Rapid prediction of pork quality : correlation of fresh meat measurements to pork water holding capacity and its technological quality

C. Kapper

Research output: Thesisinternal PhD, WU

Abstract

 Water holding capacity (WHC) of pork defines the sensory appreciation and processing yields of meat. Pork varies in WHC and is mainly generated by differences in post mortem muscle metabolism of carcasses. Nowadays, the pork processing industry performs sorting of carcasses and primal cuts on the basis of weight and lean characteristics. Additional sorting by WHC can further optimize processing yields of pork products. The aim of this thesis was to validate rapid prediction of pork WHC. The first objective of this thesis was to investigate the possibilities of a rapid prediction of pork WHC by measuring parameters such as pH, colour L*, drip loss%, water absorption, and by NIRS at laboratory scale and at pig processing plant scale. Results revealed that NIRS prediction equations could be developed to predict drip loss% and colour L* of pork samples. Equations for colour a*, b*, and pHu were not applicable for prediction of WHC. The positive results of NIRS to predict WHC and colour L* at laboratory scale led to further research to study NIRS prediction of pork quality (pH, colour L*, and WHC) under pig processing plant conditions. It was concluded that NIRS prediction equations can be used for screening WHC at pig processing plants. Also, characterization of moisture loss from muscle early post mortem and whether these losses are useful in predicting WHC of fresh pork was investigated. Results revealed moisture losses from muscle tissue early post mortem which suggested that select time periods correspond to culmination of biochemical and physical events facilitating moisture release, which can be used for early drip prediction. Results suggested an approach for capturing moisture release early post mortem which may be used to predict WHC in pork. The second objective was to investigate if predictions of pork WHC could be used to optimize processing of pork. Technological yields could not be predicted (R2< 0.21 and RPD < 1.1) by NIRS. Pre-selection of back bacons by NIRS predicted WHC values, did result in significant different average pHu and colour L* between both groups. It was concluded that NIRS can be used to predict rapid fresh ham quality for sorting and optimization of the cooked ham process. The overall conclusion of this thesis is that NIRS prediction equations for WHC can be developed for pork loin samples measured at pig processing plants and that these prediction equations can be used to optimize processing of pork.

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Urlings, Bert, Promotor
  • Klont, R.E., Co-promotor, External person
  • Verdonk, J.M.A.J., Co-promotor
Award date21 Dec 2012
Place of PublicationS.l.
Publisher
Print ISBNs9789461734280
Publication statusPublished - 2012

Fingerprint

water holding capacity
meat quality
pork
meat
prediction
color
sorting
swine
drip loss
ham
bacon
muscles
loins
muscle tissues
water uptake
screening

Keywords

  • pigmeat
  • meat quality
  • water holding capacity
  • food processing
  • food processing quality

Cite this

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title = "Rapid prediction of pork quality : correlation of fresh meat measurements to pork water holding capacity and its technological quality",
abstract = " Water holding capacity (WHC) of pork defines the sensory appreciation and processing yields of meat. Pork varies in WHC and is mainly generated by differences in post mortem muscle metabolism of carcasses. Nowadays, the pork processing industry performs sorting of carcasses and primal cuts on the basis of weight and lean characteristics. Additional sorting by WHC can further optimize processing yields of pork products. The aim of this thesis was to validate rapid prediction of pork WHC. The first objective of this thesis was to investigate the possibilities of a rapid prediction of pork WHC by measuring parameters such as pH, colour L*, drip loss{\%}, water absorption, and by NIRS at laboratory scale and at pig processing plant scale. Results revealed that NIRS prediction equations could be developed to predict drip loss{\%} and colour L* of pork samples. Equations for colour a*, b*, and pHu were not applicable for prediction of WHC. The positive results of NIRS to predict WHC and colour L* at laboratory scale led to further research to study NIRS prediction of pork quality (pH, colour L*, and WHC) under pig processing plant conditions. It was concluded that NIRS prediction equations can be used for screening WHC at pig processing plants. Also, characterization of moisture loss from muscle early post mortem and whether these losses are useful in predicting WHC of fresh pork was investigated. Results revealed moisture losses from muscle tissue early post mortem which suggested that select time periods correspond to culmination of biochemical and physical events facilitating moisture release, which can be used for early drip prediction. Results suggested an approach for capturing moisture release early post mortem which may be used to predict WHC in pork. The second objective was to investigate if predictions of pork WHC could be used to optimize processing of pork. Technological yields could not be predicted (R2< 0.21 and RPD < 1.1) by NIRS. Pre-selection of back bacons by NIRS predicted WHC values, did result in significant different average pHu and colour L* between both groups. It was concluded that NIRS can be used to predict rapid fresh ham quality for sorting and optimization of the cooked ham process. The overall conclusion of this thesis is that NIRS prediction equations for WHC can be developed for pork loin samples measured at pig processing plants and that these prediction equations can be used to optimize processing of pork.",
keywords = "varkensvlees, vleeskwaliteit, waterbergend vermogen, voedselverwerking, kwaliteit voor voedselverwerking, pigmeat, meat quality, water holding capacity, food processing, food processing quality",
author = "C. Kapper",
note = "WU thesis 5387",
year = "2012",
language = "English",
isbn = "9789461734280",
publisher = "s.n.",
school = "Wageningen University",

}

TY - THES

T1 - Rapid prediction of pork quality : correlation of fresh meat measurements to pork water holding capacity and its technological quality

AU - Kapper, C.

