Spectroscopic determination of the photodegradation of monovarietal extra virgin olive oils and their binary mixtures through intelligent systems

Torrecilla, José S.; Vidal, Sara; Aroca-Santos, Regina; Wang, Selina C.; Cancilla, John C.

doi:10.1016/j.talanta.2015.06.042

Cited by 13 publications

(6 citation statements)

References 26 publications

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“…In such cases, the discriminating factors are derived from the absorption spectra, but they are not directly related to the pigments concentration. An example is the method based on the calculation of chaotic parameters (Lyapunov exponent, autocorrelation coefficients and fractal dimensions), further treated to find correlations index [10,11,55] and the application of PCA on large sets of data, including UV-vis spectral ones, further treated with class-modelling methods [56].…”

Section: Methods Based On Vis Absorption For Pigments Identification mentioning

confidence: 99%

“…It is well known that chlorophylls completely degrade into pheophytins after few months after the bottling and that the pheophytins themselves evolve into pyropheophytins depending on storage conditions. However, as reported in several works [5,[51][52][53][54][55][56][57][58][59][60], typical range of concentrations of various pigments can be associated with EVOOs and these quantities can be used to discriminate them from non-EVOOs. Most of the applications of the chromatographic methods refer to Spanish EVOOs [56][57][58], while the recently developed UV-vis based mathematical approach [5] has been mainly applied to Italian [5,51,52,54] and Spanish EVOOs [5,53] as well as Greek and Tunisian EVOOs [53,54].…”

Section: Authenticity and Quality Studies Based On Pigments Quantificmentioning

confidence: 99%

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Pigments in Extra‐Virgin Olive Oil: Authenticity and Quality

Lazzerini¹,

Cifelli²,

Domenici³

2016

Products From Olive Tree

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Pigments, divided into carotenoids and chlorophyll derivatives, are responsible for the colour of extra-virgin olive oil (EVOO). The concentration of pigments in EVOO depends on several factors, such as the maturity of olives before oil production, the cultivar and the geographic origin of olives. Pigments naturally degrade in olive oil (OO) during storage, and they may decompose due to light, temperature and oxygen exposure. The nature and concentration of pigments in EVOOs are different from seed oils, and this is a base of their use to reveal oil treatments and sophistication. In this chapter, the analytical methods, mainly chromatographic and spectroscopic, applied to identify and quantify pigments are overviewed. In particular, the applications of these methods to check the authenticity and the quality of extra-virgin olive oil are discussed.

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Section: Methods Based On Vis Absorption For Pigments Identification mentioning

confidence: 99%

Section: Authenticity and Quality Studies Based On Pigments Quantificmentioning

confidence: 99%

Pigments in Extra‐Virgin Olive Oil: Authenticity and Quality

Lazzerini¹,

Cifelli²,

Domenici³

2016

Products From Olive Tree

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“…As an alternative to methods based on wet chemistry, ultraviolet (UV)–visible spectroscopy has been preferred in measuring the amounts of absorbing species for food analysis due to its ease of use and nondestructive nature, as well as its good sensitivity and accuracy . However, this technique has been rarely used in geographical classification and in harvesting year differentiation of olive oils .…”

Section: Introductionmentioning

confidence: 99%

“…As an alternative to methods based on wet chemistry, 24,25 ultraviolet (UV)-visible spectroscopy has been preferred in measuring the amounts of absorbing species for food analysis due to its ease of use and nondestructive nature, as well as its good sensitivity and accuracy. [26][27][28] However, this technique has been rarely used in geographical classification 29 and in harvesting year differentiation of olive oils. 21 In a very recent study, fatty acid profiling was compared with UV-visible fingerprints for classification of Moroccan Argan oils, 30 and in another study used visible spectroscopy fused with basic quality parameters in classification of Spanish extra virgin olive oils.…”

Section: Introductionmentioning

confidence: 99%

Authentication of Turkish olive oils by using detailed pigment profile and spectroscopic techniques

2020

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BACKGROUND Minor compounds of olive oil could have discriminatory characteristics in the authentication of this product. It was aimed to determine the detailed pigment profiles of Turkish olive oils and use them in differentiation of the samples in comparison to fast, reliable, and environmentally friendly Fourier‐transform infrared (FTIR) and ultraviolet (UV)–visible spectroscopic techniques. Pigment contents of 91 olive oils obtained from different locations for two consecutive harvesting years were determined with chromatographic analysis and FTIR and UV–visible spectra of these samples were also obtained. All data were analyzed with orthogonal partial least‐squares discriminant analysis to investigate the differentiation ability of these methods with regard to their detailed pigment and spectroscopic profiles. RESULTS Pheophytin a (2.78–8.98 mg kg−1) and lutein (1.19–4.07 mg kg−1) were the major pigments in all samples. Pigment profiles provided successful classification of olive oils with respect to their designated origins and harvesting year with average correct classification rates of 97%. UV–visible spectroscopy has quite similar results with pigment profiles in terms of its discriminatory power. In addition, FTIR and fused data were slightly better in discrimination of the samples, and the fused dataset has the highest correct classification rate of 100%. CONCLUSION Use of detailed pigment profiles is quite promising in authentication of olive oils. However, UV–visible and FTIR spectroscopic techniques could be reliable alternatives for the same purposes. All of the techniques studied have great potential in ‘protected designation of origin’ certification studies. © 2020 Society of Chemical Industry

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“…ANNs are non-linear techniques which function as biological neurons under precise training. They have been applied for the classification of EVOO in terms of their origin, 5 to prevent adulterations with other types of vegetable oils, 6,7 to determine the load of polyphenols in olive mill water, 8,9 or to predict the quality parameters of EVOO. [10][11][12][13] Already at a process level studies have been made 14,15 for the application of the ANNs to predict 'online' the fat losses in the pomace starting from the spectra of the oils as they exit the horizontal decanter centrifuge and certain technological variables in the process.…”

Section: Introductionmentioning

confidence: 99%

A predictive artificial neural network model as a simulator of the extra virgin olive oil elaboration process

Funes

Allouche

Beltrán

et al. 2017

Journal of Near Infrared Spectroscopy

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Nine neural models were created to predict the characteristics of the extra virgin olive oil developed as a quality objective and by-products. These models are designed with the help of data of process variables from physical sensors such as temperature, flows, current intensity, etc. and physicochemical ones like the near infrared spectrum of the olive mass. The results obtained for the extractability of the process (fatty content and moisture) were highly significant correlations (r 2 !0.90) and with similar prediction errors (root mean of squared error of prediction) relative to other analysis techniques which measure the by-product directly. For prediction the models gave correlations above 0.94, with the exception of ultraviolet absorption coefficients (0.72-0.84), with small prediction errors and the quality indicator relative error range with values above the optimal 10. The set of developed artificial neural networks models constitute the basis of the global 'simulator' tool of the extra virgin olive oil process. This simulator can perform a predictive optimization of the process to pre-adjust the process variables according to the goals marked in productivity or quality, from an near infrared spectral database or by real-time scanning. This simulator could be integrated into a control system that performs the function of a 'virtual plant' that allows the said system to adjust in real time the appropriate variables to meet the objectives.

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Spectroscopic determination of the photodegradation of monovarietal extra virgin olive oils and their binary mixtures through intelligent systems

Cited by 13 publications

References 26 publications

Pigments in Extra‐Virgin Olive Oil: Authenticity and Quality

Pigments in Extra‐Virgin Olive Oil: Authenticity and Quality

Authentication of Turkish olive oils by using detailed pigment profile and spectroscopic techniques

A predictive artificial neural network model as a simulator of the extra virgin olive oil elaboration process

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