A Fuzzy Logic Application to Predict Egg Production on Laying Hens
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Date
2019
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Abstract
Fuzzy logic has a great potential for researchers and it has been developed over the last two decades. In animal science, there are limited numbersof studies on fuzzy logic approach. This study was carried out to examine the Fuzzy logic applications for prediction of the egg production data. Eggproduction records were obtained from the commercial poultry farm in Izmir, Turkey. Egg production traits of brown laying hens at 22 to 40 weeksof age were analyzed with Fuzzy logic system. In this study, Fuzzy logic model was developed for the prediction of egg production values of threeclasses; top, middle and lower (bottom for the cage effect) production. For this purpose 120 data lines representing 4 inputs consisting of cage, ageat sexual maturity (ASM), body weight at sexual maturity (BWSM), body weight at mature age (BW) and 1 output, egg production (EP) that collecteddaily and individually were used in a Fuzzy logic model. The similarities between predicted and original production records were investigated, thecoefficient of determination (R2) was found as 0.89 which was also shown the prediction’s success rate. The probability of egg production at ASM of168 days, BWSM of 1500 g and BW of 1820 g was found 98.97% while egg production’s probability at ASM of 157 days, BWSM of 1720 g and BW of1940 g was determined as 97.97%. These results were also concluded that layers reached at sexual maturity later have lower egg production. Theresults illustrated that Fuzzy model could provide an effective and accurate prediction for classifying egg production of laying hens. However, sincethe applications of fuzzy logic related to the prediction of egg production are limited, this work will be pioneered by future studies.