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Several factors influence grapevine's quality and productivity; among them, there are weather and climate. Temperature, solar radiation, precipitation and soil moisture have relevant impacts on crop growth and yield. Recently crop growth models were used as tools to assess climate variability and change in crop yields and quality. Crop growth models are currently employed at a regional scale for agricultural needs, environmental applications, and/or for supporting the process of decision-making and planning in agriculture. Some crop growth models are adaptable to various crops and can simulate crop growth and plant development, as well as water and nitrogen balances. Specific crop growth models have also been developed to simulate grapevine growth and development. Generally, crop growth models include specific modules calculating the occurrence of phenological stages, that can also be used as stand-alone routines. Finally, grapevine phenology has recently been studied in connection with climate change by means of grape harvest dates used to reconstruct past climate and, more rarely, future climate. The numerical crop growth model IVINE (Italian Vineyard Integrated Numerical model for Estimating physiological values) was developed at our dept. to simulate grapevine phenological and physiological processes. The boundary conditions required by IVINE are hourly meteorological data related to some air and soil values (among which the more relevant are air temperature and soil moisture), while other inputs are initial conditions and parameters characterizing geography, soil texture, grapevine variety, and cultivation interventions. The main IVINE outputs are: the phenological stages (e.g. dormancy exit, bud-break, fruit set, veraison, and harvest), the leaf development, the yield, the berry sugar concentration, and the leaf water potential. The IVINE requires some experimental parameters depending on the cultivar, which have been evaluated through some calibration experiments for some popular Italian varieties. IVINE includes theoretical physically based equations for processes such as water balance and photosynthesis, and empirical equations for others. Long-term simulations carried out in Italian territory show, in the period 1980-2010, significant trends in almost all physio-phenological variables, as well as a reduction in interannual variability, correlated with the climate change still ongoing.IVINE model performances depend on the quality of input data: the use of experimental data measured not far from the vineyard could improve the quality of the simulation, even if the model seems able to account for the interannual variability of the meteorological conditions, which reflects in the pheno-physiological trends interannual variability. During the presentation, the model will be introduced, and a sketch of the main results obtained will be discussed.

Integrated pest management (IPM) practices proved to be efficient in reducing pesticide use and ensuring economic farming sustainability. Digital decision support systems (DSS) to support the adoption of IPM practices from plant protection services are required by European legislation. Available DSSs used by Italian plant protection services are heterogeneous with regards to disease forecasting models, datasets for their calibration, and level of integration in operational decision-making. This study presents the MISFITS-DSS, which has been jointly developed by a public research institution and nine regional plant protection services with the objective of harmonizing data collection and decision support for Italian farmers. Participatory approach allowed designing a predictive workflow relying on specific domain expertise, in order to explicitly match actual user needs. The DSS calibration entailed the risk of grapevine downy mildew infection (5-point scale from very low to very high), and phenological observations in 2012-2017 as reference data. Process-based models of primary and secondary infections have been implemented and tested via sensitivity analysis (Morris method) under contrasting weather conditions. Hindcast simulations of grapevine phenology, host susceptibility and disease pressure were post-processed by machine-learning classifiers to predict the reference infection risk. Results indicate that IPM principles are implemented by plant protection services since years. The accurate reproduction of grapevine phenology (RMSE = 4-14 days), which drove the dynamic of host susceptibility, and the use of weather forecasts as model inputs contributed to reliably predict the reference infection risk (88% balanced accuracy). We did a pioneering effort to homogenize the methodology to deliver decision support to Italian farmers, by involving plant protection services in the DSS definition, to foster a further adoption of IPM practices.

The numerical crop growth model IVINE (Italian Vineyard Integrated Numerical model for Estimating physiological values) was originally developed at the dept. of Physics, Univ. of Torino, as a research model with the aim to simulate grapevine phenological and physiological processes. Since vines are generally strongly sensitive to meteorological conditions, the model should be able to evaluate the environmental forcing effects on vine growth and, eventually, on its production. IVINE model requires a set of hourly meteorological and soil data as boundary conditions; the more relevant input for the model to correctly simulate the plant growth are: air temperature and soil moisture. Among the principal IVINE outputs, we mention: the main philological stages (dormancy exit, bud-break, fruit set, veraison, and harvest), the leaf development, the yield, the berry sugar concentration, and the predawn leaf water potential. The IVINE requires to set some experimental parameters depending on the cultivar; at present, IVINE is optimized for Nebbiolo and other common varieties (such as, for example, cvs. Barbera, Vermentino, Cannonau, etc for Italy), but validation experiments have been performed only for Nebbiolo variety, due to the difficulty to gather all required measurements useful to drive the model and to compare its outputs for several consecutive years in the same vineyard. In the frame of the second part of the EU JPI-FACCE project named MACSUR (Modelling European Agriculture with Climate Change for Food Security), some data relative to vineyards displaced in several European countries were made available, thus we tried to execute simulations with IVINE in those vineyards. Since input data required by IVINE were not all present, we decided to extract input data from the international GLDAS database in the nearest grid point to the experimental vineyard, and to run the trusted land surface model UTOPIA on those points in order to evaluate soil variables required by IVINE. The main results obtained by those simulations, as well as the few possible validations with experimental observations, will be shown and commented. As a summary, we can say that the simulation carried out with IVINE seems able to well account for the interannual variability of the meteorological conditions, and the used settings seems able to allow a sufficiently valid simulation of the pheno-physiological conditions of the vineyards, but the approximation in the input data causes departures larger than if local measurements would be used.

Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the “Monferrato” area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962–2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P< 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.

The numerical crop growth model Italian Vineyard Integrated Numerical model for Estimating physiological values (IVINE) was developed in order to evaluate environmental forcing effects on vine growth. The IVINE model simulates vine growth processes with parameterizations, allowing the understanding of plant conditions at a vineyard scale. It requires a set of meteorology data and soil water status as boundary conditions. The primary model outputs are main phenological stages, leaf development, yield, and sugar concentration. The model requires setting some variety information depending on the cultivar: At present, IVINE is optimized for Vitis vinifera L. Nebbiolo, a variety grown mostly in the Piedmont region (northwestern Italy). In order to evaluate the model accuracy, IVINE was validated using experimental observations gathered in Piedmontese vineyards, showing performances similar or slightly better than those of other widely used crop models. The results of a sensitivity analysis performed to highlight the effects of the variations of air temperature and soil water potential input variables on IVINE outputs showed that most phenological stages anticipated with increasing temperatures, while berry sugar content saturated at about 25.5 °Bx. Long-term (60 years, in the period 1950⁻2009) simulations performed over a Piedmontese subregion showed statistically significant variations of most IVINE output variables, with larger time trend slopes referring to the most recent 30-year period (1980⁻2009), thus confirming that ongoing climate change started influencing Piedmontese vineyards in 1980.

The embryonic and post-embryonic development of Scaphoideus titanus, the main vector of grapevine Flavescence doree, was studied under laboratory conditions, at constant temperatures (T = 15, 18, 20, 22, 24, 27, and 29 °C). The data obtained were fitted to the equation of Briere, and the model was validated against independent field data. The minimum cardinal temperature for eggs ranged from 18 to 20 °C, the duration of egg hatching was minimum at T = 24 °C, egg hatchability was optimum at 22 °C, and very few eggs hatched at T ≥ 27 °C. The duration of post-embryonic development clearly shortened as the temperature increased, both overall and within the same life stage, almost half-reducing itself from 18 to 29 °C. Within the same temperature tested, the early instars took less time to moult compared to the late ones. The data obtained provided a significant fit with the equation of Briere. Validation was satisfactory, particularly concerning third instar nymphs and adults, which are the key life instars f...

Climate has an important impact on grape and wine qualitative parameters. Experiments in controlled conditions have shown that the major climatic factors affecting polyphenol accumulation are radiative and thermal conditions; in particular, high temperatures inhibit anthocyanin formation and modify the composition of the anthocyanin fraction. The aim of this study was to compare climatic data and berry composition throughout a ten-year period, in order to explore the relationships between phenolic compounds concentration in ‘Nebbiolo’ grapes and climatic trends. Phenolic compounds concentration was monitored during the 2000-2009 period at four vineyard sites in Piedmont. Meteorological data were collected in the study areas and bioclimatic indexes were calculated. A qualitative and climatic dataset was created and correlation analysis was carried out. The results show that bioclimatic indexes linked to temperature have the highest impact on anthocyanin and flavonoid concentration, while little effects of global light radiation and of rainfall were observed.

BACKGROUND: Since the beginning of the 1980s deuterium nuclear magnetic resonance and carbon-13 mass spectrometry have proved to be reliable techniques for detecting adulteration and for classifying natural products by their geographic origin. Scientific literature has so far mainly focused on data acquired at regional level where isotopic parameters are correlated to climatic mean data relative to large territories. RESULTS: Nebbiolo and Barbera wine samples of various vintages and from different areas within the Piedmont region (northern Italy) were analysed using SNIF-NMR and GC-C-IRMS and a large set of meteorological parameters were recorded by means of weather stations placed in fields where the grapes were grown. Correlations between isotopic (2H and 13C) data and several climatic parameters at a local level (mean temperature, total rainfall, mean humidity and thermal sums) were attempted and some linear correlations were found. CONCLUSIONS: Mean temperature and total rainfall were found to be correlated to isotopic (2H and 13C) abundance in linear direct and inverse proportions respectively. Lower or no correlations between deuterium and carbon-13 abundances and other meteorological parameters such as mean humidity and thermal sums were found. Moreover, wines produced from different grape varieties in the same grape field showed significantly different isotopic values. Copyright © 2011 Society of Chemical Industry

