial point of view such as duration, cost and environmental impact of analyses that should be overcome. It would be economically and environmentally profitable and viable to find a promising alternative, which is more compatible with the current state of the art in tehnological development. Many food fluorophores can be used as marker for monitoring the quality of edible oil throughout storage (Sikorska, Khmelinskii, & Sikorski, 2019a). Thus the development of FFFS instruments, methods of data analysis, and availability of suitable software should promote wider usage of fluorescence in food research and real-world application.

Although FFFS is a method, which has been exploited extensively for monitoring food quality [START_REF] Hassoun | Monitoring changes in whiting (Merlangius merlangus) fillets stored under modified atmosphere packaging by front face fluorescence spectroscopy and instrumental techniques[END_REF][START_REF] Karoui | Front-face fluorescence spectroscopy as a rapid and nondestructive tool for differentiating various cereal products: A preliminary investigation[END_REF][START_REF] Karoui | Mid infrared and fluorescence spectroscopies coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems[END_REF]Karoui, Nicolaï, & de Baedemaeker, 2008;[START_REF] Ullah | Time-temperature dependent variations in beta-carotene contents in carrot using different spectrophotometric techniques[END_REF][START_REF] Ullah | Comparison among different postharvest ripening treatment based on carotene contents in mango using UV-Vis and Raman spectroscopy[END_REF], this non-destructive technique has not been fully explored in the determination of the quality of oil products and the comprehension of physico-chemical interactions of lipids with other component occurring within food matrices during storage. In line with this objective, FFFS was used, for instance, to monitor changes in sponge cakes during aging (Botosoa, Chèné, Karoui, 2013a, 2013b). The technique was, recently, presented among high-potential innovative technologies for food quality evaluation (Sikorska et al., 2019a). In addition to its higher sensitivity and selectivity, its multidimensional character, and its usefulness for studying minor and trace components in complex food matrices, FFFS is benefiting from recent technology development to improve its performance in reducing significantly acquisition time of EEM and monitoring specific fluorophores (NADH or tryptophan) and bioprocesses. Several achievements can be cited in that direction such as replacing photomultiplier tubes (PMT) detectors with charge-coupled device (CCD) ones, using compact portable devices with diode lasers or LEDs for food samples measurements, or more advanced sensor like the filter-based Bio View sensor, and usage of optical light guides (Sikorska et al., 2019a). FFFS provides several analytical informations in a non-destructive manner; in addition, sample treatment (extraction or digestion) is not required. This is in line with the view of green chemistry (Gredilla, Fdez-Ortiz de Vallejuelo, Elejoste, de Diego, & Madariaga, 2016). Moreover, the use of FFFS coupled with chemometric tools presented numerous advantages in terms of going in-depth in the comprehension of physico-chemical interactions between fluorescent molecules and their environment within food samples. Several studies have explored the use of FFFS coupled with multiway data analysis, such as PARAFAC. Concerning food research, PARAFAC was applied in investigating the relationship between sugar impurities and its quality at the molecular level [START_REF] Bro | Explorative study of sugar production using fluorescence spectroscopy and PARAFAC analysis[END_REF], screening method for dioxin contamination in fish oil [START_REF] Pedersen | Screening for dioxin contamination in fish oil by PARAFAC and N-PLSR analysis of fluorescence landscapes[END_REF], monitoring chemical changes in dry-cured Parma ham during maturation (Moller, Parolari, Gabba, Christensen, & Skibsted, 2003), and the stability of processed cheese, yogurt [START_REF] Christensen | Fluorescence spectroscopy and PARAFAC in the analysis of yogurt[END_REF], and edible oils during storage [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF][START_REF] Christensen | Multivariate autofluorescence of intact food systems[END_REF][START_REF] Sikorska | Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage[END_REF].

To the best of our knowledge, up to date; no research study was conducted to determine the oxidative stability of the following four selected vegetable edible oils together, namely rapeseed oil (RO), linseed oil (LO), sunflower oil (SO), and extra virgin olive oil (EVOO) by using 3D Fluorescence spectroscopy coupled with PARAFAC. Due to its importance in the human diet, olive oil (OO) was the most studied in understanding the chemical changes undergone after thermal oxidation [START_REF] Tena | Chemical changes of thermoxidized virgin olive oil determined by excitation-emission fluorescence spectroscopy (EEFS)[END_REF][START_REF] Saleem | Investigating temperature effects on extra virgin olive oil using fluorescence spectroscopy[END_REF]Domínguez Manzano, Muñoz de la Peña, & Durán Merás, 2019). Recently, [START_REF] Sikorska | Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage[END_REF] depicted, by applying PARAFAC to EEM, the presence of four fluorophores in cold-pressed rapeseed oil that showed different evolution during storage at ambient room temperatures (18 -25 °C) for 6 months.

