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Data-Mining Methodology to Improve the Scientific Production Quality in Turkey Meat and Carcass Characterization Studies
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Orientador(es)
Resumo(s)
The present research aims to describe how turkey meat and carcass quality traits define the
interest of the scientific community through the quality standards of journals in which studies are
published. To this end, an analysis of 92 research documents addressing the study of turkey carcass
and meat quality over the last 57 years was performed. Meat and carcass quality attributes were
dependent variables and included traits related to carcass dressing, muscle fiber, pH, colorimetry,
water-holding capacity, texture, and chemical composition. The independent variables comprised
publication quality traits, including journal indexation, database, journal impact factor (JIF), quartile,
publication area, and JIF percentage. For each dependent variable, a data-mining chi-squared
automatic interaction detection (CHAID) decision tree was developed. Carcass or piece yield was
the only variable that did not show an impact on the publication quality. Moreover, color and pH
measurements taken at 72 h postmortem showed a negative impact on publication interest. On the
other hand, variables including water-retaining attributes, colorimetry, pH, chemical composition,
and shear force traits stood out among the quality-enhancing variables due to their low inclusion in
papers, while high standards improved power.
Descrição
Palavras-chave
data-mining turkey meat quality physical traits chemical profile publication quality traits biostatistical tool
Contexto Educativo
Citação
Salgado Pardo, J.I.; Navas González, F.J.; González Ariza, A.; León Jurado, J.M.; Carolino, N.; Carolino, I.; Delgado Bermejo, J.V.; Camacho Vallejo, M.E. Data-Mining Methodology to Improve the Scientific Production Quality in Turkey Meat and Carcass Characterization Studies. Animals 2024, 14, 2107. https://doi.org/10.3390/ani14142107
Editora
MDPI