Authors:
J. Felfoldi Corvinus University of Budapest Department of Physics and Control 14-16 Somloi str H-1118 Budapest Hungary

Search for other papers by J. Felfoldi in
Current site
Google Scholar
PubMed
Close
,
L. Baranyai Corvinus University of Budapest Department of Physics and Control 14-16 Somloi str H-1118 Budapest Hungary

Search for other papers by L. Baranyai in
Current site
Google Scholar
PubMed
Close
,
F. Firtha Corvinus University of Budapest Department of Physics and Control 14-16 Somloi str H-1118 Budapest Hungary

Search for other papers by F. Firtha in
Current site
Google Scholar
PubMed
Close
,
L. Friedrich Corvinus University of Budapest Dept. of Refrigeration and Livestocks’ Products Technology 44 Menesi str H-1118 Budapest Hungary

Search for other papers by L. Friedrich in
Current site
Google Scholar
PubMed
Close
, and
Cs. Balla Corvinus University of Budapest Dept. of Refrigeration and Livestocks’ Products Technology 44 Menesi str H-1118 Budapest Hungary

Search for other papers by Cs. Balla in
Current site
Google Scholar
PubMed
Close
Restricted access

The fat content (fat distribution) of the pork and beef raw material is one of their most important quality characteristics. Image processing methods were applied to provide with quantitative parameters related to these properties. Different hardware tools were tested to select the appropriate imaging alternative. Statistical analysis of the RGB data was performed in order to find appropriate classification function for segmentation. Discriminant analysis of the RGB data of selected image regions (fat-meat-background) resulted in a good segmentation of the fat regions. Classification function was applied on the RGB images of the samples, to identify and measure the regions in question. The fat-meat ratio and textural parameters (entropy, contrast, etc.) were determined. Comparison of the image parameters with the sensory evaluation results showed an encouraging correlation.

  • Barbin, D., Elmasry, G., Sun, D., Allen, P. (2012) Near-infrared hyperspectral imaging for grading and classification of pork. Meat Science, 90/1, 259–268.

    Allen P. , 'Near-infrared hyperspectral imaging for grading and classification of pork ' (2012 ) 90 Meat Science : 259 -268 .

    • Search Google Scholar
  • Brewer, M.S., Zhu, L.G., McKeith, F.K. (2001). Marbling effects on quality characteristics of pork loin chops: consumer purchase intent, visual and sensory characteristics. Meat Science, 59, 153–163.

    McKeith F.K. , 'Marbling effects on quality characteristics of pork loin chops: consumer purchase intent, visual and sensory characteristics ' (2001 ) 59 Meat Science : 153 -163 .

    • Search Google Scholar
  • Council Regulation (EC) No 1234/2007 of 22 October 2007 establishing a common organisation of agricultural markets and on specific provisions for certain agricultural products.

  • Firtha, F. (2007) Development of data reduction function for hyperspectral imaging. Progress in Agricultural Engineering Sciences, 3, 67–88.

    Firtha F. , 'Development of data reduction function for hyperspectral imaging ' (2007 ) 3 Progress in Agricultural Engineering Sciences : 67 -88 .

    • Search Google Scholar
  • Firtha, F., Jasper, A., Friedrich, L., Felföldi, J. (2012) Hyperspectral qualification of aged beef sirloin. CIGR-AgEng, International Conference on agricultural engineering, Valencia, SPC-03: IV International workshop on Computer Image Analysis in agriculture. P1876.

    Felföldi J. , '', in Hyperspectral qualification of aged beef sirloin. CIGR-AgEng, International Conference on agricultural engineering, Valencia, SPC-03: IV International workshop on Computer Image Analysis in agriculture , (2012 ) -.

  • Huang, H., Liu, L., Ngadi, M.O., Gariépy, C. (2013) Prediction of pork marbling scores using pattern analysis techniques. Food Control, 31/1, 224–229.

    Gariépy C. , 'Prediction of pork marbling scores using pattern analysis techniques ' (2013 ) 31 Food Control : 224 -229 .

    • Search Google Scholar
  • Hwang, Y., Kim, G., Jeong, J., Hur, S., Joo, S. (2010) The relationship between muscle fiber characteristics and meat quality traits of highly marbled Hanwoo (Korean native cattle) steers. Meat Science, 86/2, 456–461.

    Joo S. , 'The relationship between muscle fiber characteristics and meat quality traits of highly marbled Hanwoo (Korean native cattle) steers ' (2010 ) 86 Meat Science : 456 -461 .

