The effect of covariate of alternate bearing in adaptation studies in olive (Olea europaea L.)

Document Type : scientific research article

Authors

1 Ph.D. Student, Dept. of Plant Breeding, Faculty of Agriculture, Imam Khomeini International University, Qazvin, Iran,

2 Assistant Prof., Dept. of Plant Breeding, Faculty of Agriculture, Imam Khomeini International University, Qazvin, Iran

3 Associate Prof., Temperate and Cold Fruits Research Institute (TCFRI), Horticulture Science Research Institute, Karaj, Iran

Abstract

Background and objectives: In order to confirm the existence of interactions in quantitative terms, the most obvious method is to participate in the results of each year in combined analysis. In the meantime, horticultural products are affected by the influence of the inner (not the year) of the plant, and their alternate bearing from year to year, low or high. In this research, in order to eliminate this effect and Adjusting the mean of the years, the alternate bearing index of each genotype is used as auxiliary variable in the model in order to determine the changes of each component of combined analysis and finally, using stability parameters, varieties and genotypes compatible with The environmental conditions of this climate are introduced.
Materials and Methods: For this research, 100 genotypes and cultivars collected from all over Iran were used. These genotypes and cultivars were planted in a completely randomized block design (RCBD) with three replications at Olive Tarom Research Station and estimated yield of each tree in kg per tree for 6 years from 2011 to 2016. The Alternate bearing effect was deduced from the data by calculating the ABI for each genotype during successive two-year periods and correcting the averages using it. Finally, the data were analyzed and combined in two main and corrected formulas, and finally from Ten stability parameters were used to identify a stable cultivar in year.
Results: The results of combined analysis of variance for different methods had a significant difference. So that the genetic component of the combined analysis table increased 61 percent in the corrected data compared to the original data. Also, the effect of the year of this table was dramatically justified from 37 to 14 percent, down 23 percent. The amount of interaction in both cases for corrected and non-corrected data was significant with 35% and 32%, respectively. The comparisons performed for the pair of corresponding years using the t-student test indicated the difference in mean performance for both the same year for the original and corrected data. The value of this parameter was calculated positively and negatively in succession. Which shows that the effect of interacting the auxiliary variable is the alternate bearing index in the calculations. The absolute value of this parameter represents more exposure genotypes or varieties of the phenomenon of alternate bearing. The most stable cultivars in this study with desirable function and using the data correction method, Koroneiki and Conservalia cultivars, were determined according to three factors of stability in yield, yield and oil quality.
Conclusion: The existence of an alternate bearing in horticultural products can significantly alter the results of compatibility studies in these products. The internal phenomenon, which does not depend on the year and its parameters, changes the actual suitability of the genotypes and the numbers of participants in the experiment. Intervening the alternate bearing index in compatibility analysis as an auxiliary variable is an important factor in reducing the effects of alternate bearing in calculations, adjusting the meanings of each genotype environment, and ultimately making the correct decision to reject or accept the adaptation of a genotype. This difference in the overall survey and determining the compatibility of cultivars is obvious in the two corrected and main data sets. On the other hand, consideration of the amount of yield, in addition to stability, is essential in determining the optimal cultivar.