The objective of the present study was to determine the impact of heating at 60 °C for 15 days on the quality of RO, LO, SO, and EVOO. Structural changes were monitored at the molecular level by applying 3D FFFS coupled with PARAFAC.

Material and methods

Oil sampling and oil thermo-oxidation procedure

A set of 4 edible oils was purchased from a local supermarket and a local producer (Arras, France). The sample collection included 1 sample of 1L of: i) RO; ii) SO; iii) EVOO, and iiii) unrefined and cold-pressed LO.

Oil samples (45 mL) were poured into flasks (VWR-France) of 26 mm in diameter, with the surface-to-volume ratio of 0.47 cm 2 / mL and placed into a convection oven (Air Concept, FIRLABO, Emerainville, France), heated and maintained at 60 °C during experimentation, except the sample aged 0 day (fresh oil). No mechanical stirring was applied during the heating period and the flasks were covered with aluminum foil to avoid photo-oxidation. The dishes were introduced into the oven "with" and "without" lids to compare the impact of the presence of air in the headspace of flasks. The samples were analyzed at 0, 3, 6, 9, 13, and 15 day(s). One flask of each oil was taken out of the oven and used for 3D fluorescence spectroscopy analysis.

Fluorescence measurements

Fluorescence spectra were recorded using a Fluoromax-4 spectrofluorimeter (Jobin Yvon, Horiba, NJ, USA). The spectrofluorimeter was equipped with xenon lamp source used to excite fluorescence, excitation and emission monochromators, a photomultiplier (PM) (range 200 -850 nm) used as emission detector to measure the intensity of fluorescence, a thermostated front-face sample-cell holder and the temperature was controlled by a Haake A25, AC 200 temperature controller (Thermo-Scientific, France). The incidence angle of the excitation radiation was set at 60° to ensure that reflected light, scattered radiation and depolarization phenomena were minimized. The sample is illuminated by the photons of excitation (light beam: ~ 3 mm in height and ~ 0.3 mm width) in its center during 2-3 minutes. The PM responds to individual photons, and the pulses can be detected as an average signal or counted as individual photons. The PM is useful for low-level light detection due to its capacity to amplify low-noise and its sensitivity depends on the incident wavelength.

Fluorescence intensity is a simultaneous function of the excitation and emission wavelengths.

The intensity values of a fluorescence emission spectrum are determined by keeping the excitation wavelength (λex) constant while the emission wavelengths (λem) are scanned.

Similarly, the intensity values of a fluorescence excitation spectrum are determined by remaining the λem constant, while the λex are scanned. When measuring several emission spectra at different λex (or vice versa), a three-dimensional fluorescence landscape, the socalled fluorescence excitation-emission matrix (EEM), is obtained. The spectra of oil samples were scanned at ambient temperature in a 10 x 10 mm quartz cuvette for a volume of 3 mL.

Raw non-smoothed data were recorded. For every oil samples, an EEM was obtained by measuring the emission spectra from 300 to 650 nm at 1 nm intervals with excitation at every 1 nm from 280 to 400 nm. The measurements started with the highest excitation wavelength and ended with the lowest to minimize the photodecomposition of the oil samples. The three main components of the spectrofluorimeter (lamp, monochromators and PM) are wavelengthdependent, therefore, they cause distorsions in the fluorescence spectra. All spectra were corrected for instrumental distortions in excitation using a rhodamine cell in the reference channel. For correcting the excitation spectra, the output R of the PM is directly proportional to the flux of photons emitted by the excited sample. This relationship can be written as R ∝ I0εφf, where I0 is the excitation intensity, ε is the molar absorptivity, and φf is the quantum yield of fluorescence efficiency of the selected fluorophor (i.e. the ratio between the number of photons emitted and the number of photons used to excite the system). However, the quantum efficiency of the detector, the bandwidth of the monochromator, and the transmission efficiency of the monochromator must be taken into account for determining the true emission spectrum. Based on these elements, the dependence of the uncorrected emission spectrum can be expressed as follows

dF dλ = dI dλ       P λ B λ M λ = dI dλ       S λ
where dF / dλ is the apparent or observed intensity of fluorescence emission at wavelength λ ; dI / dλ is the true intensity at λ; Pλ, Bλ, and Mλ represent the relative quantum efficiency of the PM, the relative bandwidth of the monochromator, and the fraction of light transmitted by the monochromator, respectively, at λ. These last three factors were combined into a single factor in Sλ, which is called spectral sensitivity factor of the monochromator-PM combination. The true emission spectrum dI / dλ can be determined from the apparent emission spectrum by dividing each ordinate dF / dλ by the corresponding value of Sλ.

