disruptive measurement technologies!€¦ · graham gardner . disruptive measurement technologies!...

Graham Gardner

Disruptive measurement technologies!

Outline • Carcase measurement – the status quo

• Project to accelerate development

– Beef and lamb industries

• Detail progress for some technologies

Precision measurement from paddock/pen to plate

Predict quality and amount of final product

Conception Live Animal Carcase Retail Cuts Cooked Product Value Value Value Value

Australian Lamb Market • Lamb traded largely on carcase weight

• Fat penalties only at the extremes

• 5mm < GR tissue depth < 20mm

Loin Eating Quality and HSCW

40

50

60

70

80

90

100

14 19 24 29 34

Ove

rall

Liki

ng

Hot Standard Carcase Weight (kg)

50

52

54

56

58

60

62

64

66

55 56 57 58 59 60 61 62 63

Actu

al CT

Lean

%

Predicted CT Lean% (predicted from HSCW and GR Estimate)

R2=0.20; RMSE=2.67 Palpated GR and HSCW

Beef isn’t much better…

Sheep Cattle

P8 Fat Depth GR tissue depth

9

Meat Standards Australia eating quality model Industry feedback - MSA

• Lean meat yield – More fat trimmed (labour/waste) – Inconsistent retail cut size

• Eating quality – Consumer confidence

Variability in these traits has a cost!

• Variability can be managed with… –carcase sorting (prior to fabrication) –cut sorting for cut size and EQ


• Variability can be managed with… –carcase sorting (prior to fabrication) –cut sorting for cut size and EQ


If we can measure it!

We need measurement technologies!

This project is supported by funding from the Australian Government Department of Agriculture and Water Resources as part of its Rural R&D for Profit programme in partnership with Research & Development Corporations, commercial companies, state departments and universities

Advanced Livestock Measurement Technologies



Conception Live Animal Carcase Retail Cuts Cooked Product

Hyperspectral NitFom

DEXA GR Probe

Synergy with Automation

3D Imaging

Value Value Value Value

LMY:

Eating Quality:




Enhanced Beef MSA

Cuts-based Lamb MSA

New Breeding Values

Enhanced Producer Feedback

Systems to improve

compliance

Cut wt prediction systems

Profit functions to optimise

carcase use 0

0.02

0.04

0.06

0.08

0.1

0.12

10 15 20 25 30 35 $

Benchmarking systems

0

0.02

0.04

0.06

0.08

0.1

0.12

10 15 20 25 30 35

Prioritising Techs for investment


Measurement tech. priorities Earlier the better!


Measurement tech. priorities Earlier the better!

– Ease of implementation/speed – Precision/accuracy – Cost vs benefit

Measurement tech. priorities

$$$ Return per lamb is less!

Lean Meat Yield

Devices for yield measurement

Eye muscle

Ultrasound

Sheep Probe

Devices for yield measurement

Hyperspectral Camera

Point measures for prediction

Devices for yield measurement Devices for yield measurement

GR Knife

Lean Redistribution of muscle

+8%

+ 5%

- 5%

Measured here!

Lean Redistribution of muscle

+8%

+ 5%

- 5%

Measured here! Biased!

Need to move towards systems that measure whole carcase lean!

Whole carcase LMY technologies

Computed Tomography

Whole carcase LMY technologies

3D imaging

Computed Tomography

DEXA

2D X-Ray for driving robots Scott Technology

Adapt existing 2D Xray hardware

Dual Energy Images Low Energy Image High Energy Image

R value = ln(I/I0)LowEnergy/ln(I/I0)HighEnergy

To drive industry adoption of yield measurement and payment

JBS Bordertown, SA

1 Agistment, SA

100 lambs (29kg)

100 lambs (24kg)

400 lambs (24kg) DEXA

Kirby Nucleus Flock

1 600 lambs

Hyperspectral

CT Scanning

Calibration

Nucleus Flock/DEXA

0

5

10

15

20

25

30

35

40

45

10 15 20 25 30 35 40

GR Ti

ssue D

epth

(mm)

Hot Standard Carcase Weight (kg)

Nucleus Flock Kill 6 (30/9)Nucleus Flock Kill 5 (9/9)Nucleus Flock Kill 4 (5/8)Nucleus Flock Kill 3 (29/7)Nucleus Flock Kill 2 (22/7)Nucleus Flock Kill 1 (24/6)

Predicting CT Fat%

12

17

22

27

32

12 17 22 27 32

Actu

al CT

Fat%

Predicted CTFat%

12

17

22

27

32

12 17 22 27 32

Actu

al CT

Fat%

Predicted CTFat%

12

17

22

27

32

12 17 22 27 32

Actu

al CT

Fat%

Predicted CTFat%

12

17

22

27

32

12 17 22 27 32

Actu

al CT

Fat%

Predicted CTFat%

R2=0.84, RMSE=1.64 R2=0.85, RMSE=1.43

R2=0.85, RMSE=1.35 R2=0.87, RMSE=1.45

First Test Nucleus Flock kill 1

Nucleus Flock kill 2 Nucleus Flock kill 3

15

20

25

30

35

40

15 20 25 30 35 40

Actu

al F

at %

Predicted Fat %

R2=0.88, RMSE=1.54

Predicting CT Fat%

R2 - 0.91 RMSE - 0.054kg

Predicting round weight using HCWT plus DEXAfat value

So where to next…? • Predict cut weights

• Further hard-ware development

• Improved image analysis techniques

• Calibration systems

• Industry confidence

Beef DEXA

Beef DEXA Development R2 = 0.85 R2 = 0.93

Forequarter Fat Forequarter Bone

Forequarter Lean

R2 = 0.62

Weak association for hindquarter bone (R2 = 0.54)

No association!

