Optimizing housing temperature for broilers

Research output: Contribution to conferenceAbstract


Thermal discomfort caused by a too-high or too-low ambient temperature (Ta) is a significant obstacle in sustainable production of broilers. A suboptimal housing temperature is associated with poor health, poor welfare, and lower productivity. The production rates of broilers have changed dramatically over the past decades as a result of genetic selection, adjusted management, and nutrition. These changes have implications for the generation of metabolic heat and consequently, for the optimal housing temperature. The golden standard to determine optimal housing temperature is the use of heat production obtained in climate respiration chambers. These chambers are characterized by limited availability and high costs. Consequently, alternative and easier methods to determine optimal housing temperature are needed. Additionally, the optimal housing temperature might be affected by the RH. This project aims to determine the optimal housing temperature of broilers at different ages and RH, based on metabolic heat production and alternative parameters, such as behavior and vocalizations of the chickens. The first experiment was conducted in three consecutive batches, with two chambers per batch. Each chamber provided a space of 0.8 m2. During the first 48 hours after placement (days 0-2), the Ta was maintained at a fixed level of 33°C. Subsequently, from day 2 to day 3, the Ta was adjusted to 32°C for 24 hours. From day 3 to day 7, there was a gradual decrease in Ta at a rate of 1oC per 4 hours until it reached a Ta at which the heat production increased. Thereafter, the Ta was increased stepwise with 1oC per 4 hours until the Ta was reached which represents the current guidelines for optimal housing temperature. Starting from day 7 until day 35, the Ta was adjusted in steps of 2°C per 4 hours. Metabolic heat production was determined continuously by measuring oxygen consumption and carbon dioxide production. The behavior will be determined through continuous video observations, using scan sampling, with a focus on thermoregulatory behavior. For vocalization of the broilers, microphones were placed in each chamber. The relationship between Ta and vocalizations might be determined by distinguishing different frequencies and amplitudes within the vocalization pattern. Based on all the factors included in the experiments and data obtained, a dynamic algorithm will be developed to predict optimal housing temperatures of broilers, using machine learning techniques.
Original languageEnglish
Publication statusPublished - 24 Oct 2023
EventADP Science Day 2023 - Landgoed Welderen, Elst, Netherlands
Duration: 24 Oct 202324 Oct 2023


OtherADP Science Day 2023


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