Mathematical analyses of data tables

The fluorescence data of oils can be presented in an I x J x K three-way data array, which will be trilinear. The first index (I) refers to the samples, the second (J) to the emission wavelengths and the third (K) to the excitation wavelengths. In order to model these data, PARAFAC was used.

The PARAFAC model can be put in the equation as follow:

x ijk = a if f =1 F ∑ b jf c kf -e ijk i = 1,…,I; j = 1,…,J; k = 1,…,K
where xijk is the intensity of the ith sample at the jth variable (emission mode) and at the kth variable (excitation mode) aif, bjf and ckf are parameters describing the importance of the sample / variables to each component and the residuals, eijk, contain the variation not captured by the model [START_REF] Andersen | Practical aspects of PARAFAC modeling of fluorescence excitation-emission data[END_REF].

The PARAFAC components estimate the signals from the individual fluorophores if the data are approximately low-rank trilinear and when the correct number of components is used. In that case, the scores in aif may be interpreted as the relative concentration of analyte f in sample i. The j-vector bf with elements bjf (j = 1, …, J) is the estimated emission spectrum of this analyte and likewise cf is the estimated excitation spectrum. However, some mathematical conditions must be fulfilled to allow the decomposition to be unique and to provide meaningful estimates [START_REF] Andersen | Practical aspects of PARAFAC modeling of fluorescence excitation-emission data[END_REF], namely:

-the uniqueness of the decomposition depending on the linearly independence of the spectra and concentration profiles;

-the assumption of the validity of the additivity and linearity of the signal.

The disturbance of the trilinearity of the data can be caused by the inner-filter effects, which may come from high concentrations, scattering and quenching. Furthermore, uncertain estimates can be created because of the abundance of missing data and spectral similarities.

Consequently, chemical interpretation should be done with care. Moreover, PARAFAC model can be validated using fit values, visual assessment of the loadings, residual analysis, core consistency diagnostic, jack-knifing and especially by a split-half analysis.

All analyses of the data in this work were performed with PLS Toolbox 7.9 and 8.0 (Eigenvector Research Inc., Wenatchee, WA, USA) and Matlab version R 2013b (The MathWorks, Natick, MA, USA).

Results and discussion

Analysis of edible vegetable oils fluorescence landscapes

Fig. 1a presents the EEM spectra in the form of a contour map of fresh EVOO as an example.

The for the fresh edible oil samples are seen with 342 < λex < 400 nm and 403 < λem < 518 nm for RO, 338 < λex < 386 nm and 408 < λem < 484 nm for SO, 343 < λex < 360 nm and 514 < λem < 531 nm for EVOO, and 340 < λex < 356 nm and 519 < λem < 542 nm for LO; whereas the highest fluorescence peaks for the uncapped edible oil samples are observed with λex = 349 nm and λem = 442 nm for RO, 344 < λex < 387 nm and 414 < λem < 481 nm for SO, 345 < λex < 372 nm and 512 < λem < 531 nm for EVOO, and 340 < λex < 356 nm and 519 < λem < 542 nm for LO.

The excitation and emission characteristics indicate that the fluorescence peaks arise from oxidation products, polyphenols, and tocopherols, which are expected to be present in edible vegetable oils. Indeed, the peak observed in the region λex = 300 -400 nm and λem = 400 -500 nm (Figs 1b, c, d ande) was attributed to the oxidation products contained in vegetable oils [START_REF] Tena | Chemical changes of thermoxidized virgin olive oil determined by excitation-emission fluorescence spectroscopy (EEFS)[END_REF]. Some previous works reported that polyphenols can present peaks in the region of λex = 260 -310 nm and λem = 310 -370 nm [START_REF] Zandomeneghi | Fluorescence of vegetable oils: olive oils[END_REF][START_REF] Ali | Phenolic profile and thermal stability of monovarietal extra virgin olive olive oils based on synchronous fluorescence spectroscopy[END_REF]. Moreover, the same peak may correspond to the tocopherols. But this attribution was considered to be erroneous according to [START_REF] Christensen | Multivariate autofluorescence of intact food systems[END_REF]. Actually, this component does not agree with the fluorescence characteristics of tocopherol found in the literature (Duggan, Bowman, Brodie, & Udenfriend, 1957). Recently, it has been reported that the emission of some fluorescent components at 525 nm was not fully resolved and this fluorescent compound corresponds to the more than one chemical compound present in vegetable oil [START_REF] Sikorska | Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage[END_REF].