Beef DEXA Development

Eating Quality “Let’s start with IMF”

• Near infrared probe (hot carcase)

• Computed tomography (hot carcase)

• Electrical impedance probe (hot carcase)

• High resolution RGB camera (cold carcase)

• Hyperspectral camera (cold carcase)

IMF Technologies

Hyperspectral Imaging

Carometec

Autofom

Fat-o-meter Ultrafom

Hyperspectral Camera

Hyperspectral IMF

R² = 0.5025

0

1

2

3

4

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6

7

8

9

10

0 2 4 6 8 10

Pred

icte

d IM

F

Chemical IMF

• For grading: • Eye muscle area • IMF (marbling scores) • Fat colour • Meat colour • Subcutaneous fat • Separate fat from bone and IMF from bonedust • Ossification

Hyperspectral Imaging

A key component of MLA’s R&D strategy

Summary • Need carcase measurement:

• transparency • LMY/Eating quality antagonism

• Advanced livestock measurement technologies • Good progress in LMY measurement

• DEXA one option • Still need cheap alternatives for small plants – GR, 3D

• IMF for eating quality promising • hyperspectral

Summary • Need carcase measurement:

• transparency • LMY/Eating quality antagonism

• Advanced livestock measurement technologies • Good progress in LMY measurement

• DEXA one option • Still need cheap alternatives for small plants – GR, 3D

• IMF for eating quality promising • hyperspectral

Paid for what you produce!

Questions?

Hyperspectral Imaging Danish Ham

Bone

Meat

Fat

IMF?

Cheaper LMY alternatives

3D imaging GR Probe

Improved image analysis

Influence of abattoir factors?

• Spray chilling

• Carcase orientation (180 degree turn)

• Carcase temperature

• Time post mortem (but no loss in precision)

The genetic trend is worrying…

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Chan

ge in

Bre

edin

g Va

lue

Year of Birth

LAMBPLAN Genetic Trends (May 2016) Carcase Weight (kg)Intramuscular Fat (%)Shear Force (Newtons)Lean Meat Yield (%)

The genetic trend is worrying…

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Chan

ge in

Bre

edin

g Va

lue

Year of Birth

LAMBPLAN Genetic Trends (May 2016) Carcase Weight (kg)Intramuscular Fat (%)Shear Force (Newtons)Lean Meat Yield (%)

We need to measure these traits!



DEXA

Carcase Calculator rework

CT Scanning

DEXA Lean Value = 52



What does extra precision mean for the carcase calculator?

$100

$150

$200

$250

$300

$350

$400

10 15 20 25 30 35 40

Carca

se Va

lue ($

)

Hot Carcase Weight (kg)

GR = 5 mm

GR = 10 mm

GR = 15 mm

GR = 20 mm

GR = 25 mm

$39.70

$12.20

What does extra precision mean for the carcase calculator?

$100

$150

$200

$250

$300

$350

$400

10 15 20 25 30 35 40

Carca

se Va

lue ($

)


GR = 5 mm

GR = 10 mm

GR = 15 mm

GR = 20 mm

GR = 25 mm

$100

$150

$200

$250

$300

$350

$400

10 15 20 25 30 35 40

Carca

se Va

lue ($

)


CT Lean % = 64.7

CT Lean % = 59.3

CT Lean % = 54

CT Lean % = 48.6

CT Lean % = 43.2

$39.70

$76.15 $12.20

$31.91

DEXA

Carcase Calculator rework

CT Scanning




50

52

54

56

58

60

62

64

66

52 54 56 58 60 62 64

Actu

al CT

Lean

%

Predicted CT Lean% (predicted from HSCW and GR Knife)

Knife GR & HSCW R2=0.30; RMSE=2.34

Price Grid

Yield Measurement Boning Room: Benchmark Efficiency

Boning error = difference between expected versus actual saleable meat

Boning Room: Less Fat Trim/Labour

Retail: Cut Consistency

Capturing the value of LMY% Long Term Population Response to Selection

Estimate yield gain/yr in response to price signal

Immediate quality response Producers with good muscling genetics will target grid

Immediate supply response a) Supply may increase (if bonus system)

Carcase Sorting Optimise allocation of carcases to different fabrication end-points

VIAscan predicts lean meat yield

46

48

50

52

54

56

58

47 49 51 53 55 57 59

Bon

ers

Lean

Mea

t Yi

eld

(%)

VIAScan Lean Meat Yield (%)

R2=0.45; RMSE=2.30

50

52

54

56

58

60

62

64

66

52 54 56 58 60 62 64 66

Actu

al CT

Lean

%

Predicted CT Lean% (predicted from Cut Weights)

Cut weights and tissue depths R2=0.66; RMSE=1.63


• Predict quality and amount of final product


Hyperspectral NitFom

DEXA GR Probe

Synergy with Automation

3D Imaging

Value Value Value Value

LMY:

Eating Quality:

Producer Feedback

Data to genetic databases Predict eating quality

Predict cut wt

Optimal use of carcases

Forecast carcase fat, muscle & bone

from live animal

Lamb DEXA Development • Sooner the better!

2012 2013 2014 2015 2016 2017 Phase 1

1st Prototype test

Phase 2 Phase 3 Phase 4

Com. prototype ready! Support adoption

Collect calibration data using com. prototype

Test processing factors

Expt prototype ready

Border Leicester

Coopworth

Dohne Merino Merino Poll Merino

Poll Dorset Texel Suffolk White Suffolk

-2

-1.5

-1

-0.5

0

0.5

1

1.5Fa

t Res

idua

l %

Und

er-p

redi

cted

O

ver-p

redi

cted

Residual effects of sire breed

disruptive measurement technologies!€¦ · graham gardner . disruptive measurement technologies!...

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