Towards practical application of sensors for monitoring animal health; design and validation of a model to detect ketosis

The Journal of Dairy Research
Machteld SteenselsIlan Halachmi

Abstract

The objective of this study was to design and validate a mathematical model to detect post-calving ketosis. The validation was conducted in four commercial dairy farms in Israel, on a total of 706 multiparous Holstein dairy cows: 203 cows clinically diagnosed with ketosis and 503 healthy cows. A logistic binary regression model was developed, where the dependent variable is categorical (healthy/diseased) and a set of explanatory variables were measured with existing commercial sensors: rumination duration, activity and milk yield of each individual cow. In a first validation step (within-farm), the model was calibrated on the database of each farm separately. Two thirds of the sick cows and an equal number of healthy cows were randomly selected for model validation. The remaining one third of the cows, which did not participate in the model validation, were used for model calibration. In order to overcome the random selection effect, this procedure was repeated 100 times. In a second (between-farms) validation step, the model was calibrated on one farm and validated on another farm. Within-farm accuracy, ranging from 74 to 79%, was higher than between-farm accuracy, ranging from 49 to 72%, in all farms. The within-farm sensitiv...Continue Reading

References

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Citations

Jun 9, 2018·Journal of the Science of Food and Agriculture·Grzegorz GrodkowskiTon Baars
Aug 30, 2018·The Journal of Dairy Research·Christopher H Knight
Nov 30, 2018·Annual Review of Animal Biosciences·Ilan HalachmiMatti Pastell
May 21, 2020·The Journal of Dairy Research·Ephraim Maltz
Sep 3, 2020·Animals : an Open Access Journal From MDPI·Fan ZhangBenhai Xiong
May 13, 2021·Proceedings. Biological Sciences·Joanna Stachowicz, Christina Umstätter

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