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Short Course
AUSTRALIAN NEAR INFRARED SPECTOSCOPY
GROUP
SHORT COURSE IN NEAR INFRARED SPECTROSCOPY
Department of Primary Industries, Hamilton Centre, Hamilton, Victoria, 6th-8th April 2008
A short course on NIR spectroscopy, entitled "Near
Infrared Technology: Getting the Best out of Light" will be offered as
a
precursor to the 13th ANISG Conference. This course should
be of great value to those who are relatively new to the field, or
others who wish to brush up on their skills.
The course will be led by well-known NIR identity and pioneer of
NIR in the grain industry, Dr Phil Williams of PDK Grain, Nanaimo, BC, Canada.
Phil Williams received his PhD degree from the University of Wales,
Aberystwyth, Wales in Chemistry in 1958, and began his career in
Australia at the Agricultural Research Institute, Wagga Wagga,
NSW. During his 37-year career with the Canadian Grain
Commission, Phil pioneered the practical application of NIR that played
a key role in the early establishment of the NIR industry. His
work started with the earliest commercial NIR instrument in 1972 and
quickly led to converting protein testing for Canada's export wheat to
NIR between 1975 and 1977. In his 32 years of experience with
NIR, Phil has been instrumental in introducing the technology to many
countries of the world; worked with more than 50 types and models of
instruments; and has written step-by-step operating manuals for several
NIR instruments and software packages. His contributions include
co-editing one of the major reference books in the NIR field, in its
second edition in 2001. Throughout his career in the government
and since forming PDK Grain, Phil has been consulted widely for his NIR
expertise by grain, feed, forage, fibre, and major food companies,
research organizations, universities, Canadian and foreign government
departments, and international organizations.
The course will run from 0930 to 1700 hours on Sunday 6th April and
from 0900 to 1700 hours on Monday 7th April. Laboratory visits
and group discussions will also be included on Tuesday 8th April.
Certificates will be presented to all delegates who complete the course.
PLEASE NOTE!
On this
occasion, the course will cover three days instead of the usual two
days. Course participants will not be able to stay overnight in
Hamilton on Monday 7th April, due to accommodation being booked out
that night ONLY for another event. Instead, course participants
staying for the conference (commencing Wednesday 9th April) will be
taken by coach on Monday evening to the lovely coastal town of Port
Fairy, one hour’s drive south of Hamilton, where they will stay
overnight in accommodation organised by ANISG.
On Tuesday 8th
April, a visit is being organised to the NIR laboratory of the Murray
Goulburn Co-operative Ltd dairy processing plant at nearby
Koroit. Some other interesting landmarks in the area will be
included in the tour, which will then return to Hamilton for an
inspection of the FEEDTEST laboratory, located at the Department of
Primary Industries conference venue. Discussions with Phil
Williams on the course topics will then continue as required, followed
by presentation of certificates.
Course participants will be free to organise their own activities on the evening of Tuesday 8th April.
The table of contents for Phil’s course is currently as follows:
Module 1. Introduction and the Economic Benefits of Near-infrared Technology
1.1 The First Words
1.2 The Economic Benefits of NIR Implementation
1.3 What Does the Operator Really Need to Know?
1.4 Near-infrared Spectroscopy and its Early History
1.5 Basic Principles of NIR
1.5.1. The Physics
1.5.2. The Chemistry
1.6 The Texture Factor
1.7 The Advantages and Disadvantages of NIR
Module 2. Applications, including Routine Analysis and Networking
2.1 Scope of NIR Applications
2.2 Feed Industry
2.3 Flour Milling
2.4 Forage Analysis
2.5 Grain Handling
2.5.1 Composition
2.5.2 Classification
2.5.3 Grading
2.6 Manure Analysis
2.7 Mixing and Blending Efficiency
2.8 Near-infrared Discriminant Analysis
2.9 Near-infrared Networking
2.10 Plant Breeding
2.11 Precision Agriculture
2.12 Soil, Peat and Compost Analysis
2.13 Wine analysis
2.14 Wool analysis
Module 3. Instrumentation
3.1 Types of NIR Instruments
3.2 Criteria for Instrument Selection
3.2.1 Purpose for the instrument
3.2.2 The economics
