ATR-IR-Detection of Fusarium Fungi on Cereals

Research project P 14096 ATR-IR-Detection of Fusarium Fungi on Cereals Rudolf KRSKA 24.01.2000 Mycotoxins are generally considered tp be toxic substances produced by certain types of fungi which grow on plants of agricultural importance either before harvest or during storage. Presently, 25% of world`s food crops are affected by mycotoxins. Of several hundred different mould species, fungi of the genera Fusarium are the most important in the more temperate and colder parts of the world. Numerous surveys and monitoring studies on the presence of mycotoxins indicate that the large group of trichothecenes (in particular deoxynivalenol - DON) belong to the most prevalent Fusarium mycotoxins with respect to agricultural production in Europe. The most noticeable acute symptoms caused by DON are diarrhea, dermal toxicity, vomiting and headache. Up to now the only approach to asses the extent of Fusarium demage are the time consuming chemical analytical methods to analyze the mycotoxin content. Therefore, rapid and efficient testing methods that allow the detection of Fusarium mycotoxins are still required. The new idea of this proposal is the sensitive determination of the fungus itself present on the kernels by means of a non-destructive and simple method in order to evaluate the degree of contamination of the crop. The proposed method is based without any sample preparation upon pressing the sample against an internal reflection diamond ATR (attenuated total reflection)-crystal mounted in the sample chamber of a portable FTIR (Fourier Transform Infrared) spectrometer enabling in the record mid-infrared absorption spectra at the interface sample/crystal. This technique allows analysing single kernels as well as grained samples for the evaluation of a representative average. Because of its inherent sensitivity to the near-surface region of the sample, maize kernels. Appropriate chemometric data evaluation techniques such as neural networks will be employed to evaluate the ATR measurements. Automated qualification and quantification routines will be established leading to an easy to use and rapid routine method for mycotoxin determination. A major potential application of the developed detection system is e.g. the pre-screening of incoming cereals for the production of food and feeding stuffs or for import/export control with the aim to provide immediate information on the mycotoxin contamination level. Preliminary IR-ATR evaluation could thus deem grain "Fusarium-free" and - due to the good correlation between the DON-content and the amount of Fusarium fungi present on the kernel-free of DON-contamination.

A proposal for the extension of the FWF project P-14096 CHE for another year is presented. Promising results from studies obtained during the first 2 years of this project show the potential of the developed method, if parameters that determine the spectral variability are investigated and additional information can be incorporated in classification and quantification models. The major goal of the third year is the further optimisation of the developed mid-infrared/attenuated total reflection (IR/ATR) method (see enclosed report) for the determination of the degree of contamination of Fusarium fungi on maize and its major metabolite deoxynivalenol (DON). This is done by the detection of spectral changes in the mid-IR spectrum caused by modification of biological and chemical properties of the maize matrix. Through the extension of the combination of near infrared with mid infrared regions region to 8000 cm-1 complementary spectral information will be obtained, which should lead to further improvement of the method. Finally, for the optimised IR-ATR method, a stable chemometric model will be developed featuring a high prediction ability (e.g. artificial neural networks). Influences of cereal maize type and type of fungus on the classification/quantification model will be investigated and a decision will be made, if different maize varieties as well as different fungi can be incorporated into the model. Moreover, the potential of diffuse reflection spectroscopy (DR) for the determination of fungal invasion will be developed utilising again a combination of the NIR and the MIR range. A sample holder will be developed that enables repeatable DR measurements of powdered samples, facilitating high throughput measurements that are necessary for the construction of a large spectral database that will be used for chemometric modelling. All information obtained from the above measurements will be included into a chemometric model. Non parametric models such as artificial neural networks as well as established methods e.g. PCA and PLS will be used for modelling and by the selection of suitable variables (i.e. spectral windows, but also by adding information about genotype and type of fungus) this method will enable the reliable and correct prediction of fungal invasion on cereals.