Aim of this study was to evaluate the factors that influence the activity time budget patterns of farmed dairy goats kept indoors. Dairy goats in three farms located in Northern Italy were continuously recorded from September 2021 to April 2022, and 20 days per farm were randomly selected for the analysis. Five categories of behaviours (i.e., resting, feeding, moving, standing, other behaviours) were assessed by a single assessor applying a scan sampling method at 30 min interval. Information on routines was collected (e.g., time of feed delivery, milking, cleaning, adding/removing bedding). Percentages of activities performed by goats were analysed by aligned rank transformation ANOVA to test the effects of Farm (F; F1, F2, F3), Time Band (TB; D: dark, L: light), Season (S; S1: cold season, T = 5.9±3.07 °C; S2: temperate season, T = 13.7±4.81 °C) and their interactions (i.e., F×TB and F×S). Our analysis showed that time budget of activities was significantly affected by both F×TB and F×S interactions (e.g., resting: F1-L: 31.8%, F2-L: 38.6%, F1-S1: 50.3%, F3-S1: 58.4%, P<0.05; feeding: F2-L: 34.4%, F3-L: 44.7%, F1-S2: 21.4%, F3-S2: 26.8%, P<0.05; moving: F2-L: 4.7%, F3-L: 8.1%, F2-S1: 2.5%, F3-S1: 4.1%, P<0.001). This suggests that management could influence the time budget of goats: for example, higher resting was found in F3 compared to F1 and F2 during D, possibly due to higher stocking density and amount of straw litter; 77.3% vs. 70.7% and 66.1%, respectively; P<0.001). Although preliminary, the results of this study show that routine and management can have a significant effect on time budget of goats. Furthermore, this study suggests the importance of including information on farm routines when planning behavioural observations, especially if used in welfare assessment protocol.

Factors influencing the time budget of dairy goats in intensive farming systems

Benedetta Torsiello;Manuela Renna;Luca Battaglini;
2025-01-01

Abstract

Aim of this study was to evaluate the factors that influence the activity time budget patterns of farmed dairy goats kept indoors. Dairy goats in three farms located in Northern Italy were continuously recorded from September 2021 to April 2022, and 20 days per farm were randomly selected for the analysis. Five categories of behaviours (i.e., resting, feeding, moving, standing, other behaviours) were assessed by a single assessor applying a scan sampling method at 30 min interval. Information on routines was collected (e.g., time of feed delivery, milking, cleaning, adding/removing bedding). Percentages of activities performed by goats were analysed by aligned rank transformation ANOVA to test the effects of Farm (F; F1, F2, F3), Time Band (TB; D: dark, L: light), Season (S; S1: cold season, T = 5.9±3.07 °C; S2: temperate season, T = 13.7±4.81 °C) and their interactions (i.e., F×TB and F×S). Our analysis showed that time budget of activities was significantly affected by both F×TB and F×S interactions (e.g., resting: F1-L: 31.8%, F2-L: 38.6%, F1-S1: 50.3%, F3-S1: 58.4%, P<0.05; feeding: F2-L: 34.4%, F3-L: 44.7%, F1-S2: 21.4%, F3-S2: 26.8%, P<0.05; moving: F2-L: 4.7%, F3-L: 8.1%, F2-S1: 2.5%, F3-S1: 4.1%, P<0.001). This suggests that management could influence the time budget of goats: for example, higher resting was found in F3 compared to F1 and F2 during D, possibly due to higher stocking density and amount of straw litter; 77.3% vs. 70.7% and 66.1%, respectively; P<0.001). Although preliminary, the results of this study show that routine and management can have a significant effect on time budget of goats. Furthermore, this study suggests the importance of including information on farm routines when planning behavioural observations, especially if used in welfare assessment protocol.
2025
76th Annual Meeting of the European Federation of Animal Science (EAAP)
Innsbruck (Austria)
25-29 Agosto 2025
Book of Abstracts of the 76th Annual Meeting of the European Federation of Animal Science
European Federation of Animal Science (EAAP)
396
396
Dairy goats, time budget, scan sampling method, intensive systems
Benedetta Torsiello, Silvana Mattiello, Manuela Renna, Luca Battaglini, Stefania Celozzi, Monica Battini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2095411
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