3.2.3 Instrument type
3.2.4 Instrument size and portability
3.2.5 Internal reference
3.2.6 Spectral range
3.2.7 Sample presentation system
3.2.8 Instrument software
3.2.9 Calibration system and transferability among instruments
3.2.10 The operating manual
3.2.11 Simplicity in use
3.2.12 Instrument durability
3.2.13 Spectral quality
3.2.14 Instrument precision
3.2.15 Instrument peripherals
3.2.16 Suitability for field operation
3.2.17 Instrument technical support
2.2.18 Instrument company longevity
3.2.19 Instrument cost
3.2.20 Instrument networking
3.2.21 Instrument maintenance and diagnostics
Module 4. Reference Analysis and Factors Affecting its Interpretation
4.1 Introduction
4.2 Methods
4.2.1 Approved reference methods
4.2.2 Approved methods with some subjectivity
4.2.3 Approved physico-chemical methods for functionality
4.2.4 Arbitrary reference methods
4.3 Inter- and Intra-laboratory Reproducibility
Module 5. Statistical Terms Necessary to the Evaluation of Accuracy and Precision
5.1 Independent and Dependent Variables
5.2 Useful Statistics for Evaluating NIR Calibrations
5.2.1 Mean
5.2.2 Standard deviation (SD)
5.2.3 Coefficient of variability (CV %)
5.2.4 Bias (mean difference between NIR and reference data)
5.2.5. Coefficient of correlation (r)
5.2.6 Coefficient of determination (r2)
5.2.7 Coefficient of regression (b) and intercept (a)
5.2.8 Distribution of differences between NIR and reference data
5.2.9 Standard error of a single test (SET)
5.2.10 Standard error of prediction or validation (SEP or SEV)
5.2.11 Standard error of cross-validation (SECV)
5.2.12 Root mean square of prediction (RMSEP or RMSEV)
5.2.13 True test error (TTE)
5.2.14 Ratio of SEP to SD ref. data of validation samples (RPD)
5.2.15 Ratio of SEP to range ref. data of validation samples (RER)
5.3 Summary of Statistical Terms
Module 6. Introduction to NIR Software
6.1 Types of NIR Software
6.2 Purposes of NIR Software
6.2.1 Initial set-up and standardization
6.2.2 Recording of spectra
6.2.3 Regular analysis
6.2.4 Data handling
6.2.5 Mathematical pretreatment
6.2.6 Scatter correction
6.2.7 Calibration model development
6.2.8 Calibration model evaluation
6.2.9 Slope/bias correction
6.2.10 Outlier detection
6.2.11 Discriminant analysis (classification)
6.2.12 Instrument networking
6.2.13 Instrument diagnostics
6.2.14 Special graphics
6.2.15 Report Generation
6.2.16 Client Service
Module 7. Sampling, Sample Preparation, and Sample Presentation
7.1 What is a Sample?
7.2 The Truly Representative Sample
7.3 Sampling
7.4 Sample Preparation
7.5 Sample Presentation: Reflectance
7.6 Sample presentation: Transmittance
7.7 Sample presentation: Turntable
7.8 Sample presentation: Fibre-optic probes
7.9 Sample storage
Module 8. Variables that Can Affect Performance of NIR Instruments
8.1 The Early words
8.2 Variables
8.3 Instrument Factors
8.4 Sample Factors
8.5 Operator Factors
Module 9. Calibration Development and Evaluation Methods
9.1 Introduction
9.2 Basic Steps in Calibration
9.2.1 Reference methods and their error
9.2.2 Verify that the instrument is working properly
9.2.3 Verify the precision of the NIRS analysis
9.2.4 Sources of variance
9.2.5 Assembly of samples with all variance
9.2.6 Identify a sample preparation system
9.2.7 Preparation of samples for scanning
9.2.8 Scanning of samples
9.2.9 Selection of samples for calibration
9.2.10 Reference analysis
9.2.11 Development and optimization of the calibration
9.2.12 Entering calibration model to the instrument
9.2.13 Verifying accuracy and reproducibility of NIR predictions
9.2.14 Supplement calibration model with future samples analyzed for monitoring
9.2.15 Calibration transferability
9.3 How to Improve a Calibration
9.4 Final words
Module 10. Interpretation of Calibration Evaluation
10.1 First words
10.2 Scope of Calibration Evaluation
10.3 Analysis of Precision
10.4 Accuracy and bias
10.5 Graphical Distribution of Samples During Calibration
10.6 Spectral Basis of Calibrations
10.6.1 The PLS Loadings
10.6.2 The PLS Regression Coefficients (Vectors)
10.7 Assignments of wavelengths to constituents
10.8 The Very Final Words
Module 11. References, Recommendations for future reading and General Index
11.1 References Cited
11.2 Recommendations for Further Reading
11.3 Index
11.4 Appendix. Table for conversion of cm-1 to nanometres
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