Introduction: The aim of this study was to evaluate the transformative potential of precision livestock farming (PLF) in dairy production, nutrition, and reproductive efficiency by implementing proactive management strategies that utilize real-time data. Methods: Data were gathered from a commercial dairy farm, employing a 3D accelerometer system attached to ear-tags to monitor activity and rumination behavior. Additionally, information on animal-related events such as oestrus, artificial insemination, clinical diseases, and treatments was recorded. Results: It was observed that there were differences in rumination between positive and negative cows in the days following artificial insemination (AI). Specifically, from day 0 to day 16, negative cows exhibited a higher rumination time compared to positive cows, with this contrast being particularly significant on days 9 and 10. Over the duration of the study, cows that tested negative produced, on average, 0.78 kg more milk per day. Discussion: This suggests that animals with higher milk production were less likely to be pregnant, potentially due to increased nutrient allocation to the mammary gland, resulting in a more pronounced negative energy balance and consequently lower conception rates. Furthermore, the accelerometer utilized in this study was capable of distinguishing differences in daily lying time between pregnant and non-pregnant animals on the days of oestrus return. This finding highlights the potential for developing a system alert to identify “probable pregnant” and “probable non-pregnant” animals.

Two years of precision livestock management: harnessing ear tag device behavioral data for pregnancy detection in free-range dairy cattle on silage/hay-mix ration

Cavallini, Damiano;Giammarco, Melania;Vignola, Giorgio;De Matos Vettori, Julio;Prasinou, Paraskevi;Formigoni, Andrea;Fusaro, Isa
2025-01-01

Abstract

Introduction: The aim of this study was to evaluate the transformative potential of precision livestock farming (PLF) in dairy production, nutrition, and reproductive efficiency by implementing proactive management strategies that utilize real-time data. Methods: Data were gathered from a commercial dairy farm, employing a 3D accelerometer system attached to ear-tags to monitor activity and rumination behavior. Additionally, information on animal-related events such as oestrus, artificial insemination, clinical diseases, and treatments was recorded. Results: It was observed that there were differences in rumination between positive and negative cows in the days following artificial insemination (AI). Specifically, from day 0 to day 16, negative cows exhibited a higher rumination time compared to positive cows, with this contrast being particularly significant on days 9 and 10. Over the duration of the study, cows that tested negative produced, on average, 0.78 kg more milk per day. Discussion: This suggests that animals with higher milk production were less likely to be pregnant, potentially due to increased nutrient allocation to the mammary gland, resulting in a more pronounced negative energy balance and consequently lower conception rates. Furthermore, the accelerometer utilized in this study was capable of distinguishing differences in daily lying time between pregnant and non-pregnant animals on the days of oestrus return. This finding highlights the potential for developing a system alert to identify “probable pregnant” and “probable non-pregnant” animals.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11575/161442
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