Sistema fuzzy para predição do desempenho produtivo de frangos de corte de 1 a 21 dias de idade

Ponciano, Patrícia Ferreira; Yanagi, Tadayuki; Schiassi, Leonardo; Campos, Alessandro T.; Nascimento, José Wallace Barbosa do

doi:10.1590/s0100-69162012000300004

Cited by 26 publications

(51 citation statements)

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“…In research conducted by Ponciano et al (2012) to predict the productive performance of 1-21-day-old broilers, using the mathematical model, average values of standard deviations were obtained of 4.77 g, 1.41 g, and 1.88 g g -1…”

Section: Resultsmentioning

confidence: 99%

“…Seeking to quantify the importance of temperature variation in the second week of life, input variables used were age of birds (S, days), called age S1 (Figure 1). The ranges accepted for input variables (S, T) are listed in Table 1 and those shown were represented in triangular shape for the air temperature input variable and trapezoidal for age because of better representing input data classes, solutions found by several authors (Schiassi et al, 2015;Ponciano et al, 2012;Nascimento et al, 2011;Pereira et al, 2008).…”

Section: Fuzzy Model Developmentmentioning

confidence: 99%

“…Thus, for the development of fuzzy logic, it is necessary that the professional be qualified to avoid possible contradictions in the interactions between the rules. According to the combination of duration and temperature of thermal stress, 12 rules are defined and for each rule, a weighting factor of 1 was assigned, as adopted by Ponciano et al (2012) and Yanagi Junior et al (2012).…”

Section: Fuzzy Model Developmentmentioning

confidence: 99%

“…For output variables, the relevance curves were characterized as triangular (Figure 2), for reproducing better responses with the smaller standard deviation values, and thus, are used by several authors (Pereira et al, 2008;Ponciano et al, 2012).…”

Section: Fuzzy Model Developmentmentioning

confidence: 99%

“…They have been applied to evaluate animal welfare (Pandorfi et al, 2007) and growth performance of broiler chickens (Schiassi et al, 2015;Ponciano et al, 2012), production cost analysis (Nääs et al, 2010), monitoring systems for electricity transmission networks (Almeida & Kagan, 2010), estrus detection in dairy cows (Ferreira et al, 2007), and workers in intensive systems .…”

Section: Introductionmentioning

confidence: 99%

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Effect of thermal environment on performance of broiler chickens using fuzzy modeling

et al. 2017

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RESUMOThis study aimed to develop a decision-support system based on fuzzy set theory, which can estimate welfare depending on the production responses of broiler chickens raised in climatic chambers. In the first phase, the influence of four different air temperature conditions on the performance of broilers was identified. Thus, the effect of air temperature on productivity was evaluated. In the second phase, a model was developed using the fuzzy set theory, in which feed intake responses, weight gain, and feed conversion were established according to age and the air temperature at which the birds were maintained, obtaining an efficient evaluation of the thermal environment. The results indicate that the proposed methodology is a promising technique for the determination of the level of thermal comfort endured by broilers, capable of assisting in making decisions on control of the thermal environment, avoiding productivity losses.Key words: mathematical models; environmental comfort; climatic chambers. Efeito do ambiente térmico sobre o desempenho de frangos de cortes usando modelagem fuzzyEste estudo teve como objetivo desenvolver um sistema de apoio à decisão com base na teoria dos conjuntos fuzzy, que pode estimar o bem-estar de acordo com as respostas de produção de frangos de corte criados em câmaras climatizadas. Na primeira fase, identificou-se a influência de quatro diferentes condições de temperatura do ar sobre o desempenho dos frangos. Assim, foi avaliado o efeito da temperatura do ar na produtividade. Na segunda fase, foi desenvolvido um modelo usando a teoria dos conjuntos fuzzy, onde as respostas consumo de ração, ganho de peso e conversão alimentar foram estabelecidos de acordo com a idade e a temperatura do ar em que as aves foram mantidas, para obtenção de uma avaliação eficaz do ambiente térmico. Os resultados indicaram que a metodologia proposta é uma técnica promissora para a determinação do nível de conforto térmico sofrido por frangos de corte, capazes de auxiliar na tomada de decisões sobre o controle do ambiente térmico, evitando perdas de produtividade.Palavras-chave: modelos matemáticos; conforto ambiental; câmaras climáticas. 338Flávio Alves Damasceno et al.

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Section: Resultsmentioning

confidence: 99%