Upload
others
View
5
Download
0
Embed Size (px)
Citation preview
Meat Quality Grading TodayPaul Allen
What is meat quality?
• Can mean different things at each point in the supplychain
• Consumer is ultimate arbiter – if it doesn’t satisfyexpectations then they may not purchase again
• At point of sale – appearance is important – colour,fatness, marbling, lack of drip, packaging
• After cooking – tenderness, juiciness, flavour, overallexperience
• Can be assessed by trained panels – more descriptorscan be used
• Can be assessed by untrained consumers - largenumbers
Why grade on palatability?
• Inconsistent eating quality –AUS, US, IRL
• Beef consumption declining
• Increased competition
• EUROP grading unrelatedto palatability
• Consumers willing to payfor quality
Current meat quality grading Most countries DO NOT grade on eating quality
Notable exceptions are US and Australia
US – Carcasses graded on yield and quality
Quality grade is based on visual assessment of marbling (loin) and maturity(hand held camera systems can be used)
Marbling is the amount and distribution of visible flecks of fat within the eyemuscle at 12th/13th rib
Marbling is primary factor in determining quality grade
Maturity (physiological age) is assessed visually
Degree of ossification of cartilage on vertebrae and spinal processes, colourof bones
Colour and texture (fineness of grain) of loin muscle (less emphasis thanossification)
All these are combined to give an overall quality grade – Prime, Choice, Select
Australia - Measures to improve tenderness known but not interactions - alsobased on expert panels not consumers
MSA solution – predictive model using PACCP approach
The PACCP approach
Conception
Consumption
Consumerfeedback
GeneticsNutrition
Pre-slaughter factors
Post-slaughter factors
Chilling/ageing
Processing
Cooking
Packaging
Critical Control Points
MSA grading
Assess effect of pre and postmortem factors to producepredictive model
Effects measured as responseof consumers
Large database – 65,000consumers, 420,000 samples
Very detailed protocols forsampling, cooking etc.
Cuts based model
• Original model graded carcasses
• Became clear that cuts weredifferent – can’t predictpalatability of all cuts by gradingcarcass as cuts responddifferently to various factorsparticularly ageing, carcasssuspension and cooking method
• Therefore developed cuts basedmodel – palatability of individualcuts predicted for range ofcooking methods
Factors in the model Predictors
Breed (BI)
sex
growth rate
Electrical stimulation
hanging method
Marbling
Ossification
ageing
cooking method
pH
rib fat
Basic criteria
minimum stress
• Thresholds for
– ossification score
– pHu
– colour
– rib fat
Components of palatability
Combination of all factors that make beefenjoyable to eat, assessed by sensoryanalysis and weighted to give quality score
Main factors are
tenderness x 0.4
juiciness x 0.1
flavour x 0.2
overall liking x 0.3
= Meat Quality Score
Consumer grades
Ungraded 3 star 4 star 5 star
Grindingbeef
Everydayquality
Better thanEveryday
Premiumquality
MeatQualityScore
< 48 48 - 63 64 - 79 80+
Format Name Input ?Aged cut muscle GRL RST SFR TSL
% or X if doubt EPBI 0 spinalis SPN081 77 67 77 73
M/F Sex M tenderloin TDR034 82 76
Y or ? / N HGP N tenderloin TDR062 78 77 80 74
Y/N MFV N tenderloin TDR063 73
Y/N
SlYrd
N cube roll CUB045 69 69 69 71
striploin STA045 65 65 67 67
Y/N RnFl N striploin STP045 63 64 66 67
Weight in Kg
HSCW
268 oyster blade OYS036 63 60 66 69
AT/TS/TL/TC/TX
Hang
TX?
