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Wheat
Triticale
Sorghum
Barley
Soya
Canola
AusScan and NIR Workshop
Veterinary Science Conference Centre, University of Sydney, Camperdown
Campus, Seminar room 115
18th February 2016
Page 1
Wheat
Triticale
Sorghum
Barley
Soya
Canola
Contents …………………………………………………………….Page2
Introduction ………………………………………………………… 3
Practical Application of NIR and data management
Ivan Ward - Agri-Torque ………………………………………….... 10
Foss Instruments for AusScan
Sam Openshaw – Foss Australia …………………………………. 41
The Future of NIR Spectroscopy - Poultry and Swine
Chris Piotrowski - Aunir UK ………………………………………… 50
Why you should be using AusScan technology
Tony Edwards - ACE Livestock Consulting ………………………. 80
Questions and Answers
Caroline Noonan – Aunir UK ……………………………………….. 105
Contacts ……………………………………………………………... 111
Page 2
1World first energy values for cereals fed to livestock.
Pig Digestible Energy (DE);
Poultry Apparent Metaboliseable Energy (AME) and
Ruminant Metaboliseable Energy (ME) values
Wheat
Triticale
Sorghum
Barley
Introduction
Page 3
2
World first “heat damage” – Soybean and Canola
Reactive lysine values
SID lysine (and other amino acids)
Soya
Canola
Introduction
Page 4
Spectrum downloaded to PC
calibrated
(10 to 60 sec)
Wet Chemistry(Up to a week)
Introduction: What is AusScan Online?
Original AusScan
Set-up
Page 5
Spectrum downloaded to PC
Spectrum Uploaded
to AusScan Online
Analysis• Pig DE
• Reactive L
(10 to 60 sec)
(3 - 5 mins)
Internet
Latest
calibrations
Introduction: What is AusScan Online?
Page 6
Wheat
Triticale
Sorghum
Barley
Introduction: Workshop Objectives
The Workshop Objectives
• Improve knowledge and understanding of NIR technology
• Application on the technology – data management
• Using AusScan On-line – Demonstration
• The Future of NIR
• How to Utilises Energy values in your operation
• Interaction / Questions
Page 8
Typical NIR Projects
Replacement of old NIRS
Integration of NIRS platform into feed manufacturing
Expanding components being measured
Improve accuracy and component range
Central data management
Monitoring NIRS performance
Purchased vs in-house Calibration Development
Page 11
Overview
Importance of Nutrient Information
NIR Overview
NIR Opportunities
Investigation of NIR Results
Purchased Calibrations
Page 12
Importance of Nutrient Information
Feed Manufacturing
Ingredients
In-Process
Final Product
Recipe
optimisation
Animal Production
Page 13
Importance of Nutrient Information
Feed Manufacturing
Ingredients
Growing Seasons
Growing Regions
Storage
Suppliers
Substrates
Processes
Manufacturing
Ingredients
Equipment and processes
Operators
Throughput
Environment conditions during
manufacturing
Storage
Grinding Weighing Mixing
Pelleting \ Extruding Conditioning Cooling \ DryingRecipe
Optimisation
Page 14
NIR – the tool of choice for nutrient
analysis
Accurate
Little sample preparation
Quick testing time Non-destructive testing
Multi-components can be predicted with a single analysis
Suitable to inline and at-line evaluation of feedstuffs
Page 16
NIR Basics
Electromagnetic radiation
Spectroscopy uses electromagnetic radiation (light) to analyse materials by
describing the energy transfer between light and matter.
Shining light on materials
Page 17
NIR Basics
NIR has enabled real time evaluation of nutritional characteristics of
Ingredients, such as
Moisture
Protein
Amino acids
Starch
Fat
Energy (AME, DE)
………….