Keywords


1.Ahmadikhah, A. 2010. Advanced Plant Breeding. Gorgan University of Agricultural Sciences and Natural Resources, , Iran. 482p. (In Persian)
2.Anonymous. 2017. Meteorological Reports of 2011, 2012, 2013, 2014, 2015 and 2016. Meteorological Organization of Islamic Republic of Iran. (In Persian)
3.Azimi, M., Arji, I., Zeinanloo, A.A., Taslimpour, M.R. and Ramazani Malakrodi, M. 2016. Evaluation of Adaptability of some Olive (Olea europeae L.) cultivars in different climates of Iran. Seed Plant. Improv.. J. 32: 1. 275-292.
4.Badii, M.H., Castillo, J. and Wong, A. 2008. Uso de Analisis de Covarianza (ANCOVA) en investigacion cientofica (Use of covariance analysis (ANCOVA) in scientific research). Innova. Neg.5: 25-38.
5.Balzarini, M.G., Gonzalez, L., Tablada, M., Casanoves, F., Di Rienzo, J.A. and Robledo, C.W. 2008. Manualdel Usuario, Editorial Brujas, Cordoba, Argentina.
6.Becker, H.C. and Leon, J. 1988. Stability analysis in plant breeding. Plant Breed. 101: 1. 1-23.
7.Bertschinger Stadler, L.W., Weibel, P.F. and Schumacher, R. 1998. New methods of control of flowering in apple. Turrialba. 31: 3. 284-288.
8.Brandiej, E. and Meverty, B.E. 1994. Genotype × environmental interaction and stability of seed yield of oil rapeseed. Crop Sci. 18. 344-353.
9.Choudhary, V., Ojha, N., Golden, A.and Prinz, W.A. 2015. A conserved family of proteins facilitates nascent lipid droplet budding from the ER. J. Cell. Biol. 211: 2. 261-71.
10.Cornelius P.L. and Crossa, J. 1999. Prediction assessment of shrinkage estimators of multiplicative models for multi-environment trials. Crop Sci.39: 998-1009.
11.Darvishnia. A. and Jafarzadeh, M. 2017. Alternate bearing in citrus. Jahad-e-keshavarzi mazansaran, Sari. (In Persian)
12.DeLury, D.B. 1948. The Analysis of Covariance. Biometrics. 4: 153-170.
13.Di Rienzo, J.A., Casanoves, F., Balzarini, M.G., Gonzalez, L., Tablada, M. and Robledo, C.W. 2013. InfoStat, version. 2013, Grupo InfoStat, Facultad de Ciencias Agropecuarias, Universidad Nacional de Cordoba, Argentina. URL http://www.infostat.com.
14.Eberhart, S.T. and Russell, W.A. 1966. Stability parameters for comparing varieties 1. Crop Sci. 6: 1. 36-40.
15.Fairfield, S.H. 1957. Interpretation of adjusted treatment means and regressions in analysis of covariance. Biometrics. 13: 282-308.
16.Farshadfar, E. 2015. Genotype and environment interaction in plant breeding. Razi University Publications, Kermanshah, Iran. 531p. (In Persian)
17.Food and Agriculture organization. 2017. Olive. http://fenix.fao.org/ wds/excels/ e05fe853-df33-478a-b934-1545ba36da4b.xls.
18.Francis, T.R. and Kannenberg, L.W. 1978. Yield stability studies in short season maize. I-A descriptive method for grouping genotypes. Can. J. Plant. Sci. 58: 4. 1029-1034.
19.Gabriel, K.R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrka. 58: 453-467.
20.Gauch, H.G. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sci. 46: 1488-1500.
21.Gauch, H.G. and Zobel, R.W. 1996. AMMI analysis of yield trials. P 85-122. In: Kang, M.S. and Gauch, H.G. (eds.) Genotype by Environment Interaction, CRC Press, Boca Raton, FL, USA.
22.Gonzalez-Martinez, S.C., Mariette, S., Ribeiro, M.M., Burban, C., Raffin, A., Chambel, M.R., Ribeiro, C.A.M., Aguiar, A., Plomion, C., Alia, R., Gil, L., Vendramin, G.G. and Kremer, A. 2004. Genetic resources in maritime pine (Pinus pinaster Aiton): molecular and quantitative measures of genetic variation and differentiation among maternal lineages. For. Ecol. Manag. 197: 103-115.
