scholarly journals Impact of previous and current year’s climatic conditions on the quality and yield of three wine grape varieties and vintage evaluation in Tokachi, Hokkaido, Japan

2021 ◽  
Vol 21 (0) ◽  
pp. 65-73
Author(s):  
Zenta NISHIO ◽  
Hakaru AZUMA ◽  
Seiji SHIMODA ◽  
Tomoyoshi HIROTA
Author(s):  
Алла Анатольевна Полулях ◽  
Владимир Александрович Волынкин ◽  
Ирина Александровна Васылык

Крымский полуостров - регион с разнообразными почвенными и климатическими условиями, является родиной более 70 сортов винограда. Сортимент винограда Крыма формировался на протяжении длительного времени в определённых условиях и обладает рядом ценных свойств и признаков. В статье приводится описание основных ампелографических и хозяйственно-биологических характеристик перспективного местного крымского столово-технического сорта среднепозднего периода созревания Солнечная Долина 58. Сорт пригоден для культивирования в юго-восточной прибрежной зоне Крыма при схеме посадки кустов 1,5 х 3,0 м и нагрузке 60 глазков на куст при обрезке 6-8 глазков. Хорошо растет и плодоносит на щебенистых почвах. Перспективен для приготовления красных столовых и десертных вин, и для потребления в свежем виде на месте. Сорт встречается только в коллекциях. The Crimean Peninsula as a region with a diversity of soil and climatic conditions is a home to more than 70 grape varieties. The assortment of grapes has been formed over a long period of time under certain conditions and has a number of valuable properties and traits. The article describes main ampelographic and economic-biological characteristics of the promising local Crimean table and wine grape variety ‘Solnechnaya Dolina 58’. The variety is suitable for cultivation in the south-eastern coastal zone of Crimea with bushes planting scheme of 1.5 x 3.0 m and a load of 60 eyes per bush when pruning 6-8 eyes. It grows well and fructifies on rank soils. It has good prospects for making red table and dessert wines, as well as for fresh consumption. The variety is met in collections only.


2014 ◽  
Vol 3 (3) ◽  
pp. 218-225
Author(s):  
R. G. Somkuwar ◽  
M. A. Bhange ◽  
A. K. Upadhyay ◽  
S. D. Ramteke

SauvignonBlanc wine grape was characterized for their various morphological, physiological and biochemical parameters grafted on different rootstocks. Significant differences were recorded for all the parameters studied. The studies on vegetative parameters revealed that the rootstock influences the vegetative growth thereby increasing the photosynthetic activities of a vine. The highest photosynthesis rate was recorded in 140-Ru grafted vine followed by Fercal whereas the lowest in Salt Creek rootstock grafted vines.The rootstock influenced the changes in biochemical constituents in the grafted vine thereby helping the plant to store enough food material. Significant differences were recorded for total carbohydrates, proteins, total phenols and reducing sugar. The vines grafted on1103-Pshowed highest carbohydrates and starch followed by 140-Ru,while the least amount of carbohydrates were recorded in 110-R and Salt Creek grafted vines respectively.Among the different rootstock graft combinations, Fercal showed highest amount of reducing sugar, proteins and phenols, followed by 1103-P and SO4, however, the lowest amount of reducing sugar, proteins and phenols were recorded with 110-R grafted vines.The vines grafted on different rootstocks showed changes in nutrient uptake. Considering this, the physico-biochemical characterization of grafted vine may help to identify particularrootstocks combination that could influence a desired trait in commercial wine grape varieties after grafting.


Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4850 ◽  
Author(s):  
Carlos S. Pereira ◽  
Raul Morais ◽  
Manuel J. C. S. Reis

Frequently, the vineyards in the Douro Region present multiple grape varieties per parcel and even per row. An automatic algorithm for grape variety identification as an integrated software component was proposed that can be applied, for example, to a robotic harvesting system. However, some issues and constraints in its development were highlighted, namely, the images captured in natural environment, low volume of images, high similarity of the images among different grape varieties, leaf senescence, and significant changes on the grapevine leaf and bunch images in the harvest seasons, mainly due to adverse climatic conditions, diseases, and the presence of pesticides. In this paper, the performance of the transfer learning and fine-tuning techniques based on AlexNet architecture were evaluated when applied to the identification of grape varieties. Two natural vineyard image datasets were captured in different geographical locations and harvest seasons. To generate different datasets for training and classification, some image processing methods, including a proposed four-corners-in-one image warping algorithm, were used. The experimental results, obtained from the application of an AlexNet-based transfer learning scheme and trained on the image dataset pre-processed through the four-corners-in-one method, achieved a test accuracy score of 77.30%. Applying this classifier model, an accuracy of 89.75% on the popular Flavia leaf dataset was reached. The results obtained by the proposed approach are promising and encouraging in helping Douro wine growers in the automatic task of identifying grape varieties.