Page 18
NIR Opportunities
Cheaper, FASTER MORE RESULTS
More samples are measured,
Improved nutrient profile
Supplier TonnesMoisture
(%)
Brian's Logistics 19.60 11.4
Ward's Transport 44.10 13.3
Jackson Brothers 40.20 12.7
Brian's Logistics 20.00 11.1
Max & Co. Corn Growers 43.40 12.1
Brian's Logistics 24.00 10.7
Jackson Brothers 44.80 13.2
Brian's Logistics 23.40 11.0
Max & Co. Corn Growers 26.80 11.3
Max & Co. Corn Growers 20.40 12.2
Jackson Brothers 43.45 12.0
Brian's Logistics 23.40 10.6
Max & Co. Corn Growers 41.80 12.3
Brian's Logistics 24.60 11.1
Max & Co. Corn Growers 42.70 12.1
Brian's Logistics 23.90 10.5
Max & Co. Corn Growers 20.02 10.9
Brian's Logistics 22.80 11.0
Jackson Brothers 24.30 11.5
Page 19
NIR Opportunities
Correct ingredient nutrient levels used by the formulation software
Optimised recipe’s nutrient levels close to actual production
nutrient levels
Reduce nutrient overages in feed
Final feed meeting specifications
Capturing ingredient variation in nutrient levels $$$
•Nutrient levels
•Ingredient inclusion limits
Feed Specification
•Cost
•Availability
•Nutrient levels
•Ingredient inclusion limits
Ingredients
•Ingredient list
•Ingredient quantity
Optimised Recipe
Page 20
NIR Opportunities
Inline
Same benefits as at-line NIR – capturing nutrient variation
+
Automatic measurements
Many more measurement points
Feedback to process control computer
Real time
Page 21
Investigation of NIR Results
Data Management and Integrity
Calibrations
Reference Analysis
Site NIRS
Formulation Software
Reports
Result Interpretation
Business Systems
DATA CONNECTION
and VERIFICATION
Page 23
Investigation of NIR Results
Sampling
Sample
NIRS Hardware
Reference Analysis and
Calibrations
NIR Protocols and NIR User
Result Interpretation
Page 25
Investigation of NIR Results
Sampling
Sampling error?
Can the product be resampled?
Can the sample be re-analysed?
New Product?
New Ingredient?
Page 26
Investigation of NIR Results
Sample
Correct Sample and Correct Label?
Sample ID
Sample presentation
Ground
Whole
Pellets
Crumble
Composite sample?
Page 27
Investigation of NIR Results
NIRS Hardware
Regular Servicing
Monitoring - Standards test results
Cleanliness
NIRS
Cup
Grinder Maintenance and particle size consistency
Page 28
Investigation of NIR Results
Calibrations
Component Range
Feed types included
Reports – independent validation with statistics
(correlation, validation error)
Page 29
Investigation of NIR Results
Calibrations - Reviewing
Routinely challenge your calibrations with a selection of samples, in order to
have data available should a query be presented
i.e. from customers, suppliers, users
Page 31
Investigation of NIR Results
NIR Protocols
Training of NIRS users
Sampling, to make sure results are representing the whole lot of product
Capturing opportunity
Protocol for accepting and rejecting inbound ingredients
Protocol for failing final product
Page 32
Investigation of NIR Results
Result Interpretation
Pass or Fail - LIMITS Ingredients
Purchase orders \ contracts
Final product
Specifications
Formulation
Production
Page 33
Investigation of NIR Results
Environmental Conditions
Ambient temperature
Ambient humidity
Sample temperature at time of analysis
Page 34
Investigation of NIR Results
Purchased Calibrations Sampling
Sample
NIRS Hardware
Reference Analysis and
Calibrations
NIR Protocols and NIR User
Result Interpretation
Page 36
Investigation of NIR Results
Purchased Calibrations
Calibrations
Reference Analysis
Site NIRS
Formulation Software
Reports
Result Interpretation
Business Systems
DATA CONNECTION
and VERIFICATION
Page 37
NIR Opportunities
Purchased Calibrations
Advantages
New animal performance indicators of ingredients not previously available
such as Energy (i.e. AME, DE)
Reference analysis and calibration performed by calibration supplier, with
larger datasets
Potential to support the investigation of calibration accuracy
Page 38
NIR Opportunities
Purchased Calibrations
Improvements
Local and new season samples may need to be added to the calibration
Reference analysis and calibration accuracy
Page 39
Dedicated Analytical Solutions THE XDS
Scanning range 400-2500nm
Dual detector system (Si & PbS)
Pre-dispersive NIR system
Transmission and reflectance measurement
Operating with ISIscan – PLS, ANN & LOCAL calibration models
