20.500.12556/DKUM-59300 An attempt to predict conformation and fatness in bulls by means of artificial neural networks using weight, age and breed composition information The present study aimed to predict conformation and fatness grades in bulls based on data available at slaughter (carcass weight, age and breed proportions) by means of counter-propagation artificial neural networks (ANN). For chemometric analysis, 5893 bull carcasses (n=2948 and n=2945 for calibration and testing of models, respectively) were randomly selected from the initial data set (n≈27000; one abattoir, one classifier, three years period). Different ANN models were developed for conformation and fatness by varying the net size and the number of epochs. Tested net parameters did not have a notable effect on models’ quality. Respecting the tolerance of ±1 subclass between the actual and predicted value (as allowed by European Union legislation for on-spot checks), the matching between the classifier and ANN grading was 73.6 and 64.9% for conformation and fatness, respectively. Success rate of prediction was positively related to the frequency of carcasses in the class. govedo goveje meso mastnost mesa struktura mesa klavna teža ANN modeli modeli za napovedovanje bovine beef meat meat structure slaughter weight ANN models forecasting models true false true Angleški jezik Slovenski jezik Znanstveno delo 2016-05-11 04:00:43 2017-07-24 11:30:05 2022-06-20 03:06:18 2019-07-11 11:09:18 2015 0 0 str. 45-52 Letn. 14 2015 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 1594-4077 636:637 1544840 4637800 10.4081/ijas.2015.3198 1594-4077 URN:SI:UM:DK:MHB4HPF7 Italian_Journal_of_Animal_Science_2015_Candek-Potokar_et_al._An_Attempt_to_Predict_Conformation_and_Fatness_in_Bulls_by_Means_of_Artific.pdf Italian_Journal_of_Animal_Science_2015_Candek-Potokar_et_al._An_Attempt_to_Predict_Conformation_and_Fatness_in_Bulls_by_Means_of_Artific.pdf 1 EF324A07A8807F93D15B19475F1C3FEC 035c0e9c42cb22dd950cd9623675394110c4cdf9c3e36433ba238745ddb41a5a 722d03ec-7c0e-11eb-bb7a-00155d0001ca https://dk.um.si/Dokument.php?lang=slv&id=114496 http://www.tandfonline.com/doi/full/10.4081/ijas.2015.3198 1 https://dk.um.si/Dokument.php?lang=slv&id=91369 Fakulteta za kmetijstvo in biosistemske vede 0 0 0