| Titre : | Improving data management and decision support systems in agriculture |
| Auteurs : | L. Armstrong, ed. |
| Type de document : | E-Book |
| Editeur : | Cambridge [United Kingdom] : Burleigh Dodds Science Publishing, 2020 |
| ISBN/ISSN/EAN : | 978-1-00-304787-2 |
| Format : | 340 p. |
| Langues : | Anglais |
| Langues du résumé : | Anglais |
| Catégories : |
Catégories principales 06 - AGRICULTURE. FORÊTS. PÊCHES ; 6.5 - Gestion des ExploitationsThésaurus IAMM AGRICULTURE ; AIDE A LA DECISION ; ANALYSE DE DONNEES ; COLLECTE DE DONNEES ; TRAITEMENT DES DONNEES ; DONNEE STATISTIQUE ; DONNEE DE PRODUCTION ; SYSTEME DE PRODUCTION ; MODELE ; AGRICULTURE DE PRECISION |
| Résumé : | This collection reviews and summarises the wealth of research on key challenges in developing better data management and decision support systems (DSS) for farmers and examples of how those systems are being deployed to optimise efficiency in crop and livestock production. Part 1 reviews general issues underpinning effective decision support systems (DSS) such as data access, standards, tagging and security. Part 2 contains case studies of the practical application of data management and DSS in areas such as crop planting, nutrition and use of rotations, livestock feed and pasture management as well as optimising supply chains for fresh produce. With its distinguished editor and international team of authors, Improving data management and decision support systems in agriculture will be a standard reference for researchers in agriculture and computer science interested in improving data management, modelling and decision support systems in farming, as well as government and other agencies supporting the use of precision farming techniques, and companies supplying decision support services to the farming sector. |
| Note de contenu : |
Part 1: General issues
• 1. Key challenges for data management and decision making in agriculture • 2. Improving data access for more effective decision making in agriculture • 3. Improving data standards and integration for more effective decision making in agriculture • 4. Improving data identification/tagging for more effective decision making in agriculture • 5. Advances in data security for more effective decision making in agriculture • 6. Advances in Artificial Intelligence (AI) for more effective decision making in agriculture • 7. Improvements in precision agriculture/geospatial technologies/autonomous vehicles/real-time data for more effective decision making in agriculture Part 2: Case studies • 8. Developing planting/sowing decision support systems for farmers • 9. Developing decision support systems for managing crop growth/health: • 10. Developing decision support systems for applying crop fertiliser • 11. Developing decision support systems for crop rotations/cover cropping • 12. Developing decision support systems for crop yield prediction/harvesting • 13. Decision support systems for pest monitoring and management • 14. Developing decision support systems for agricultural supply chains • 15. Developing decision support systems for livestock management • 16. Developing decision support systems for pasture and rangeland management • 17. Developing decision support tools for small-holding and community gardens systems |
| Cote : | Réservé lecteur CIHEAM |
| URL / DOI : | https://doi.org/10.1201/9781003047872 |
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