Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review

N Prieto, R Roehe, P Lavin, G Batten, S Andres

Research output: Contribution to journalReview article

321 Citations (Scopus)

Abstract

Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria. 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)175 - 186
Number of pages12
JournalMeat Science
Volume83
Issue number2
DOIs
Publication statusFirst published - 2009

Fingerprint

near-infrared spectroscopy
meat products
product quality
reflectance
meat
meat quality
sensory properties
myoglobin
color
marbling
juiciness
intramuscular fat
water holding capacity
shears
sensory evaluation
firmness
collagen
flavor
crude protein
chemical composition

Bibliographical note

62100053

Keywords

  • NIR spectroscopy
  • Meat
  • Meat products
  • Quality
  • Review

Cite this

Prieto, N ; Roehe, R ; Lavin, P ; Batten, G ; Andres, S. / Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review. In: Meat Science. 2009 ; Vol. 83, No. 2. pp. 175 - 186.
@article{207d25e6e162447fba9a2f3af6a0d1c9,
title = "Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review",
abstract = "Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria. 2009 Elsevier Ltd. All rights reserved.",
keywords = "NIR spectroscopy, Meat, Meat products, Quality, Review",
author = "N Prieto and R Roehe and P Lavin and G Batten and S Andres",
note = "62100053",
year = "2009",
doi = "http://dx.doi.org/10.1016/j.meatsci.2009.04.016",
language = "English",
volume = "83",
pages = "175 -- 186",
journal = "Meat Science",
issn = "0309-1740",
publisher = "Elsevier",
number = "2",

}

Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review. / Prieto, N; Roehe, R; Lavin, P; Batten, G; Andres, S.

In: Meat Science, Vol. 83, No. 2, 2009, p. 175 - 186.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Application of near infrared reflectance spectroscopy to predict meat and meat products quality: a review

AU - Prieto, N

AU - Roehe, R

AU - Lavin, P

AU - Batten, G

AU - Andres, S

N1 - 62100053

PY - 2009

Y1 - 2009

N2 - Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria. 2009 Elsevier Ltd. All rights reserved.

AB - Over the past three decades, near infrared reflectance (NIR) spectroscopy has been proved to be one of the most efficient and advanced tools for the estimation of quality attributes in meat and meat products. This review focuses on the use of NIR spectroscopy to predict different meat properties, considering the literature published mainly in the last decade. Firstly, the potential of NIR to predict chemical composition (crude protein, intramuscular fat, moisture/dry matter, ash, gross energy, myoglobin and collagen), technological parameters (pH value; L*, a*, b* colour values; water holding capacity; Warner–Bratzler and slice shear force) and sensory attributes (colour, shape, marbling, odour, flavour, juiciness, tenderness or firmness) are reviewed. Secondly, the usefulness of NIR for classification into meat quality grades is presented and thirdly its potential application in the industry is shown. The review indicates that NIR showed high potential to predict chemical meat properties and to categorize meat into quality classes. In contrast, NIR showed limited ability for estimating technological and sensory attributes, which may be mainly due to the heterogeneity of the meat samples and their preparation, the low precision of the reference methods and the subjectivity of assessors in taste panels. Hence, future work to standardize sample preparation and increase the accuracy of reference methods is recommended to improve NIR ability to predict those technological and sensory characteristics. In conclusion, the review shows that NIR has a considerable potential to predict simultaneously numerous meat quality criteria. 2009 Elsevier Ltd. All rights reserved.

KW - NIR spectroscopy

KW - Meat

KW - Meat products

KW - Quality

KW - Review

U2 - http://dx.doi.org/10.1016/j.meatsci.2009.04.016

DO - http://dx.doi.org/10.1016/j.meatsci.2009.04.016

M3 - Review article

VL - 83

SP - 175

EP - 186

JO - Meat Science

JF - Meat Science

SN - 0309-1740

IS - 2

ER -