Investigation of the Grapevine`s Leaf Traits and Identifying Grape Cultivars by Applying Image Processing

Document Type : Research Paper

Author

Assistant professor, Department of Horticultural science, Faculty of Agriculture, University of Maragheh, Maragheh, Iran

10.22084/ppt.2025.30349.2147

Abstract

Introduction
Grapevine is a plant belonging to the genus Vitis and belonging to the Vitaceae family, as one of the most common garden products in the world and in Iran. The high distribution of grapes in the world (Southern Europe, Asia Minor, East Asia and North and Central America) may be due to its high level of biodiversity. Grapes are one of the most important fruit products in Iran, which are very important for fresh consumption and raisins. With the production of about two million tons of grapes, Iran ranks ninth in the world among the countries that produce this product. In this way, identifying the most and most stable phenotypic traits in grapes is one of the main goals in evaluating the biodiversity of grapes. The unique aspect of grape leaves in terms of morphological diversity is having significant diversity compared to other products. Recently, a high heritability test for grape leaves has been carried out on a genetic basis based on leaf morphological characteristics. Identifying the most and most stable phenotypic traits in grapes is one of the main goals in evaluating the biodiversity of grapes, and it is necessary to conduct such studies with accurate biometric software. The purpose of this study is to investigate the diversity of leaf traits and to identify grape varieties through leaf shape using image processing in a computer environment.
 
Materials and Methods
In this part of the research, 3 mature and healthy leaves from the middle parts of the one-year branches were taken non-randomly and purposefully from 24 grape varieties that were identified from different orchards in Maragheh and the suburbs. The samples were photographed on a white background. Then, it was photographed with a 12 mega pixel camera using shadowless and coaxial light. The samples were photographed by special computer photography software in size 768x1024 with 300 dpi resolution. Finally, using ImageJ software, 14 variables for each photo (leaf area, leaf circumference, average red-green-blue color space (RGB), average intensity of red (R), average intensity of green (G), average intensity of blue (B), length, width, color, roundness, left, right, top and bottom) morphometrics were obtained, which were tested and analyzed in the next steps. The data obtained from the present study were analyzed using SPSS var21.0 software based on a completely randomized design. Image J8.0 software was used to analyze the images. In the first step, a simple analysis of variance was performed for the measured traits, and the average data was compared by Duncan's multiple range test. Excel software was used to draw graphs.
 
Results and Discussion
The results of the variance analysis of agricultural traits data showed that the difference between genotypes was significant among all traits, which indicates a high genetic diversity among the investigated genotypes. According to the simple correlation between the studied traits, the highest correlation between x7 and x8 traits was obtained with a value of 0.994 and the lowest correlation value between x5 and x14 traits or zero value was obtained. In the present study, the results of grouping by cluster analysis were consistent with the results of analysis into principal components. The results of this research showed that x9 variable (Hue) has a different discriminating power in terms of the separation of the studied germplasm, and in other words, it can create a distinct grouping.
 
 
 
 
 
 
 
 
Conclusions
In the results of this research, a large variety of changes among the genotypes or cultivars investigated in terms of the measured traits was observed, which indicates the high genetic potential among the cultivars. According to the variance analysis table of grape leaf traits, all traits were significant at the statistical probability level of 1%. The results of analysis into components showed that the first four components have characteristic root values above one and in total justify 95% of the changes in leaf morphometric data. Also, according to the grouping of studied genotypes, they have different leaf morphometric characteristics and therefore they are placed in different groups. For example, G7 is different from other genotypes and is placed in a separate group The grouping of the morphometric variables measured in the leaves of the studied grape genotypes showed that the variable x9 (Hue) has different discriminating power in terms of the separation of the studied germplasm, and in other words, it can create a distinct grouping.