Application of PARAFAC on excitation-emission matrix obtained from edible vegetable oils during oil aging at 60 °C

As shown in Fig. S1a and1b, the presence of the massive band of peaks (in the dashed circle) in the place of the first Rayleigh scatter is the result of masking the 1 st and 2 nd Rayleigh scatter options available on the Fluoromax-4 spectrofluorimeter. For the edible oil data set, non-trilinear parts were removed by using EEM filter (Fig. S2a and2b) or flucut function.

An attempt was performed by removing the top part of the 3D spectra which is > 9.2*1e 6

CPS) and replacing it with NaN but no reliable model was obtained.

To resolve the profile of fluorophores in edible oils during storage, PARAFAC was applied to the raw EEM to fit the array. Two, three, four, five components models were performed. The explained variance for each number of components is given in Table 1. The relative change in explained variances increases from 1 to 5 components model. Although the 4 and 5 components models exhibited the highest percentage of explained variance, only the 3 components model obtained the highest scores of similarity measure of splits (83.8 %) and the highest number of components. Therefore, the split-half analysis and investigation of residuals suggested that the evolution of edible vegetable oils EEM fluorescence spectra during their storage were best-fitted by a three-component model (Table 1). This model exhibited the optimal value of the number of components, explained variance and similarity measure of splits. [START_REF] Sikorska | Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage[END_REF] reported an optimal PARAFAC model with four components (explained variance 99.1 %, core consistency value 70) during investigating the EEMs of different RO samples during storage. The authors used core consistency and a visual inspection of both the residuals and the loadings to validate their model.

Fig. 2 provides the split-half model estimates for all three components in the emission and excitation modes, respectively. It is noticeable that the spectra were very similar to each other and had the same peak positions, from which it can be concluded that the three-component PARAFAC model is appropriate for edible oil samples studied in the present case. measured edible oil samples. The estimated excitation spectra presented maxima at 395 nm (component 1), 344 nm (component 2) and 355 nm (component 3) (Fig. 3b). This trend corresponds to the peaks in the raw fluorescence landscapes (Fig. S1). While their corresponding estimated emission spectra exhibit their maxima at 487 nm, 420 nm and 528 nm, respectively (Fig. 3a).

The pair of excitation/emission wavelength (395/487 nm) corresponds to the maximum fluorescent intensity of the first component. According to previous findings, these spectra are similar to those of oxidation products [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF]. An intensive band in the range 450 -650 nm was attributed to the oxidation products while studying chemical changes of thermo-oxidized virgin olive oil [START_REF] Tena | Evaluation of virgin olive oil thermal deterioration by fluorescence spectroscopy[END_REF][START_REF] Tena | Chemical changes of thermoxidized virgin olive oil determined by excitation-emission fluorescence spectroscopy (EEFS)[END_REF]. Based on these findings, the first component can be assigned to secondary oxidation products such as ketones, aldehydes and other carbonyl compounds in agreement with the findings of [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF].

The second pair of excitation/emission wavelength (344/420 nm) corresponds to the maximum fluorescent intensity of the second component. Rodriguez Delgado, Malovana, Perez, Borges, & Garcia Montelongo ( 2001) reported that phenolic compounds show maximum excitation between 265 and 335 nm, and maximum emission in the 358 -426 nm range. Although the maximum emission (420 nm) of this excitation/emission wavelength is comprised between 358 and 426 nm, its maximum excitation (344 nm) is not included between 265 and 335 nm. Again, according to [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF], oils at early degradation stages exhibit strong fluorescence between λex = 315 -370 nm; λem = 415 -460 nm.

Moreover, this component, which was ascribed to compounds formed during cold-pressed rapeseed oil oxidation, appeared at 320/420 nm in excitation/emission [START_REF] Sikorska | Front-face fluorescence spectroscopy and chemometrics for quality control of cold-pressed rapeseed oil during storage[END_REF]. In accordance with those findings, the second component could be hypothesized to correspond to primary oxidation compounds, such as conjugated hydroperoxides [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF], present in edible oil samples.

