Spatial variability of enthalpy in rabbit house with and without ridge vent

Abstract

The profitability of a rabbit farming system must consider the rabbit’s breed, nutrition, management, sanitation and mainly the thermal environment that the animal will be exposed during the productive period. The aim of this study was to compare the internal thermal environment of two rabbit houses, one with ridge vent and the other without ridge vent. Geostatistical technique was used to evaluate the spatial variability of enthalpy. Data were collected at 48 points in each house during eight days at the end of summer season 2016. Measurements of dry-bulb temperature, relative humidity and wind speed were made for 1 min at three times a day at 7:00 a.m., 12:00 a.m. and 5:00 p.m. In addition, the enthalpy was calculated and a data analysis was performed using geostatistical tools and isocolor maps through interpolation by kriging. Based on results from geostatistics, it was possible to characterize the variability magnitude and structure of this variable inside the rabbits’ houses with and without ridge vent. The heterogeneity of the spatial distribution of enthalpy in several regions of two houses was also observed through generated isocolor maps. The ridge vent assisted in obtaining a more favorable internal environment for rabbit breeding because this house showed more comfortable conditions of enthalpy values, besides lower heterogeneity of the spatial distribution of enthalpy.

Decision Trees for Predicting the Physiological Responses of Rabbits

“…In addition, animals reared under thermal stress can suffer losses in performance and production due to eating disorders, weight gain, feed conversion, water consumption, changes in blood parameters and enzymatic and hormonal reactions in addition to the imbalance of proteins, energy, and minerals [40,41]. Therefore, the proposed decision trees can be used to evaluate the physiological responses of rabbits to their thermal environment in order to better understand this relationship, leading to an enhancement of both animal welfare and production efficiency [1]. In this sense, for applications in intensive rabbit breeding, in an attempt to mitigate the harmful effects of environmental stress, the housing characteristics and equipment must be adequate to provide appropriate comfort to the animals, while also supporting the management of breeding, providing greater financial gain for the producer [1].…”

“…The profitability of a rabbit farming system must consider the rabbit’s breed, nutrition, management, and sanitation as well as the thermal environment of the animal during the productive period [1]. Currently, increasing pressure has emerged from public opinion and consumers for farms to improve housing conditions and comply with animal welfare standards [2].…”

Effect of the Spatial Distribution of the Temperature and Humidity Index in a New Zealand White Rabbit House on Respiratory Frequency and Ear Surface Temperature

“…This characterizes the environmental conditions of these animals within the production system, which is of paramount importance [11]. In this context, the development of new technologies that improve existing housing environments at a low production cost is necessary to better understand the effects of thermal conditions on rabbit farming and to assist producers in obtaining maximum productivity [10,14].…”

“…Environmental variables, such as dry bulb temperature (t db , • C) and RH, as well as climatic indices, such as the temperature and humidity index (THI), can be evaluated inside a facility through spatialization and geostatistics [14,15]. The use of geostatistics makes it possible to quantitatively characterize the spatial variability of these variables inside a rabbit house environment, preventing biased interpretations of data and allowing the observation of spatial dependence through kriging maps [13][14][15][16].…”

“…In tropical countries such as Brazil, only a few studies have evaluated the thermal comfort of rabbit production facilities; thus, farmers and researchers have searched for computational tools that can assist in the evaluation and decision-making processes for supporting better animal production environments [14].…”