Calibration development with WinISI
Sealed to keep out dirt and moisture
Operating temperature range: 10°C – 35°C
Page 43
Dedicated Analytical Solutions THE XDS
Standardised instrument – transferable calibrations
NIST wavelength standardisation – equal wavelength settings for all instruments
Internal reference - reference will be clean and constant height quality
Page 44
Dedicated Analytical Solutions THE XDS
Flexible sample presentation – standard XDS sample cup, plastic bags, glass vials and beakers
Horizontal transport - stops + scans - moves sample over window for non-homogeneous samples, improved precision with static measurement
Page 45
Dedicated Analytical Solutions THE DS2500
Scanning Monochromator
400-2500 nm
400 -1100 Si detectors
1100-2500 PbS detectors
0.5 or 2.0 nm data resolution
Backward compatible calibrations
Operating temperature: 5-40°C
Humidity: <93%RH
IP 65 (dust and waterproof)
Page 46
Dedicated Analytical Solutions THE DS2500
Internal standards to control the stability of the spectrometer
Improved transferability Internal wavelength reference -
Runs automatically at start-up and on user demand
Wavelength correction (linearization)
Auto-linearization
Page 47
Dedicated Analytical Solutions THE DS2500
RFID for sample cup identification
Scanning time: < 1 min(adjustable sub samples)
Reflectance for dry samples and slurries
Transflectance for opaque samples (liquids )
Page 48
Dedicated Analytical Solutions AusScan Demonstration
Select the Product
Scan the sample
Select the samples
Export to the .nir file
Open the AUNIR website
Go to AusScan
Login with credentials
Upload the .nir file
Page 49
www.aunir.com
The Future of NIR Spectroscopy – Poultry and SwineChris PiotrowskiDirector, Aunir
Page 50
Sugar
Ingredients
Grocery
Retail
Agriculture
A leading multinational in the expanding international markets for sugar and sugar-derived co-products, with operations in the UK, Spain, Southern
Africa and China
Yeast and bakery ingredients and speciality ingredients supplying plant and artisanal bakers, food service and wholesales channels, as well as high-value
ingredients for food and non-food applications, operating worldwide
Primark, a major retail group offering customers quality, up-to-the-minute fashion at value-for-money prices, with over 275 stores in the UK, Ireland, Spain, Portugal, Germany, the Netherlands, Belgium, Austria and France
Supplies products and services to farmers, feed and food manufacturers, processors and retailers, employing over 2,000 people, with distribution
across 65 countries
Hot beverages, sugar and sweeteners, meat, vegetable oils, bread, baked goods and cereals, herbs and spices, and world foods,
with manufacturing facilities in Europe, the Americas and Australasia
Group at a glance ABF 14/15 Revenue £12.8bn
Page 51
www.aunir.com
What makes a good calibration?
Modelling software
Hardware
Spectroscopy Applications
Page 52
NIR spectrometers
Full range
(Scanning)
Dispersive
Foss Unity
FT
Bruker Buchi Thermo
Limited range
Diode Array
Perten
Hardware
Page 53
www.aunir.com
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Lab Based Micro NIR In-Line HandHeld
All scans are not created equal with NIR hardwareHardware
Page 56
Spectral data (X) Reference values (Y)
Y
X
Y = X . B + C
Library = dataset
Current approach (Linear Regression=LR)
Equation ~ calibration~ model ~ fit
Modelling software
Page 59
Pros and Cons (LR)
Pros:• Small size of the equations• Easy to encrypt• Easy to implement and transfer
Cons:• Doesn’t work well in non-linear situations• Doesn’t work with heterogeneous databases• Sometimes accuracy is compromised• Updates require recalibration• It is static• Customer can not add their data
Modelling software
Page 61
Pros and Cons (LWR)
Pros:• Best accuracy• Can work with heterogeneous database • It is dynamic• Easy to maintain and update• Customer can add their data
Cons:• Computationally intensive• Can be slow• Difficult to encrypt• Requires optimisation• Easy to corrupt the database – needs to be managed
Modelling software
Page 66
www.aunir.com
Applications
What are the benefits of NIR?
• Ease of use
• Fast
• Non-contact
• High precision
• Non-destructive
• Glass transparent
• Large sampling size
• Multi-component analysis
• Handles high concentration
