Utilizing GIS tools to analyze viticultural choices under climate change scenario in North-East of Italy

Vineyard areas are constantly decreasing in Italy as well as in Europe. North-eastern regions in Italy are showing an opposite trend, steadily expanding with increased winegrowing areas. In viticulture and wine production, climate is arguably the most critical aspect in ripening fruit to achieve optimum characteristics to produce a given wine style. According to WMO and IPCC, climate is changing and the world is experiencing unprecedented climate extremes. Despite recent zoning aimed at defining key factors in determining the suitability of a given region for specific varieties and wine types, the expansion of viticulture in North East of Italy has led to some irrational planting choices about row orientation, dimensions, and slope. Under these conditions, the consequences of some extreme weather events may be more severe. The main objective of this study was to verify whether row orientation, aspect, and slope of vineyards, in combination with climate conditions, may affect yield and fruit quality. An area localized in the Northern Italy was analyzed, taking advantage of QGIS tools. The investigated parameters included: row orientation, slope, area, age of plantation, aspect ratio and distance between rows. Such variables have been combined with management information (planting distances, scion/rootstock combination, use of irrigation) and environmental information (yearly weather conditions). Data resulting from GIS analysis, vineyard management and environmental information have been correlated with 10-years yield and must quality parameters. Furthermore, satellite imagery from sample vineyards were collected and investigated in order to analyze the responses of the plants to different weather conditions. The results of the analysis highlighted how the mean slope of investigated vineyards is in general ranging between 1 and 3 degrees, with a prevalent Southern exposure. Rows do not exhibit a dominant orientation, mainly due to the following reasons: - the reduced dimensions available for vine cultivation, especially in hilly areas, where the vineyards are planted along contours, in order to limit erosion - the need for mechanisation, which calls for longer rather than larger rows. The results enabled to create a connection between row orientation, climate and soil conditions, and grapevine yield and quality responses to be considered as a guide for future planting choices more suitable to the restrictions imposed by increasing extreme weather events

Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards

Heatwaves are common in many viticultural regions of Australia. We evaluated the potential of satellite-based remote sensing to detect the effects of high temperatures on grapevines in a South Australian vineyard over the 2016-2017 and 2017-2018 seasons. The study involved: (i) comparing the normalized difference vegetation index (NDVI) from medium- and high-resolution satellite images; (ii) determining correlations between environmental conditions and vegetation indices (Vis); and (iii) identifying VIs that best indicate heatwave effects. Pearson's correlation and Bland-Altman testing showed a significant agreement between the NDVI of high- and medium-resolution imagery (R = 0.74, estimated difference ??0.093). The band and the VI most sensitive to changes in environmental conditions were 705 nm and enhanced vegetation index (EVI), both of which correlated with relative humidity (R = 0.65 and R = 0.62, respectively). Conversely, SWIR (short wave infrared, 1610 nm) exhibited a negative correlation with growing degree days (R = -0.64). The analysis of heat stress showed that green and red edge bands-the chlorophyll absorption ratio index (CARI) and transformed chlorophyll absorption ratio index (TCARI)-were negatively correlated with thermal environmental parameters such as air and soil temperature and growing degree days (GDDs). The red and red edge bands-the soil-adjusted vegetation index (SAVI) and CARI2-were correlated with relative humidity. To the best of our knowledge, this is the first study demonstrating the effectiveness of using medium-resolution imagery for the detection of heat stress on grapevines in irrigated vineyards.</p

Analysis and impact of recent climate trends on grape composition in north-east Italy

Climate is the most relevant factor influencing the ripening of high quality grapes to produce a given wine style. This notion should be taken into account, given the increase of extreme weather events (EWE) related to climate change. Under this evolving climate scenario, North-East Italian wine regions have seen a recent expansion, potentially disregarding optimal planting choices. The use of marginal land, indeed, could lead to the establishment of vineyards in areas where it is not possible to take advantage of the best row orientation, slope and aspect. Under these conditions, the consequences of some EWE may be more severe. The objective of this study is to verify whether planting options in combination with climate conditions, may affect yield and fruit quality. An area localised in Northern Italy was analysed for row orientation and slope, taking advantage of QGIS tools. The area was also examined for climate conditions, using weather conditions and climate indices. Such variables were combined with 10-year yield and must composition of four varieties (Chardonnay, Pinot Gris, Merlot and Glera) by using linear regression. The paper reports the most significant relationships between climatic conditions and grapevine composition. The results showed high positive correlation between sugar concentration and the number of frost days during the year in three varieties. The sugar content was positively correlated with the relative humidity in June in three varieties and negatively correlated with the number of days with a temperature >25°C during the month of June in two varieties. The content of tartaric acid showed high correlations with thermal indices of May in all varieties

