Development, validation and application of a fast UHPLC-HRMS method for the analysis of amino acids and biogenic amines in wines and musts.

Farming management practices aiming at conserving soil moisture have been developed in arid and semiarid-areas facing water scarcity problems. Organic mulching is an effective method to manipulate the crop-growing microclimate increasing crop yield by controlling soil temperature, and retaining soil moisture by reducing soil evaporation. In this sense, the effectiveness of different organic mulching materials (straw mulch and grapevine pruning debris) applied within the row of a vineyard was evaluated on the soil and on the vine in a Tempranillo vineyard located in La Rioja (Spain). Organic mulches were compared with a traditional bare soil management technique (based on the use of herbicides to avoid weed incidence). Mulching coverages favourably influenced the soil water retention throughout all the grapevine vegetative cycle. However, the soil-moisture variation was not the same under different mulching materials, being the straw mulch (SM) the one that retained more water in comparison with grapevine pruning debris (GPD) based-cover. The changes of soil moisture in the upper surface layer (0–10 cm) were highly dynamic, probably due to water vapour fluxes across the soil-atmospheric interface. However, both, SM and GPD reduced these fluctuations as compared with bare soils. A similar trend occurred with soil temperature. Both organic mulches altered soil temperature in comparison with bare soil by reducing soil temperature in summer and raising it in winter. Moreover, the same buffering effect for the temperature on the covered soil also remains in the deeper layers. To conclude, we could see that organic mulching had a positive impact on soil-moisture storage and soil temperature and the extent of this effect depends on the type of mulching materials. These changes led to higher rates of photosynthesis and stomatal conductivity compared to bare soils, also favouring crop growth and grape yields.

The aim of this work was to analyze the phenology variability of Tempranillo and Chardonnay cultivars, related to the climatic characteristics in La Mancha Designation of Origin, and their potential changes under climate change scenarios. Phenological dates referred to budbreak, flowering, veraison and harvest were analyzed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The thermal requirements to reach each of these phenological stages were calculated and expressed as the GDD accumulated from DOY=60. Changes in phenology were projected by 2050 and 2070 taking into account those values and the projected temperatures and precipitation, simulated under two Representative Concentration Pathway (RCP) scenarios –RCP4.5 and RCP8.5– using an ensemble of models. The average phenological dates during the period under study were, April 16th ± 6.6 days and April 5th ± 6.0 days for budbreak, May 31st ± 6.0 days and May 27th ± 5.3 days for flowering, July 26th ± 5.6 days and July 25th ± 5.8 days for veraison, and Ago 23rd ± 10.8 days and Ago 17th ± 9.0 days for harvest, respectively, for Tempranillo and Chardonnay. The projected changes in temperature imply an average change in the maximum growing season (April-August) temperatures of 1.2 and 1.9°C by 2050, and 1.6 and 2.6°C by 2070, under the RCP4.5 and RCP8.5 scenarios, respectively. A reduction in precipitation is predicted, which vary between 15% for 2050 under RCP4.5 scenario and up to 30% by 2070 under RCP8.5. The advance of the phenological dates for 2050, could be of 6, 7, 7, and 8 days for Tempranillo and 4, 6, 6 and 9 days for Chardonnay, respectively for budbreak, flowering, veraison and harvest under the RCP4.5 scenario. Under the RCP8.5 emission scenario, the advance could be up to 30% higher.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Grapevine trunk diseases including Eutypa dieback are a major factor in the decline of vineyards and may lead to loss of productivity, reduced income, and premature reworking or replanting. Several studies have yielded results indicating that vines may be more likely to express symptoms of vascular disease if their health is already compromised by stress. In Australia and many other wine-growing regions it is a common practice for canes to be wrapped tightly around the cordon wire during the establishment of permanent cordon arms. It is likely that this practice may have a negative effect on health and longevity, as older cordons that have been trained in this manner often display signs of decay and dieback, with the wire often visibly embedded within the wood of the cordon. It is possible that adopting a training method which avoids constriction of the vasculature of the cordon may help to limit the onset of vascular disease symptom expression. A survey was conducted during the spring of two consecutive growing seasons on vineyards in South Australia displaying symptoms of Eutypa lata infection when symptomless shoots were 50–100 cm long. Vines were assessed as follows: (i) the proportion of cordon exhibiting dieback was rated using a 0–100% scale; (ii) the proportion of canopy exhibiting foliar symptoms of Eutypa dieback was rated using a 0–100% scale; (iii) the severity of strangulation was rated using a 0–4 point scale. Images were also taken of each vine for the purpose of measuring plant area index (PAI) using the VitiCanopy App. The goal of the survey was to determine if and to what extent any correlation exists between severity of strangulation and cordon dieback, in addition to Eutypa dieback foliar symptom expression.