Page 67
www.aunir.com
• Analytes of interest should be organic
• Concentration > 0.01% = 1000 ppm
What can be measured by NIR?Applications
Page 68
www.aunir.com
Limitations of NIR
• Not sensitive to minerals
• Not a trace analysis method
• It is a secondary method
Applications
Page 69
www.aunir.com
Products Total & SID Amino Acids Chemical Energy Wheat Alanine Acid Detergent Fibre Broiler AMEBarley Arginine Amylase Broiler AME IntakeOats Aspartic acid Arabinose Estimated ME CattleTriticale Cysteine Arabinoxylan (DM) Estimated ME SheepSorghum Glutamic acid Ash Pig Faecal DE (As received)Corn Glycine B-Glucan (DM) Pig Ileal DE (As received)Legume Grains Histidine Digestible Starch Gross EnergySoya & Rape Isoleucine Fat
Leucine Galactose Fatty AcidsLysine Hydration Capacity Linoleic acidMethionine Lignin Oleic acidPhenylalanine Moisture Palmitic acidProline Neutral Detergent Fibre Stearic acidSerine OligosaccharidesThreonine ProteinTryptophan Resistant StarchTyrosine StarchValine Total Insoluble NSP (DM)Reactive Lysine Total Soluble NSP (DM)
Xylose
AusScan OnlineApplications
Page 70
www.aunir.com
Ground Corn – Particle Size
Sieve Number N Mean SD Min Max SEC RSQ SECV RPD
Ø16 122 14.76 10.061 0.0 44.9 4.890 0.764 5.606 2.1
Ø20 118 37.14 15.140 0.0 82.6 4.793 0.900 5.056 3.2
Ø30 124 56.26 10.538 24.6 87.9 3.913 0.862 4.319 2.7
Ø40 124 68.24 6.926 47.5 89.0 2.707 0.847 2.976 2.6
Ø50 124 75.55 5.287 59.7 91.4 2.092 0.843 2.364 2.5
Ø70 123 79.80 4.526 66.2 93.4 1.737 0.853 2.030 2.6
Ø100 125 83.62 3.860 72.0 95.2 1.457 0.857 1.628 2.6
Ø140 123 86.90 3.119 77.5 96.3 1.256 0.838 1.350 2.5
Ø200 122 89.01 2.609 81.2 96.8 0.966 0.863 1.079 2.7
Ø270 124 90.56 2.241 83.8 97.3 0.945 0.822 1.050 2.4
Pan 126 99.74 0.474 98.3 101.2 0.468 0.026 0.468 1.0
Applications
Page 72
www.aunir.com
Constituent N Mean Range SD SEC RSQ RPD
Salt 17973 0.56 0.010 4.79 0.410 0.109 0.930 4
Calcium 16139 1.25 0.010 8.40 0.926 0.309 0.889 3
Phosphorus 15777 0.64 0.020 3.28 0.137 0.060 0.810 2
Sodium 16079 0.19 0.001 2.50 0.127 0.049 0.850 3
Magnesium 15642 0.20 0.010 0.86 0.086 0.028 0.894 3
Potassium 16051 0.89 0.110 2.56 0.248 0.073 0.913 3
ApplicationsMinerals
Page 73
www.aunir.com
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Co
eff
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of
Var
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Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5
ProteinOil
Spectroscopy
Mixer Profile – 10 samples, NIR spectraPage 74
www.aunir.com
Mixer Profile - % Coefficient of Variation
Mixing time (min)
NIR Sodium Crude Protein
Crude fat
1.0 19.2 81.4 40.3 49.5
2.0 4.4 55.5 8.5 9.3
3.0 2.9 8.1 4.0 6.3
4.0 1.0 11.1 3.2 3.8
5.0 3.4 5.9 4.0 5.5
NIR gives a direct measure of mixability; all other methods report the mixability of a specific feed additive or component, and includes assay variation.
Spectroscopy
Page 75
www.aunir.com
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Ab
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Raw MaterialsCorn Wheat Whole Rape PeasDDGS Full Fat Soy Rape Meal SunflowerSoya Corn Gluten Fish Meal Feather Meal
Spectroscopy
Page 76
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Ab
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Feed Formulation
Fish Meal 2% Full Fat Soya 5% Whole Rape 10% Soya 13% DDGS 15% Wheat 55% Final Feed
Spectroscopy
Page 77
www.aunir.com
Summary
• Instruments will get smaller and more affordable
• Modelling software will become more powerful producing more accurate calibrations
• Applications will continue to grow in complexity
• NIR will be recognised as a true primary spectroscopy technique
Page 78
Why you should be using AUSSCAN technology
AC EdwardsACE Livestock Consulting Pty Ltd
PO Box 108 Cockatoo Valley SA [email protected]
Page 80
Introduction
• All biological functions are energy dependent.
• Pig meat production is energy driven.
• To understand constraints and how to achieve maximum efficiency we need to appreciate the source of energy, its delivery into the pig, the tools the pig has to extract this energy (and how we might assist it) and how it utilizes this energy.
• The pigs is a very adaptive omnivore and can use a wide range of feedstuffs – but these vary in energy content, palatability and transit time.
