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The effects of SEGs ("Shoot from vines-Enological-Granule") on winemaking within the same variety are well established. However, the interaction of different SEG varieties combined with micro-oxygenation (MOX) and its subsequent evolution in the bottle has not been investigated to date. In this work, Tempranillo wines were treated with two doses of SEGs from Tempranillo and Cabernet Sauvignon (12 and 24 g/L) and subjected to two fixed MOX doses (LOTR, 6.24 mg/L·month, and HOTR, 11.91 mg/L·month). After that, the wines were bottled, and their chemical composition and sensory profile were analysed after 3 and 6 months. Although no clear trend directly associated with the use of MOX was observed, in terms of chemical composition, wines showed an evolution in their chemical profile over time, with compounds such as vanillin increasing as more oxygen was added. Regarding their sensorial profile, the wines were more rounded after 6 months that in bottling, where SEGs or toasted descriptors, studied at the taste phase, were slightly more intense with the low SEG dose and HOTR combination.

The design, construction and validation of a device for the accurate measurement of the dissolved oxygen content in wine and simultaneously the variation of its spectral fingerprint is presented. The novelty of this system is due to two innovative approaches. First, robustness in measurements is obtained by using cuvettes designed to simultaneously measure the dissolved oxygen and color. Secondly, automatic monitoring is performed to ensure that measurements are always taken at the same cuvette position. The fine-tuning of the device with the study of white and red wines makes it possible, on the one hand, to establish the appropriate measurement conditions and, on the other hand, to determine the amount of oxygen required to cause specific changes in the wine spectrum, information that could not be obtained until now. The preliminary results are very interesting, presenting precise data on the amount of oxygen consumed by the wine and the variations in its visible spectrum, thus reflecting the modification of the responsible phenolic compounds. This information is of great interest, since it helps to optimize the handling of the wine and, if necessary, to moderate the uptake of oxygen in each type of wine to ensure the maintenance of the color during the winemaking and conservation processes of each type of wine. The results of the experiments indicate that this new instrument is feasible and accurate for detecting oxygen changes during wine production.

The ageing of wines in oak barrels is a key stage in the production of high-quality red wines, with the type of oak chosen and the amount of oxygen received by the wine being the determining factors of the process. This work analyses the effect of ageing the same red wine in barrels with different oxygenation rates for one year (OTR), specifically the effect on the evolution of anthocyanins, their derivatives and the appearance of new pigments according to the oxygen dosage in barrels. Results show that wines aged in High-Wood-OTR barrels have a large quantity of monomeric anthocyanins and wine aged in Low-Wood-OTR barrels presents a major intensity of colour. Moreover, using LC-MS analysis, it was possible to detect and identify different families of anthocyanin derivatives, including the tentative identification of two new aldehyde-flavanol-methylpyranoanthocyanin pigments.

Oxygen is an important factor in the wine aging process, and the oxygen transmission rate (OTR) is the parameter of the wood that reflects its oxygen permeation. OTR has not been considered in the cooperage industry yet; however, recent studies proposed a nondestructive method for estimating the OTR of barrel staves, but an efficient method to combine these staves to build barrels with a desired OTR is needed to implement it in the industry. This article proposes artificial intelligence methods for selecting staves for the construction of barrel heads or bodies with a desired target OTR. Genetic algorithms were used to implement these methods in consideration of the known OTR of the staves and the geometry of the wine barrels. The proposed methods were evaluated in several scenarios: homogenizing the OTR of the actual constructed barrels, constructing low-OTR and high-OTR barrels based on a preclassification of the staves and implementing the proposed method in real cooperage conditions. The results of these experiments suggest the suitability of the proposed methods for their implementation in a cooperage in order to build controlled OTR barrels.

Wood is one of the most highly valued materials in enology since the chemical composition and sensorial properties of wine change significantly when in contact with it. The need for wood in cooperage and the concern of enologists in their search for new materials to endow their wines with a special personality has generated interest in the use of other Quercus genus materials different from the traditional ones ( Q. petraea , Q. robur and Q. alba ) and even other wood genera. Thereby, species from same genera such as Q. pyrenaica Willd. , Q. faginea Lam. , Q. humboldtti Bonpl. , Q. oocarpa Liebm. , Q. stellata Wangenh, Q. frainetto Ten., Q. lyrata Walt., Q. bicolor Willd. and other genera such as Castanea sativa Mill. (chestnut), Robinia pseudoacacia L. (false acacia), Prunus avium L. and P. cereaus L. (cherry), Fraxinus excelsior L. (European ash) and F. americana L. (American ash) have been studied with the aim of discovering whether they could be a new reservoir of wood for cooperage. This review aims to summarize the characterization of tannin and low molecular weight phenol compositions of these alternative woods for enology in their different cooperage stages and compare them to traditional oak woods, as both are essential to proposing their use in cooperage for aging wine., Competing Interests: The authors declare no conflict of interest.

A combination of physical-chemical analysis has been used to monitor the aging of red wines from D.O. Toro (Spain). The changes in the chemical composition of wines that occur over the aging time can be used to distinguish between wine samples collected after one, four, seven and ten months of aging. Different computational models were used to develop a good authenticity tool to certify wines. In this research, different models have been developed: Artificial Neural Network models (ANNs), Support Vector Machine (SVM) and Random Forest (RF) models. The results obtained for the ANN model developed with sigmoidal function in the output neuron and the RF model permit us to determine the aging time, with an average absolute percentage deviation below 1%, so it can be concluded that these two models have demonstrated their capacity to predict the age of wine.