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Assessment of Sensitivity and Profitability of an Intravaginal Sensor for Remote Calving Prediction in Dairy Cattle

Authors :
Martina Crociati
Lakamy Sylla
Giuseppe Stradaioli
Maurizio Monaci
Alfonso Zecconi
Source :
Sensors; Volume 21; Issue 24; Pages: 8348, Sensors, Vol 21, Iss 8348, p 8348 (2021), Sensors (Basel, Switzerland)
Publication Year :
2021
Publisher :
Multidisciplinary Digital Publishing Institute, 2021.

Abstract

One critical point of dairy farm management is calving and neonatal first care. Timely calving assistance is associated with the reduction of calf mortality and postpartum uterine disease, and with improved fertility in dairy cattle. This study aimed to evaluate the performance and profitability of an intravaginal sensor for the prediction of stage II of labor in dairy farms, thus allowing proper calving assistance. Seventy-three late-gestating Italian Holstein cows were submitted to the insertion of an intravaginal device, equipped with light and temperature sensors, connected with a Central Unit for the commutation of a radio-signal into a cell phone alert. The remote calving alarm correctly identified the beginning of the expulsive phase of labor in 86.3% of the monitored cows. The mean interval from alarm to complete expulsion of the fetus was 71.56 ± 52.98 min, with a greater range in cows with dystocia (p = 0.012). The sensor worked correctly in both cold and warm weather conditions, and during day- or night-time. The intravaginal probe was well tolerated, as any cow showed lesions to the vaginal mucosa after calving. Using sex-sorted semen in heifers and beef bull semen in cows at their last lactation, the economic estimation performed through PrecisionTree™ software led to an income improvement of 119 € and 123 €/monitored delivery in primiparous and pluriparous cows, respectively. Remote calving alarm devices are key components of “precision farming” management and proven to improve animal welfare, to reduce calf losses and to increase farm incomes.

Details

Language :
English
ISSN :
14248220
Database :
OpenAIRE
Journal :
Sensors; Volume 21; Issue 24; Pages: 8348
Accession number :
edsair.doi.dedup.....775eed8b5eac19e385bac527cdf47719
Full Text :
https://doi.org/10.3390/s21248348