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Predicting pH values,tenderness and cooking loss of chilled pork based on near infrared spectroscopy

近红外光谱技术预测猪肉的pH、嫩度和蒸煮损失



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ChineseJournalofBioprocessEngineering
Vol.10No.6
Nov.2012
doi:10.3969/j.issn.1672-3678.2012.06.011
STUM
:2011-12-23
OGV!

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(31271896);
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:1672-3678(2012)06-0051-05
PredictingpHvalues,tendernessandcookinglossofchiledpork
basedonnearinfraredspectroscopy
DONGQingli,XIONGCheng,HUMenghan,YAOYuan
(SchoolofMedicalInstrumentandFoodEngineering,UniversityofShanghaiforScienceandTechnology,Shanghai200093,China)
Abstract:Thefeasibilitybyusingnearinfraredspectroscopy(NIR)topredictphysicalatributesof
chiledporkwasfocusedon,andtheefectsofdiferentmethodsofpreprocessingspectraandmodelingon
theaccuracyoftheestablishedmodelswerestudiedThesampleswereselectedfromtheundercutofone
batchcarcassesafter24hpostmortem,thedifusereflectancespectramswith400010000cm-1scan
ninginformationwerecolectedformodeling.Theresultsshowedthatthemathematicalmodelforpredic
tingpHvaluesofchiledporkbyPLSaftervalidationtestwasprovedandithadhighercorelationparam
eters(R2C=088,R

P=080,SEC=008,SEP=008),whilefortendernessandcookinglosswithlower
ones(R2C=050and057,R

P=034and050).Moreover,thestudyalsoindicatedthatthemethodfor
smoothingspectracombinedwithmultiplicativescatercorection(MSC)orstandardnormalvariable
transformation(SNV)wasbeterthanothermethodsofpretreatmentspectra.
Keywords:nearinfraredspectroscopy;physicalcharacteristics;pork;partialleastsquares
  
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Fig.1 RelationshipbetweenpredictedandmeasuredpH
valuesofchiledporkafter24hpostmortem
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Table1 InteractivevalidationforpredictingpHvaluesbydiferentmethodsfor
preprocessingspectraandeliminatingoutliers
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R2C R

P R

C R

P R

C R


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MSC 077 071 079 073 029 029
SNV 075 058 076 074 084 082
Sa3+Db1 051 041 059 057 037 034
Sa3+MSC 077 071 072 072 076 065
Sa3+SNV 075 058 075 068 088 080
Db1+MSC 077 060 075 068 XXX XXX
Db1+SNV 077 055 075 068 XXX XXX
S2 00079 00103 00036 00058 00696 00507
   
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Table2 Interactivevalidationforpredictingtendernessbydiferentmethodsfor
preprocessingspectraandeliminatingoutliers
®ÉÊ"“
rsÄ ÙP ÎG
R2C R

P R

C R

P R

C R


Db1 042 039 045 057 020 014
MSC 046 029 028 025 019 039
SNV 050 034 014 018 019 033
Sa3+Db1 040 028 045 030 020 020
Sa3+MSC 054 049 043 037 033 034
Sa3+SNV 022 034 031 029 017 025
Db1+MSC 020 025 051 016 015 015
Db1+SNV 020 025 051 016 021 026
S2 00197 00066 00169 00189 00029 00083
¡
3 
§¨‰D0˜š›xy%ÌÍ{ΫxyûËůÏ@ÂäʼnÆÇ
Table3 Interactivevalidationforpredictingcookinglossratesbydiferentmethodsfor
preprocessingspectraandeliminatingoutliers
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R2C R

P R

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P R

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SNV 015 014 019 018 016 015
Sa3+Db1 028 015 008 002 018 028
Sa3+MSC 020 020 046 045 043 041
Sa3+SNV 037 024 014 011 037 024
Db1+MSC 057 050 XXX XXX 018 018
Db1+SNV 057 050 XXX XXX 045 009
S2 00396 00299 00182 00292 00254 00156
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[1] 
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UãŠN6OÈ
,2000.
[2] 
RX

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A

©d^ª«vw¬­O±{{HN
¯UYZ[
[J].
n{â5-Ög
.2010,36(12):141145.
[3] 
SQ»

ÏT

ÔUa

A

[©d^IÇ-ª«N¯±{ó
4³Y±}£¤
[J].
ª«F⪫vw
,2006,26(12):
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[4] 
DT)

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A

E±²³Y©d^ª«“N¯
¬­£¤
[J].
ª«F⪫vw
,2006,26(4):640642.
[5] 
X¬Y

Z­õ

[F,
A

°±
pH
%YS©d^ª«O
EN¯£¤
[J].
ª«F⪫vw
,2010,30(3):681684.
[6] TejerinaD,LópezParaMM,GarcíaToresS.Potentialusedof
nearinfraredreflectancespectroscopytopredictmeatphysico
chemicalcompositionofguineafowl(Numidameleagris)reared
underdiferentproductionsystems[J].FoodChem,2009,113:
12901296.
[7] SavenijeB,GeesinkGH,vanderPalenJGP,etal.Predictionof
porkqualityusingvisible/nearinfraredreflectancespectroscopy
[J].MeatSci,2006,73:181184.
[8] PrietoN,RossDW,NavajasEA,etal.Onlineapplicationof
visibleandnearinfraredreflectancespectroscopytopredictchem
icalphysicalandsensorycharacteristicsofbeefquality[J].Meat
Sci,2009,83:96103.
[9] AndrésS,SilvaA,SoaresPereiraAL,etal.Theuseofvisible
andnearinfraredreflectancespectroscopytopredictbeefM.lon
gisimusthoracisetlumborumqualityatributesmeat[J].Meat
Sci,2008,78:217224.
[10] PrevolnikM,CandekPotokarM,korjancD.Predictingporkwa
terholdingcapacitywithNIRspectroscopyinrelationtodiferent
referencemethods[J].JFoodEng,2010,98:347352.
[11] YanceyJWS,AppleJK,MeulenetJF,etal.Consumerrespon
sesfortendernessandoveralimpressioncanbepredictedbyvisi
bleandnearinfraredspectroscopy,MeulenetOwensrazorshear,
andWarnerBratzlershearforce[J].MeatSci,2010,85:
487492.
[12] 
,`f

=]
.^
µ‹©H¨Y§N´Œâ;ܯŒ-VY
ÍFvw£¤
[J].
n{æF
,2004(9):4955.
[13] AndrésS,MurayI,NavajasEA,etal.Predictionofsensory
characteristicsoflambmeatsamplesbynearinfraredreflectance
spectroscopy[J].MeatSci,2007,76:509516.
[14] 
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