    • Search Google Scholar
  • Jackman, P., Sun, D., Du, C., Allen, P. (2009) Prediction of beef eating qualities from col-our, marbling and wavelet surface texture features using homogenous carcass treatment. Pattern Recognition, 42/5, 751–763.

    Allen P. , 'Prediction of beef eating qualities from col-our, marbling and wavelet surface texture features using homogenous carcass treatment ' (2009 ) 42 Pattern Recognition : 751 -763 .

    • Search Google Scholar
  • Jackman, J., Sun, D., Allen, P., Brandon, K., White, A. (2010a) Correlation of consumer assessment of longissimus dorsi beef palatability with image colour, marbling and surface texture features. Meat Science, 84/3, 564–568.

    White A. , 'Correlation of consumer assessment of longissimus dorsi beef palatability with image colour, marbling and surface texture features ' (2010 ) 84 Meat Science : 564 -568 .

    • Search Google Scholar
  • Jackman, P., Sun, D., Allen, P., Valous, N.A., Mendoza, F., Ward, P. (2010b) Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection. Meat Science, 84/4, 711–717.

    Ward P. , 'Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection ' (2010 ) 84 Meat Science : 711 -717 .

    • Search Google Scholar
  • Jeremiah, L.E. (1996) The influence of subcutaneous fat thickness and marbling on beef: Palatability and consumer acceptability. Food Research International, 29/5–6, 513–520.

    Jeremiah L.E. , 'The influence of subcutaneous fat thickness and marbling on beef: Palatability and consumer acceptability ' (1996 ) 29 Food Research International : 513 -520 .

    • Search Google Scholar
  • Kuchita, K., Yamagi, K., Yamagishi, T. (1993) Meat quality evaluation method by image analysis and its applications. Chikusan-Kenkyu, 47, 71–73.

    Yamagishi T. , 'Meat quality evaluation method by image analysis and its applications ' (1993 ) 47 Chikusan-Kenkyu : 71 -73 .

    • Search Google Scholar
  • Li, J., Tan, J., Martz, F.A., Heymann, H. (1999) Image texture features as indicators of beef tenderness. Meat Science, 53, 17–22

    Heymann H. , 'Image texture features as indicators of beef tenderness ' (1999 ) 53 Meat Science : 17 -22 .

    • Search Google Scholar
  • Liu, L., Ngadi, M.O., Prasher, S.O., Gariépy, C. (2012) Objective determination of pork marbling scores using the wide line detector. Journal of Food Engineering, 110/3, 497–504.

    Gariépy C. , 'Objective determination of pork marbling scores using the wide line detector ' (2012 ) 110 Journal of Food Engineering : 497 -504 .

    • Search Google Scholar
  • Mendoza, F., Valous, N.A., Sun, D., Allen, P. (2009) Characterization of fat-connective tissue size distribution in pre-sliced pork hams using multifractal analysis. Meat Science, 83/4, 713–722.

    Allen P. , 'Characterization of fat-connective tissue size distribution in pre-sliced pork hams using multifractal analysis ' (2009 ) 83 Meat Science : 713 -722 .

    • Search Google Scholar
  • Moon, S.S., Yang, H.S., Park, G.B., Joo, S.T. (2006) The relationship of physiological ma-turity and marbling judged according to Korean grading system to meat quality traits of Hanwoo beef females. Meat Science, 74, 516–521.

    Joo S.T. , 'The relationship of physiological ma-turity and marbling judged according to Korean grading system to meat quality traits of Hanwoo beef females ' (2006 ) 74 Meat Science : 516 -521 .

    • Search Google Scholar
  • Ngapo, T.M., Riendeau, L., Laberge, C., Fortin, J. (2012) Marbling and ageing — Part 2. Consumer perception of sensory quality. Food Research International (Article in press: FRIN-04080; No of Pages 7).

    Fortin J. , '', in Marbling and ageing — Part 2. Consumer perception of sensory quality , (2012 ) -.

  • Qiao, J., Ngadi, M.O., Wang, N., Gariépy, C., Prasher, S.O. (2007) Pork quality and mar-bling level assessment using a hyperspectral imaging system. Journal of Food Engineering, 83/1, 10–16.

    Prasher S.O. , 'Pork quality and mar-bling level assessment using a hyperspectral imaging system ' (2007 ) 83 Journal of Food Engineering : 10 -16 .

    • Search Google Scholar
  • Shiranita, K., Miyajima, T., Takiyama, R. (1998) Determination of meat quality by texture analysis. Pattern Recognition Letters, 19, 1319–1324.

    Takiyama R. , 'Determination of meat quality by texture analysis ' (1998 ) 19 Pattern Recognition Letters : 1319 -1324 .

