DEVELOPING A MATHEMATICAL MODEL FOR DETERMINING THE STATE OF CATTLE HOOVES BASED ON THERMOGRAM PROFILES

Inflammation in the cow hooves leads to a decrease in milk yield and may cause early culling of animals. Early diagnosis of the disease provides a reduction in the cost of treatment, allows maintaining the health and milk production of animals. The use of infrared thermography to determine the temperature of cattle limbs is a fast and non-invasive way to obtain reliable information about the animal's health. To develop a mathematical model for determining the state of cattle limbs based on the profiles of hoof thermograms, the authors processed the data of 20 cows of the Yaroslavl breed, which are on the 2^nd-4^th lactation, with a lactation period ranging between months 1 and 7. The data array was formed using a Guide C400M thermal imager in the IR range. Data on the physiological state of cattle were entered into the Matlab R2019b program. For color gradation, the RGB color space was selected. The presented mathematical model for processing the profile of thermograms makes it possible to collect information on the spatial and temporal dynamics of cattle hoof temperatures by thermophysiological categories. When determining the state of the limbs, the areas of spatio-temporal distribution of temperature in the hoof are identified in the form of a transformed segmentation profile of the thermogram into a matrix, where RGB is assigned to the pixels from each fragment of the area, indicating a certain temperature. Exceeding the values R > 230, G > 103, B < 0 symbolizes a temperature above 40°C and means the presence of inflammation in the hoof. The developed algorithm will allow a farm veterinarian to automatically receive information about the state of the hooves of each cow, determine the focus of inflammation, its location, and diagnose the disease.

dairy farming, diagnostics of hoof diseases, infrared thermography, Matlab

1. Концевая С.Ю. Биоинертный копытный клей для лечения копыт и копытец // Эффективное животноводство. 2021. № 2 (168). С. 61-63. EDN: NRKPDX.

2. Родионов Г.В. Стрессоустойчивость и стрессореактивность // Ветеринария сельскохозяйственных животных. 2006. № 2. С. 41-47. EDN: TEROWX.

3. Ярован Н.И., Смагина Т.В. Морфо-биохимические изменения крови при окислительном стрессе у коров с болезнями копыт // Проблемы и перспективы инновационного развития агротехнологий: Сборник материалов XX Международной научно-производственной конференции. Белгород: Белгородский государственный аграрный университет имени В.Я. Горина, 2016. С. 27-28. EDN: XSXNHF.

4. Самойлов А.А. Некробактериоз крупного рогатого скота (эпизоотология, диагностика и меры борьбы): Автореф. дис.. д-ра ветеринар. наук. Новосибирск, 1991. С. 25. EDN: ZJLFLD.

5. Hansen M.F., Smith M.L., Smith L.N., Abdul Jabbar K., Forbes D. Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device.Computers in Industry. 2018; 98: 14-22. https://doi.org/10.1016/j.compind.2018.02.011

6. Pavkin D.Yu., Dorokhov A.S., Vladimirov F.E., Dovlatov I.M., Lyalin K.S. Algorithms for detecting cattle diseases at early stages and for making diagnoses and related recommendationsm. Applied Sciences (Switzerland). 2021; 11: 11148. https://doi.org/10.3390/app112311148

7. Proshkin Y.A., Smirnov A.A., Sokolov A.V., Dovlatov I.M., Kachan S.A. Study of thermal modes of operation of SMD-LEDs in phyto-lamps. IOP Conference Series: Earth and Environmental Science. «International Conference on World Technological Trends in Agribusiness)). 2021; 624: 012091. https://doi.org/10.1088/1755-1315/624/1/012091

8. Moorman V.J., Reiser R.F., Mahaffey C.A., Peterson M.L.; McIlwraith C.W., Kawcak C.E. Use of an inertial measurement unit to assess the effect of forelimb lameness on three-dimensional hoof orientation in horses at a walk and trot. American journal of veterinary research. 2014; 75 (9): 800-808. https://doi.org/10.2460/ajvr.75.9.800

9. Mohling C.M.; Johnson A.K., Coetzee J.F., Karriker L.A., Abell C.E., Millman S.T., Stalder K.J. Kinematics as objective tools to evaluate lameness phases in multiparous sows. Livestock scienc. 2014; 165: 120-128. https://doi.org/10.1016/j.livsci.2014.04.031

10. Moorman V.J., Reiser R.E., Peterson M.L., McIlwraith C.W., Kawcak C.E. Effect of forelimb lameness on hoof kinematics of horses at a trot. American journal of veterinary research. 2013; 74 (9): 1192-1197. https://doi.org/10.2460/ajvr.74.9.1192

11. Кирсанов В.В., Павкин Д.Ю., Никитин Е.А., Довлатов И.М Методика оптимизации параметров машинного кормления крупного рогатого скота // Агроинженерия. 2021. № 1 (101). С. 10-14. https://doi.org/10.26897/2687-1149-2021-1-10-14

12. Tijssen M., Hernlund E., Rhodin M., Bosch S., Voskamp J.P, Nielen M., Serra Bragana F.M. Automatic detection of breakover phase onset in horses using hoof-mounted inertial measurement unit sensors. PLOS ONE. 2020; 15 (7): e0236181. https://doi.org/10.1371/joumal.pone.0236181

13. Мамедова Р.А. Особенности обработки тепловизионных изображений для диагностики заболеваний конечностей КРС // Техника и технологии в животноводстве. 2021. № 4 (44). С. 37-41. EDN: FLSSZZ.