Analysis of color and texture characteristics of cereals on digital images

Abstract

The color of the grain shell of cereals is an important feature that characterizes the pigments and metabolites contained in it. The grain shell is the main barrier between the grain and the environment, so its characteristics are associated with a number of important biological functions: moisture absorption, grain viability, resistance to pre-harvest germination. The presence of pigments in the shell affects various technological properties of the grain. Color characteristics, as well as the appearance of the grain shell are an important indicator of plant diseases. In addition, the color of the grains serves as a classifying feature of plants. Genetic control of the color formation of both grains and other plant organs is exerted by genes encoding enzymes involved in the biosynthesis of pigments, as well as regulatory genes. For a number of pigments, these genes are well understood, but for some pigments, such as melanin, which causes the black color of grains in barley, the molecular mechanisms of biosynthesis are still poorly understood. When studying the mechanisms of genetic control of grain color, breeders and geneticists are constantly faced with the need to assess the color characteristics of their shell. The technical means of addressing this problem include spectrophotometers, spectrometers, hyperspectral cameras. However, these cameras are expensive, especially with high resolution, both spatial and spectral. An alternative is to use digital cameras that allow you to get high-quality images with high spatial and color resolution. In this regard, recently, in the field of plant phenotyping, methods for evaluating the color and texture characteristics of cereals based on the analysis of two-dimensional images obtained by digital cameras have been intensively developed. This mini-review is devoted to the main tasks related to the analysis of color and texture characteristics of cereals, and to methods of their description based on digital images.