Keywords

Main Subjects

References

 Alba, V., Bergamini, C., Cardone, M. F., Gasparro, M., Perniola, R., Genghi, R. and Antonacci, D. (2014). Morphological variability in leaves and molecular characterization of novel table grape candidate cultivars (Vitis vinifera L.). Molecular Biotechnology, 56(6), 557-570. https://doi.org/10.1007/s12033-013-9729-6
Alba, V., Bergamini, C., Genghi, R., Gasparro, M., Perniola, R. and Antonacci, D (2015). Ampelometric leaf trait and SSR loci selection for a multivariate statistical approach in Vitis vinifera L. biodiversity management. Molecular Biotechnology, 57(8), 709-719. https://doi.org/10.1007/s12033-015-9862-5
Al Bashish D, Braik M, Bani-Ahmad S.2011. Detection and classification of leaf diseases using K-means-based segmentation and neura netwroks based classification. Information Technology Journal, 10, 2:267-275. https://doi.org/10.1192/bjp.111.479.1009-a
Andrade, I. M., Mayo, S. J., Kirkup, D. and Van Den Berg, C. (2008). Comparative morphology of populations of Monstera Adans. (Araceae) from natural forest fragments in Northeast Brazil using elliptic Fourier Analysis of leaf outlines. Kew Bulletin, 63, 193-211. https://doi.org/10.1007/s12225-008-9032-z
Badenes, M. L., Martinez-Calvo, J. and Llacer, G (2000). Analysis of a germplasm collection of loquat (Eriobotrya japonica Lindl.). Euphytica, 114(3), 187–194. https://doi.org/10.1023/A:1003950215426
Calderon, A. A., Zapata, J. M. and Ros Barcelo, A (1995). Peroxidase isoenzymes as markers of cell de-differentiation ingrapevines (Vitis vinifera). Vitis, 34(4), 207-210. DOI: https://doi.org/10.5073/vitis.1995.34.207-210
Chitwood, D. H., Ranjan, A., Martinez, C. C., Headland, L. R., Thiem, T., Kumar, R. and Sinha, N. R. (2014). A modern ampelography: a genetic basis for leaf shape and venation patterning in grape. Plant Physiology, 164(1), 259-272. https://doi.org/10.1104/pp.113.229708
Cope, J. S., Corney, D., Clark, J. Y., Remagnino, P. and Wilkin, P. 2011. Plant Species Identi_cation using Digital Morphometrics: a Review. Elsevier. https://doi.org/10.1016/j.eswa.2012.01.073
Crespan, M., Botta, R. and Milani, N (1999). Molecular characterization of twenty seeded and seedless table grape cultivars (Vitis vinifera L.). Vitis-Geilweilerhof, 38, 87-92.
Doulati Baneh, H., (1386). Evaluation of genetic diversity of some grape cultivars in West Azerbaijan province using molecular markers and their relationship with agronomic traits. PhD thesis, Faculty of Agriculture, Tabriz University. (In Persian)
Dogan, A., Uyak, C., Keskin, N., Akcay, A., Sensoy, R. I. G. and Ercisli, S (2018). Grapevine leaf area measurements by using pixel values. Comptes rendus de l’Académie bulgare des Sciences, 71(6), 772-779.
Dolph, G. E (1977). The effect of different calculational techniques on the estimation of leaf area and the construction of leaf size distributions. Bulletin of the Torrey Botanical Club, 264-269 https://doi.org/10.2307/2484308.
Doulati Baneh, H., Nazemia, A., Mohammadi, S. A., Hassani, G. and Henareh, M (2010). Identification and evaluation of west Azarbaijan grape cultivars by ampelography and ampelometery. Plant Products Technology, 10, 13- 23.
Gerrath, J., Posluszny, U., & Melville, L. (2015). Taming the wild grape: Botany and horticulture in the Vitaceae. Iranian Journal of Horticultural Science, (42), 82-87. https://doi.org/10.1007/978-3-319-24352-8
Gulve, P. P, Tambe, S. S, Pandey, M. A, Kanse, M. S. 2015. Leaf disease detection of cotton plant using image processing techniques. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), 50-54.
Iwata, H., & Ukai, Y (2002). SHAPE: a computer program package for quantitative evaluation of biological shapes based on elliptic Fourier descriptors. Journal of Heredity, 93(5), 384-385 https://doi.org/10.1093/jhered/93.5.384.
Iwata, H., Ebana, K., Uga, Y., Hayashi, T., & Jannink, J. L (2010). Genome-wide association study of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis. Molecular Breeding, 25(2), 203-215. https://doi.org/10.1007/s11032-009-9319-2
Kandiannan, K., Parthasarathy, U., Krishnamurthy, K. S., Thankamani, C. K. and Srinivasan, V. (2009). Modeling individual leaf area of ginger (Zingiber officinale Roscoe) using leaf length and width. Scientia Horticulturae, 120(4), 532-537. https://doi.org/10.1016/j.scienta.2008.11.037
Kliewer, W. M. and Weaver, R. J. (1971). Effect of Crop Level and Leaf Area on Growth, Composition, and Coloration ofTokay'Grapes. American Journal of Enology and Viticulture, 22(3), 172-177.
Karami, M.J. 2009. Study of characteristics of irrigated grape cultivars grown in Kurdistan. Seed Plant. 25: 1-31. (In Persian)
Leao, P. C. D. S., Cruz, C. D. and Motoike, S. Y. (2011). Genetic diversity of table grape based on morphoagronomic traits. Scientia Agricola, 68(1), 42-49. https://doi.org/10.1590/S0103-90162011000100007
Leishman, M. R., Wright, I. J., Moles, A. T. and Westoby, M (2000). The evolutionary ecology of seed size. Seeds: the ecology of regeneration in plant communities, 2, 31-57. https://doi.org/10.1079/9780851994321.0031
Moosazadch, R., Shoor, M., Tehranifar, A., Davarinczhad, G. H. and Mokhtaryan, A (2012). Identity of some grape cultivars based on fruits and their seeds morphological characteristics. Plant Science. Research, 4, 1-9.
Moosazadeh, R., Shoor, M., Tehranifar, A., Davarinezhad, G. and Mokhtaryan, A. (2013). Identity of some grape cultivars based on fruits and their seeds morphological characteristics. Quart. Journal. Plant Science, Research, 28, 1-8.
Mohsenin, N. N (1986). Physical Properties of Plant and Animal Materials, Gordon and Breach Science Publishers, New York, NY, USA
Mongkolchart N, Ketcham M. 2014. The measurement of brown planthopper by image processing. In International Conference on Advanced Computational Technologies & Creative Media (ICACTCM 2014). August 14 – 15, Pattaya, Thailand.
Mondini, L., Noorani, A. and Pagnotta, M. A. (2009). Assessing plant genetic diversity by molecular tools. Diversity, 1: 19-35.
Najmaddin, C (2014). Leaf anatomy and palynological differences among selected cultivars of Vitis vinifera and Parthenocissus quinquefolia (Vitaceae). History, 9(21), 6-12.
Neto, J. C., Meyer, G. E. Jones, D. D. and small, A. K. 2006. Plant species identification using Elleptic Fourier leaf shape Analysis. Computers and Electronics in Agriculture, 50(2)121-134. https://doi.org/10.1016/j.compag.2005.09.004
Nejatian, M.A. & Doulati Baneh, H. (2016). Identification, distinctness and registration of commercial and native grape cultivars of Iran. Iranian Journal of Horticaltural Sciences, 47(3), 581-594. (In Persian). https://doi.org/0.22059/ijhs.2016.59820  
Pagnoux, C., Bouby, L., Ivorra, S., Petit, C., Valamoti, S. M., Pastor, T. and Terral, J. F. (2015). Inferring the agrobiodiversity of Vitis vinifera L.(grapevine) in ancient Greece by comparative shape analysis of archaeological and modern seeds. Vegetation History and Archaeobotany, 24, 75-84. https://doi.org/10.1007/s00334-014-0482-y
Rafiei, M., Erfani Moghadam, Javad and Fazeli, Arash (2015). Investigating the genetic diversity between the cohorts of different grape cultivars in Arak city based on morphological characteristics. Journal of Production Research, 13, 115-134. (In Persian). https://doi.org/10.22069/jopp.2017.9482.1900
Salayeva, S. J., Ojaghi, J. M., Eshghi, R. A. and Akparov, Z.I (2013). Morphological variation and relationships of Azerbaijan cultivated and wild grape populations. In International Caucasia Forestry Symposium. 1055-1063.
Sefc, K. M., Lefort, F., Grando, M. S., Scott, K. D., Steinkellner, H., & Thomas, M. R (2001). Microsatellite markers for grapevine: a state of the art. In Molecular Biology & Biotechnology of the Grapevine. Springer, Dordrecht, 433-463. https://doi.org/10.1007/978-94-017-2308-4_17
 
