An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus
ABSTRACT: The study investigates the economics of sensor-assisted dairy health management and indicates a certain economic potential in the use of a commercial rumen bolus capable of tracking activity and core body temperature. The economic evaluation was performed applying a stochastic model with t...
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Elsevier
2025-03-01
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| Series: | Journal of Dairy Science |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0022030224013717 |
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| author | J. Pfrombeck M. Gandorfer E. Zeiler J. Ettema |
| author_facet | J. Pfrombeck M. Gandorfer E. Zeiler J. Ettema |
| author_sort | J. Pfrombeck |
| collection | DOAJ |
| description | ABSTRACT: The study investigates the economics of sensor-assisted dairy health management and indicates a certain economic potential in the use of a commercial rumen bolus capable of tracking activity and core body temperature. The economic evaluation was performed applying a stochastic model with the net return (NR) of investment of the sensor system as the target variable. The calculated NR considers the gross margin (GM) for both sensor-assisted and visual health monitoring, time savings through sensor-assisted monitoring, additional time spent addressing false positive messages from the sensor system, labor costs, and all costs associated with the investment in the sensor system. The analysis relies on a dataset acquired from a dairy research and demonstration farm on which 65 dairy cows were equipped with the sensor system. A comparison of health-related messages issued by the rumen bolus with disease diagnoses shows that the sensor system issued a message in 7 of 11 cases of retained placenta (sensitivity = 64%), in 19 of 31 cases of clinical hypocalcemia (sensitivity = 61%), in 30 of 70 cases of mastitis (sensitivity = 43%), in 6 of 24 cases of metritis (sensitivity = 25%), and in 2 of 42 cases of diseases of the locomotor system (sensitivity = 5%) in a defined observation period, in many cases several days before the visual diagnosis. SimHerd (A/S Viborg, Denmark) was applied to determine the GM as a function of incidence, SCC, risk of a mild case of disease, and days of milk withdrawal. In a workshop, veterinarians (n = 9) used the dataset to assess the effect of using the sensor system on these parameters. The empirical distributions given by the veterinarians' individual assessments were used to model the parameters considered in the calculation of the “sensor-assisted” GM. For the modeled Holstein herds with a milk yield of 9,000 kg, simulation results show that average NR of investment ranges from +€23 to +€119/cow per year for a herd of poor health, from −€12 to +€84/cow per year for a herd of average health, and from −€33 to +€63/cow per year for a herd of good health, depending on the scenario. The assumptions made regarding changes in labor had a strong influence on the calculated NR of investment. For a full economic evaluation of the sensor system, other functions (estrus detection, calving detection) and functional extensions (e.g., monitoring rumination) have to be considered. |
| format | Article |
| id | doaj-art-200d3bb75def4874afb80b28c227bfd6 |
| institution | OA Journals |
| issn | 0022-0302 |
| language | English |
| publishDate | 2025-03-01 |
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| series | Journal of Dairy Science |
| spelling | doaj-art-200d3bb75def4874afb80b28c227bfd62025-08-20T02:01:01ZengElsevierJournal of Dairy Science0022-03022025-03-0110832573259410.3168/jds.2024-25255An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolusJ. Pfrombeck0M. Gandorfer1E. Zeiler2J. Ettema3Institute für Agricultural Engineering and Animal Husbandry, Bavarian State Research Center for Agriculture, 94099 Ruhstorf an der Rott, Germany; Corresponding authorInstitute für Agricultural Engineering and Animal Husbandry, Bavarian State Research Center for Agriculture, 94099 Ruhstorf an der Rott, GermanyFaculty of Sustainable Agriculture and Energy Systems, University of Applied Science Weihenstephan-Triesdorf, 85354 Freising, GermanySimHerd A/S, 8300 Tjele, DenmarkABSTRACT: The study investigates the economics of sensor-assisted dairy health management and indicates a certain economic potential in the use of a commercial rumen bolus capable of tracking activity and core body temperature. The economic evaluation was performed applying a stochastic model with the net return (NR) of investment of the sensor system as the target variable. The calculated NR considers the gross margin (GM) for both sensor-assisted and visual health monitoring, time savings through sensor-assisted monitoring, additional time spent addressing false positive messages from the sensor system, labor costs, and all costs associated with the investment in the sensor system. The analysis relies on a dataset acquired from a dairy research and demonstration farm on which 65 dairy cows were equipped with the sensor system. A comparison of health-related messages issued by the rumen bolus with disease diagnoses shows that the sensor system issued a message in 7 of 11 cases of retained placenta (sensitivity = 64%), in 19 of 31 cases of clinical hypocalcemia (sensitivity = 61%), in 30 of 70 cases of mastitis (sensitivity = 43%), in 6 of 24 cases of metritis (sensitivity = 25%), and in 2 of 42 cases of diseases of the locomotor system (sensitivity = 5%) in a defined observation period, in many cases several days before the visual diagnosis. SimHerd (A/S Viborg, Denmark) was applied to determine the GM as a function of incidence, SCC, risk of a mild case of disease, and days of milk withdrawal. In a workshop, veterinarians (n = 9) used the dataset to assess the effect of using the sensor system on these parameters. The empirical distributions given by the veterinarians' individual assessments were used to model the parameters considered in the calculation of the “sensor-assisted” GM. For the modeled Holstein herds with a milk yield of 9,000 kg, simulation results show that average NR of investment ranges from +€23 to +€119/cow per year for a herd of poor health, from −€12 to +€84/cow per year for a herd of average health, and from −€33 to +€63/cow per year for a herd of good health, depending on the scenario. The assumptions made regarding changes in labor had a strong influence on the calculated NR of investment. For a full economic evaluation of the sensor system, other functions (estrus detection, calving detection) and functional extensions (e.g., monitoring rumination) have to be considered.http://www.sciencedirect.com/science/article/pii/S0022030224013717digitalMonte Carlo methodsensitivitynet returnSimHerd |
| spellingShingle | J. Pfrombeck M. Gandorfer E. Zeiler J. Ettema An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus Journal of Dairy Science digital Monte Carlo method sensitivity net return SimHerd |
| title | An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus |
| title_full | An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus |
| title_fullStr | An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus |
| title_full_unstemmed | An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus |
| title_short | An economic evaluation of sensor-assisted health monitoring in dairy farming using the example of a rumen bolus |
| title_sort | economic evaluation of sensor assisted health monitoring in dairy farming using the example of a rumen bolus |
| topic | digital Monte Carlo method sensitivity net return SimHerd |
| url | http://www.sciencedirect.com/science/article/pii/S0022030224013717 |
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