1 resultado para Regression equation
em Digital Repository at Iowa State University
Filtro por publicador
- Academic Research Repository at Institute of Developing Economies (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (1)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (1)
- Applied Math and Science Education Repository - Washington - USA (2)
- Archive of European Integration (1)
- Aston University Research Archive (6)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (3)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (103)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (3)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (5)
- Brock University, Canada (8)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- CentAUR: Central Archive University of Reading - UK (129)
- Cochin University of Science & Technology (CUSAT), India (8)
- Collection Of Biostatistics Research Archive (1)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (92)
- Cor-Ciencia - Acuerdo de Bibliotecas Universitarias de Córdoba (ABUC), Argentina (1)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- CUNY Academic Works (3)
- Dalarna University College Electronic Archive (2)
- Department of Computer Science E-Repository - King's College London, Strand, London (1)
- Digital Commons at Florida International University (2)
- Digital Repository at Iowa State University (1)
- DigitalCommons@The Texas Medical Center (3)
- Diposit Digital de la UB - Universidade de Barcelona (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (10)
- Instituto Politécnico do Porto, Portugal (13)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (2)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Martin Luther Universitat Halle Wittenberg, Germany (3)
- Massachusetts Institute of Technology (3)
- Ministerio de Cultura, Spain (8)
- Publishing Network for Geoscientific & Environmental Data (5)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (10)
- Repositório da Produção Científica e Intelectual da Unicamp (7)
- Repositório da Universidade Federal do Espírito Santo (UFES), Brazil (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (15)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (186)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (5)
- School of Medicine, Washington University, United States (1)
- Scielo Saúde Pública - SP (60)
- Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom (3)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (3)
- Universidad Politécnica de Madrid (1)
- Universidade do Minho (4)
- Universidade Estadual Paulista "Júlio de Mesquita Filho" (UNESP) (2)
- Universidade Federal do Rio Grande do Norte (UFRN) (2)
- Universitat de Girona, Spain (12)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (4)
- Université de Lausanne, Switzerland (74)
- Université de Montréal, Canada (26)
- University of Queensland eSpace - Australia (48)
- University of Southampton, United Kingdom (4)
Resumo:
An evaluation of carcass data collected over a two year period from southwest Iowa steer tests and 4-H carcass shows was conducted to compare USDA yield grades called by the Federal grader to yield grades calculated by actual carcass measurements. A regression equation was developed to predict called yield grade from carcass measurements. A comparison of the generated equation with the USDA equation used in calculating yield grades suggest that USDA graders accurately predict preliminary yield grades based on fat thickness, but may not have adequate time at line speeds to fully account for adjustments in ribeye size relative to carcass weight.