A methodical approach for evaluating the variability of productivity and fruit quality in the genetic collections of strawberry (Fragaria × ananassa Duch.)
https://doi.org/10.18699/VJ19.540
Abstract
For strawberry (Fragaria × ananassa Duch., 2n = 8x = 56), which is the leading berry crop in the world, research into the genotype × environment interaction is important. A complicated genomic composition, the diversity of genetic control systems, and a strong modifying effect of growing conditions on the implementation of quantitative traits make it necessary to improve methods for analysis of the genotypic variability of economically valuable traits with the aim of identifying genotypes that are characterized by stability and adaptive qualities in a wide ecological range of growing conditions. In 2016–2018, twenty-seven strawberry varieties were studied in the collections of North Caucasian Federal Scientific Center of Horticulture, Viticulture and Krymsk Experiment Breeding Station, VIR Branch. Field experiments and data counts were set and carried out according to a single scheme. The following characteristics were studied: the number of inflorescences (units per plant), the number of berries (units per plant), the average weight of berry and berry of the first order (g), total and marketable yield (g per plant), firmness of fruit (g), sugar content in berries on Degrees Brix (°Bx), sugar-acid index. The purpose of this work was the development of a methodical approach to assessing the contribution of the genotype– environment interaction to the variability of the traits of productivity and fruit quality and the determination of strawberry varieties with a stable genotype. To this end, the mathematical models of two- and three-factor analysis of variance and cluster analysis using Ward’s method were employed. According to the results of this work, strawberry varieties grown in different climatic conditions show differences in the structure of the variability of the traits of productivity and fruit quality. For the conditions of the city of Krymsk, the influence of the genotype of the variety was predominant, and for the conditions of the city of Krasnodar, in addition to the influence of the genotype of the variety, the environmental component in the form of the genotype–environment interaction is also significant. A statistically significant influence of the growing zone has been established for the traits of productivity and fruit quality, with the exception of the average weight of fruit. At the same time, differences in the mean values of the traits of varieties can be both significant and partially or completely absent. To identify varieties with promise for cultivation in the areas studied, it is recommended to use cluster analysis on the informative complex of traits with the calculation of the Euclidean distances for varieties that were grown under different conditions. The magnitude of the Euclidean distance will be the measure of the influence of a particular environment on the genotype of plants. The smaller the value of the Euclidean distance in a variety, according to the complex of the traits studied, the more stable this variety is.
About the Authors
V. I. LapshinRussian Federation
Krasnodar.
V. V. Yakovenko
Russian Federation
Krasnodar.
S. N. Shcheglov
Russian Federation
Krasnodar.
V. N. Podorojny
Russian Federation
Krymsk.
References
1. Zubov A.A. The Theoretical Basis of Strawberry Breeding. Michurinsk, 2004. (in Russian)
2. Kirtbaya E.K., Shcheglov S.N. Strawberry. Krasnodar, 2003. (in Russian)
3. Kopylov V.I. Strawberry. Simferopol, 2007. (in Russian)
4. Lakin G.F. Biometrics. Moscow, 1990. (in Russian)
5. Mandel I.D. Cluster Analysis. Moscow, 1988. (in Russian)
6. Matala V. Strawberry Cultivation. St. Petersburg, 2003. (in Russian)
7. Program and Methodology of the Study of Fruit, Small Fruit, and Nut-bearing Crop Varieties. Orel, 1999. (in Russian)
8. Fadeeva T.S. Strawberry Genetics. Leningrad: LGU Publ., 1975. (in Russian)
9. Allard R.W., Bradshaw A.D. Implications of genotype-environment interactions in applied plant breeding. Crop Sci. 1964;4:503-508.
10. Annicchiarico P. Additive main effects and multiplicative interaction (AMMI) analysis of genotype-location interaction in variety trials repeated over years. Theor. Appl. Genet. 1997;94:1072-1077. DOI 10.1007/s001220050517.
11. Finlay K.W., Wilkinson G.N. The analysis of adaptation in a plant-breeding programme. Aust. J. Agric. Res. 1963;14:742-754. DOI 10.1071/AR9630742.
12. Fontana D.C., Cocco C., Diel M.I., Pretto M.M., Holz E., Werner A., Testa V., Caron B.O., Stolzle J., Pinheiro M.V.M., Schmidt D. The performance of strawberry cultivars in Southern Brazil. Int. J. Curr. Res. 2016;08(07):33889-33893.
13. Gabriel A., Resende J.T.V., Zeist A.R., Resende L.V., Resende N.C.V., Galvão A.G., Zeist R.A., Lima Filho R.B., Corrêa J.V.W., Camargo C.K. Phenotypic stability of strawberry cultivars assessed in three environments. Gen. Mol. Res. 2018;17(3):1-11. DOI 10.4238/gmr18041.
14. Gauch H.G. Model selection and validation for yield trials with interaction. Biometrics. 1988;44:705-715. DOI 10.2307/2531585.
15. Gauch H.G., Zobel R.W. Predictive and postdictive success of statistical analysis of yield trials. Theor. Appl. Genet. 1988;76:1-10. DOI 10.1007/BF00288824.
16. Global Conservation Strategy for Fragaria (Strawberry). Scripta Horticulturae. 2008;4:1-87. Available at http://www.actahort.org/chronica/pdf/sh_6.pdf
17. Lόpez-Medina J., Vazquez E., Medina J.J., Dominguez F., Lopez-Aranda J.M., Bartual R., Flores F. Genotype × environment interaction for planting date and plant density effects on yield characters of strawberry. J. Hortic. Sci. Biotechnol. 2001;76(5):564-568.
18. Mathey M.M., Mookerjee S., Mahoney L.L., Gündüz K., Rosyara U., Hancock J.F., Stewart P.J., Whitaker V.M., Bassil N.V., Davis T.M., Finn C.A. Genotype by environment interactions and combining ability for strawberry families grown in diverse environments. Euphytica. 2017;213(5):112-123. DOI 10.1007/s10681-017-1892-6.
19. Nachit M.M., Nachit G., Ketata H., Gauch H.G., Zobel R.W. Use of AMMI and linear regression models to analyse genotype-environmental interaction in durum wheat. Theor. Appl. Genet. 1992;83: 597-601. DOI 10.1007/BF00226903.
20. Sieczko L., Masny A., Pruski K., Żurawicz E., Mądry W. Multivariate assessment of cultivars’ biodiversity among the Polish strawberry core collection. Hort. Sci. (Prague). 2015;42(2):83-93. DOI 10.17221/123/2014-HORTSCI.
21. Singh G., Kachwaya D.S., Kumar R., Vikas G., Singh L. Genetic variability and association analysis in strawberry (Fragaria × ananassa Duch). Electronic J. Plant Breed. 2018;9(1):169-182. DOI 10.5958/0975-928X.2018.00021.2.
22. Zobel R.W., Wright M.J., Gauch H.G. Statistical analysis of a yield trial. Agron. J. 1988;80(3):388-393. DOI 10.2134/agronj1988.00021962008000030002x.