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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. Lapshin
North Caucasian Federal Scientific Center of Horticulture, Viticulture, Winemaking
Russian Federation
Krasnodar.


V. V. Yakovenko
North Caucasian Federal Scientific Center of Horticulture, Viticulture, Winemaking
Russian Federation
Krasnodar.


S. N. Shcheglov
Kuban State University
Russian Federation
Krasnodar.


V. N. Podorojny
Krymsk Experiment Breeding Station – Branch of Federal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resourses (VIR)
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.


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