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Differentiation and classification of eco-products using a validated analytical and holistic methods

Project


Project code: 02OE170/F1
Contract period: 15.06.2004 - 15.06.2007
Budget: 456,239 Euro
Purpose of research: Basic research

The objective of the project was to examine agricultural plant products to investigate if differences could be determined on the basis of ecological or conventional growing methods and if such differences in coded samples can be used to identify the growing method. Testing was performed on apples, corn, carrots and wheat. The samples originated on the one hand from defined long-term trials and on the other hand from selected ecological and conventional farming operations. The investigation utilized methods that had previously been validated for differentiating between ecologically and conventionally grown wheat and carrots. In this project the examination was broadened to include the products apples and corn, as well as variations in type, location and year of cultivation. This allowed a step to be made beyond the testing of samples from scientific growing experiments to more real-world conditions. The methods used in the examination were the physiological amino acid status (PAS) and the measurement of fluorescent excitation spectra (FAS) of samples that had not been cut into smaller pieces (whole samples). The PAS method allowed the origin of sample pairs (ecological/conventional) to be differentiated and to be correctly identified for the most part. In this case the reliability of the results for samples taken from scientific growing experiments was greater than for samples taken from commercial farming operations. With the FAS method it was similarly possible to differentiate between all of the types of samples from the growing systems. It was also possible to achieve a higher rate of correct results in the classification of unknown samples. A statistical procedure was applied, which enabled the growing methods of unknown samples to be determined following “training“ on known samples. In so doing, the certainty of the classification increased as the data basis for the “training“ of the evaluation function grew larger. The employed methods work comparatively and are based on a sufficiently large ensemble of samples from the sample age group to be tested. The two methods work independently of one other and can even be employed together to improve reliability.

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