Assessment of the size and shape of berries using the ImageJ program on the example of honeysuckle - D. Yu. Nokhrin; L. V. Ufimtseva; N. V. Glaz (Труды по прикладной ботанике, генетике и селекции)
Background. Digital technologies are increasingly used in agriculture to solve a variety of problems. However, in horticulture and industrial production of fruit and berry crops, qualitative evaluation and scoring of the most important morphological indicators of fruits are still common, and measurements are carried out manually. The aim of this study was to develop an algorithm for using the ImageJ package for quick and accurate measurements of the size and shape of berries.Materials and methods. The material included 190 berries of 3 blue honeysuckle (Lonicera caerulea L.) cultivars: ‘Amazonka’, ‘Lazurit’, and ‘Lenita’. The berries were laid out on a white sheet of paper with a ruler on top of the glass and photographed with additional lighting from below. The analysis of the obtained images was carried out using the public domain package ImageJ (v. 1.51k) and included automatic search for objects and their measurement by 7 indicators: area, perimeter, maximum and minimum Feret diameters, aspect ratio, circularity, and surface roundness (1-Solidity). Statistical analysis included the calculation of the minimum, maximum and mean values with a nonparametric 95% CI (bootstrap, percentile method), comparison of cultivars using the Kruskal–Wallis test, and search for the most typical objects based on the results of a between-group PCA.Results. It was shown how the size and shape indicators from the ImageJ package related to classical measurements in pomology, including length, diameter, and berry shape index. For all indicators, the differences between cultivars were highly statistically significant (p < 0.001). The prospects of using the surface roughness index for quantitative characterization of the degree of deviation of fruits from their natural shape due to mechanical and other deformations are discussed.Conclusion. The results of the automatic image analysis in the ImageJ package can be used in horticulture, breeding, and production of fruits and berries.