Abstract

In livestock farming, during calving often human assistance is required to the cow and the unborn in order to guarantee their health and preserve the herd. Reliable calving time prediction is fundamental to enable the operator to act quickly and reduce potential injury to the calf directly caused by the mother or by environmental factors. The prediction is of particular importance for pregnant cows in extensive grazing areas where, because of the territorial extension, it is difficult to quickly intervene when needed. In order to solve these problems, a new GPS-Calving Alarm (GPS-CAL) was designed, manufactured and tested to analyze its technical and economic performance. The device accurately identifies the time when delivery begins and advises the farmer via SMS. The SMS includes birth event date and hour, animal ID and geographical coordinates of the partum point. The position is measured through a GPS receiver embedded in the device. By importing the GPS coordinates into a common application for mobile phones and following the visual instructions, it is possible to reach the animals at pasture. In order to evaluate device performance, both laboratory and field tests were carried out. Laboratory tests showed GPS adopted receiver accuracy (1.2m) and an adequate battery life (over 1month) for monitoring calving events in grazing areas. Field tests, carried out in intensive and extensive breeding conditions, confirmed that the GPS-CAL system worked well, and was highly reliable (sensitivity of 100%, positive predictive value PPV of 100%). Finally, the economic aspects relative to the adoption of the GPS-CAL system were analyzed. The possibility to monitor 10calvings/year by each device, at a unitary cost of €31,5/birth, sustainable by the farmer were taken into consideration. The originality and effectiveness of the GPS-CAL system, as confirmed by workers in the sector, allowed the authors, the Università degli Studi di Milano and the Sisteck (Sassuolo, Italy) to patent the system in Italy and Europe.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.