23.Hoblyn, T.N., Grubb, N.H. and Painter, A.C., and Wates, B.l. l936. Studies in biennial bearins- I. J. Ponrol. Hort. Sci. 1: 139-76.
24.Hosseini-Mazinani, M., Torkzaban, B. and Arab, J. 2012. Iranian olive catalogue "Morphological and molecular characterization of Iranian olive germplasm". National Institute of Genetic Engineering and Biotechnology, Tehran. (In Persian)
25.Karimizadeh, R., Dehghani, H. and Dehghanpour, Z. 2006. Using Cluster Analysis for stability of maize hybrids.
J. Water Soil Sci. 10: 3. 337-348.(In Persian)
26.Kempton, R.A. 1984. The use of bi-plots in interpreting variety-by-environment interactions. J. Agric. Sci. Cambridge. 103: 123-135.
27.Kiritsakis, A. and Markakis, P. 1987. Olive oil: a review. Adv. Food Res.31: 453-482.
28.Outhwaite, A.D. and Rutherford, A. 1955. Covariance analysis as alternative to stratification in the control of gradients. Biometrics. 11: 431-440.
29.Perkins, J.M. and Jinks, J.L. 1971. Environmental and genotype environment components of variability. III. Multiple line and crosses. Heredity. 23: 339-356.
30.Pinthus, M.J. 1973. Estimate of genotypic value: A proposed method. Euphytica. 22. 121-123.
31.Rakshit, S., Ganapathy, K.N., Gomashe, S. S., Rathore, A., Ghorade, R.B., Nagesh Kumar M.V., Ganesmurthy, K., Jain, S.K., Kamtar, M.Y., Sachan, J.S., Ambekar, S.S., Ranwa, B.R., Kanawade, D.G., Balusamy, M., Kadam, D., Sarkar, A., Tonapi, V.A. and Patil, J.V. 2012. GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multilocation data. Euphytica. 185: 465-479.
32.Rayner, A.A., Bingham, V. and Fienberg, E.S. 1991. Testing hierarchical treatment components in analysis of covariance. Biometrics.47: 1183-1191.
33.Roemer, T. 1917. Sind die ertragsreichen Sorten ertragssichers. Mitt. DLG. 87-89.
34.Salvador, M.D., Aranda, F., G´omez-Alonso, S. and Fregapane, G. 2001. Cornicabra virgin olive oil: a study of five crop seasons. Composition, quality and oxidative stability. Food Chem.74: 267-274.
35.Sharifi, P. and Aminpanah, H. 2017.Evaluation of genotype × environment interactions, stability and a number of genetic parameters in rice genotypes. Plant Genet. Res. 3: 2. 25-42.
36.Tabatabaei, M. 1995. Olive trees and olive oil. Ministry of Agriculture, Tehran, Iran. 400p. (In Persian)
37.Torkzaban, B., Ataei, S., Saboora, A., Azimi, M. and Hosseini Mazinani, m. 2010. Study of variation of some unknown olive genotypes in collection of Tarom research station in Iran, applying morphological markers. Iran. J. Boil.
23: 4. 520-531. (In Persian)
38.Tsimidou, M. and Karakostas, K.X. 1993.Geographical classifica-tion of Greek Virgin olive oil by non parametric multivariate Evaluation of fatty acid composition. J. Sci. Food Agric.62: 253-257.
39.Wahi, S.D. and Malhotra, P.K. 1993. Estimation of repeatability of fruit yield in presence of biennial rhythm. Indian Agricultural Statistics Research Institute Publication, New Delhi.
40.Wishart, J. 1936. Test of significance in the analysis of covariance. J. Roya. Stat. Soc. 3: 79-82.
41.Wrick, G. 1962. Uber eine method zur refassung der okologischen streubreite in feldversuchen. Flazenzuecht. 47: 92-96.
42.Yan, W. and Kang, M.S. 2003. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton, FL, USA.
43.Yan, W., Hunt, L.A., Sheng, Q. and Szlavnics, Z. 2000. Cultivar evaluation and mega environment investigations based on the GGE biplot. Crop Sci.40: 597-605.
44.Zeinanloo A.A., Shahsavari, A., Mohammadi, A. and Naghavi, M.R. 2012. Variance component and heritability of some fruit characters in olive (Olea europaea L.). Sci. Hort.123: 68-72.