Following the need for actions aimed at making food production more sustainable and less harmful to the environment, the livestock sector must become more efficient, in particular with respect to greenhouse gases emitted by cattle (e.g., methane from enteric fermentation and methane and nitrous oxide from manure storage and management). In this framework, the INDACAT project aims to adopt Precision Livestock Farming (PLF) tools to continuously monitor cows under multiple aspects of the entire cattle chain to manage and quantify the progress achievable with the introduction of innovative monitoring in cattle farming. Each of the four involved research units will focus on a specific aspect of cattle farming, and in particular on the assessment of barn environment (i.e. microclimate and air quality, energy and water use) of intensive and organic dairy cattle farms, on the grazing behavior of cows in extensive systems (i.e. use of GIS and IoT innovative technology), on the social behavior and interactions among cows in intensive systems (i.e. validation of proximity sensors and analysis of social behavior data in relation to animal welfare and performance), and lastly on the weaning and growth of female calves (i.e. traditional and innovative weaning techniques). Through data collection and subsequent processing, the expected outcomes of INDACAT project include an overall improvement in livestock efficiency leading towards resource-efficient and competitive farming, farm digitalization and more sustainable productions.
The attended outcomes of the project INstructions from PLF Data Analysis to improve the CATtle farming (INDACAT) / D. Lovarelli, G. Bambi, M. Barbari, V. Becciolini, M. Bonfanti, M. Bovo, S.M.C. Porto, P. Tassinari, M. Guarino - In: Precision Livestock Farming 2024[s.l] : ECPLF, 2024 Sep. - ISBN 979-12-210-6736-1. - pp. 1650-1656 (( Intervento presentato al 11. convegno European Conference on Precision Livestock Farming tenutosi a Bologna nel 2024.
The attended outcomes of the project INstructions from PLF Data Analysis to improve the CATtle farming (INDACAT)
D. Lovarelli
Primo
;M. GuarinoUltimo
2024
Abstract
Following the need for actions aimed at making food production more sustainable and less harmful to the environment, the livestock sector must become more efficient, in particular with respect to greenhouse gases emitted by cattle (e.g., methane from enteric fermentation and methane and nitrous oxide from manure storage and management). In this framework, the INDACAT project aims to adopt Precision Livestock Farming (PLF) tools to continuously monitor cows under multiple aspects of the entire cattle chain to manage and quantify the progress achievable with the introduction of innovative monitoring in cattle farming. Each of the four involved research units will focus on a specific aspect of cattle farming, and in particular on the assessment of barn environment (i.e. microclimate and air quality, energy and water use) of intensive and organic dairy cattle farms, on the grazing behavior of cows in extensive systems (i.e. use of GIS and IoT innovative technology), on the social behavior and interactions among cows in intensive systems (i.e. validation of proximity sensors and analysis of social behavior data in relation to animal welfare and performance), and lastly on the weaning and growth of female calves (i.e. traditional and innovative weaning techniques). Through data collection and subsequent processing, the expected outcomes of INDACAT project include an overall improvement in livestock efficiency leading towards resource-efficient and competitive farming, farm digitalization and more sustainable productions.File | Dimensione | Formato | |
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