Naslov
Precizne tehnologije u funkciji realizacije optimalne tjelesne kondicije krmača
(Precise technologies in the function of realizing the optimal physical condition of sows)

Autori
Gantner, Vesna

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Zbornik predavanja - 17.savjetovanje uzgajivača svinja u Republici Hrvatskoj / Sokolić, D. - Osijek : Hrvatska agencija za poljoprivredu i hranu, 2022, 99-107

Skup
17. savjetovanje uzgajivača svinja u Republici Hrvatskoj

Mjesto i datum
Tuhelj, Hrvatska, 12.04.2022. - 13.04.2022

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Domaća recenzija

Ključne riječi
precizne tehnologije ; tjelesna kondicija ; krmače
(precision technologies ; physical condition ; sows)

Sažetak
The application of precise technologies in animal production implies automated remote detection and monitoring of identified animals with regard to productivity, fertility, health and welfare characteristics based on analysis of production data (animal recording), images, sounds, body weight and fitness and various real-time biological parameters. Furthermore, the application of these technologies enables early detection of individual disorders, diseases and physiological / health status at the level of an individual animal, group of animals or at the level of the entire farm. Precision technologies work by having sensors (cameras, microphones, thermometers and accelerometers) monitor or record information such as images, sound, the temperature of an animal or object, and the movements of groups or individual animals. Sensor data is stored or sent directly to the main processor followed by analysis using various algorithms. A software algorithm is a computer procedure that precisely defines what steps a computer needs to take to solve a particular problem using input to determine the solution (output). Developers initiate the process by writing an algorithm that instructs the computer how to perform certain actions needed to solve the problem. The value of the algorithm for farmers depends on its ability to transform sensor data to biological outcome. Examples of sensor data are the percentage of time a pig spends lying down to determine the biological result of “lameness” or coughing frequency to detect the biological outcome of “respiratory disease”. Finally, sensor data, combined with individual animal identifications, reference observations and production data, are integrated into algorithms to provide relevant information and warnings on pig health, productivity, fertility and welfare.

Izvorni jezik
Hrvatski

Znanstvena područja
Poljoprivreda (agronomija)

POVEZANOST RADA