• ENERGY INTAKE = ENERGY CONTENT IN FEED X FEED INTAKE
Page 81
Cereals LegumesAnimal
Protein
Vegetable
Protein
Milling
offals
Synthetic
amino acids
Food
industry by-
products
Sundry
Wheat* Lupins* Meatmeal* Soyabeanmeal* Millmix* Lysine* Whey Minerals*
Barley* Peas* Blood meal* Full fat soya Rice pollard* Methionine* Brewers yeast Vitamins*
Oats* Faba beans Fishmeal* Cottonseed meal* Oat offals Threonine Bread Various
additives
(Groats) Chickpeas Poultry meal Sunflower meal Pea offals Tryptophan Biscuits Tallow*
Sorghum* Mung beans Milk powder Canola meal* Hominy Isoleucine Breakfast
cerealsVegetable
oils
Triticale Lentils Yeast Peanut meal Valine Confectionery waste Chicken oils
Maize Vetch Feather meal
Safflower meal Arginine Pet food
waste Lucerne
Rye plasma Copra Distillers grain Molasses
Rice Potato waste Cassava
Millet Fruit waste
Olive waste
Palm kernel meal
Materials used in stockfeed manufacture in Australia
* Major use items ACE Livestock Consulting Pty Ltd
Page 82
Table 1 Typical nutrient composition and energy values
of feedstuffs (growing pigs)Starch
+Sugars %
Fat % NDF% Protein% DE
MJ/kg
NE
MJ/kg
Groats 57.5 8.5 10 12 16.0 11.90
White Rice 74.0 1.5 5.3 7.5 15.5 11.61
Corn 64.6 4.0 9.0 8 14.3 11.18
Sorghum 63.0 3.5 8 9 14.25 10.97
Wheat 63.0 2.3 8.5 11 14.0 10.61
Triticale 60.0 2.1 11 11 13.7 10.41
Cassava 67.5 0.7 10 3 12.8 10.16
Barley 53.9 2.6 16.0 10 13.0 9.66
Oats 38.3 6.8 24.0 9 11.6 8.38
Wheat Bran 17.5 4.5 44 15.3 9.4 6.11
Rice Bran 30.0 21 13.0 14.5 14.06 10.55
Rice Bran Ext. 24.5 1 34 15.5 8 4.88
Soybean Meal Exp. 12.0 8.5 11.0 44 15.7 9.42
Canola Meal Exp. 7.7 7.5 28.3 34 13.0 7.3
Sunflower Meal Exp. 8.0 8.0 36.0 32 10.0 6.20
Palm Kernel Exp. 2.5 8.5 58.0 16.5 9.0 5.67
Copra Exp. 10.3 8.2 49.7 20.5 9.9 6.20
Meat & Bone Meal 0 11 6 50 11.7 6.84
Blood Meal 0 0.5 0 88 18.0 9.00
Fish Meal 0 8.9 1 65 16.1 9.50
Tallow 0 99 0 0 35.0 32.0
Soya Oil 0 98.5 0 0 36.9 33.0
Page 83
Grain Industry Descriptions
• Wheat – AGP, AH, ASW, SFW, Feed (F1, F2, etc.)• Barley – Malt, F1, F2, F3
The differentiation is based on • Variety• Test weight (kg/Hl)• Screenings %• Falling No.• Protein %
All of these are poorly correlated to energy value
Page 84
Traditional ways of arriving at Energy Values
Issues
Book values Relevance, methods employed
In vivo digestibility assay Long delays, extreme cost
Wet chemistry Delays, errors, cost
Estimation by regression equations using proximate analysis
For example:
GE = 17.3 + 0.0617 CP + 0.2193 EE + 0.0387CF – 0.1867 Ash + ∆ (correction coefficient)
DE = 0.2247 CP + 0.3171 EE + 0.1720 ST + 0.0318 NDF + 0.1632 Residue
Page 85
Estimating energy values
• Various equations have been developed to estimate energy values by adjusting a basal component up or down relative to chemical composition.
• E.g. • DE (MJ/kg DM) = 17.44 x 0.016EE +0.008CP-0.038ASH-0.015NDF
• NE (MJ/KG DM) = 0.703DE + 0.0066EE – 0.0041CP – 0.0041CF +0.0020ST
DE = Digestible energy, NE= net energy, EE = ether extract, CP = crude protein, CF = crude fibre, NDF = neutral detergent fibre, ST = starch (expressed in g/kg)
Page 86
Estimating DE content of raw materials
• The DE content of unknown materials can be approximated from the proximate analysis
GE/kg
Moisture Nil
Ash Nil
Protein 23.6 MJ X % Crude Protein X Digestibility coefficient
Fat 37.3 MJ X % Crude Fat X Digestibility coefficient
Fibre 17.5 MJ X % Crude fibre X Digestibility coefficient
NFE (CHO) 17.5 MJ X % NFE X Digestibility coefficient
Page 87
Estimating DE of wheat
GE (MJ/kg) DE contribution
Moisture 11% 0
Ash 1.5% 0
Protein 10% X 23.6 X 0.85 = 2.01
Fat 2% X 39.3 X 0.90 = 0.71
Fibre 2.5% X 17.5 X 0.30 = 0.13
NFE (CHO) 73% X 17.5 X 0.85 = 11.24
100% 16.4 14.09
NFE = Nitrogen free extraction, CHO = carbohydrateNFE includes starch, sugars and NDF
Page 88
Based on in vivo animal feeding research
Funding from grains, pig, chicken meat, layer, beef and dairy industries
Technology in use - testing labs, feed mills, integrated livestock producers
WELCOME AUSSCAN !
Real time reliable measurement of DE + more.
Page 89
AusScan NIR
• One technical development that has proved valuable is the AusScan NIR assessment of feedstuffs.
