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ONLINE COURSE – Quantitative analysis of infrared spectroscopy data for soil and plant sciences (SPEC02) This course will be delivered live
9 January 2024 - 11 January 2024
£365.00
Event Date
Tuesday, January 9th, 2024
COURSE FORMAT
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE
TIME ZONE – `Central European Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
About This Course
By the end of the course, participants should be able to:
- Select the best pre-processing techniques for their own raw infrared spectral data.
- Apply data exploration techniques and avoid the common pitfalls in tackling a data analysis of infrared spectral data.
- Select the optimal sample size and the best sampling design to subset spectral data and send the samples for laboratory analysis.
- Understand and apply approaches for spectral data outlier detection.
- Apply statistical multivariate modelling methods to infrared spectroscopy data and validate the model predictions.
Intended Audiences
- This course is aimed at anyone who wishes to introduce into the analysis of visible, near and mid-infrared spectral data for plant and soil sciences. It is particularly suited for:
- Graduate, post-graduate or post-doctoral level researchers who wish to learn how to analyse their own infrared data in R.
- Applied researchers and analysts in the environmental or ecological sector with a role in handling and analysing infrared spectroscopy data.
Course Details
Availability – TBC
Duration – 3 days
Contact hours – Approx. 20 hours
ECT’s – Equal to 2 ECT’s
Language – English
Teaching Format
Assumed quantitative knowledge
Assumed computer background
Equipment and software requirements
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open-source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve the learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Tuesday 9th
Classes from 09:00 to 17:00 CET
DAY 1
– Introduction to spectral inference in soil and plant sciences
– Handling spectral data
– Practical
– The pre-processing of raw spectra
– Practical
– Exploratory spectral analysis
– Practical
Wednesday 10th
Classes from 09:00 – 17:00 CET
DAY 2
– Spectral similarity analysis
– The detection of outliers
– Practical
– Selecting the samples for laboratory analysis
– Practical
Thursday 11th
Classes from 09:00 – 17:00 CET
DAY 3
– Estimating properties from spectra
-Multivariate statistical models
– Practical
– Validation of the predictions
– Practical
– Bring your own data! – OR large exercise estimating properties from raw spectra
– Discussion & questions
Alexandre Wadoux
Alexandre Wadoux is a Research Associate in digital soil mapping at the University of Sydney and recently moved to the French National Institute for Agronomic and Environmental Research in Montpellier (France) to work on his Marie-Curie Fellowship. He has an undergraduate degree from the University of Angers in France, a MSc in soil science from the University of Tubingen in Germany, a Master in epistemology of sciences from the University of Nantes in France and a PhD in applied geostatistics from Wageningen University in the Netherlands. He has made contributions to several quantitative aspects of soil and environmental science through the development of methods for spatial sampling, mapping and assessment using geostatistics, statistical learning algorithms and spectroscopy. He is the author of the book “Soil Spectral Inference with R” published in 2021 with Springer.