However, they reported that HVK was strongly correlated to SKCS hardness index. Some caution is warranted because their sample set was artificially prepared by blending non-vitreous kernels in various amounts to a fully vitreous base sample. Image analysis, or machine vision, has promise as a rapid aid to wheat grading and classification. Image analysis classifies kernels on the basis of size, shape and texture. Attempts to use image analysis for variety identification have been disappointing.
Machine vision does have enormous potential for assessing wheat physical condition.
The methods are based on the relative translucency of vitreous and non-vitreous durum wheat kernels. The procedure of Symons et al. Machine vision systems that can rapidly and objectively measure surface discoloration should be possible. Luo et al. Each wheat class has a unique kernel size, colour, and shape.