• This has been developed in Australia from cooperation between government and industry and provides the following outputs from a single scan
Moisture Total insoluble NSP Faecal residual starch
Protein Insoluble arabinoxylans AME Broilers
Fat B-glucans AME Intake index
Fibre (Crude, NDF, ADF) Hydration capacity Faecal DE pigs
Ash ME Cattle Ileal DE pigs
Total Starch ME Sheep Faecal DE Intake index
Total soluble NSP Acidosis Index (Ruminants)
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AusScan reveals variation
Wheat Barley Oats Triticale SorghumSheep 12.7-13.7 11.5-13.9 11.2-15.7 12.3-13.4 13.6-14.3Cattle 12.2-13.1 12.2-13.2 10.8-13.4 12.9-13.2 10.2-13.2Pigs 12.4-15.0 10.6-14.7 - 12.3-16.5 15.5-16.6Broilers 12.4-15.6 11.2-13.7 12.6-14.6 11.0-14.6 15.2-16.5Layers 13.1-17.1 11.0-14.8 12.7-16.4 11.6-14.4 15.5-16.3
1 MJ DE/kg = $25-30/T1 % protein = $4-5/T
• Knowledge of actual feeding value allows for – more astute purchasing– Real time formulation adjustments to maintain consistent diet specs which in turn
underpins consistent performance
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Parabolic nature of energy cost/MJOND= optimal nutrient density
• This optimal nutrient density is a mathematical option and doesn’t necessarily correspond to optimal performance in the stock or the lowest cost/kg pigmeat produced. This latter parameter requires more in depth modelling.
Cost/MJ DE
DE
Cost due to energy value falling faster than the cost/T
Cost due to extra protein to balance the energy + more energy dense materials
OND
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Consequences of Unidentified Drift in Energy Content of Feed
• Under supply → ↑VFI, ↑FCR, wasted protein
or same VFI, ↑ FCR, poorer growth
• Over supply → ↓ VFI, maybe ↑ FCR, protein shortfall, -advantage is forfeited
The consequences of a performance disturbance are probably greater than the economic aspects of feed cost.
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AusScan Services Beyond Energy
• Lysine is particularly vulnerable to binding reactions which render it unavailable to the animal. Heat damage and Maillard reactive damage due to exposure to reducing sugars can compromise lysine availability.
• The reactive lysine assay identifies lysine molecules with a free epsilon amino group, which implies its availability for protein synthesis.
• Hence a comparison of total lysine and reactive lysine content reflects the degree of availability of the lysine (or conversely the extent of damage).
• Currently total and reactive lysine assays are available for all feedstuffs, while a test for the full SID amino acid spectrum for soybean meal is also now available. It is planned that this will extend to all feedstuff in due course.
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Value of Reactive Lysine and SID AA Values
• With diets being formulated to the 10 essential amino acids in a ideal protein balance supported by an adequate pool of non-essential amino acids, the need to know the actual contribution of available amino acids for each feedstuff becomes paramount.
• With 7 of the 10 essential amino acids available in synthetic form (lysine, methionine, threonine, tryptophan, isoleucine, valine, arginine) at commercially acceptable prices, we have the capacity to accurately balance the amino acid profile of diets –if we understand the true contribution from the base materials.
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Conclusions
• Knowledge of the real time energy content and digestible amino acid control of feedstuffs is fundamental to effective feed formulation.
• Without control of the nutrient content and balance in the diets, performance will be inevitably compromised and remain variable.
• Investment in AusScan technology will be a major step forward in achieving this control.
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So, why you should be using AusScan Technology
• It is simply the best current means of monitoring energy content in feedstuffs.
• It is– Rapid– Accurate– Repeatable– Reasonable priced– Various output formats can be selected– Provides complimentary information on the amino acid
content of protein meals as well as reactive lysine content.
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AusScan and NIR Workshop Questions and Answers February 18th 2016
1. General Questions
TOPIC General Questions
Question 1
Some concern about this tech is the way in which calibrations are updated and verified.
What assurances can Aunir give in this regard? Is it a national type calibration or region specific? Is there any
weaknesses in the calibrations??
Answer 1
The data is as global as we can get. It was primarily based on Australian grains but has subsequently been
supplemented with grains from South America, North America and Europe. In vivo analysis is very expensive
which is why the AusScan Online calibrations are so unique ‐ to replicate this work would cost millions of
dollars. The idea behind the AusScan Online website is to generate funds which can be reinvested into further
research, thus preserving the longevity of the work the Pork CRC started.
Question 2
Will labs or users be involved in the re‐calibration processes – can we see the data for ourselves and make a
judgement? Had experience where released calibrations yield very poor correlation with wet chemistry when
checked at random.
Answer 2
After each update to the AusScan Online calibrations, a report will be made available for full transparency. The
first report was written by Prof. John Black and efforts are currently being made to produce this information in
a shorter format. This will be circulated to all AusScan Online customers in due course.
Question 3 Could you please outline the standardization protocol ‐ frequency of checks and transparency of outcomes?