Extreme Weather Events in Agriculture: A Systematic Review

Despite the increase of publications focusing on the consequences of extreme weather events (EWE) for the agricultural sector, a specific review of EWE related to agriculture is missing. This work aimed at assessing the interrelation between EWE and agriculture through a systematic quantitative review of current scientific literature. The review analysed 19 major cropping systems (cereals, legumes, viticulture, horticulture and pastures) across five continents. Documents were extracted from the Scopus database and examined with a text mining tool to appraise the trend of publications across the years, the specific EWE-related issues examined and the research gaps addressed. The results highlighted that food security and economic losses due to the EWE represent a major interest of the scientific community. Implementation of remote sensing and imagery techniques for monitoring and detecting the effects of EWE is still underdeveloped. Large research gaps still lie in the areas concerning the effects of EWE on major cash crops (grapevine and tomato) and the agronomic dynamics of EWE in developing countries. Current knowledge on the physiological dynamics regulating the responses of main crops to EWE appears to be well established, while more research is urgently needed in the fields of mitigation measures and governance systems

Sensori di monitoraggio, dalla teoria al campo

Per poter trarre piena utilit\ue0 e vantaggio dai diversi sensori disponibili sul mercato, i tanti dati raccolti devono essere elaborati e tradotti in informazioni pratiche e comprensibili, soprattutto in un settore agricolo come quello italiano caratterizzato da grande frammentazione e dimensioni ridotte. Per fare questo salto qualitativo servono competenze, formazione e investiment

Automatic Bunch Detection in White Grape Varieties Using YOLOv3, YOLOv4, and YOLOv5 Deep Learning Algorithms

Over the last few years, several Convolutional Neural Networks for object detection have been proposed, characterised by different accuracy and speed. In viticulture, yield estimation and prediction is used for efficient crop management, taking advantage of precision viticulture techniques. Convolutional Neural Networks for object detection represent an alternative methodology for grape yield estimation, which usually relies on manual harvesting of sample plants. In this paper, six versions of the You Only Look Once (YOLO) object detection algorithm (YOLOv3, YOLOv3-tiny, YOLOv4, YOLOv4-tiny, YOLOv5x, and YOLOv5s) were evaluated for real-time bunch detection and counting in grapes. White grape varieties were chosen for this study, as the identification of white berries on a leaf background is trickier than red berries. YOLO models were trained using a heterogeneous dataset populated by images retrieved from open datasets and acquired on the field in several illumination conditions, background, and growth stages. Results have shown that YOLOv5x and YOLOv4 achieved an F1-score of 0.76 and 0.77, respectively, with a detection speed of 31 and 32 FPS. Differently, YOLO5s and YOLOv4-tiny achieved an F1-score of 0.76 and 0.69, respectively, with a detection speed of 61 and 196 FPS. The final YOLOv5x model for bunch number, obtained considering bunch occlusion, was able to estimate the number of bunches per plant with an average error of 13.3% per vine. The best combination of accuracy and speed was achieved by YOLOv4-tiny, which should be considered for real-time grape yield estimation, while YOLOv3 was affected by a False Positive&ndash;False Negative compensation, which decreased the RMSE

Livello di meccanizzabilit\ue0 delle aziende viticole italiane

The evaluation of the potential mechanizability of existing viticultural areas is important to establish planting criteria of new vineyards. In this study, we designed a new mechanizability index, based on spatial and management parameters to categorize the Italian regions by their level of mechanizability. Il Friuli Venezia Giulia showed the highest mechanizability level, while the mountain regions, such as Liguria, Valle d'Aosta and Trentino-Alto Adige were the less mechanizable

Rilevare il deficit idrico della vite per irrigare al meglio

Il cambiamento climatico in corso richiede l\u2019implementazione di una serie di strategie volte alla riduzione dell\u2019impronta idrica della vite con un uso sempre pi\uf9 ponderato dell\u2019irrigazione, pertanto risulta fondamentale determinare lo stato idrico della pianta per adattare le pratiche agronomiche alle condizioni effettive del vignet

Sensori ottici per la raccolta dei dati in agricoltura

L\u2019impiego di sensori ottici posizionati a bordo del trattore, di droni, di aeromobili con pilota o di satelliti permette la raccolta di dati sulla vegetazione, come alterazioni delle dimensioni, variazioni nella pigmentazione, riduzioni di clorofilla, chiusura degli stomi e altre risposte fogliari sintomatiche di diversi stress biotici e abiotic