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1.
Sci Data ; 10(1): 782, 2023 11 08.
Article in English | MEDLINE | ID: mdl-37938260

ABSTRACT

Monitoring livestock feeding behavior may help assess animal welfare and nutritional status, and to optimize pasture management. The need for continuous and sustained monitoring requires the use of automatic techniques based on the acquisition and analysis of sensor data. This work describes an open dataset of acoustic recordings of the foraging behavior of dairy cows. The dataset includes 708 h of daily records obtained using unobtrusive and non-invasive instrumentation mounted on five lactating multiparous Holstein cows continuously monitored for six non-consecutive days in pasture and barn. Labeled recordings precisely delimiting grazing and rumination bouts are provided for a total of 392 h and for over 6,200 ingestive and rumination jaw movements. Companion information on the audio recording quality and expert-generated labels is also provided to facilitate data interpretation and analysis. This comprehensive dataset is a useful resource for studies aimed at exploring new tools and solutions for precision livestock farming.


Subject(s)
Acoustics , Cattle , Feeding Behavior , Animals , Female , Farms , Lactation
2.
Data Brief ; 30: 105623, 2020 Jun.
Article in English | MEDLINE | ID: mdl-32420421

ABSTRACT

This dataset is composed of correlated audio recordings and labels of ingestive jaw movements performed during grazing by dairy cattle. Using a wireless microphone, we recorded sounds of three Holstein dairy cows grazing short and tall alfalfa and short and tall fescue. Two experts in grazing behavior identified and labeled the start, end, and type of each jaw movement: bite, chew, and chew-bite (compound movement). For each segment of raw audio corresponding to a jaw movement we computed four well-known features: amplitude, duration, zero crossings, and envelope symmetry. These features are in the dataset and can be used as inputs to build automated methods for classification of ingestive jaw movements. Cow's grazing behavior can be monitored and characterized by identifying and analyzing these masticatory events.

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