Radun V., Dokic D., Gantner V. (2021). Implementing artificial intelligence as a part of precision dairy farming for enabling sustainable dairy farming. Economics of agriculture, 01/12/2021, vol. 68, n. 4, p. 869-880.
https://doi.org/10.5937/ekoPolj2104869R
https://doi.org/10.5937/ekoPolj2104869R
Titre : | Implementing artificial intelligence as a part of precision dairy farming for enabling sustainable dairy farming (2021) |
Auteurs : | V. Radun ; D. Dokic ; V. Gantner |
Type de document : | Article |
Dans : | Economics of agriculture (vol. 68, n. 4, December 2021) |
Article en page(s) : | p. 869-880 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 06 - AGRICULTURE. FORÊTS. PÊCHES ; 6.6 - Technique Agricole (sols, engrais, mécanisation)Thésaurus IAMM INTELLIGENCE ARTIFICIELLE ; EXPLOITATION LAITIERE ; PRODUCTION LAITIERE ; AGRICULTURE DE PRECISION ; DURABILITE ; IMPACT SUR L'ENVIRONNEMENT ; ELEVAGE ; SYSTEME DE PRODUCTION ; PRODUCTION ANIMALE ; CROATIE |
Résumé : | The purpose of this paper is to consider implementation of Artificial Intelligence as a part of Precision Dairy Farming, as a way of processing, analysing and managing Big data, in order to enable sustainable dairy cattle farm. Increasing the volume of livestock production in the future and measuring the level of environmental impact becomes one of the most pressing concerns. The aim is to evaluate the impact of animals production level on the ammonium pollution from dairy cattle farm using precision dairy farming technologies. The results indicate significant variability in estimated ammonium pollution from dairy cattle farms due to the animals production indicating positive correlation between daily milk production and ammonium pollution. The test day records, as Artificial Intelligence application in precision dairy farming could be used both for assessing the ammonium pollution from farms and timely prevention and correction of inadequate management towards sustainable dairy production systems. |
Cote : | En ligne |
URL / DOI : | https://doi.org/10.5937/ekoPolj2104869R |