This document discusses the use of near-infrared spectroscopy (NIRS) for chemical analysis of feeds and foods. NIRS allows rapid, non-destructive testing of multiple components at once. It is faster and cheaper than traditional wet chemistry methods. NIRS works by measuring how organic compounds absorb near-infrared light. Absorption data is used to build calibration models that can then predict nutrient content of new samples. NIRS is advantageous as it provides real-time, multi-component analysis without chemicals or waste.

1. Chemical Analysis via NIR Spectroscopy
Yonas Asmare, ILRI
Identifying Investment Opportunities for Livestock Feed Resources Development in
the Eastern Africa Sub-Region, ILRI Addis, 13–15 December 2017

2. Purpose
• Introduce Near-infrared Spectroscopy (NIRS)
• Describe:
– Benefits to use NIRS
– How NIRS can be used for feed/Food
Nutrient content analysis
– Advances on NIRS instrumentation

3. Spectroscopy
Spectroscopy is the study of the interaction
between matter and electromagnetic radiation.
Historically, spectroscopy originated through
the study of visible light dispersed according
to its wavelength, by a prism.

4. Electromagnetic Spectrum and NIRS

5. Organic compounds absorb NIR energy
To have an absorption in the near infrared region, the
constituent of interest must have covalent bonds such
as:
O-H, C-H, C=0 C-N, S=O, P-O N-H and S-H.
Inorganic measurements are indirect measurement.
Interaction, Absorption and Measurement

6. Pre-Dispersive
Monochrometer:
Grating
PbS Detector
Polychromatic
Light
Monochromatic
Light

7. R² =0.999
A= 83.205C +0.0167
NIR absorbances obey the Beer/Lambert law
Beers-Lambert Law:
A = abC
Data (spectra) of 7 samples from Visible Spectrometer, Scanning range 300nm-600n

8. 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1100 1300 1500 1700 1900 2100 2300
Wavelength, nm
Log1/R
15 % Fat
10 % Fat
6 % Fat
Effect of Constituent Concentration
On NIR Spectra:
Fat Content in Fishmeal

9. Advantages of NIRS

10. The Traditional Wet-Chemistry Method
Example:
Analysis of
Nitrogen
Kjeldahl
Procedure:
Other Running
Costs;
Chemicals
Big Space
Time required for 18
sample is 1 day
Skilled and trained
Personnel
S.N
Procedure 18 Sample
Per Run
Required Input Cost (USD)
1 Sample grinding Sample mill >1000
2 Sample weighing analytical balance >2000
sampleTubes >100
3 Add Chemical chemicals
4
Heating the samples at
350C
Block digester and
scrubber
>1000
6
Dilution with distilled
water
water distiller >2000
7 Mixing vortex mixer >200
8
Steam distillation and
titration
Kjeltec equipment >30000
9 Data analysis computer >300
Sum total> 36,600

11. Qualitative trait prediction in plant breeding based
on Near Infrared Spectroscopy (NIRS)
Non-evasive
c. 200 samples/d
>30 traits
Physico-chemical
c. 60 000 USD
Calibration
Validation
NIRS equations sharable across
compatible instruments
At ILRI

12. Disadvantages of Wet-chemistry and Advantages of NIRS
Wet Chemistry NIRS
Slow =Time delay 200sample per
month per 8 component
Fast 200sample per day for
>30component
Destructive Non Destructive
Costly
Only initial investment and
calibration development is costly
Personal health and safely Issue No issue
Environmental issues No issue
Single component per day per
person per 18 sample
Multi component per day per
person per 200 sample
Real time data-on site
Equation Sharable across similar platforms

13. How can NIRS work for you?

14. Model Development and Prediction
Software for Chemo-metrics
• WinISI,
• ISI scan,
• Matlab

15. First step: Get NIR spectra (1000 sample)

16. Second step: Sample selection
Objective: Sample selection for wet-chemistry
NIRS can be used to select sample sets from a
large group of samples which:
Retain a maximum representation of overall
sample population variability
Samples selected better than random because:
Greater recovery of range
Higher variance
Better Kurtosis (more even distribution)

17. • Do Wet chemistry only on those selected
sample set
• Calibrations are developed by combining Wet-
chemistry data and NIRS Spectra(Data)
• These calibrations can be used to predict the
remaining samples.
Requires large sample sets
ncalibration :100 samples recommended
Third step: Model development

18. Methionine prediction by NIRS

19. ILRI-Lab-ID DM% ASH% N(%) NDF% ADF% ADL%
ME(MJ/k
g) IVOMD%
83708 96.09 11.82 0.82 77.18 51.70 6.53 6.64 46.42
83709 95.91 12.58 0.84 74.86 50.59 6.14 6.76 47.26
83710 96.22 11.81 0.79 77.89 52.36 6.65 6.66 46.45
83711 96.19 12.23 0.81 75.85 50.79 6.27 6.67 46.71
83712 96.18 10.35 0.76 77.44 51.06 6.43 6.69 46.46
83713 95.52 12.35 1.03 74.52 49.44 6.36 6.59 46.50
83714 96.14 12.19 0.92 75.09 49.74 6.18 6.69 47.06
83715 96.53 12.22 0.87 76.33 51.40 6.50 6.67 46.83
83716 95.91 12.26 1.04 73.52 48.49 6.09 6.70 47.39
83717 96.04 12.03 0.86 75.94 51.37 6.38 6.63 46.46
83718 96.10 11.29 0.84 76.97 51.13 6.53 6.62 46.31
83719 96.11 11.68 0.80 77.14 52.24 6.67 6.70 46.80
83720 96.35 11.02 0.74 78.81 52.78 6.68 6.61 46.07
NIRS prediction result
NIRS
-Up to 30
parameter in
1minutes;
-200 samples per
day.
-3USD per sample
Traditional wet-
chemistry
-it takes 1month to
analyze 200
sample.
-USD68 per sample
for 8 parameters

20. Tools

21. The Tools
Foss NIRS system model 5000 & 6500
Stationary
NIRS

22. Mobile handheld NIRS
• About USD 40 000 but price
decreasing
• Application currently developed and validated
at ILRI India and Ethiopia
Brimrose
Luminar 5030
Phazir
Mobile NIRS medium size

23. Real time application of mobile-NIRS

24. Miniaturized NIRS
• Scio, Pocket
Molecular Sensor
startup company
o 900nm -1052
nm
o Need internet
connection
o Data saved on
the cloud
• NIR Scan Nano;
Texa Instruments
o 900-1700nm

25. Limitations of NIR Technology
• The most important limitation of the technology lies in the
development of calibrations.
• Different calibrations apply to
different products such as:
o corn leaf vs. sugarcane leaf.
• At present NIRS is not practical for small sample groups

26. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
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