Assessment of the size and shape of berries using the ImageJ program on the example of honeysuckle

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.

1. Chuanromanee T.S., Cohen J.I., Gillian L. Ryan G.L. Morphological analysis of size and shape (MASS): An integrative software program for morphometric analyses of leaves. Applications in Plant Sciences. 2019;7(9):e11288. DOI: 10.1002/aps3.11288

2. Ferreira T., Rasband W. ImageJ user guide: IJ 1.46r Revised edition. 2012. Available from: http://imagej.nih.gov/ij/docs/guide/user-guide.pdf [accessed July 13, 2020].

3. GOST 33823-2016. Frozen fruits. General specifications (Frukty bystrozamorozhennye. Obshchiye tekhnicheskiye usloviya). Moscow: Standartinform; 2016. [in Russian] URL: https://files.stroyinf.ru/Data2/1/4293752/4293752544.pdf [дата обращения: 17.03.2022].

4. GOST R 54778-2011. Machines for harvesting fruits and berries. Test methods (Mashiny dlya uborki plodov i yagod. Metody ispytaniy). Moscow: Standartinform; 2020. [in Russian] URL: https://files.stroyinf.ru/Data/514/51463.pdf [дата обращения: 17.03.2022].

5. GOST R 57976-2017. Fruits and vegetables. Terms and definitions (Frukty i ovoshchi svezhiye. Terminy i opredeleniya). Moscow: Standartinform, 2016. [in Russian] URL: https://files.stroyinf.ru/Data2/1/4293740/4293740749.pdf [дата обращения: 18.03.2022].

6. GOST R 58012-2017. Fresh edible honeysuckle. Specifications (Zhimolost svezhaya syedobnaya. Tekhnicheskiye usloviya). Moscow: Standartinform; 2011. [in Russian] URL: https://files.stroyinf.ru/Data2/1/4293740/4293740841.pdf [дата обращения: 18.03.2022].

7. Hammer Ø., Harper D.А.Т., Ryan P.D. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica. 2001;4(1):4.

8. Ibáñez S., Grimplet J., Baroja E., Hernaiz S., Ibáñez J. Characterization of the reproductive performance of a collection of grapevine cultivars. Acta Horticulturae. 2019;1248:345-352. DOI: 10.17660/ActaHortic.2019.1248.50

9. ImageJ. Image processing and analysis in Java: [site]. Available from: https://imagej.nih.gov/ij [accessed July 13, 2020].

10. Iwata H., Ukai Y. SHAPE: a computer program package for quantitative evaluation of biological shapes based on elliptic Fourier description. Journal of Heredity. 2002;93(5):384-385. DOI: 10.1093/jhered/93.5.384

11. Jing Z.B., Yao C.C., Liu Z.D. Isolation and identification of Pseudomonas syringae pv. actinidiae in Shaanxi Province, China. Acta Horticulturae. 2018;1218:279-286. DOI: 10.17660/ActaHortic.2018.1218.38

12. Mollick A.S., Yamasaki H. Phenotypic variations in croton Co­ diaeum variegatum (L.) Blume characterized by digital image-based procedure. Acta Horticulturae. 2012;937:393-400. DOI: 10.17660/ActaHortic.2012.937.48

13. Nokhrin D.Yu. Laboratory workshop on biostatistics (Laboratorny praktikum po biostatistike). Chelyabinsk: Chelyabinsk State University; 2018. [in Russian]

14. Saxena L., Armstrong L. A survey of image processing techniques for agriculture. 2014. Available from: https://ro.ecu.edu.au/ecuworkspost2013/854 [accessed July 13, 2020].

15. Schlager S. Morpho and Rvcg – Shape analysis in R: R-packages for geometric morphometrics, Shape analysis and surface manipulations. In: G. Zheng, Sh. Li, G. Székely (eds). Statistical Shape and Deformation Analysis: Methods, Implementation and Applications. Cambridge, MA: Academic Press; 2017. p.217-256. DOI: 10.1016/B978-0-12-810493-4.00011-0

16. Sedov E.N., Ogoltsova T.P. (eds). Program and methodology of variety studies for fruit, berry and nut crops (Programma i metodika sortoizucheniya plodovykh, yagodnykh i orekhoplodnykh kultur). Orel: VNIISPK; 1999. [in Russian]

17. Ufimtseva L.V., Glaz N.V. Тhe influence of meteorological conditions on the biochemical composition and taste of the fruit. Pomiculture and Small Fruits Culture in Russia. 2018;55:151-159. [in Russian] DOI: 10.31676/2073-4948-2018-55-151-159

18. Vasiliev A.A., Gasymov F.M. Environmental plasticity of various plum cultivars under the conditions of Сhelyabinsk Province. Proceedings on Applied Botany, Genetics and Breed­ ing. 2019;180(2):25-29. [in Russian] DOI: 10.30901/2227-8834-2019-2-25-29

19. Vasilyev A.G., Vasileva I.A., Shkurikhin A.O. Geometric morphometrics: from theory to practice. Moscow: KMK; 2018. [in Russian]

20. Vibhute A., Bodhe S.K. Applications of image processing in agriculture: A survey. International Journal of Computer Applications. 2012;52(2):34-40.

21. White A.G., Bailey D.G. Digital imaging; A useful technique for analysing fruit shape in pears. Fruit Varieties Journal. 1995.49(4):224-226.