Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review
The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyar...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Horticulturae |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2311-7524/9/3/399 |
| _version_ | 1797611357597597696 |
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| author | Massimo Vincenzo Ferro Pietro Catania |
| author_facet | Massimo Vincenzo Ferro Pietro Catania |
| author_sort | Massimo Vincenzo Ferro |
| collection | DOAJ |
| description | The potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyard monitoring is set to increase in the coming years, enabling large amounts of information to be obtained. However, the large number of sensors developed and the great amount of data that can be collected are not always easy to manage, as it requires cross-sectoral expertise. The preliminary section of the review presents the scenario of precision viticulture, highlighting its potential and possible applications. This review illustrates the types of sensors and their operating principles. Remote platforms such as satellites, unmanned aerial vehicles (UAV) and proximal platforms are also presented. Some supervised and unsupervised algorithms used for object-based image segmentation and classification (OBIA) are then discussed, as well as a description of some vegetation indices (VI) used in viticulture. Photogrammetric algorithms for 3D canopy modelling using dense point clouds are illustrated. Finally, some machine learning and deep learning algorithms are illustrated for processing and interpreting big data to understand the vineyard agronomic and physiological status. This review shows that to perform accurate vineyard surveys and evaluations, it is important to select the appropriate sensor or platform, so the algorithms used in post-processing depend on the type of data collected. Several aspects discussed are fundamental to the understanding and implementation of vineyard variability monitoring techniques. However, it is evident that in the future, artificial intelligence and new equipment will become increasingly relevant for the detection and management of spatial variability through an autonomous approach. |
| first_indexed | 2024-03-11T06:27:45Z |
| format | Article |
| id | doaj.art-18cc5d061ae64413b57a5e949772f10b |
| institution | Directory Open Access Journal |
| issn | 2311-7524 |
| language | English |
| last_indexed | 2024-03-11T06:27:45Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Horticulturae |
| spelling | doaj.art-18cc5d061ae64413b57a5e949772f10b2023-11-17T11:25:06ZengMDPI AGHorticulturae2311-75242023-03-019339910.3390/horticulturae9030399Technologies and Innovative Methods for Precision Viticulture: A Comprehensive ReviewMassimo Vincenzo Ferro0Pietro Catania1Department of Agricultural, Food and Forest Sciences (SAAF), University of Palermo, Building 4, 90128 Palermo, ItalyDepartment of Agricultural, Food and Forest Sciences (SAAF), University of Palermo, Building 4, 90128 Palermo, ItalyThe potential of precision viticulture has been highlighted since the first studies performed in the context of viticulture, but especially in the last decade there have been excellent results have been achieved in terms of innovation and simple application. The deployment of new sensors for vineyard monitoring is set to increase in the coming years, enabling large amounts of information to be obtained. However, the large number of sensors developed and the great amount of data that can be collected are not always easy to manage, as it requires cross-sectoral expertise. The preliminary section of the review presents the scenario of precision viticulture, highlighting its potential and possible applications. This review illustrates the types of sensors and their operating principles. Remote platforms such as satellites, unmanned aerial vehicles (UAV) and proximal platforms are also presented. Some supervised and unsupervised algorithms used for object-based image segmentation and classification (OBIA) are then discussed, as well as a description of some vegetation indices (VI) used in viticulture. Photogrammetric algorithms for 3D canopy modelling using dense point clouds are illustrated. Finally, some machine learning and deep learning algorithms are illustrated for processing and interpreting big data to understand the vineyard agronomic and physiological status. This review shows that to perform accurate vineyard surveys and evaluations, it is important to select the appropriate sensor or platform, so the algorithms used in post-processing depend on the type of data collected. Several aspects discussed are fundamental to the understanding and implementation of vineyard variability monitoring techniques. However, it is evident that in the future, artificial intelligence and new equipment will become increasingly relevant for the detection and management of spatial variability through an autonomous approach.https://www.mdpi.com/2311-7524/9/3/399remote sensingproximal sensingprecision viticulturephotogrammetryimage processingmachine learning |
| spellingShingle | Massimo Vincenzo Ferro Pietro Catania Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review Horticulturae remote sensing proximal sensing precision viticulture photogrammetry image processing machine learning |
| title | Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review |
| title_full | Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review |
| title_fullStr | Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review |
| title_full_unstemmed | Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review |
| title_short | Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review |
| title_sort | technologies and innovative methods for precision viticulture a comprehensive review |
| topic | remote sensing proximal sensing precision viticulture photogrammetry image processing machine learning |
| url | https://www.mdpi.com/2311-7524/9/3/399 |
| work_keys_str_mv | AT massimovincenzoferro technologiesandinnovativemethodsforprecisionviticultureacomprehensivereview AT pietrocatania technologiesandinnovativemethodsforprecisionviticultureacomprehensivereview |