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.

Evaluation of healthy and sensory indexes of sweetened beverages using an electronic tongue.

Overconsumption of sugar-sweetened beverages may increase the risk of health problems and so, the evaluation of their glycemic load and fructose-intolerance level is essential since it may allow establishing possible relations between physiologic effects of sugar-rich beverages and health. In this work, an electronic tongue was used to accurately classify beverages according to glycemic load (low, medium or high load) as well to their adequacy for people suffering from fructose malabsorption syndrome (tolerable or not): 100% of correct classifications (leave-one-out cross-validation) using linear discriminant models based on potentiomentric signals selected by a meta-heuristic simulated annealing algorithm. These results may be partially explained by the electronic tongue's capability to mimic the human sweetness perception and total acid flavor of beverages, which can be related with glycemic load and fructose-intolerance index. Finally, the E-tongue was also applied to quantify, accurately, healthy and sensory indexes using multiple linear regression models (leave-one-out cross-validation: Radj>0.99) in the following dynamic ranges: 4.7

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.

Cyclic voltammetry: a tool to quantify 2,4,6-trichloroanisole in aqueous samples from cork planks boiling industrial process.

Chloroanisoles, namely 2,4,6-trichloroanisole, are pointed out as the primary responsible of the development of musty off-flavours in bottled wine, due to their migration from cork stoppers, which results in huge economical losses for wine industry. A prevention step is the detection of these compounds in cork planks before stoppers are produced. Mass spectrometry gas chromatography is the reference method used although it is far beyond economical possibilities of the majority of cork stoppers producers. In this work, a portable cyclic voltammetry approach was used to detect 2,4,6-trichloroanisole extracted from natural cork planks to the aqueous phase during the cork boiling industrial treatment process. Analyses were carried out under ambient conditions, in less than 15 min with a low use of solvent and without any sample pre-treatment. The proposed technique had detection (0.31±0.01 ng/L) and quantification (0.95±0.05 ng/L) limits lower than the human threshold detection level. For blank solutions, without 2,4,6-trichloroanisole addition, a concentration in the order of the quantification limit was estimated (1.0±0.2 ng/L), which confirms the satisfactory performance of the proposed methodology. For aqueous samples from the industrial cork planks boiling procedure, intra-day repeatabilities were lower than 3%, respectively. Also, 2,4,6-trichloroanisole contents in the aqueous samples determined by this novel approach were in good agreement with those obtained by GC-MS (correlation coefficient equal to 0.98), confirming the satisfactory accuracy of the proposed methodology. So, since this novel approach is a fast, low-cost, portable and user-friendly method, it can be an alternative and helpful tool for in-situ industrial applications, allowing accurate detection of releasable 2,4,6-trichloroanisole in an earlier phase of cork stoppers production, which may allow implementing more effective cork treatments to reduce or avoid future 2,4,6-trichloroanisole contaminations of wine.