Sestak, Z., Catsky, J. and Jarvis, P. G. (1971) Plant photosynthetic production. Manual of methods. The Hague: Junk N.V. Publishers.
Singleton, V.L., Zaya, J. and Trousdale, E.K. (1986). Caftaric and coutaric acids in fruit of Vitis. Phytochemistry, 25, 2127–2133. https://doi.org/10.1016/0031-9422(86)80078-4
Stransky, Christoph, Hannes Baumann, Svein-Erik Fevolden, Alf Harbitz, Hans Høie, Kjell H. Nedreaas, Arnt-Børre Salberg, and Tuula H. Skarstein. "Separation of Norwegian coastal cod and Northeast Arctic cod by outer otolith shape analysis." Fisheries Research 90, no. 1-3 (2008): 26-35. https://doi.org/10.1016/j.fishres.2007.09.009
Terral, J. F., Tabard, E., Bouby, L., Ivorra, S., Pastor, T., Figueiral, I. and Tardy, C (2010). Evolution and history of grapevine (Vitis vinifera) under domestication: new morphometric perspectives to understand seed domestication syndrome and reveal origins of ancient European cultivars. Annals of botany, 105(3), 443-455. https://doi.org/10.1093/aob/mcp298
Tosun, O. and Şenol, R (2016). Görüntü işleme metotlarıyla yaprak alanı tayini ile bitki gelişiminin gözlenmesi. El-Cezeri Journal of Science and Engineering, 3(1). https://doi.org/10.31202/ecjse.67161
Volume 17, Issue 1
June 2025
Pages 13-28

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