The third pair of excitation/emission (355/528 nm) corresponds to the maximum fluorescent intensity of the third component. Despite several identification attempts, the assignment of this component to its real chemical structure remained uncertain. Moreover, the spectral ranges of excitation between 300 and 400 nm and emission between 400 and 695 included chlorophylls, which peak is used to be much more intense than those of other components (Guimet, Ferré, Boqué, & Rius, 2004;[START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF]. However, the peak is usually detected at 695 nm [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF], but has already been detected at 681 nm [START_REF] Kyriakidis | Fluorescence spectra measurement of olive oil and other vegetable oils[END_REF], and even at 668 nm [START_REF] Christensen | Multivariate autofluorescence of intact food systems[END_REF]Sikorskaet al., 2019a). These wavelengths are outside of the range of emission wavelength fixed in the present study to such an extent that this hypothesis can be excluded. As it was previously reported, the peak at λem = 525 nm was also attributed to vitamin E from EVOO (Guimet et al., 2004). This hypothesis was confirmed by the same authors who observed an increase in the fluorescent intensity at 525 nm after the addition of vitamin E to EVOO. Previously, the same experiment has already been performed to attempt the same peak identification [START_REF] Kyriakidis | Fluorescence spectra measurement of olive oil and other vegetable oils[END_REF]. However, [START_REF] Christensen | Fluorescence spectroscopy and PARAFAC in the analysis of yogurt[END_REF] reported that this component was erroneously assigned to tocopherol based on the results obtained by [START_REF] Kyriakidis | Fluorescence spectra measurement of olive oil and other vegetable oils[END_REF].

Recently, the pair of excitation/emission corresponding to 360/530 nm was considered as one of the components detected in studying the evolution of fluorescence of cold-pressed rapeseed oil during storage (Sikorska et al., 2019a). The authors found the origin of this component less obvious as well. The loading of its emission profile presented a similarity with the present profile which exhibits additional broad emission with low-intensity on the short-wavelength side. This was explained by the fact that the emission of some fluorescent components was not fully resolved, and therefore this component corresponded to more than one chemical.

The score of the model are estimates of the relative concentration of the three fluorophores in every edible oil samples identified by the loadings and are therefore measures of the amount of the fluorophores as shown in Fig. 4. Oil samples were grouped according to their botanical origins for easier interpretation. For every botanical group, the concentrations of the three components can be calculated. For example, it can be observed that the concentrations of the first and second components, corresponding hypothetically to primary and secondary oxidation products showed the following tendency RO > SO > EVOO > LO. Indeed, refined oils, namely RO and SO, exhibited the highest score of relative concentrations of both oxidation products compared with unrefined ones (EVOO and LO). This implies that the evolution of these oxidation compounds throughout the 15 days of storage depends on the previous refining step undergone by the edible oils. This profile is, to our best knowledge the first time, obtained with PARAFAC model. It is well known that refined oils are more reliable to undergo oxidation processes when compared with unrefined oils (Guimet et al., 2004). The main reason would be due to the refining process, which may decrease the natural antioxidants (phenolic compounds, tocopherols and beta-carotene) contained in edible vegetable oils.

Regarding the third component, the tendency showed the following order LO > EVOO > RO > SO during the 15 days of storage. Unrefined oils are supposed to contain less natural antioxidant compounds (vitamin E) since the refining process drastically decreased its content. This tendency may be explained by the difference between vitamin E and/or its derivative contents in both categories of edible oils. Regarding the profile of tocopherol, the order is in agreement with the contents of (β + γ) tocopherols in the investigated oils which values are approximatively 363 mg/kg, 281 mg/kg, and 25.2 mg/kg for cold-pressed LO, refined RO, and refined SO, respectively (Gliszczyńska-Świgło, Sikorska, Khmelinskii, & Sikorski, 2007). The value for EVOO (12.3 mg/Kg) is normally the lowest between the four edible oils studied; however, the presence of the important peak corresponding to chlorophyll close to 525 nm may interfere and could present an impact in the increase of fluorescence intensity of EVOO at this wavelength. In fact, only EEM of EVOO presented an increase of fluorescence intensity between 625 and 650 nm that should correspond to the beginning or the tail of the chlorophyll's peak. [START_REF] Guimet | Excitation-emission fluorescence spectroscopy combined with three-way methods of analysis as a complementary technique for olive oil characterization[END_REF] has already reported that, in EVOOs, the chlorophyll peak was much more intense than those of the other fluorescent molecules and can influence strongly the fluorescence intensity of the peak at 525 nm. Consequently, the different magnitude of this peak may cause problems when handling the data and, for this reason, the fluorescent region of chlorophylls has been often removed.