Russian vine ◽  
2020 ◽  
Vol 14 ◽  
pp. 85-89
Author(s):  
N.A Tikhomirova ◽  
◽  
M.R. Beibulatov ◽  
N.A. Urdenko ◽  
R.A. Buival ◽  
...  

The economic efficiency of the cultivation of grapes as a branch of agriculture depends on the adaptation of grape varieties to the soil and climatic conditions of the place of growth. When developing new agricultural practices and technological solutions for the cultivation of grapes, it is necessary to assess the econom-ic efficiency of the proposed innovative ap-proaches. The cultivation of such grape varie-ties is becoming important and relevant, which, with high productivity and the use of differen-tiated care technology, require minimal costs when servicing the bushes and harvesting. In-creasing labor productivity in the viticulture industry is the most important condition for the intensive development of production. One of these conditions today is the formation of a bush according to the technology element, the shape of a bush AZOS-1, which allows to re-duce the cost of care and harvesting of grapes. The conducted research on the technology of cultivation of table grape varieties in connec-tion with the use of a new form of bush made it possible to economically substantiate the economic efficiency of growing grapes.


2021 ◽  
Vol 2 (68) ◽  
pp. 162-176
Author(s):  
Roman Alekseyevich Buival ◽  
◽  
Magometsaigit Rasulovich Beibulatov ◽  
Nadezhda Aleksandrovna Tikhomirova ◽  
Natalia Aleksandrovna Urdenko ◽  
...  

2016 ◽  
Vol 18 (02) ◽  
pp. 160-163
Author(s):  
Gurlabh S. Brar ◽  
M.I.S. Gill ◽  
N.K. Arora ◽  
H.S. Dhaliwal
Keyword(s):  

2015 ◽  
Vol 19 (1) ◽  
pp. 76-98 ◽  
Author(s):  
Delia Elena Urcan ◽  
Mihai-Lucian Lung ◽  
Simone Giacosa ◽  
Fabrizio Torchio ◽  
Alessandra Ferrandino ◽  
...  

2004 ◽  
Author(s):  
George Kerridge ◽  
Angela Gackle

Riesling, Chardonnay, Shiraz and Cabernet Sauvignon grapes can make magnificent wines but there are also many other excellent wine varieties that for many of us are rarely experienced. Vines for Wines will expand the wine lover’s knowledge and appreciation of a great range of wines and help to explore their individual preferences for specific varieties, blends, flavours and styles. This book is based on the highly successful Wine Grape Varieties, which is an aid to identifying grape vines. Vines for Wines, however, focuses on wines from the average consumer’s point-of-view, introducing the different wine grape varieties and the wines made from them, including blends. Each variety is represented by a colour photograph of the grape variety, its current world plantings, wine produced and notes describing the varietal characters for each wine grape variety. The tasting terms and wine notes for each variety provide a benchmark for the consumer to assess the quality of wines they drink, and to allow them to share and compare their experiences confidently with other wine lovers.


2019 ◽  
Vol 15 ◽  
pp. 01004 ◽  
Author(s):  
M. Retallack ◽  
L. Thomson ◽  
M. Keller

We provide a summary of two recent studies that investigated the role that three native insectary plants can play in promoting predatory arthropods, and thereby to enhance biological control of vineyard pests in Australia. Native plants are preferred as supplementary flora, as they are locally-adapted to Australia's climatic conditions. Stands of mature Bursaria spinosa, Leptospermum continentale and Rytidosperma ssp. located adjacent to, or in vineyards, in South Australia were sampled for arthropods in 2013/14. Grapevines were also sampled to explore relationships between each plant and associated arthropods using common diversity indices. Twenty seven thousand and ninety-one individual invertebrate specimens were collected, comprising 20 orders and 287 morphospecies. These were categorised into functional groups of predators, herbivores and other. Predatory arthropods dominated the diversity of morphospecies present on each plant. The richness of predator morphospecies across all plant types was nearly double the number found in association with grapevines. It may be possible to increase the functional diversity of predatory arthropods by more than 3x when either B. spinosa or L. continentale is present versus grapevines only, and increase the net number of predator morphospecies by around 27% when Rytidosperma ssp. are planted in combination with grapevines. The selected plants provide a suitable habitat to support diverse and functional populations of predatory arthropods. The opportunity to plant selected native insectary species could help wine grape growers save time and resources by producing fruit with lower pest incidence, while enhancing biodiversity associated with vineyards.


Author(s):  
Yan Hao ◽  
Yanjun Wang ◽  
Yashan Li ◽  
Kexu Cui ◽  
Tingting Xue ◽  
...  

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