wheat ausscan and nir workshop - feed grain partnership and nir worksh… · ausscan and nir...

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

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

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

2

World first “heat damage” – Soybean and Canola

Reactive lysine values

SID lysine (and other amino acids)

Soya

Canola

Introduction

Spectrum downloaded to PC

calibrated

(10 to 60 sec)

Wet Chemistry(Up to a week)

Introduction: What is AusScan Online?

Original AusScan

Set-up

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?

95% confidence limit

Measure within 0.26 MJ/kg

Introduction: Robust Calibrations

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

Thank you

Application of NIR

Technology in the Feed Mill18th February 2016

Ivan Ward

Agri-Torque

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

Overview

Importance of Nutrient Information

NIR Overview

NIR Opportunities

Investigation of NIR Results

Purchased Calibrations


Feed Manufacturing

Ingredients

In-Process

Final Product

Recipe

optimisation

Animal Production


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


Variation

Unable to control

Measure and control

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

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

ElectromagneticspectrumNIR_20150630_v0 2.mp4

NIR Basics

NIR has enabled real time evaluation of nutritional characteristics of

Ingredients, such as

Moisture

Protein

Amino acids

Starch

Fat

Energy (AME, DE)

………….

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


Max & Co. Corn Growers 43.40 12.1















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

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

NIR Opportunities

Inline


Data Management and Integrity

Calibrations

Reference Analysis

Site NIRS

Formulation Software

Reports

Result Interpretation

Business Systems

DATA CONNECTION

and VERIFICATION


Sampling

Sample

NIRS Hardware

Reference Analysis and

Calibrations

NIR Protocols and NIR User



Sampling

Sampling error?

Can the product be resampled?

Can the sample be re-analysed?

New Product?

New Ingredient?


Sample

Correct Sample and Correct Label?

Sample ID

Sample presentation

Ground

Whole

Pellets

Crumble

Composite sample?


NIRS Hardware

Regular Servicing

Monitoring - Standards test results

Cleanliness

NIRS

Cup

Grinder Maintenance and particle size consistency


Calibrations

Component Range

Feed types included

Reports – independent validation with statistics

(correlation, validation error)


Calibrations

Ring tests


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


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



Pass or Fail - LIMITS Ingredients

Purchase orders \ contracts

Final product

Specifications

Formulation

Production


Environmental Conditions

Ambient temperature

Ambient humidity

Sample temperature at time of analysis


Purchased Calibrations Sampling

Sample

NIRS Hardware

Reference Analysis and

Calibrations

NIR Protocols and NIR User




Calibrations

Reference Analysis

Site NIRS

Formulation Software

Reports


Business Systems

DATA CONNECTION

and VERIFICATION

NIR Opportunities


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

NIR Opportunities


Improvements

Local and new season samples may need to be added to the calibration

Reference analysis and calibration accuracy

NIR Technology in the Feed Mill

Thank YOU!

Ivan Ward, Agri-Torque

Dedicated Analytical Solutions

Dedicated Analytical Solutions

FOSS Instruments ForAusScan

Dedicated Analytical Solutions AGENDA

The XDS

The DS2500

The AusScan

demonstration

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


Standardised instrument – transferable calibrations

NIST wavelength standardisation – equal wavelength settings for all instruments

Internal reference - reference will be clean and constant height quality


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

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)


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


RFID for sample cup identification

Scanning time: < 1 min(adjustable sub samples)

Reflectance for dry samples and slurries

Transflectance for opaque samples (liquids )

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

www.aunir.com

The Future of NIR Spectroscopy – Poultry and SwineChris PiotrowskiDirector, Aunir

Aunir.mpg

Aunir.mpg

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

www.aunir.com

What makes a good calibration?

Modelling software

Hardware

Spectroscopy Applications

NIR spectrometers

Full range

(Scanning)

Dispersive

Foss Unity

FT

Bruker Buchi Thermo

Limited range

Diode Array

Perten

Hardware

www.aunir.com

NIR spectrometers

Limited range

Hand-Held

Hardware

NIR Spectra contain repetitive informationHardware

www.aunir.com

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Lab Based Micro NIR In-Line HandHeld

All scans are not created equal with NIR hardwareHardware

www.aunir.com

Hardware

www.aunir.com

What is NIR4 Farm?Hardware

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

Modelling software

Different scenarios (LR)

Y

X

Y

X X

Y

X

Y

X

Y

X

Y

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

Y

X

New approach (Locally Weighted Regression=LWR)

Modelling software

Modelling software

Merging datasets (LWR)

Modelling software

16.31% protein

LWR Prediction16.1%

16.2% 16.45% ?

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

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

www.aunir.com

• Analytes of interest should be organic

• Concentration > 0.01% = 1000 ppm

What can be measured by NIR?Applications

www.aunir.com

Limitations of NIR

• Not sensitive to minerals

• Not a trace analysis method

• It is a secondary method

Applications

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

www.aunir.com

Particle Size Whole Corn Corn Flour

Applications

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

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

www.aunir.com

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Co

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Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5

ProteinOil

Spectroscopy

Mixer Profile – 10 samples, NIR spectra

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

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

www.aunir.com

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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

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

www.aunir.com

Making Light Work. Together.Chris Piotrowski – [email protected]

Aunir.mpg

Aunir.mpg

mailto:[email protected]

http://www.aunir.com/

Why you should be using AUSSCAN technology

AC EdwardsACE Livestock Consulting Pty Ltd

PO Box 108 Cockatoo Valley SA [email protected]

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

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

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

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

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

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)

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

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

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.

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)

http://www.google.com.au/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=hNLqq4lq_0EZUM&tbnid=nqd8r9oCGgYjDM:&ved=0CAUQjRw&url=http://blogs.wsj.com/photojournal/2009/10/14/pictures-of-the-day-283/&ei=Z15bUafSEomtkAXZ0oHYBg&psig=AFQjCNG-kVbF-53Pkce3ZpCtRFP8tgl0hA&ust=1365028829581121


What parts do we use?

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



14 MJ DE

15 MJ DE

13 MJ DE

Nutrient constraint parametric

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

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.

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.

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.

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.

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.

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



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



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

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


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


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

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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