Decision Trees for Predicting the Physiological Responses of Rabbits
1
Federal University of Lavras (UFLA), Department of Agricultural Engineering, Lavras, Minas Gerais 37200-900, Brazil
2
Faculty of Economics, Administrative and Accounting Sciences, Universidad del Sinú Elías Bechara Zainúm, Montería, Córdoba 230001, Colombia
3
Federal University of Lavras (UFLA), Department of Agricultural Engineering, Lavras, Minas Gerais 37200-900, Brazil
4
Federal University of Lavras (UFLA), Department of Animal Science, Lavras, Minas Gerais 37200-900, Brazil
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University of Firenze, Department of Agriculture, Food, Environment and Forestry, Firenze 50145, Italy
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Universidad Nacional de Colombia, Sede Medellin, Facultad de Ciencias Agrarias, Departamento de Ingeniería Agrícola Alimentos, Medellín 050004, Colombia
7
University of Firenze, Department of Agriculture, Food, Environment and Forestry, Firenze 50145, Italy
*
Author to whom correspondence should be addressed.
Animals 2019, 9(11), 994; https://doi.org/10.3390/ani9110994
Received: 7 October 2019 / Revised: 30 October 2019 / Accepted: 8 November 2019 / Published: 18 November 2019
(This article belongs to the Section Animal Welfare)
Simple Summary
The primary aim of this paper is to develop decision trees to predict rabbits’ physiological responses, such as the respiratory rate or ear temperature, based on environmental variables (dry bulb temperature and relative humidity). The decision tree for ear temperature exhibited better statistical indices, indicating the benefits of using the ear temperature as an indicator of thermal stress. Our findings confirm that the resulting decision trees are powerful classifiers, and the results can be easily understood. Hence, the proposed decisions trees can aid in investigating the influence of environmental conditions on physiological responses and, consequently, the rabbits’ welfare. These results can be used in practical situations and can be obtained in real time to support rabbit breeders in decision-making to improve environmental conditions for rabbits.
The thermal environment inside a rabbit house affects the physiological responses and consequently the production of the animals. Thus, models are needed to assist rabbit producers in decision-making to maintain the production environment within the zone of thermoneutrality for the animals. The aim of this paper is to develop decision trees to predict the physiological responses of rabbits based on environmental variables. The experiment was performed in a rabbit house with 26 rabbits at eight weeks of age. The experimental database is composed of 546 observed data points. Sixty decision tree models for the prediction of respiratory rate (RR, mov.min−1) and ear temperature (ET, °C) of rabbits exposed to different combinations of dry bulb temperature (tdb, °C) and relative humidity (RH, %) were developed. The ET model exhibited better statistical indices than the RR model. The developed decision trees can be used in practical situations to provide a rapid evaluation of rabbit welfare conditions based on environmental variables and physiological responses. This information can be obtained in real time and may help rabbit breeders in decision-making to provide satisfactory environmental conditions for rabbits.
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Keywords:
ear temperature; respiratory rate; thermal environment; rabbit breeder; welfare
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MDPI and ACS Style
Ferraz, P.F.P.; Hernández-Julio, Y.F.; Ferraz, G.A.e.S.; Moura, R.S.d.; Rossi, G.; Saraz, J.A.O.; Barbari, M. Decision Trees for Predicting the Physiological Responses of Rabbits. Animals 2019, 9, 994. https://doi.org/10.3390/ani9110994
AMA Style
Ferraz PFP, Hernández-Julio YF, Ferraz GAeS, Moura RSd, Rossi G, Saraz JAO, Barbari M. Decision Trees for Predicting the Physiological Responses of Rabbits. Animals. 2019; 9(11):994. https://doi.org/10.3390/ani9110994
Chicago/Turabian StyleFerraz, Patrícia Ferreira Ponciano, Yamid Fabián Hernández-Julio, Gabriel Araújo e Silva Ferraz, Raquel Silva de Moura, Giuseppe Rossi, Jairo Alexander Osorio Saraz, and Matteo Barbari. 2019. "Decision Trees for Predicting the Physiological Responses of Rabbits" Animals 9, no. 11: 994. https://doi.org/10.3390/ani9110994
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