Computation, AI and Simulation in Bioinformatics, Horticulture, Viticulture and Winemaking

A special issue of Computation (ISSN 2079-3197).

Deadline for manuscript submissions: 30 June 2024 | Viewed by 1517

Special Issue Editors


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Guest Editor
Humanitarian Pedagogical Academy, V.I. Vernadsky Crimean Federal University, 295007 Simferopol, Russia
Interests: computer science; computer simulation; neural networks; AI; modeling; precision farming; horticulture; viticulture; winemaking

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Guest Editor
Humanitarian Pedagogical Academy, V.I. Vernadsky Crimean Federal University, 295007 Simferopol, Russia
Interests: computer simulation; precision farming; viticulture; winemaking

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Guest Editor
Institute of Physics and Technology, V.I. Vernadsky Crimean Federal University, 295007 Simferopol, Russia
Interests: computer science; computer simulation; bioinformatics; neural network; viticulture

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Guest Editor
Nikitsky Botanical Gardens—National Scientific Center of Russian Academy of Sciences, 298648 Yalta, Russia
Interests: computer simulation; precision farming; viticulture; introduction; variety study and selection of apricot

Special Issue Information

Dear Colleagues,

Computations in horticulture, viticulture, and winemaking have significantly expanded the development of intelligent technologies in this area of research, allowing us to solve the problems of controlling and monitoring all phases of plant growth.

In terms of the use of AI in agriculture, such trends as the development of precision farming, crop production within a controlled environment, the introduction of robotic agricultural machinery, and unmanned aerial vehicles for monitoring agricultural land are more pronounced.

This happens through the use of resource-efficient sensors, deep machine learning, and intelligent computer applications for gardening.

We would like to receive manuscripts related to the methods and technologies of "smart" gardening, viticulture, and winemaking.

In addition, studies on bioinformatics, robotics, and precision farming are also welcome.

Dr. Anatoliy Kazak
Dr. Anna Dorofeeva
Dr. Marina Rudenko
Dr. Vadim Korzin
Guest Editors

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. Computation 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 1800 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

  • deep machine learning
  • smart horticulture, horticulture, viticulture, and winemaking
  • precision farming
  • sensors
  • agricultural robotics
  • information systems and AI in agriculture

Published Papers (1 paper)

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Research

18 pages, 9991 KiB  
Article
Intelligent Monitoring System to Assess Plant Development State Based on Computer Vision in Viticulture
by Marina Rudenko, Anatoliy Kazak, Nikolay Oleinikov, Angela Mayorova, Anna Dorofeeva, Dmitry Nekhaychuk and Olga Shutova
Computation 2023, 11(9), 171; https://doi.org/10.3390/computation11090171 - 03 Sep 2023
Cited by 1 | Viewed by 1248
Abstract
Plant health plays an important role in influencing agricultural yields and poor plant health can lead to significant economic losses. Grapes are an important and widely cultivated plant, especially in the southern regions of Russia. Grapes are subject to a number of diseases [...] Read more.
Plant health plays an important role in influencing agricultural yields and poor plant health can lead to significant economic losses. Grapes are an important and widely cultivated plant, especially in the southern regions of Russia. Grapes are subject to a number of diseases that require timely diagnosis and treatment. Incorrect identification of diseases can lead to large crop losses. A neural network deep learning dataset of 4845 grape disease images was created. Eight categories of common grape diseases typical of the Black Sea region were studied: Mildew, Oidium, Anthracnose, Esca, Gray rot, Black rot, White rot, and bacterial cancer of grapes. In addition, a set of healthy plants was included. In this paper, a new selective search algorithm for monitoring the state of plant development based on computer vision in viticulture, based on YOLOv5, was considered. The most difficult part of object detection is object localization. As a result, the fast and accurate detection of grape health status was realized. The test results showed that the accuracy was 97.5%, with a model size of 14.85 MB. An analysis of existing publications and patents found using the search “Computer vision in viticulture” showed that this technology is original and promising. The developed software package implements the best approaches to the control system in viticulture using computer vision technologies. A mobile application was developed for practical use by the farmer. The developed software and hardware complex can be installed in any vehicle. Such a mobile system will allow for real-time monitoring of the state of the vineyards and will display it on a map. The novelty of this study lies in the integration of software and hardware. Decision support system software can be adapted to solve other similar problems. The software product commercialization plan is focused on the automation and robotization of agriculture, and will form the basis for adding the next set of similar software. Full article
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