Surface temperature distribution in broiler houses

Effects of cold stress on physiologic metabolism in the initial phase and performance of broiler rearing

This study aimed to investigate the effects of 8 h of cold stress (18 °C) every day in broiler chicks during the first 7 days of rearing on crop filling analysis, yolk sac consumption, digestive and immune organs weights, and physiological metabolism at seven days and performance between 1 and 35 days. Cobb500 male broiler chickens (n = 274) were randomly assigned to two treatments. The treatments consisted of varying environmental temperatures during the first week post-housing. Chicks were reared at a thermoneutral temperature (32 °C) or under cold stress (18 °C) for 8 h/day during the first week, and both groups were subsequently reared at a thermoneutral temperature for 8-35 days. The thermoneutral group reached 90% full crop after 48 h of housing (P < 0.05), while the cold-stressed group had more empty crops at 2 h and 48 h after housing (P < 0.05). The chick cloacal temperature was not affected by the treatments (P > 0.05). Additionally, the treatment did not affect serum amylase and corticosterone levels, feed intake, body weight gain, or feed conversion ratio (P > 0.05, while the cold-stressed group had elevated heterophil/lymphocyte count at day 7 (P < 0.05). The thermoneutral group showed higher viability (%) at 7 and 35 days and a higher production factor at 35 days (P < 0.05). Broiler chickens under cyclic cold stress experienced decreased yolk sac absorption during the first week and increased feed intake and feed conversion ratio after 35 days of rearing. Viability was also lower in the cold-stressed group. An appropriate strategy to minimize these adverse effects is to rear the chicks in a thermoneutral environment during the first week.

Impacts of Air Velocity Treatments under Summer Condition: Part I—Heavy Broiler’s Surface Temperature Response

Simple Summary

The surface temperature variation of heavy broilers (42–61 d age) under heat stress is an important indicator of thermal comfort, but it is not well studied and reported yet. This study examined the variation of surface temperatures of broilers through two dynamic air velocity treatments under hot summer conditions. It was discovered that the surface temperatures varied over age, daytime, and environmental factors (air temperature, relative humidity, and temperature humidity index). A simple linear regression model to predict the surface temperature of heavy broilers was developed. The findings from this study will enhance knowledge to understand the broilers’ responses under heat stress, which will be helpful in providing necessary management decisions to create a comfortable thermal environment.

Abstract

Heavy broilers exposed to hot summer conditions experience fluctuations in surface temperatures due to heat stress, which leads to decreased performance. Maintaining a bird’s homeostasis depends on several environmental factors (temperature, relative humidity, and air velocity). It is important to understand the responses of birds to environmental factors and the amount of heat loss to the surrounding environment to create thermal comfort for the heavy broilers for improved performances and welfare. This study investigates the variation in surface temperatures of heavy broilers under high and low air velocity treatments. Daytime, age and bird location’s effect on the surface temperature variation was also examined. The experiment was carried out in the poultry engineering laboratory of North Carolina State University during summers of 2017, 2018, and 2019 as a part of a comprehensive study on the effectiveness of wind chill application to mitigate heat stress on heavy broilers. This live broiler heat stress experiment was conducted under two dynamic air velocity treatments (high and low) with three chambers per treatment and 44 birds per chamber. Surface temperatures of the birds were recorded periodically through the experimental treatment cycles (flocks, 35–61 d) with infrared thermography in the morning, noon, evening, and nighttime. The overall mean surface temperature of the broilers under two treatments was found to be 35.89 ± 2.37 °C. The variation in surface temperature happened due to air temperature, thermal index, air velocity, bird’s age, daytime, and position of birds inside the experimental chambers. The surface temperatures were found lower under high air velocity treatment and higher under low air velocity treatment. During the afternoon time, the broilers’ surface temperatures were higher than other times of the day. It was also found that the birds’ surface temperature increased with age and temperature humidity indices. Based upon the experimental data of five flocks, a simple linear regression model was developed to predict surface temperature from the birds’ age, thermal indices, and air velocity. It will help assess heavy broilers’ thermal comfort under heat stress, which is essential to provide a comfortable environment for them.

Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations

Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens' welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new "nest-usage-sensor" was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a "Multiple Nest Occupation Threshold" of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved.

A Monitoring System for Laying Hens That Uses a Detection Sensor Based on Infrared Technology and Image Pattern Recognition

In Italy, organic egg production farms use free-range housing systems with a big outdoor area and a flock of no more than 500 hens. With additional devices and/or farming procedures, the whole flock could be forced to stay in the outdoor area for a limited time of the day. As a consequence, ozone treatments of housing areas could be performed in order to reduce the levels of atmospheric ammonia and bacterial load without risks, due by its toxicity, both for hens and workers. However, an automatic monitoring system, and a sensor able to detect the presence of animals, would be necessary. For this purpose, a first sensor was developed but some limits, related to the time necessary to detect a hen, were observed. In this study, significant improvements, for this sensor, are proposed. They were reached by an image pattern recognition technique that was applied to thermografic images acquired from the housing system. An experimental group of seven laying hens was selected for the tests, carried out for three weeks. The first week was used to set-up the sensor. Different templates, to use for the pattern recognition, were studied and different floor temperature shifts were investigated. At the end of these evaluations, a template of elliptical shape, and sizes of 135 × 63 pixels, was chosen. Furthermore, a temperature shift of one degree was selected to calculate, for each image, a color background threshold to apply in the following field tests. Obtained results showed an improvement of the sensor detection accuracy that reached values of sensitivity and specificity of 95.1% and 98.7%. In addition, the range of time necessary to detect a hen, or classify a case, was reduced at two seconds. This result could allow the sensor to control a bigger area of the housing system. Thus, the resulting monitoring system could allow to perform the sanitary treatments without risks both for animals and humans.

First Results of a Detection Sensor for the Monitoring of Laying Hens Reared in a Commercial Organic Egg Production Farm Based on the Use of Infrared Technology

The development of a monitoring system to identify the presence of laying hens, in a closed room of a free-range commercial organic egg production farm, was the aim of this study. This monitoring system was based on the infrared (IR) technology and had, as final target, a possible reduction of atmospheric ammonia levels and bacterial load. Tests were carried out for three weeks and involved 7 ISA (Institut de Sélection Animale) brown laying hens. The first 5 days was used to set up the detection sensor, while the other 15 days were used to evaluate the accuracy of the resulting monitoring system, in terms of sensitivity and specificity. The setup procedure included the evaluation of different color background (CB) thresholds, used to discriminate the information contents of the thermographic images. At the end of this procedure, a CB threshold equal to an increase of 3 °C from the floor temperature was chosen, and a cutoff level of 196 colored pixels was identified as the threshold to use to classify a positive case. The results of field tests showed that the developed monitoring system reached a fine detection accuracy (sensitivity = 97.9% and specificity = 94.9%) and the IR technology proved to be a possible solution for the development of a detection sensor necessary to reach the scope of this study.