SciELO - Scientific Electronic Library Online

 
vol.28 número1Efeito da substituição de farinha de peixe, farinha de frango ou sub-produtos do frango pela soja integral fermentada em dietas de leitões pós desmameEstrutura genética de uma população de bovinos da raça Holandesa na Colômbia índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Não possue artigos similaresSimilares em SciELO
  • Em processo de indexaçãoSimilares em Google

Compartilhar


Revista Colombiana de Ciencias Pecuarias

versão impressa ISSN 0120-0690

Resumo

MUNERA BEDOYA, Oscar D et al. Fuzzy system to predict physiological responses of Holstein cows in southeastern Brazil. Rev Colom Cienc Pecua [online]. 2015, vol.28, n.1, pp.42-53. ISSN 0120-0690.

Background:thermal environment exerts a direct influence on animal performance. Environmental factors, in different circumstances, may affect milk production and fertility of animals, compromising the profitability of the activity. Under heat stress conditions dairy cows reduce feed intake and, consequently, milk production. Sweating and panting are some of the mechanisms these animals use to relieve thermal stress. In addition, animals often suffer physiological and behavioral changes caused by heat stress.Objective: the goal of the present study was to develop and evaluate a model based on fuzzy set theory to predict rectal temperature (°C), and respiratory rate (breaths per minute) responses of Holstein cows exposed to different environmental thermal conditions. Methods: the proposed fuzzy model was based on data obtained experimentally (5,884 records) as well as from the literature (792 records) referring to the effect of environmental variables on both physiological responses. Input variables of each record were dry bulb air temperature and relative humidity. Output variables were rectal temperature and respiratory rate. Results: the adjusted model was evaluated for its ability to predict response variables as a function of input variables. The model was able to predict respiration rate with an average standard error of 7.73 and rectal temperature with an average standard error of 0.27. Conclusion: a fuzzy model was developed to predict physiological responses. The error (%) of model prediction for respiration rate and rectal temperature was +/- 12 and 0.5%, respectively.

Palavras-chave : animal performance; predictive model; rectal temperature; respiratory rate.

        · resumo em Português | Espanhol     · texto em Inglês     · Inglês ( pdf )