Application of the FTIR technique as a non-invasive tool to discriminate Portuguese olive oils with Protected Designation of Origin.

Three Portuguese olive oils with PDO ('Azeite do Alentejo Interior', 'Azeites da Beira Interior' and 'Azeite de Trás-os-Montes') were studied considering their physicochemical quality, antioxidant capacity, oxidative stability, total phenols content, gustatory sensory sensations and Fourier transform infrared (FTIR) spectra. All oils fulfilled the legal thresholds of EVOOs and the PDO's specifications. Olive oils from 'Azeite da Beira Interior' and 'Azeite de Trás-os-Montes' showed greater total phenols contents and antioxidant capacities, while 'Azeites da Beira Interior' presented higher oxidative stabilities. Linear discriminant models were developed using FTIR spectra (transmittance and the 1st and 2nd derivatives), allowing the correct identification of the oils' PDO (100 % sensitivity and specificity, repeated K-fold-CV). This study also revealed that multiple linear regression models, based on FTIR transmittance data, could predict the sweet, bitter, and pungent intensities of the PDO oils (R2 ≥0.979±0.016; RMSE≤0.26±0.05, repeated K-fold-CV). This demonstrates the potential of using FTIR as a non-destructive technique for authenticating oils with PDO.

Geographical discrimination of olive oils from Cv. 'Galega Vulgar'.

Olive oils from seven Portuguese regions were selected to study the effect of the geographical origin on the oils' composition. Quality parameters, fatty acids, tocopherols, hydroxytyrosol and tyrosol derivatives, and oxidative stability were evaluated. All olive oils could be classified as extra virgin, and the geographical origin significantly affected the oils chemical composition. Principal component analysis further confirmed the significant impact of the geographical origin on the composition and, indirectly, on stability of the oils, showing that the evaluated parameters could be used as markers for geographical origin identification. Alternatively, Fourier transform infrared spectroscopy was applied, allowing to establish a linear discriminant model that correctly identified the geographical origin of the olive oils with a mean sensitivity of 99 ± 3 % (internal validation), confirming the impact of the oil origin on its characteristics. This finding allowed foreseeing the future application of the spectroscopy approach as a green, fast and non-invasive authentication tool.

Does water addition during the industrial milling phase affect the chemical-sensory quality of olive oils? The case of cv. Arbequina oils.

At olive oil industrial extraction, water addition is a practice overcoming the formation of thick pastes. The effect of water addition (0 to 6.2%, kgadded water/kgolives), during the industrial milling of cv. Arbequina olives, on the oils' chemical-sensory quality, was evaluated. Despite the extra virgin olive oil classification, compared with the water incorporation (1.2-6.2%), extraction without water addition resulted into oils that showed less primary oxidation (lower peroxide values and K232), greater total phenolic content (+12-22%) and higher oxidative stability (+22-31%). No water addition increased the oils secoiridoids content (+5-13%), mainly oleacein (+27-79%). Oils extracted without water addition had a more intense ripe fruity sensation (≥ +11%) but lower fruit intensities (at least -4%). Thus, the quality and stability of the cv. Arbequina oils can be favoured if extracted without adding water during the olives industrial milling.

Impact of fresh olive leaves addition during the extraction of Arbequina virgin olive oils on the phenolic and volatile profiles.

Leaves incorporation during the extraction of olive oils can enhance their chemical-sensory quality. Thus, leaves from cvs. Arbequina or Santulhana were added (1%, w/w) during the extraction of Arbequina oils using an Abencor system, being discussed the impacts on the phenolics and volatiles formation enzymatic pathways. Leaves addition contributed to a significant decrease (P-value < 0.05) of the contents of secoiridoids (-11%), C6-aldehydes (-16%), and ester compounds (-22%). This could be tentatively related to a reduction of the enzymatic activity of secoiridoids biosynthesis and lipoxygenase pathways, promoted by the leaves' addition. Moreover, in the presence of leaves, the oils' total contents of phenolics and volatiles were significantly reduced (-7 and -17%, respectively). Contrary, the incorporation of leaves significantly increased (P-value < 0.05) the contents of C6-alcohols (+37%) and the intensities of the green fruity (+25%) and apple (+30%) sensations.

Formulation and Optimization of Nanoemulsions Using the Natural Surfactant Saponin from Quillaja Bark.

Replacing synthetic surfactants by natural alternatives when formulating nanoemulsions has gained attention as a sustainable approach. In this context, nanoemulsions based on sweet almond oil and stabilized by saponin from Quillaja bark with glycerol as cosurfactant were prepared by the high-pressure homogenization method. The effects of oil/water (O/W) ratio, total surfactant amount, and saponin/glycerol ratio on their stability were analyzed. The formation and stabilization of the oil-in-water nanoemulsions were analyzed through the evaluation of stability over time, pH, zeta potential, and particle size distribution analysis. Moreover, a design of experiments was performed to assess the most suitable composition based on particle size and stability parameters. The prepared nanoemulsions are, in general, highly stable over time, showing zeta potential values lower than -40 mV, a slight acid behavior due to the character of the components, and particle size (in volume) in the range of 1.1 to 4.3 µm. Response surface methodology revealed that formulations using an O/W ratio of 10/90 and 1.5 wt% surfactant resulted in lower particle sizes and zeta potential, presenting higher stability. The use of glycerol did not positively affect the formulations, which reinforces the suitability of preparing highly stable nanoemulsions based on natural surfactants such as saponins.

A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools.

Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors' sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation.

Practical procedure for discriminating monofloral honey with a broad pollen profile variability using an electronic tongue.

Colour and floral origin are key parameters that may influence the honey market. Monofloral light honey are more demanded by consumers, mainly due to their flavour, being more valuable for producers due to their higher price when compared to darker honey. The latter usually have a high anti-oxidant content that increases their healthy potential. This work showed that it is possible to correctly classify monofloral honey with a high variability in floral origin with a potentiometric electronic tongue after making a preliminary selection of honey according their colours: white, amber and dark honey. The results showed that the device had a very satisfactory sensitivity towards floral origin (Castanea sp., Echium sp., Erica sp., Lavandula sp., Prunus sp. and Rubus sp.), allowing a leave-one-out cross validation correct classification of 100%. Therefore, the E-tongue shows potential to be used at analytical laboratory level for honey samples classification according to market and quality parameters, as a practical tool for ensuring monofloral honey authenticity.

Single-cultivar extra virgin olive oil classification using a potentiometric electronic tongue.

Label authentication of monovarietal extra virgin olive oils is of great importance. A novel approach based on a potentiometric electronic tongue is proposed to classify oils obtained from single olive cultivars (Portuguese cvs. Cobrançosa, Madural, Verdeal Transmontana; Spanish cvs. Arbequina, Hojiblanca, Picual). A meta-heuristic simulated annealing algorithm was applied to select the most informative sets of sensors to establish predictive linear discriminant models. Olive oils were correctly classified according to olive cultivar (sensitivities greater than 97%) and each Spanish olive oil was satisfactorily discriminated from the Portuguese ones with the exception of cv. Arbequina (sensitivities from 61% to 98%). Also, the discriminant ability was related to the polar compounds contents of olive oils and so, indirectly, with organoleptic properties like bitterness, astringency or pungency. Therefore the proposed E-tongue can be foreseen as a useful auxiliary tool for trained sensory panels for the classification of monovarietal extra virgin olive oils.