blade BLD095 43
blade BLD096 56 59 60 61
mm
Hump
45 chucktender CTR085 49 52 54
USDA measure uoss 140 rump RMP131 60 68 65 71
USDA measure umb 220 rump RMP231 63 71 70 69
mm RbFt 5 rump RMP005 64 72 72
Metered pH UpH 5.58 rump RMP032 71 75
Metered Temp C
Utmp
3 rump RMP087 59 64 62
knuckle KNU066 53 66 61 65
Days Aged Age 14 knuckle KNU098 61 66
Testing the MSA model
• Funding from DAFM – FIRMprogramme
• AUS – Ireland comparison
• Irish commercial sample
• Experiments to test factors
• Ageing
• Stimulation –LVES andHVES
• Breed
• Hanging method
• Boning time –24 v 48h
AUS – IRL comparison
“Matched” set of samplesfrom Ireland and AUS – 18carcasses from each country,6 muscles from each carcass,2 cooking methods
AUS samples tasted by AUSand Irish consumers
Irish samples tasted by Irishconsumers
Compare responses of AUSand Irish consumers
Test fit of model to Irish beefand Irish consumers
Consumer testing Individual muscles removed and
trimmed
Samples prepared and frozen
Cooked in standard way (grilled,roasted, yakiniku) to medium done
Groups of 20 consumers (60 forroasts) – social clubs, sports clubs,charities etc.
Rate for tenderness, juiciness,flavour, overall like
Assign quality category = stars
0
10
20
30
40
50
60
70
80
90
100
Pala
tability
score
s
Tenderness
Juiciness
Flavour
Overall
Relationship between palatabilityscores and quality category
unsatisfactory good everyday better than everyday premium
Scores for all palatability attributes increased with quality category
% of cuts falling in quality categories
0%
20%
40%
60%
80%
100%
unsatisfactory good
everyday
better than
everyday
premium
Beef
Cut
f illet
striploin
rump
blade
outside round
round
Considerable variability in quality for striploin, rump and round
IU YIU GIT YIT GIS YIS GIR YIR GIO YIO GIBYIBG
40
30
20
10
0
-10
-20
-30
-40
0
Iris h R e s idua ls (Ir-M )
Irish consumers v model
Deviations from model significant only for grilled striploin andYakiniku topside
Irish v AUS consumers
U YU GT YT GS YS GR YR GO YO GB YB G
40
30
20
10
0
-10
-20
-30
-40
0
D iffe re nc e s (Ir-A u)
Deviations significant only for Yakiniku, rump and tenderloin
Ageing and stimulation –Effect on MQS
0
10
20
30
40
50
60
70
80
90
LVES NON LVES NON
14 days 28 days
Striploin
Topside
Outside
At 28 days LVES tended to improve MQS of striploin but reducedMQS for outside. Significant negative effect of ageing on OR.
Overall conclusions
• Irish beef fits model at least as well as AUS beef
• Model fits Irish consumers at least as well as AUS
Irish consumers score beef in similar way to AUSconsumers, but not identical (Irish more weight onflavour) and model may need optimising
Model tested over wide range of factors with moderatelylarge database - over 1100 samples
Accounts for different factors reasonably well in mostcircumstances
Some exceptions may be due to electrical inputs on linenot accounted for
Success of MSA in AUS
Number of carcasses graded annually
0
100
200
300
400
500
600
700
99/00 00/01 01/02 02/03 03/04 04/05 05/06
Year
No.ofcarc
asses
MSA grading pays
Average prices ($/kg, Real Dec'05)
15
16
17
18
19
20
21
Nov-04 Dec-04 Jan-05 Feb-05 M ar -05 M ar -05 Apr -05 M ay-05 Jun-05 Jul -05 Aug-05 Aug-05 Sep-05
MSA NonMSALinear (MSA) Linear (NonMSA)
What’s the future for meat qualitygrading?
USDA model not appropriate since grading occurs atquartering
Rapid methods (such as NIR) have promise but arealso most likely to be applied at quartering
MSA predictive model could be adopted
May not be optimised for Irish beef
MSA model also tested in NI, France, Poland –international effort to derive a European model
Could include age, breed etc. from ID, genetics, NIR,images of loin etc.
Thank youfor
listening!