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Titolo:
NEW FIELD TESTING SYSTEMS FOR AI-BOARS
Autore:
BRANDT H; WORNER R;
Indirizzi:
UNIV GOTTINGEN,INST TIERZUCHT & HAUSTIERGENET,ALBRECHT THAER WEG 3 D-37075 GOTTINGEN GERMANY
Titolo Testata:
Archiv fur Tierzucht
fascicolo: 3, volume: 38, anno: 1995,
pagine: 299 - 304
SICI:
0003-9438(1995)38:3<299:NFTSFA>2.0.ZU;2-5
Fonte:
ISI
Lingua:
ENG
Keywords:
GENOTYPE-ENVIRONMENT INTERACTIONS; ELECTRONIC IDENTIFICATION; SOW MANAGEMENT PROGRAMS; MEAT PERCENTAGE; SUCCESSFUL MATINGS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
NO
Recensione:
Indirizzi per estratti:
Citazione:
H. Brandt e R. Worner, "NEW FIELD TESTING SYSTEMS FOR AI-BOARS", Archiv fur Tierzucht, 38(3), 1995, pp. 299-304

Abstract

Genotype with environment interaction in pig breeding as reported by MERKS (1989) leads to the conclusion to use results from the commercial production level to select potential breeding stock. With further delevopment in electronic identification and the use of computer management programmes in weaner production and fattening farms field data forreproduction and other production traits will become available for selection. The potential for using electronic identification for slaughter pigs to use the automatically recorded carcass information from abattoirs as a progeny test for AI-boars is shown. The results of about 12000 slaugter pigs from 133 boars are discussed concerning the organisation and costs of a progeny test to evaluate daily gain and meat percentage. Using only the 30 per cent best boars will increase the production level in meat percentage by 1 per cent and in daily gain by 10 grams. The usage of electronic identification systems within the different stages (nucleus, purebred and crossbred multiplier and weaner production) in modern breeding programmes to increase accuracy in estimating breeding values for carcase quantity and quality traits are discussed. The usage of data from sow management programmes to increase the accuracy of evaluation of reproduction traits are shown. Data from sow management programmes from 15 farms are analysed to evaluate the influence of AI-boars on per cent successful matings.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/12/20 alle ore 08:00:53