Quantification of the intramuscular fat content in pork using hyperspectral imaging

2015 ◽  
Author(s):  
Martin Scheeder ◽  
Andreas Vidman
Keyword(s):  
Hyperspectral Imaging ◽  
Intramuscular Fat ◽  
Fat Content ◽  
Intramuscular Fat Content

scholarly journals Beef Quality Grade Classification Based on Intramuscular Fat Content Using Hyperspectral Imaging Technology

2021 ◽  
Vol 11 (10) ◽  
pp. 4588
Author(s):  
Mohammed Raju Ahmed ◽  
DeMetris D. Reed ◽  
Jennifer M. Young ◽  
Sulaymon Eshkabilov ◽  
Eric P. Berg ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Intramuscular Fat ◽  
Individual Performance ◽  
Proximate Analysis ◽  
Fat Content ◽  
Processing Method ◽  
Binary Images ◽  
Grade Classification ◽  
Beta Coefficient ◽  
Intramuscular Fat Content

Fat content is one of the most important parameters of beef grading. In this study, a hyperspectral imaging (HSI) system, combined with multivariate data analysis, was adopted for the classification of beef grades. Three types of beef samples, namely Akaushi (AK), USDA prime, and USDA choice, were used for HSI image acquisition in the spectral range of 400–1000 nm. Spectral information was extracted from the image by applying the partial least squares discriminant analysis (PLS-DA) for the three classifications. A total of eight different types of data pre-processing procedures were tested during PLS-DA to evaluate their individual performance, with the accepted pre-processing method selected based on the highest accuracy. Chemical and binary images were generated to visualize the fat mapping of the samples. Quantitative analysis of the samples was performed for the reference measurement of the dry matter and fat content. The highest overall accuracy, 86.5%, was found using the Savitzky–Golay second derivatives pre-processing method for PLS-DA analysis. The optimal wavelength values were found from the beta coefficient curve. The chemical and binary images showed significant differences in fat mapping among the three groups of samples, with AK having the greatest intramuscular fat content and USDA choice having the least. Similar results were observed during the proximate analysis. The findings of this study demonstrate that the HSI technique is a potential tool for the fast and non-destructive determination of beef grades based on fat mapping.

Partial least squares and machine learning for the prediction of intramuscular fat content of lamb loin

Meat Science ◽  
2021 ◽  
Vol 177 ◽  
pp. 108505
Author(s):  
Stephanie M. Fowler ◽  
David Wheeler ◽  
Stephen Morris ◽  
Suzanne I. Mortimer ◽  
David L. Hopkins
Keyword(s):  
Machine Learning ◽  
Least Squares ◽  
Partial Least Squares ◽  
Intramuscular Fat ◽  
Fat Content ◽  
Intramuscular Fat Content

Selection against abdominal fat percentage may increase intramuscular fat content in broilers

2016 ◽  
Vol 133 (5) ◽  
pp. 422-428 ◽  
Author(s):  
L. Leng ◽  
H. Zhang ◽  
J.Q. Dong ◽  
Z.P. Wang ◽  
X.Y. Zhang ◽  
...  
Keyword(s):  
Intramuscular Fat ◽  
Abdominal Fat ◽  
Fat Content ◽  
Fat Percentage ◽  
Intramuscular Fat Content

scholarly journals Beef tenderness and intramuscular fat proteomic biomarkers: muscle type effect

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4891 ◽  
Author(s):  
Brigitte Picard ◽  
Mohammed Gagaoua ◽  
Marwa Al-Jammas ◽  
Leanne De Koning ◽  
Albéric Valais ◽  
...  
Keyword(s):  
Triosephosphate Isomerase ◽  
Troponin T ◽  
Intramuscular Fat ◽  
Fat Content ◽  
Biological Functions ◽  
Muscle Type ◽  
Triceps Brachii ◽  
Beef Tenderness ◽  
Fast Myosin ◽  
Intramuscular Fat Content

Tenderness and intramuscular fat content are key attributes for beef sensory qualities. Recently some proteomic analysis revealed several proteins which are considered as good biomarkers of these quality traits. This study focuses on the analysis of 20 of these proteins representative of several biological functions: muscle structure and ultrastructure, muscle energetic metabolism, cellular stress and apoptosis. The relative abundance of the proteins was measured by Reverse Phase Protein Array (RPPA) in five muscles known to have different tenderness and intramuscular lipid contents: Longissimus thoracis (LT), Semimembranosus (SM), Rectus abdominis (RA), Triceps brachii (TB) and Semitendinosus (ST). The main results showed a muscle type effect on 16 among the 20 analyzed proteins. They revealed differences in protein abundance depending on the contractile and metabolic properties of the muscles. The RA muscle was the most different by 11 proteins differentially abundant comparatively to the four other muscles. Among these 11 proteins, six were less abundant namely enolase 3 (ENO3), phosphoglucomutase 1 (PGK1), aldolase (ALDOA), myosin heavy chain IIX (MyHC-IIX), fast myosin light chain 1 (MLC1F), triosephosphate isomerase 1 (TPI1) and five more abundant: Heat shock protein (HSP27, HSP70-1A1, αB-crystallin (CRYAB), troponin T slow (TNNT1), and aldolase dehydrogenase 1 (ALDH1A1). Four proteins: HSP40, four and a half LIM domains protein 1 (FHL1), glycogen phosphorylase B (PYGB) and malate dehydrogenase (MDH1) showed the same abundance whatever the muscle. The correlations observed between the 20 proteins in all the five muscles were used to construct a correlation network. The proteins the most connected with the others were in the following order MyHC-IIX, CRYAB, TPI1, PGK1, ALDH1A1, HSP27 and TNNT1. This knowledge is important for understanding the biological functions related to beef tenderness and intramuscular fat content.

scholarly journals Effect of Intramuscular Fat Content on the Meat Quality and Antioxidative Dipeptides of Hanwoo Beef

2013 ◽  
Vol 26 (1) ◽  
pp. 117-124 ◽  
Author(s):  
Cheorun Jo ◽  
Dinesh D. Jayasena ◽  
Dong-Gyun Lim ◽  
Kyung-Haeng Lee ◽  
Jong-Ju Kim ◽  
...  
Keyword(s):  
Meat Quality ◽  
Intramuscular Fat ◽  
Fat Content ◽  
Intramuscular Fat Content
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