| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 85360 | Computers and Electronics in Agriculture | 2010 | 5 Pages |
Organic and conventional winter wheat farm pair grain samples were tested with the copper chloride crystallisation method and submitted to computerised image analyses followed by pattern recognition and classification with multivariate statistical tools.Appropriate discriminant analyses (DA) models were established. Depending on the analysed region of interest up to 100% of “unknown” samples could be correctly predicted using the DA models.
Research highlights▶ Organic and conventional winter wheat farm pair grain samples were tested with the copper chloride crystallisation method and submitted to computerised image analyses followed by pattern recognition and classification with multivariate statistical tools. ▶ Appropriate discriminant analyses (DA) models were established. Depending on the analysed region of interest up to 100% of “unknown” samples could be correctly predicted using the DA models. ▶ Organic and conventional wheat tested Copper chloride crystallisation method with image analysis applied Up to 100% of “unknown” samples correctly predicted.