Answer 3
Standardisation is only necessary on the old model Foss machines. On newer Foss models and other NIR
instruments, standardisation is not necessary. Aunir prefers to apply repeatability files to calibrations rather
than standardisation. Ingot Check is a monthly ring test service run by Aunir in Europe where known samples
are sent to all customers with the purpose of identifying any slippage of your NIR machine. If you are
interested in becoming a member of this service (even if you are based outside Europe) please get in touch
with Caroline Noonan on [email protected].
Question 4Could you please outline the risk mitigation strategy? What is the fall back position in the event of failure of
parent instrument, fire or flood for instance?
Answer 4
Aunir has sub‐master NIR machines in several different countries around the world which can be used should
anything happen to the master machine in our offices in the UK. We have kept samples that can be rescaned if
necessary. The calibrations and any electronic IP is accessed from two servers which work in constant parallel.
If one server goes down, the other instantly takes over. If both servers go down simultaneously there is a
backup that can be reinstalled on a new server within 24 hours.
Question 5We are interested in trying to set up a calibration for Ionophores. We are just really interested in a qualitative
not quantitative answer – any positive scans would be sent for testing. Would this be possible and reliable?
Answer 5Whilst NIR can detect Ionophores, it can only do so in relatively large quantities. NIR will not be accurate
enough to provide measurement of Ionophores at levels in the region of 10‐20 parts per million.
General Questions
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AusScan and NIR Workshop Questions and Answers February 18th 2016
1. General Questions
TOPIC General Questions
Question 6When doing a calibration – for example, moisture, is it important to ensure after the optimisation that the
quant you choose has included all the moisture band regions or is it more important to rely on the stats?
Answer 6
At Aunir, our preference is to select samples based on the natural variation of the population rather than
selecting for specific measurements. However, this is a matter of personal choice. As long as the sample set
covers the whole range of the samples you will measure, the calibration will be sufficient. Aunir opts to
include all natural variation to ensure that calibrations developed are robust over long periods of time and
wide geographical areas.
Question 7
What is the best way to sort out your samples so as to not place too much weight in one area just based on
the sample size? For example having 200 samples in the 8 – 10% moisture range and only 50 in the 10 – 12%
range.
Answer 7This is similar to Question 6 above. Aunir suggests that clusters of samples should be avoided, and that the
natural variation of the population should be reflected in the sample set as much as possible.
Question 8 Aunir ‐ Do you have or are you working on a urease calibration?
Answer 8
Yes ‐ we do have a urease calibration in our Ingot database. It was developed on data from Bruker
instruments. The correlation is 0.752 with an error of 0.009, range of 0.025‐0.105 and an RPD of 2. Please get
in touch with [email protected] to discuss this calibration further.
Question 9 Is it possible to produce a newsletter with energy results etc for new seasons grains?
Answer 9 Yes ‐ we have plans to release benchmarking reports by country in the future.
Question 10 A flyer/fact sheet is required on sampling procedures for grains and other feed ingredients.
Answer 10 This is a great idea ‐ thank you. We will produce information for all AusScan Online customers in due course.
Question 11 Why did the Pork CRC choose AUNIR for commercialisation?
Answer 11
Aunir are the only independent NIR calibration specialists in the world. Their team have over 25 years
experience working in the NIR industry and the heritage of their parent company is agriculture so they were a
perfect fit for helping to commercialise the AusScan calibrations.
Question 12 Will there be any more work done on cattle ME calibrations?
Answer 12
The AusScan board has budget available for further trial work to take place. As customers of AusScan, you can
have a say in how the money generated from the website is reinvested. The board have monthly phone calls
and meet annually and our technical work is covered at each meeting. Should you have any suggestions for
trials, please get in touch with the Pork CRC: Roger Campbell, Roger Campbell
([email protected]) or Charles Rikard‐Bell ([email protected])
Question 13
Could you explain to me why there are 2 different units used for the expression of amino acid content ‐ as is
g/kg for soyabean meal and % of crude protein for the grains. Given that nutritionists are entering this data
onto the same raw material specification database, shouldn't the units be the same for protein meals and
grains?
Answer 13
When the service first went live, Aunir reported the data as it was presented to them as this was how it was
delivered originally. Through customer feedback we have since adjusted the units and converted them for
consistency. If you would like to suggest other changes to the units, parameters or website please contact
[email protected]. Your feedback is very welcome.
General Questions
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AusScan and NIR Workshop Questions and Answers February 18th 2016
1. General Questions
TOPIC General QuestionsQuestion 14 What is the confidence around calibration accuracy especially in regards to starch calibration
Answer 14
Aunir will provide information sheets with the statistics for the calibrations ‐ look out for these in the coming
weeks. In the meantime, we guarantee that RPD values are always more than 2 for all AusScan calibrations
delivered via the website.
