Wheat landraces identification through glumes image analysis

Abstract

A new practical method able to identify wheat local landraces was implemented. It is based on computerized image analysis techniques and statistical identification, for the first time on the basis of glumes size, shape, colour and texture.Ears of 52 different Sicilian wheat landraces were reaped for three consecutive years. Digital images of the glumes were acquired, processed and analysed, measuring 138 quantitative morpho-colorimetic variables. The data were statistically analysed applying a Linear Discriminant Analysis. All the statistical comparisons, distinguished for systematic rank, given perfect identification performances; while an overall percentage of correct identification of 89.7% was reached when all the landraces were compared all together.Finally, the identification system was tested with an unknown glume sample, later entirely identified as Vallelunga, one of the Sicilian landraces.This work represents the first attempt of wheat landraces identification based on glume phenotypic characters, applying image analysis techniques. Considering the growing interest in local old wheat landraces, strongly linked to the renewed appreciation in traditional and typical local products, the obtained results support the application of the image analysis system not only for grading purposes, but also to define the product traceability, in order to get a “market card” for wheat landraces.