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Fuzzy Logic Model for Determining Optimal Temperature-Humidity Index Values in Dairy Farms in Temperate Climate.

Mustafa Kibarİbrahim Aytekinİlker Ali Özkan
Published in: Journal of applied animal welfare science : JAAWS (2024)
In livestock, temperature, humidity, and Temperature-Humidity Index (THI) affect the welfare, yields, health and viability of animals. This study aimed to develop optimal temperature, humidity, and THI thresholds for dairy farms in temperate climate regions using a fuzzy logic model. THI values were calculated using three different literature-derived equations, considering different temperature and humidity situations in dairy farms. The Mamdani-type fuzzy logic method was utilized to formulate linguistic expressions for temperature, humidity, and THI values. According to the THI thresholds, the areas below the Receiver Operating Characteristic (ROC) were found to be significant ( p  < 0.001) in all fuzzy algorithms. The study found 100% harmony with the THI thresholds of 66 and 72 for cattle in temperate climates, but only 73.6% harmony with the threshold of 74 for cattle adapted to tropical climate. Briefly, in temperate dairy farms, the fuzzy logic revealed that the optimal temperature, humidity and THI values should be between 14-18.5°C, 65-70% and 52.5-64.5, respectively. However, further research is required to understand the impact of thresholds determined by fuzzy logic on dairy cow production and welfare.
Keyphrases
  • climate change
  • neural network
  • healthcare
  • machine learning
  • systematic review
  • deep learning
  • social media
  • dairy cows