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Agriculture
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Precision Viticulture and Enology: Technologies and Applications
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Precision Viticulture and Enology: Technologies and Applications

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 25637

Special Issue Editor

Dr. Paolo Storchi

E-Mail Website1 Website2
Guest Editor
CREA—Research Centre for Viticulture and Enology, Viale Santa Margherita 80, 52100 Arezzo, Italy
Interests: precision viticulture; sustainability; plant–environment interactions; growing environments; quality of grapes and wine; grapevine ecophysiology; abiotic stress and climate change

Special Issue Information

Dear Colleagues,

This Special Issue of Agriculture invites original research to improve our knowledge in the field of new technology of precision and digital farming in viticulture and enology.

Over the last decade, precision farming and developed tools (GIS technology, sensors, software, actuators, and controllers) have offered new possibilities to monitor site-specific features and crop status. Moreover, tools such as information communication technologies (ICT) have developed databases and models that allow targeting better management choices. Altogether, these technological possibilities have made crop management strategies feasible which are conducive to a sustainable process and have also led to an automatic system of traceability in terms of inputs and operations applied.

We invite both theoretical and application-oriented studies to be submitted on (but not limited to) the following topics: 1) mapping plant health and crop yield; 2) soil mapping; 3) image processing from remote and proximal sensing; 4) robots and variable rate technologies; 5) decision support tools; 6) automated irrigation scheduling; 7) crop stress monitoring; 8) wineries optimization; and 9) economic analysis of efficiency and sustainability.

Research papers, communications, and review articles are all welcome. 

Dr. Paolo Storchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • Vineyard management
  • Information communication technologies
  • Remote and proximal sensing
  • Soil mapping
  • Image analysis
  • DSS
  • Web-GIS application
  • Precision irrigation
  • VRT and IoT platforms
  • Control systems of sustainability
  • Traceability
  • Wine production procedures
 

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Published Papers (5 papers)

