Enhancing Farm-Level Decision Making through Innovation
New information and knowledge are important aspects of innovation in modern farming systems. There is currently an abundance of digital and data-driven solutions that can potentially transform our food systems. At a time when the general public has concerns about how food is produced and the impact...
Guardado en:
| Formato: | Online |
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| Lenguaje: | inglés |
| Publicado: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Materias: | |
| Acceso en línea: | ONIX_20220321_9783036533551_118 |
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| _version_ | 1869527923176767488 |
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| collection | Directory of Open Access Books |
| description | New information and knowledge are important aspects of innovation in modern farming systems. There is currently an abundance of digital and data-driven solutions that can potentially transform our food systems. At a time when the general public has concerns about how food is produced and the impact of farm production systems on the environment, strategies to increase public acceptance and the sustainability of food production are required more than ever. New tools and technology can provide timely insights into aspects such as nutrient profiles, the tracking of animal or plant wellbeing, and land-use options to enhance inputs and outputs associated with the farm business. Such solutions have the ultimate aim of enhancing production efficiency and contributing to the process of learning about the advantages of the innovation, while ensuring more sustainable food supplies. At the farm level, any new information needs to be in a useful format and beneficial for management and farm decision-making. The papers in this Special Issue evaluate agri-business innovation that can enhance farm-level decision-making. |
| format | Online |
| id | doab-20.500.12854ir-79682 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-796822024-03-28T03:31:26Z Enhancing Farm-Level Decision Making through Innovation Bell, Matt J. dairy cows computer vision behaviors monitoring management behavior birth observations sheep proximal sensing LiDAR photogrammetry grasslands pastures Adversarial-VAE tomato leaf disease identification image generation convolutional neural network potato management tuber formation stage precipitation patterns thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes New information and knowledge are important aspects of innovation in modern farming systems. There is currently an abundance of digital and data-driven solutions that can potentially transform our food systems. At a time when the general public has concerns about how food is produced and the impact of farm production systems on the environment, strategies to increase public acceptance and the sustainability of food production are required more than ever. New tools and technology can provide timely insights into aspects such as nutrient profiles, the tracking of animal or plant wellbeing, and land-use options to enhance inputs and outputs associated with the farm business. Such solutions have the ultimate aim of enhancing production efficiency and contributing to the process of learning about the advantages of the innovation, while ensuring more sustainable food supplies. At the farm level, any new information needs to be in a useful format and beneficial for management and farm decision-making. The papers in this Special Issue evaluate agri-business innovation that can enhance farm-level decision-making. 2022-03-21T16:31:37Z 2022-03-21T16:31:37Z 2022 book ONIX_20220321_9783036533551_118 9783036533551 9783036533568 https://directory.doabooks.org/handle/20.500.12854/79682 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5067 https://mdpi.com/books/pdfview/book/5067 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3356-8 10.3390/books978-3-0365-3356-8 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036533551 9783036533568 84 Basel open access |
| spellingShingle | dairy cows computer vision behaviors monitoring management behavior birth observations sheep proximal sensing LiDAR photogrammetry grasslands pastures Adversarial-VAE tomato leaf disease identification image generation convolutional neural network potato management tuber formation stage precipitation patterns thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes Enhancing Farm-Level Decision Making through Innovation |
| title | Enhancing Farm-Level Decision Making through Innovation |
| title_full | Enhancing Farm-Level Decision Making through Innovation |
| title_fullStr | Enhancing Farm-Level Decision Making through Innovation |
| title_full_unstemmed | Enhancing Farm-Level Decision Making through Innovation |
| title_short | Enhancing Farm-Level Decision Making through Innovation |
| title_sort | enhancing farm level decision making through innovation |
| topic | dairy cows computer vision behaviors monitoring management behavior birth observations sheep proximal sensing LiDAR photogrammetry grasslands pastures Adversarial-VAE tomato leaf disease identification image generation convolutional neural network potato management tuber formation stage precipitation patterns thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes |
| topic_facet | dairy cows computer vision behaviors monitoring management behavior birth observations sheep proximal sensing LiDAR photogrammetry grasslands pastures Adversarial-VAE tomato leaf disease identification image generation convolutional neural network potato management tuber formation stage precipitation patterns thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PS Biology, life sciences thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes |
| url | ONIX_20220321_9783036533551_118 |