The contributions of each of the three PARAFAC components were shown in Fig. 5 (a-l).

The score values obtained in the PARAFAC decomposition were plotted against the storage time to explore the impact of thermo-oxidation throughout the storage period. The systematic variations of the score values, corresponding to the respective components were observed except for component 1 for LO and component 3 for SO. Regarding the evolution of oxidation products, RO showed a decrease of primary products during storage (Fig. 5a) while the secondary products showed the highest score at 9 days of storage for capped samples and decreased until the 13 th day for uncapped ones (Fig. 5b). For EVOO samples (Fig. 5c-d), the primary oxidation products reached the highest score on day 9 for capped samples and only on day 6 for uncapped ones, while the secondary products exhibited a progressive increase during 15 days of storage. For LO samples (Fig. 5e-f), the primary oxidation products progressed in a less systematic way for capped and uncapped samples; however, no compounds were detected before 13 days for both storage conditions. It is probably due to the fact that LO samples were the freshest among the four studied oils. For SO, Fig. 5g shows a slight decrease of component 2 during storage but the highest score of component 1 was reached at 3 days for capped and uncapped samples (Fig. 5h).

Regarding vitamin E (tocopherols), Fig. 5i-j showed a systematic and slight decrease for RO and EVOO during storage, while the level of vitamin E in LO samples remained stable throughout storage (Fig. 5k). The most spectacular diminution was observed with SO reaching the lowest score after 9 days of storage (Fig. 5l). It can be attributed to the fact that SO was a refined oil and contained the lowest value of tocopherols it seems that these tocopherols were more thermosensitive.

Conclusion

List of Tables:

  fluorescence landscapes of four edible vegetable oils namely RO, SO, EVOO and LO are shown in Figs. 1(b and c) for capped samples and in Figs. 1(d and e) for uncapped ones, during 15 days of storage. For the reason of clarity, the present analysis is focused only on the eight samples that represent the extreme in the experimental plan, i.e. four fresh edible oil samples (RO0, SO0, EVOO0, and LO0) and four uncapped edible oil samples (RO-L15, SO-L15, EVOO-L15, and LO-L15) stored for 15 days at 60 °C. The highest fluorescence peaks

Fig. 3

 3 Fig.3shows the emission (a) and excitation (b) spectra of three components present in edible

Fig. 1 Fig. 2 Fig. 4 Fig. 5

 1245 Fig. 1 Excitation-emission matrix contour plots of rapeseed oil (RO), sunflower oil (SO),

  Figure 1a:

  Figure 1d:

Table 1 :

 1 Explained variance as a percentage versus the number of components for PARAFAC

	models of the fluorescence data with 1-5 components
	PLS Toolbox		Number of components
		1	2	3	4	5
	Explained variance (%)	95.4	97.5	99.3	99.5	99.317
	Similarity measure of splits (%)	98.7	40.9	83.8	59.5	0.1

Acknowledgements

This work has been carried out in the framework of Alibiotech project, which is financed by the European Union, the French State and the French Region of Hauts-de-France. The authors gratefully acknowledge the financial support from the Major Domain of Interest (DIM) "Eco-Energy Efficiency" of Artois University.

This study aimed to investigate the potential of fluorescence spectroscopy coupled with PARAFAC for monitoring the thermo-oxidation at 60 °C, in the frame of the Schaal oven test, undergone by RO, SO, EVOO and LO samples during 15 days. The PARAFAC applied to fluorescence excitation-emission matrix scanned on RO, SO, EVOO, and LO samples separated three fluorophores components, which had different progression dynamics throughout storage. The results revealed, for the first time, the complexity of interpretation when PARAFAC is applied on EEM obtained from four oil fluorescence data sets. Indeed, the application of PARAFAC as multiway analysis method allowed to: (i) comprehend the evolution of primary and secondary oxidation products during storage; (ii) monitor the thermo-oxidation effect on the evolution of vitamin E depending on the refining process during their aging time; and iii) study a large number of edible oils including LO, with different profiles of mono-unsaturated and poly-unsaturated fatty acids, tocopherols, and chlorophylls.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.