Varietal identification is an important aspect of crop research and utilization. Identification using computer-based image analysis could be an alternative to visual identification. However, the effectiveness of image analysis systems needs to be established under various real conditions. Three wheat varieties were sown on three different dates. Variation in the grain size and shape of these varieties, brought about by changes in the environmental conditions, was measured using Comprehensive Image Processing Software (CIPS). Some parameters showed considerable grain-to-grain variation, which was either inherent or due to environmental changes during grain filling. Euclidean distances were calculated using either means of all the parameters (ED1), or using only those parameters that did not show a high coefficient of variation (ED2). For samples of the same variety sown at different times, Euclidean distances were smaller compared with samples of different varieties, indicating that grains of the same variety resembled one another. By using the criterion of minimum Euclidean distance it was possible to distinguish between varieties, in spite of variation in grain shape and size due to environmental conditions. It was possible to identify correctly an unknown sample, taken as a test case.