Within vineyard temperature structure and variability in the umpqua valley of Oregon

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Background: Aroma compounds are important secondary metabolite in grapes and play important roles in the flavor and quality of grape berries and their wines. Vitis amurensis grape belongs to the East Asian Vitis spp., with excellent cold and disease resistance, and exhibits strong brewing potential. However, it has not been effectively utilized and there is no systematic research on the aroma compounds of V. amurensis grapes.
Methods: To provide sufficient experimental evidence for the characteristic aroma of V. amurensis grape, HS-SPME-GC/MS was used to identify the aroma compounds of five V. amurensis (‘Beiguohong’, ‘Beiguolan’, ‘Shuangfeng’, ‘Shuanghong’, ‘Shuangyou’) and three interspecific hybrids (‘Beibinghong’, ‘Xuelanhong’, ‘Zuoyouhong’) grapes in Zuojia and Ji’an. The grape berries were collected at harvest in 2020, 2021 and 2022.

Global challenges, including adaptation to climate change, decrease of the environmental impacts and maintenance of the economical sustainability shape the future of viticulture.

Viticulture’s adaptation to the harmful effects of climate change is globally the biggest challenge of the near future. Short, extremely intensive rainfalls and longer periods of drought are getting more frequent in the Tokaj Wine Region, where the majority of the vineyards are cultivated on steep slopes. Hence, erosion has high risk, especially when combined with the loess-based soils on about ten percent of the region. The environmentally beneficial cover crop and mulch usage can effectively reduce the risk of erosion, according to research done by the Tokaj Wine Region Research Institute of Viticulture and Oenology.

There is currently a real need to improve and speed-up phenotyping in experimental set-ups to increase the number of modalities studied. Accurate information acquisition on plant status with high-throughput capacity is the main appeal of on-board systems.
A proximal sensing camera for a proxy of winter pruning weight was tested. We estimated the shoot volume of the vine by image analysis using algorithms that integrate the local shoot section area estimate along the shoot skeleton obtained by a morphological distance transform.
The study was carried out on the GreffAdapt experimental vineyard in Guyot simple training and a canopy management using vertical trellising. The planting density is 6250 vines/ha with a row spacing of 1.6×1m. Five scions grafted onto 55 rootstocks are present and the combination rootstock×scion is different every five plants.