    • Search Google Scholar
  • Sun, X., Chen, K.J., Maddock-Carlin, K.R., Anderson, V.L., Lepper, A.N., Schwartz, C.A., Keller, W.L., Ilse, B.R., Magolski, J.D., Berg, E.P. (2012) Predicting beef tenderness using color and multispectral image texture features. Meat Science, 92/4, 386–393.

    Berg E.P. , 'Predicting beef tenderness using color and multispectral image texture features ' (2012 ) 92 Meat Science : 386 -393 .

    • Search Google Scholar
  • Toraichi, K., Kwan, P.W.H., Katagishi, K., Sugiyama, T., Wada, K., Mitsumoto, M., Nakai, H., Yoshikawa, F. (2002) On a Fluency Image Coding System for Beef Marbling Evaluation. Pattern Recognition Letters, 23, 1277–1291.

    Yoshikawa F. , 'On a Fluency Image Coding System for Beef Marbling Evaluation ' (2002 ) 23 Pattern Recognition Letters : 1277 -1291 .

    • Search Google Scholar
  • Collapse
  • Expand
The author instructions are available in PDF.
Please, download the file from HERE

 

Senior editors

Editor(s)-in-Chief: Felföldi, József

Chair of the Editorial Board Szendrő, Péter

Editorial Board

  • Beke, János (Szent István University, Faculty of Mechanical Engineerin, Gödöllő – Hungary)
  • Fenyvesi, László (Szent István University, Faculty of Mechanical Engineering, Gödöllő – Hungary)
  • Szendrő, Péter (Szent István University, Faculty of Mechanical Engineering, Gödöllő – Hungary)
  • Felföldi, József (Szent István University, Faculty of Food Science, Budapest – Hungary)

 

Advisory Board

  • De Baerdemaeker, Josse (KU Leuven, Faculty of Bioscience Engineering, Leuven - Belgium)
  • Funk, David B. (United States Department of Agriculture | USDA • Grain Inspection, Packers and Stockyards Administration (GIPSA), Kansas City – USA
  • Geyer, Martin (Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Department of Horticultural Engineering, Potsdam - Germany)
  • Janik, József (Szent István University, Faculty of Mechanical Engineering, Gödöllő – Hungary)
  • Kutzbach, Heinz D. (Institut für Agrartechnik, Fg. Grundlagen der Agrartechnik, Universität Hohenheim – Germany)
  • Mizrach, Amos (Institute of Agricultural Engineering. ARO, the Volcani Center, Bet Dagan – Israel)
  • Neményi, Miklós (Széchenyi University, Department of Biosystems and Food Engineering, Győr – Hungary)
  • Schulze-Lammers, Peter (University of Bonn, Institute of Agricultural Engineering (ILT), Bonn – Germany)
  • Sitkei, György (University of Sopron, Institute of Wood Engineering, Sopron – Hungary)
  • Sun, Da-Wen (University College Dublin, School of Biosystems and Food Engineering, Agriculture and Food Science, Dublin – Ireland)
  • Tóth, László (Szent István University, Faculty of Mechanical Engineering, Gödöllő – Hungary)

Prof. Felföldi, József
Institute: MATE - Hungarian University of Agriculture and Life Sciences, Institute of Food Science and Technology, Department of Measurements and Process Control
Address: 1118 Budapest Somlói út 14-16
E-mail: felfoldi.jozsef@uni-mate.hu

Indexing and Abstracting Services:

  • CABI
  • ERIH PLUS
  • SCOPUS

2023  
Scopus  
CiteScore 1.8
CiteScore rank Q2 (General Agricultural and Biological Sciences)
SNIP 0.497
Scimago  
SJR index 0.258
SJR Q rank Q3

Progress in Agricultural Engineering Sciences
Publication Model Hybrid
Submission Fee none
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Article Processing Charge 900 EUR/article
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription fee 2025 Online subsscription: 173 EUR / 190 USD
Print + online subscription: 200 EUR / 220 USD
Subscription Information Online subscribers are entitled access to all back issues published by Akadémiai Kiadó for each title for the duration of the subscription, as well as Online First content for the subscribed content.
Purchase per Title Individual articles can be purchased at the prices indicated.

Progress in Agricultural Engineering Sciences
Language English
Size B5
Year of
Foundation
2004
Volumes
per Year
1
Issues
per Year
1
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 1786-335X (Print)
ISSN 1787-0321 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Jan 2024 28 26 0
Feb 2024 39 6 0
Mar 2024 67 0 1
Apr 2024 21 0 0
May 2024 21 0 0
Jun 2024 40 0 0
Jul 2024 12 0 0