Hazel (Corylus avellana L.) and black alder (Alnus glutinosa (L.) Gaertn.) are important sources of airborne pollen and represent an allergen threat during the flowering period. Researches on airborne pollen concentrations in both species are useful in allergology, as well as for fruit production for hazel. The aims of the present study were: (1) to investigate the relationships between environmental conditions and the airborne pollen concentration of hazel and black alder during the flowering period by correlation and multiple regression analysis and (2) to predict the pollen season start (PSS) by using a sequential model, in order to obtain a helpful tool in allergology and hazel cultivation. In this study, the applied method defines the pollen season as the period in which 90 % of the total season’s catch occurred, using a data set of 18 years (1996–2014). The relationships between daily meteorological parameters (temperature, humidity, rainfall and wind speed) during the 14-day period that precedes the PSS and the PSS of hazel and black alder (day of the year) were investigated. The results showed that mean temperature and the number of rainy days before the PSS are the main factors influencing PSS for both taxa. Moreover, the chilling and heat needed to break dormancy were estimated in order to predict the PSS of both species. Different years and different thresholds of temperature and chill days were used to calibrate and validate the model.

In this work, we analyse the role of climatic constraints in shaping the distribution of alien plant species along the elevation gradient in the European Alps. Alien species occurrence was recorded in 278 plots located beside rivers, from 100 to 2,100 m a. s. l. Climate variables were calculated from the data recorded by 145 meteorological stations and interpolated by a multiple regression approach. Both richness and occurrence of aliens were modelled. In particular, relationships between the occurrence of alien plants and (1) elevation or (2) the climatic variables, were tested by applying generalised linear models and generalised linear mixed models; the model parameters obtained were used to estimate upper elevation limits of alien occurrence and their related climate values. Sixty-eight alien species were encountered, the majority (71%) invasive in Italy and worldwide. A steep decrease in alien species richness with elevation was found, with the probability of alien species occurrence decreasing by half for each 100 m increase in elevation. Minimal adequate models based on (1) non-transformed climatic variables and (2) derived PCA values, confirmed that occurrence of alien plant species along the elevation gradient was positively related to the minimum temperature, the mean temperature and the heat sum for the spring season, rather than to the incidence of absolute minimum temperature and frost days, as usually assumed. Although further experimental analyses are needed, these results support the hypothesis that, referring to climate factors, elevation limits along rivers are mainly established by low spring temperatures which operate at the level of population viability rather than plant survival.

The paper summarizes the preliminary results from the analysis of data collected during the 2008 and 2009 vegetative seasons in a northern Italy vineyard (Vitis vinifera L., Barbera variety) and the simulations carried out in the same period with the land surface model UTOPIA. The aim of the work is to study the influence of the meteorological factors on the plant conditions. We collected a set of standard and advanced meteorological, physiological and physical data and we investigated the performance of UTOPIA in describing the different components of the energy and hydrological processes (in particular the evapotranspiration), with a special focus on the vegetation and soil. The comparison between observed data and UTOPIA simulations showed satisfactory results for the soil variables (RRMSE ranging between 15% and 40%, and correlation coefficients of 0.9). Net radiation and sensible heat fluxes RRMSE (30% and 63% respectively) suggest that both the calibration of the vegetation parameters (including the influence of the grass among vine rows) and the availability of more specific measurements are very important.

The effects of environmental conditions on the variability in germination dynamics of Plasmopara viticola oospores were studied from 1999 to 2003. The germination course was determined indirectly as the relative infection incidence (RII) occurring on grape leaf discs kept in contact with oospores sampled from a vineyard between March and July. The time elapsed between 1 January and the infection occurrence was expressed as physiological time, using four methods: (i) sums of daily temperatures > 8 ° C; (ii) hourly temperatures > 10 ° C; (iii) sums of hourly rates from a temperature-dependent function; or (iv) sums of these rates in hours with a rain or vapour pressure deficit ≤ 4·5 hPa (hydro-thermal time, HT). An equation of Gompertz in the form RII = exp[ − a · exp( − b · HT)] produced an accurate fit for both separate years ( R 2 = 0·97 to 0·99) and pooled data ( R 2 = 0·89), as well as a good accuracy in cross-estimating new data ( r between observed and cross-estimated data were between 0·93 and 0·99, P < 0·0001). It also accounted for a great part of the variability in oospore germination between years and both between and within sampling periods. Therefore, the equation of Gompertz (with a = 15·9 ± 2·63 and b = 0·653 ± 0·034) calculated over hydro-thermal time, a physiological time accounting for the effects of both temperature and moisture, produced a consistent modelling of the general relationships between the germination dynamics of a population of P. viticola oospores and weather conditions. It represents the relative density of the seasonal oospores that should have produced sporangia when they have experienced favourable conditions for germination.