1. Heterogeneity of mycotoxin contamination of crops
RIKILT RD project 2015
Ine van der Fels-Klerx, Theo de Rijk, Martin Alewijn, Yannick Weesepoel

2. Mycotoxins Secondary metabolites from fungi that can infect crops
Under conducive conditions
Local weather; warm and humid weather
Field management farmer
Harvest and storage conditions
Causing disease and deaths in humans and animals
EC legislation setting maximum limits for presence of mycotoxins in commodities, feed and/or food

3. Mycotoxins Major classes of present concern
Aspergillus mycotoxins, e.g. aflatoxins, ochratoxin A
Penicillium mycotoxins, e.g. ochratoxin A and patulin
Fusarium mycotoxins, e.g. trichothecenes, fumonisins and zearalenone
Whitaker, Cannavan et al. 2010

4. Heterogenous distribution
Spatial distribution of aflatoxin B1 in maize in the field, pre-harvest

5. Sampling & analysis Official & private control
Sampling & analysis plan
Number (sub)samples, size sub- and aggregate samples, sampling preparation
Mycotoxin detection procedure, defined accept/reject limit (e.g. regulatory limit)
1- Sampling: taking a sample from a lot; 2- Sample preparation: milling the sample to reduce the size of its particles and take a subsample for analysis, and; 3- Analysis: extract the mycotoxin from the subsample and quantify it (Whitaker et al., 2011).

6. Variability mycotoxin sampling & analysis
Reasons
Inhomogeneity of distribution of mycotoxins in batch; sampling variance (largest source of variability)
Detection methods: expensive and time-consuming, or less sensitive and accurate
Limited costs for sampling (too few samples/ size)
No 100% certainty of determined lot concentration
Seller’s and buyer’s risk

7. Performance of sampling plan
The performance of a sampling & analytical plan can be determined from an operating characteristic (OC) curve
Good lots (lots with a concentration less than or equal to the legal limit) will test bad and be rejected by the sampling plan seller’s risk
Bad lots (lots with a concentration greater than the legal limit) will test good and be accepted by the sampling program buyer’s risk
Operating characteristic Curve

8. How to reduce variability ?
Increasing laboratory sample size (or number of samples of a given size)
Increasing the number of subsamples
Increasing test portion size
Grinding the sample into smaller particles
Using a more precise analytical method (HPLC, LC-MS , ELISA, dipsticks, ..)
Methods with red underline will be used to optimize sampling plan.

9. Aflatoxins in maize
Aflatoxins: group of mycotoxins (B1, B2, G1, G2), A flavus and parasiticus.
AFB1 most toxic mycotoxin, genotoxic and carcinogenic.
In EC, AFB1 strictly regulated in food (EC, 2006b) and feed (EC, 2002)
AFB1 often occurs in maize, e.g Balkan incident
Regulation (EU) No 691/2013 prescribes sampling, e.g subsamples

10. Problem statement Official procedure: Resource (time, money) demanding
Could new methods such as simple video camera or ELISA be of help, e.g. for pre-screening?
Quick, low costs, high throughput, local contamination
More subsamples can be analysed at same costs. Will it improve OC curves?

11. Aim study
Evaluate if the hyperspectral camera (near infrared, NIR nm) can be used to estimate AFB1 contamination in maize batches

12. Reference set
- 100 samples of maize kernels of approx g
Collected with at regular intervals from one shipment
Analysed at RIKILT with LC-MSMS for AFB1 concentrations
3 samples with AFB1 >20 µg/kg (21.3, 25.7, 27.0 µg/kg)

13. Multispectrale imaging (MSI) - Videometer
Co-operation with Bioscience (WUR)

14. MSI – schematic overview
Camera & lens
Captures reflectance data at each LED wavelength
Integrating sphere
Diffuses light onto sample
19 LED’s
Narrowband illumination nm
Sequential strobes
Sample
Imaging time: 5-10 s

15. MSI – schematic overview

16. Principal component analysis
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PC1
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Variables: wavelengths (nm)
Reduces the amount of variables (wavelengths)
Goal: find the directions (PC’s) that maximize the
variance in the dataset.
Variables: principal components (PC’s)

17. Results

18. Conclusion
The use of the current simple videometer for detection of AB1 in maize is not effective enough
Possibly because
Lack of reference spectra of mycotoxins and–producing fungi in this matrix and with this wave lenght
Too much grit in subsamples
Experiences gained with data analysis and use of camera
In future studies, we will investigate a more proven effective camera (300 wave lenghts), available at RIKILT in 2016

19. Thanks For
Your Attention