Application of fuzzy logic for the evaluation of livestock slaughtering

Abstract

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Software to Assess Beef Cattle Body Mass Through the Fuzzy Body Mass Index

“…In agricultural engineering, mathematical models with real application in the area are being developed using numerical correction equations of temporal variables (GABRIEL FILHO et al, 2011b), or by developing systems based on artificial intelligence (GABRIEL FILHO et al, 2011ae PEREIRA et al, 2008, in companies of laying aviculture (CREMASCO et al, 2010), energy generation solar photovoltaic and wind power for rural electrification (CANEPPELE et al, 2013), evaluate vitality of catasetum fimbiratum species (Orchidacea) (PUTTI et al, 2014),evaluation of uncertainty transaction in cassava chain (GABRIEL FILHO et al, 2015) and application of controlled by fuzzy logic in electrically driven fertilizer (GARCIA et al, 2014).…”

Body and testicular development and serum testosterone concentrations in Brahman males

“…With the expansion of Fuzzy logic studies aimed at breeding animals (GABRIEL FILHO et al, 2011, one can mathematically model physical morphometric variable studies, attempting to predict how that variable behaves with time. Thus, the present study calculated the body mass index (BMI).…”

“…The variable is easy to obtain, as it requires only body weight and measurement of height at the withers as the animal is contained in the cattle crush. By using the BMI scoring nomenclature for the age of the animals in the present study, adopting the score published for adult zebu cattle with application of the fuzzy logic system according to Gabriel Filho et al (2011, the mean BMI at ages 10 and 12 months (Tab.3) fall in the "very low BMI" category; the age of 14 months is classified as "low BMI"; and the ages of 16 and 18 months are classified as "high BMI". Brahman animals in the present study were young, with continuous increase in BMI due to the increase in height at the withers in conjunction with gains in body weight.…”

Modeling a Diet Planner for Livestock Using Fuzzy Logic Approach and Ontology Model

“…For this reason, fuzzy logic is used that helps to reduce the uncertainty over the data and to obtain the absolute results. Such researches on the livestock include the Fuzzy BMI, estrus detection, herd management and so on [4,5].…”