Abstract
Total white blood cells count is an important diagnostic parameter in both human and veterinary medicines. State-of-the-art is performed by flow cytometry combined with light scattering or impedance measurements. Spectroscopy point-of-care has the advantages of miniaturization, low sampling, and real-time hemogram analysis. While white blood cells are in low proportions, while red blood cells and bilirubin dominate spectral information, complicating detection in blood. We performed a feasibility study for the direct detection of white blood cells counts in canine blood by visible-near infrared spectroscopy for veterinary applications, benchmarking current chemometrics techniques (similarity, global and local partial least squares, artificial neural networks and least-squares support vector machines) with self-learning artificial intelligence, introducing data augmentation to overcome the hurdle of knowledge representativity. White blood cells count information is present in the recorded spectra, allowing significant discrimination and equivalence between hemogram and spectra principal component scores. Chemometrics methods correlate white blood cells count to spectral features but with lower accuracy. Self-Learning Artificial Intelligence has the highest correlation (0.8478) and a small standard error of 6.92 x 10(9) cells/L, corresponding to a mean absolute percentage error of 25.37%. Such allows the accurate diagnosis of white blood cells in the range of values of the reference interval (5.6 to 17.8 x 10(9) cells/L) and above. This research is an important step toward the existence of a miniaturized spectral point-of-care hemogram analyzer.

Abstract
Shelf-life is defined as the time that a product is acceptable and meets the consumers expectations regarding food quality. It is the result of the conjunction of all services in production, distribution, and consumption. Shelf-life dating is one of the most difficult tasks in food engineering. Market pressure has lead to the implementation of shelf-life by sensory analyses, which may not reflect the full quality spectra. Moreover, traditional methods for shelf-life dating and small-scale distribution chain tests cannot reproduce in a laboratory the real conditions of storage, distribution, and consumption on food quality. Today, food engineers are facing the challenges to monitor, diagnose, and control the quality and safety of food products. The advent of nanotechnology, multivariate sensors, information systems, and complex systems will revolutionize the way we manage, distribute, and consume foods. The informed consumer demands foods, under the legal standards, at low cost, high standards of nutritional, sensory, and health benefits. To accommodate the new paradigms, we herein present a critical review of shelf-life dating approaches with special emphasis in computational systems and future trends on complex systems methodologies applied to the prediction of food quality and safety.

Abstract
Walnut leaves from nine different cultivars (Arco, Franquette, Hartley, Lara, Marbot, Mayette, Meylannaise, Parisienne and Rego) were studied for their phenolic compounds. Samples were harvested along three consecutive years, at two different geographical locations, in order to evaluate if significant differences in the phenolics composition can be related with genetic, climatic or geographical factors. Nine compounds (3-caffeoylquinic, 3-p-coumaroylquinic and 4-p-coumaroylquinic acids, quercetin 3-galactoside, quercetin 3-arabinoside, quercetin 3-xyloside, quercetin 3-rhamnoside, a quercetin 3-pentoside derivative and a kaempferol 3-pentoside derivative) were quantified using an HPLC-DAD methodology. The qualitative profiles were identical for all samples, but differences were observed in terms of individual compounds' contents. Multivariate statistical analysis was carried out, showing that significant differences exist among production years, which can be related to climatic reasons.

Abstract
The disruption of the milk fat globule membrane can lead to an excessive accumulation of free fatty acids in milk, which is frequently associated with the appearance of rancid flavors. Solid-phase microextraction and gas chromatography techniques have been shown to be useful tools in the quantification of individual free fatty acids in dairy products providing enough sensitivity to detect levels of rancidity in milk. Therefore, the aim of this study was to characterize the short-chain and medium-chain free fatty acid profile in i) raw untreated goat milk; ii) raw goat milk passing through pumps and heating units (plate-and-frame heat exchanger and ohmic heater); and iii) processed goat milk by conventional and ohmic pasteurization to determine the influence of each treatment in the final quality of the milk. Multivariate statistical analysis has shown that the treatments studied were not responsible for the variability found on free fatty acid contents. In particular, it was possible to conclude that ohmic pasteurization at 72 C for 15 s did not promote an extended modification of free fatty acid contents in goat milk when compared with that of conventional pasteurization. Furthermore, principal component analysis showed that the capric acid can be used to discriminate goat's milk with different free fatty acid concentrations. Hierarchical cluster analysis showed evidence of the existence of correlations between contents of short and medium chain free fatty acids in goat milk.

Abstract
The main purpose of this study was the characterisation of 'Serra da Lousa' heather honey by using novel statistical methodology, relevant principal component analysis, in order to assess the correlations between production year, locality and composition. Herein, we also report its chemical composition in terms of sugars, glycerol and ethanol, and physicochemical parameters. Sugars profiles from 'Serra da Lousa' heather and 'Terra Quente de Tras-os-Montes' lavender honeys were compared and allowed the discrimination: 'Serra da Lousa' honeys do not contain sucrose, generally exhibit lower contents of turanose, trehalose and maltose and higher contents of fructose and glucose. Different localities from 'Serra da Lousa' provided groups of samples with high and low glycerol contents. Glycerol and ethanol contents were revealed to be independent of the sugars profiles. These data and statistical models can be very useful in the comparison and detection of adulterations during the quality control analysis of 'Serra da Lousa' honey.

Abstract
The development of a fingerprinting strategy capable to evaluate the "oxidation status" of white wines based on cyclic voltammetry is proposed here. It is known that the levels of specific antioxidants and redox mechanisms may be evaluated by cyclic voltammetry. This electrochemical technique was applied on two sets of samples. One group was composed of normal aged white wines and a second group obtained from a white wine forced aging protocol with different oxygen, SO(2), pH, and temperature regimens. A study of antioxidant additions, namely ascorbic acid, was also made in order to establish a statistical link between voltammogram fingerprints and chemical antioxidant substances. It was observed that the oxidation curve presented typical features, which enables sample discrimination according to age, oxygen consumption, and antioxidant additions. In fact, it was possible to place the results into four significant orthogonal directions, compressing 99.8% of nonrandom features. Attempts were made to make voltammogram fingerprinting a tool for monitoring oxidation management. For this purpose, a supervised multivariate control chart was developed using a control sample as reference. When white wines are plotted onto the chart, it is possible to monitor the oxidation status and to diagnose the effects of oxygen regimes and antioxidant activity. Finally, quantification of substances implicated in the oxidation process as reagents (antioxidants) and products (off-flavors) was tried using a supervised algorithmic the partial least square regression analysis. Good correlations (r > 0.93) were observed for ascorbic acid, Folin-Ciocalteu index, total SO(2), methional, and phenylacetaldehyde. These results show that cyclic voltammetry fingerprinting can be used to monitor and diagnose the effects of wine oxidation.