Authors:
M. Rodriguez

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M. Osornio Hipolito Yrigoyen 931 Experimental Institute of Food Technology, Scientific Research Commission of the Province of Buenos Aires (B6500) 9 de Julio Argentina

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G. Hough Hipolito Yrigoyen 931 Experimental Institute of Food Technology, Scientific Research Commission of the Province of Buenos Aires (B6500) 9 de Julio Argentina

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In many occasions descriptive analysis consists of product-specific training where the samples to be measured are used during the training. Towards the end of the training period it is common practice to present these samples and reach a consensus on their profiles, which we have called Training Consensus Profiles (TCP). Following the TCP, the samples are scored by each assessor and the results are statistically analysed to obtain statistical profiles. The objective of the present work was to compare the TCP with the statistical profiles in samples from three different food categories: fernet (an herb-based alcoholic drink), mayonnaise, and spaghetti. General Procrustes analysis showed that the TCP and statistical profiles were similar. A case is made, that if this type of training and measurement are to be followed, the statistical measuring stage could be left aside, directly reporting the results obtained from the TCP. Advantages and limitations on reporting these TCP profiles are discussed.

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Senior editors

Editor(s)-in-Chief: András SALGÓ

Co-ordinating Editor(s): 

Marianna TÓTH-MARKUS

Co-editor(s): 

Anna HALÁSZ

Editorial Board

  • László ABRANKÓ (Hungarian University of Agriculture and Life Sciences, Budapest, Hungary)
  • Tamás ANTAL (University of Nyíregyháza, Nyíregyháza, Hungary)
  • Diána BÁNÁTI (University of Szeged, Szeged, Hungary)
  • József BARANYI (Institute of Food Research, Norwich, UK)
  • Ildikó BATA-VIDÁCS (Eszterházy Károly Catholic University, Eger, Hungary)
  • Ferenc BÉKÉS (FBFD PTY LTD, Sydney, NSW Australia)
  • György BIRÓ (Budapest, Hungary)
  • Anna BLÁZOVICS (Semmelweis University, Budapest, Hungary)
  • Francesco CAPOZZI (University of Bologna, Bologna, Italy)
  • Marina CARCEA (Research Centre for Food and Nutrition, Council for Agricultural Research and Economics Rome, Italy)
  • Zsuzsanna CSERHALMI (Budapest, Hungary)
  • Marco DALLA ROSA (University of Bologna, Bologna, Italy)
  • István DALMANDI (Hungarian University of Agriculture and Life Sciences, Budapest, Hungary)
  • Katarina DEMNEROVA (University of Chemistry and Technology, Prague, Czech Republic)
  • Mária DOBOZI KING (Texas A&M University, Texas, USA)
  • Muying DU (Southwest University in Chongqing, Chongqing, China)
  • Sedef Nehir EL (Ege University, Izmir, Turkey)
  • Søren Balling ENGELSEN (University of Copenhagen, Copenhagen, Denmark)
  • Éva GELENCSÉR (Budapest, Hungary)
  • Vicente Manuel GÓMEZ-LÓPEZ (Universidad Católica San Antonio de Murcia, Murcia, Spain)
  • Jovica HARDI (University of Osijek, Osijek, Croatia)
  • Hongju HE (Henan Institute of Science and Technology, Xinxiang, China)
  • Károly HÉBERGER (Research Centre for Natural Sciences, ELKH, Budapest, Hungary)
  • Nebojsa ILIĆ (University of Novi Sad, Novi Sad, Serbia)
  • Dietrich KNORR (Technische Universität Berlin, Berlin, Germany)
  • Hamit KÖKSEL (Hacettepe University, Ankara, Turkey)
  • Katia LIBURDI (Tuscia University, Viterbo, Italy
  • Meinolf LINDHAUER (Max Rubner Institute, Detmold, Germany)
  • Min-Tze LIONG (Universiti Sains Malaysia, Penang, Malaysia)
  • Marena MANLEY (Stellenbosch University, Stellenbosch, South Africa)
  • Miklós MÉZES (Hungarian University of Agriculture and Life Sciences, Gödöllő, Hungary)
  • Áron NÉMETH (Budapest University of Technology and Economics, Budapest, Hungary)
  • Perry NG (Michigan State University,  Michigan, USA)
  • Quang Duc NGUYEN (Hungarian University of Agriculture and Life Sciences, Budapest, Hungary)
  • Laura NYSTRÖM (ETH Zürich, Switzerland)
  • Lola PEREZ (University of Cordoba, Cordoba, Spain)
  • Vieno PIIRONEN (University of Helsinki, Finland)
  • Alessandra PINO (University of Catania, Catania, Italy)
  • Mojmir RYCHTERA (University of Chemistry and Technology, Prague, Czech Republic
  • Katharina SCHERF (Technical University, Munich, Germany)
  • Regine SCHÖNLECHNER (University of Natural Resources and Life Sciences, Vienna, Austria)
  • Arun Kumar SHARMA (Department of Atomic Energy, Delhi, India)
  • András SZARKA (Budapest University of Technology and Economics, Budapest, Hungary)
  • Mária SZEITZNÉ SZABÓ (Budapest, Hungary)
  • Sándor TÖMÖSKÖZI (Budapest University of Technology and Economics, Budapest, Hungary)
  • László VARGA (Széchenyi István University, Mosonmagyaróvár, Hungary)
  • Rimantas VENSKUTONIS (Kaunas University of Technology, Kaunas, Lithuania)
  • Barbara WRÓBLEWSKA (Institute of Animal Reproduction and Food Research, Polish Academy of Sciences Olsztyn, Poland)

 

Acta Alimentaria
E-mail: Acta.Alimentaria@uni-mate.hu

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2024  
Web of Science  
Journal Impact Factor 1.0
Rank by Impact Factor Q4 (Nutrition & Dietetics)
Journal Citation Indicator 0.19
Rank by Journal Citation Indicator Q4 (Nutrition & Dietetics)
Scopus  
CiteScore 1.8
CiteScore rank Q3 (Food Science)
SNIP 0.319
Scimago  
SJR index 0.226
SJR Q rank Q3

2023  
Web of Science  
Journal Impact Factor 0,8
Rank by Impact Factor Q4 (Food Science & Technology)
Journal Citation Indicator 0.19
Scopus  
CiteScore 1.8
CiteScore rank Q3 (Food Science)
SNIP 0.323
Scimago  
SJR index 0.235
SJR Q rank Q3

Acta Alimentaria
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Acta Alimentaria
Language English
Size B5
Year of
Foundation
1972
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia    
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0139-3006 (Print)
ISSN 1588-2535 (Online)

 

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