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Updated: Dec 2, 2025

Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students

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Predicting dairy cattle heat stress using machine learning techniques.

C A Becker¹, A Aghalari², M Marufuzzaman²

¹Department of Animal and Dairy Sciences, Mississippi State University, Mississippi State 39762.

Journal of Dairy Science

|November 2, 2020

Summary

This summary is machine-generated.

Machine learning models accurately predicted dairy cow heat stress severity. The random forest model excelled at identifying cows benefiting from sprinkler systems, aiding producers in preventing milk loss.

Keywords:

heat stress machine learning shade sprinklers

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Area of Science:

Animal Science
Agricultural Engineering
Data Science

Background:

Heat stress significantly impacts dairy cow welfare and productivity.
Effective heat abatement strategies are crucial for mitigating negative effects like milk loss.
Accurate, real-time assessment of heat stress severity is needed.

Purpose of the Study:

To evaluate a novel heat stress scoring system for dairy cows.
To predict the accuracy of this scoring system using machine learning.
To compare the effectiveness of different heat abatement techniques (shade, sprinklers, control).

Main Methods:

Developed a 4-point heat stress scoring system (1=no stress, 4=moribund).
Applied logistic regression, Gaussian naïve Bayes, and random forest models to predict scores.
Utilized various physiological, environmental, and production parameters as input variables.
Compared three treatments: shade structure, sprinkler system, and control.

Main Results:

Random forest demonstrated superior accuracy and precision in predicting scores for the sprinkler group.
Logistic regression and random forest showed consistency in predicting scores for control and shade groups.
Sprinkler systems yielded the highest probability of non-heat-stressed cows.
Logistic regression was most effective for predicting heat stress in control and shade groups.

Conclusions:

Machine learning models can accurately assess dairy cow heat stress.
Sprinkler systems appear most effective in preventing heat stress.
Early detection of heat stress using these methods can reduce economic losses in dairy production.