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Research

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18 pages, 8452 KiB  
Article
Modeling °Brix and pH in Wine Grapes from Satellite Images in Colchagua Valley, Chile
by Sandra N. Fredes, Luis Á. Ruiz and Jorge A. Recio
Agriculture 2021, 11(8), 697; https://doi.org/10.3390/agriculture11080697 - 24 Jul 2021
Cited by 3 | Viewed by 3955
Abstract
To monitor the ripeness and composition of wine grape berries and establish an optimal harvest date, the determination of °Brix and pH is vital. This research studies two harvest seasons of Cabernet Sauvignon wine grapes: 2017 and 2018. Field data were periodically collected [...] Read more.
To monitor the ripeness and composition of wine grape berries and establish an optimal harvest date, the determination of °Brix and pH is vital. This research studies two harvest seasons of Cabernet Sauvignon wine grapes: 2017 and 2018. Field data were periodically collected to follow the phenological state of the fruits. In parallel, eight bands and four spectral indices from Sentinel-2 image time series were used, which are directly related to the foliage properties and activity, and indirectly to the fruit evolution. They were related to the variables measured from field samples: °Brix and pH. The °Brix models obtained with the spectral indices presented an R2 of 69% and 73% in the 2017 and 2018 seasons, respectively. In pH modeling, the 2017 season had low R2 results, reaching 43%, improving considerably in the 2018 season, reaching 63.8%. Estimated Brix and pH maps were obtained, expressing the spatial variability in the evolution of the fruit, which is useful for zoning the plots and to improve the sampling task prior to harvest. They are therefore a valuable tool to monitor the maturation, to improve the efficiency of harvest and subsequently, the quality of the wine. Full article
(This article belongs to the Special Issue Precision Viticulture and Enology: Technologies and Applications)
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14 pages, 3559 KiB  
Article
Fermentative Potential of Native Yeast Candida famata for Prokupac Grape Must Fermentation
by Stojan Mančić, Bojana Danilović, Marko Malićanin, Sandra Stamenković Stojanović, Nada Nikolić, Miodrag Lazić and Ivana Karabegović
Agriculture 2021, 11(4), 358; https://doi.org/10.3390/agriculture11040358 - 16 Apr 2021
Cited by 11 | Viewed by 3958
Abstract
The fermentative potential of native Candida famata isolates from wild and cultivated blackberries was evaluated for potential application in Prokupac grape must fermentation. 5 isolates, out of a total 22 isolated yeasts, were identified as C. famata. After the initial screening of fermentative [...] Read more.
The fermentative potential of native Candida famata isolates from wild and cultivated blackberries was evaluated for potential application in Prokupac grape must fermentation. 5 isolates, out of a total 22 isolated yeasts, were identified as C. famata. After the initial screening of fermentative performances, microfermentation was performed in a sterile grape must. Produced samples were analyzed using the HPLC technique. All isolates showed an ability to grow at lower temperatures, good tolerance to 7% ethanol and 300 ppm of SO2. C. famata isolates WB-1, WB-2 and W-5 had similar fermentation performance, but WB-1 isolate was chosen for validation at a laboratory-scale level according to a pleasant, fruity aroma, highest fermentative vigor and power, good organic acid profile and the highest level of ethanol and glycerol produced in micro-vinification experiments. Good enological performance of selected C. famata WB-1 isolate is confirmed by higher level of glycerol, lower level of ethanol and acetic acid in wine samples produced in pure and sequential fermentation, when compared to the control sample. Throughout the selection of C. famata yeasts with good enological potential, this work gives a contribution in the area of precision enology, aiming to find a perfect match between non-exploited yeasts and “autochthonous” grape cultivar Prokupac. Full article
(This article belongs to the Special Issue Precision Viticulture and Enology: Technologies and Applications)
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19 pages, 4439 KiB  
Article
Measuring Canopy Geometric Structure Using Optical Sensors Mounted on Terrestrial Vehicles: A Case Study in Vineyards
by Daniel Queirós da Silva, André Silva Aguiar, Filipe Neves dos Santos, Armando Jorge Sousa, Danilo Rabino, Marcella Biddoccu, Giorgia Bagagiolo and Marco Delmastro
Agriculture 2021, 11(3), 208; https://doi.org/10.3390/agriculture11030208 - 4 Mar 2021
Cited by 4 | Viewed by 2809
Abstract
Smart and precision agriculture concepts require that the farmer measures all relevant variables in a continuous way and processes this information in order to build better prescription maps and to predict crop yield. These maps feed machinery with variable rate technology to apply [...] Read more.
Smart and precision agriculture concepts require that the farmer measures all relevant variables in a continuous way and processes this information in order to build better prescription maps and to predict crop yield. These maps feed machinery with variable rate technology to apply the correct amount of products in the right time and place, to improve farm profitability. One of the most relevant information to estimate the farm yield is the Leaf Area Index. Traditionally, this index can be obtained from manual measurements or from aerial imagery: the former is time consuming and the latter requires the use of drones or aerial services. This work presents an optical sensing-based hardware module that can be attached to existing autonomous or guided terrestrial vehicles. During the normal operation, the module collects periodic geo-referenced monocular images and laser data. With that data a suggested processing pipeline, based on open-source software and composed by Structure from Motion, Multi-View Stereo and point cloud registration stages, can extract Leaf Area Index and other crop-related features. Additionally, in this work, a benchmark of software tools is made. The hardware module and pipeline were validated considering real data acquired in two vineyards—Portugal and Italy. A dataset with sensory data collected by the module was made publicly available. Results demonstrated that: the system provides reliable and precise data on the surrounding environment and the pipeline is capable of computing volume and occupancy area from the acquired data. Full article
(This article belongs to the Special Issue Precision Viticulture and Enology: Technologies and Applications)
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17 pages, 2345 KiB  
Article
Application of a Daily Crop Water Stress Index to Deficit Irrigate Malbec Grapevine under Semi-Arid Conditions
by Krista C. Shellie and Bradley A. King
Agriculture 2020, 10(11), 492; https://doi.org/10.3390/agriculture10110492 - 22 Oct 2020
Cited by 16 | Viewed by 5473
Abstract
Precision irrigation of wine grape is hindered by the lack of an automated method for monitoring vine water status. The objectives of this study were to: Validate an automated model for remote calculation of a daily crop water stress index (CWSI) [...] Read more.
Precision irrigation of wine grape is hindered by the lack of an automated method for monitoring vine water status. The objectives of this study were to: Validate an automated model for remote calculation of a daily crop water stress index (CWSI) for the wine grape (Vitis vinifera L.) cultivar Malbec and evaluate its suitability for use in irrigation scheduling. Vines were supplied weekly with different percentages of evapotranspiration-based estimated water demand (ETc) over four growing seasons. In the fifth growing season, different daily CWSI threshold values were used to trigger an irrigation event that supplied 28 mm of water. All three indicators of vine water status (CWSI, midday leaf water potential (Ψlmd), and juice carbon isotope ratio (δ13C)) detected an increase in stress severity as the irrigation amount decreased. When the irrigation amount decreased from 100% to 50% ETc, 70% to 35% ETc, or the daily CWSI threshold value increased from 0.4 to 0.6, berry fresh weight and juice titratable acidity decreased, juice δ13C increased, the weekly CWSI increased, and Ψlmd decreased. Under the semi-arid conditions of this study, utilizing a daily CWSI threshold for irrigation scheduling reduced the irrigation amount without compromising the yield or changes in berry composition and remotely provided automated decision support for managing water stress severity in grapevine. Full article
(This article belongs to the Special Issue Precision Viticulture and Enology: Technologies and Applications)
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Review

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20 pages, 3855 KiB  
Review
State of the Art of Monitoring Technologies and Data Processing for Precision Viticulture
by Marco Ammoniaci, Simon-Paolo Kartsiotis, Rita Perria and Paolo Storchi
Agriculture 2021, 11(3), 201; https://doi.org/10.3390/agriculture11030201 - 28 Feb 2021
Cited by 46 | Viewed by 7929
Abstract
Precision viticulture (PV) aims to optimize vineyard management, reducing the use of resources, the environmental impact and maximizing the yield and quality of the production. New technologies as UAVs, satellites, proximal sensors and variable rate machines (VRT) are being developed and used more [...] Read more.
Precision viticulture (PV) aims to optimize vineyard management, reducing the use of resources, the environmental impact and maximizing the yield and quality of the production. New technologies as UAVs, satellites, proximal sensors and variable rate machines (VRT) are being developed and used more and more frequently in recent years thanks also to informatics systems able to read, analyze and process a huge number of data in order to give the winegrowers a decision support system (DSS) for making better decisions at the right place and time. This review presents a brief state of the art of precision viticulture technologies, focusing on monitoring tools, i.e., remote/proximal sensing, variable rate machines, robotics, DSS and the wireless sensor network. Full article
(This article belongs to the Special Issue Precision Viticulture and Enology: Technologies and Applications)
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