N1 - WU thesis 5387

PY - 2012

Y1 - 2012

N2 -  Water holding capacity (WHC) of pork defines the sensory appreciation and processing yields of meat. Pork varies in WHC and is mainly generated by differences in post mortem muscle metabolism of carcasses. Nowadays, the pork processing industry performs sorting of carcasses and primal cuts on the basis of weight and lean characteristics. Additional sorting by WHC can further optimize processing yields of pork products. The aim of this thesis was to validate rapid prediction of pork WHC. The first objective of this thesis was to investigate the possibilities of a rapid prediction of pork WHC by measuring parameters such as pH, colour L*, drip loss%, water absorption, and by NIRS at laboratory scale and at pig processing plant scale. Results revealed that NIRS prediction equations could be developed to predict drip loss% and colour L* of pork samples. Equations for colour a*, b*, and pHu were not applicable for prediction of WHC. The positive results of NIRS to predict WHC and colour L* at laboratory scale led to further research to study NIRS prediction of pork quality (pH, colour L*, and WHC) under pig processing plant conditions. It was concluded that NIRS prediction equations can be used for screening WHC at pig processing plants. Also, characterization of moisture loss from muscle early post mortem and whether these losses are useful in predicting WHC of fresh pork was investigated. Results revealed moisture losses from muscle tissue early post mortem which suggested that select time periods correspond to culmination of biochemical and physical events facilitating moisture release, which can be used for early drip prediction. Results suggested an approach for capturing moisture release early post mortem which may be used to predict WHC in pork. The second objective was to investigate if predictions of pork WHC could be used to optimize processing of pork. Technological yields could not be predicted (R2< 0.21 and RPD < 1.1) by NIRS. Pre-selection of back bacons by NIRS predicted WHC values, did result in significant different average pHu and colour L* between both groups. It was concluded that NIRS can be used to predict rapid fresh ham quality for sorting and optimization of the cooked ham process. The overall conclusion of this thesis is that NIRS prediction equations for WHC can be developed for pork loin samples measured at pig processing plants and that these prediction equations can be used to optimize processing of pork.

AB -  Water holding capacity (WHC) of pork defines the sensory appreciation and processing yields of meat. Pork varies in WHC and is mainly generated by differences in post mortem muscle metabolism of carcasses. Nowadays, the pork processing industry performs sorting of carcasses and primal cuts on the basis of weight and lean characteristics. Additional sorting by WHC can further optimize processing yields of pork products. The aim of this thesis was to validate rapid prediction of pork WHC. The first objective of this thesis was to investigate the possibilities of a rapid prediction of pork WHC by measuring parameters such as pH, colour L*, drip loss%, water absorption, and by NIRS at laboratory scale and at pig processing plant scale. Results revealed that NIRS prediction equations could be developed to predict drip loss% and colour L* of pork samples. Equations for colour a*, b*, and pHu were not applicable for prediction of WHC. The positive results of NIRS to predict WHC and colour L* at laboratory scale led to further research to study NIRS prediction of pork quality (pH, colour L*, and WHC) under pig processing plant conditions. It was concluded that NIRS prediction equations can be used for screening WHC at pig processing plants. Also, characterization of moisture loss from muscle early post mortem and whether these losses are useful in predicting WHC of fresh pork was investigated. Results revealed moisture losses from muscle tissue early post mortem which suggested that select time periods correspond to culmination of biochemical and physical events facilitating moisture release, which can be used for early drip prediction. Results suggested an approach for capturing moisture release early post mortem which may be used to predict WHC in pork. The second objective was to investigate if predictions of pork WHC could be used to optimize processing of pork. Technological yields could not be predicted (R2< 0.21 and RPD < 1.1) by NIRS. Pre-selection of back bacons by NIRS predicted WHC values, did result in significant different average pHu and colour L* between both groups. It was concluded that NIRS can be used to predict rapid fresh ham quality for sorting and optimization of the cooked ham process. The overall conclusion of this thesis is that NIRS prediction equations for WHC can be developed for pork loin samples measured at pig processing plants and that these prediction equations can be used to optimize processing of pork.

KW - varkensvlees

KW - vleeskwaliteit

KW - waterbergend vermogen

KW - voedselverwerking

KW - kwaliteit voor voedselverwerking

KW - pigmeat

KW - meat quality

KW - water holding capacity

KW - food processing

KW - food processing quality

M3 - internal PhD, WU

SN - 9789461734280

PB - s.n.

CY - S.l.

ER -