Question 15What is required for calibration maintenance specifically in regards to wet chemistry results required for
maintenance
Answer 15
The biggest limit is the cost of the wet chemistry analysis. The AusScan board have several R&D projects
ongoing and our budget and revenue generated through the AusScan Online website are used to reinvest in
the calibrations.
Additional question
Question 1 Ground vs whole ‐ how should I present the sample? Which is best?
Answer 1
The AusScan calibrations are based on whole grains. We also have ground grain calibrations. The whole grain
calibration set contains more data and is more up‐to‐date. Whichever standard operating procedure you
follow, make sure you choose the right product on the website. If you choose the 'whole' product but have
presented a ground sample, the website will detect and error and no results will be reported.
General Questions
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AusScan and NIR Workshop Questions and Answers 18th February 2016
2. Practical Application of NIR and data management ‐ Ivan Ward ‐ Agri‐Torque
TOPIC Practical Application of NIR and data managementQuestion 1 Is there a software program that can collect and manage data ?
Answer 1
Aunir is in the final stages of developing a new piece of software called Ingot Stat which will do just that. All
NIR results are automatically stored in the database where further data management can take place. Biases
can be applied, tolerances set, reports generated and shared, and much more. For more information about
Ingot Stat which will be launched later this year, please contact [email protected]
Application of NIR
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AusScan and NIR Workshop Questions and Answers 18th February 2016
3. Why you should be using AusScan technology ‐ Tony Edwards ‐ ACE Livestock Consulting
TOPIC Why you should be using AusScan technologyQuestion 1 Is there a case study that can be used to illustrate cost benefits to producers?
Answer 1 See slides from Tony Edwards talk
Question 2 Effect of particle size or product form on NIR prediction
Answer 2
Both whole and ground calibrations are available on the AusScan Online website. Aunir tested calibrations
based on a combined (whole and ground) data set but the calibration performance was compromised so the
data sets are separated. When using the website, please make sure that you select the correct product form
so that the right results are delivered back to you.
Question 3 Information behind the energy predication. What nutrients are calibration based and which are calculated.
Answer 3All the parameters in the AusScan Online energy product are based on true in vivo data. There are no
calculated parameters.
How Best to Utilise Energy
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AusScan and NIR Workshop Questions and Answers 18th February 2016
4. The Future of NIR Spectroscopy ‐ Poultry and Swine ‐ Chris Piotrowski ‐ Aunir UK
TOPIC The Future of NIR Spectroscopy – Poultry and SwineQuestion 1 Are there any AusScan predictions for Layer AME coming any time soon?
Answer 1
Layer AME predictions are already available as part of the Energy product on the AusScan Online website. A
full list of all the parameters included can be found by clicking this link:
http://www.aunir.com/products/ausscan‐online/ausscan‐online‐products‐and‐pricing/energy‐parameters/
Question 2 How long will it be before hand held NIR machines are available?
Answer 2
Handheld NIR devices are already available for specific applications. Aunir calibrations are available on
selected devices. 'NIR4 Feed' ‐ a portable NIR device for the analysis of raw materials and finished feeds is very
nearly complete. Aunir are supplying their Ingot range of calibrations for that project and more details can be
sought from [email protected]. At the moment, the AusScan calibrations are not available on
handheld NIR devices. Portable devices have a reduced wavelength range which compromises the accuracy of
the AusScan calibrations. Work has already started to address this and any developments will be shared with
AusScan Online customers in due course.
Question 3 What is the likely cost of these machines?
Answer 3At this moment, we are not sure of the retail price on NIR4 Feed but more information will be available in the
coming months.
Question 4 In future would we be able to predict various fibre fractions from NIR
Answer 4
Fibre fractions can already be measured using NIR and are available via the AusScan Online website through
the NSP calibrations. Click here for a full list of all the parameters that product measures:
http://www.aunir.com/products/ausscan‐online/ausscan‐online‐products‐and‐pricing/nsp‐parameters/
The Future of NIR
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Wheat
Triticale
Sorghum
Barley
Soya
Canola
CONTACTS
Caroline NoonanCommercial Marketing Manager, Aunir (a division of AB Agri)The Dovecote, Pury Hill Business ParkNr Alderton, TowcesterNN12 7LSUnited Kingdom
Mb: +44 (0)7525 734457Email: [email protected]
Chris PiotrowskiDirector, Aunir (a division of AB Agri)The Dovecote, Pury Hill Business ParkNr Alderton, TowcesterNN12 7LSUnited Kingdom
Work: +44 (0) 1327 810912Email: [email protected]
Charles Rikard-BellManager, Commercialisation and Research ImpactPork CRC LtdJS Davies BuildingUniversity of AdelaideRoseworthy Campus, SA 5371
Work: +61 8 8313 7973Mb: +61 439 513 723Email: [email protected]
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