Identification of Promising Oilseed Rape Genotypes for the Tropical Regions of Iran Using Multivariate Analysis

Document Type : Original Article

Authors

1 Horticulture Crops Research Department, Sistan Agricultural and Natural Resources Research and Education Center, AREEO, Zabol, Iran

2 Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, AREEO, Karaj, Iran

3 Horticulture Crops Research Department, Mazanderan Agricultural and Natural Resources Research and Education Center, AREEO, Sari, Iran

4 Horticulture Crops Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, Iran

5 Horticulture Crops Research Department, Boshehr Agricultural and Natural Resources Research and Education Center, AREEO, Borazjan, Iran

6 Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization, AREEO, Rasht, Iran

7 Horticulture Crops Research Department, Kermanshah Agricultural and Natural Resources Research and Education center, AREEO, Kermanshah, Iran

8 Horticulture Crops Research Department, Esfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran

9 Plant Protection Research Department, Mazanderan Agricultural and Natural Resources Research and Education Center, AREEO, Sari, Iran

Abstract

Releasing new adapted oilseed rape cultivars among the available resources of rapeseed would be a valuable method to increase the cultivar diversity in the tropical regions. Low adaptable and high yield cultivars resources of oilseed rapes are now available in the tropical regions of Iran. The current research aimed to identify new high yield and adaptable genotypes adaptable across various tropical regions. To this end, 20 new genotypes and a check variety (Dalgan) were cultivated in the five tropical regions of Iran based on a randomized complete block design (RCBD) with three replications during the 2019 to 2020 cropping season. The experimental sites are composed of five locations in Iran, including Gorgan, Sari, Rasht, Borazjan and Zabol. During the growth season, several phenological and quantitative traits were recorded. Combined ANOVA revealed significant genotype by environment interaction for all studied quantitative traits. Days to start flowering and days to end flowering showed the highest heritability. Correlation analysis showed a significant positive relationship between yield and flowering period, the number of sub-branches and also the number of pods per plant, but a negative and significant correlation with the days to maturity. Path analysis showed that the days to maturity had the most negative direct effect on yield and the days to start flowering, while the number of sub-branches had the most positive direct effect on yield. Canonical correlation showed that yield is correlated positively with phenological traits. The principal component analysis showed that the two first components covered 68.07% of all data variations which 12 genotypes were correlated with these two components. Cluster analysis categorized evaluated genotypes into three main groups. Finally, eight genotypes were selected in the current study, which had high yield and adaptability in the tropical regions of Iran.

Graphical Abstract

Identification of Promising Oilseed Rape Genotypes for the Tropical Regions of Iran Using Multivariate Analysis

Highlights

  • Flowering and maturity date highly affected the yield of oilseed rape genotypes cultivated in tropical regions of Iran.
  • Days to start flowering and days to end flowering showed the highest heritability in oilseed rape genotypes.
  • Eight promising oilseed rape genotypes were detected using bi-plot and cluster analysis,
  • Number of sub-branches and days to maturity had the most positive and negative correlation on yield, respectively.
  • Two first principal components covered 68.07% of variations related to superior genotypes.

Keywords

Main Subjects


Agahi K., Ahmadi J., Oghan H.A., Fotokian M.H., Orang S.F. 2020. Analysis of genotype× environment interaction for seed yield in spring oilseed rape using the AMMI model. Crop Breeding and Applied Biotechnology 20(1). https://doi.org/10.1590/1984-70332020v20n1a2
Ali N., Javidfar F., Elmira J.Y., Mirza M. 2003. Relationship among yield components and selection criteria for yield improvement in winter rapeseed (Brassica napus L.). Pakistan Journal of Botany 35 (2): 167-174.  
Amiri-Oghan H., Fotokian M., Javidfar F., Alizadeh B. 2012. Genetic analysis of grain yield, days to flowering and maturity in oilseed rape (Brassica napus L.) using diallel crosses. International Journal of Plant Production 3(2): 19-26.  
Amiri Oghan H., Zeinalzadeh-Tabrizi H., Fanaei H.R., Kazerani N.K., Ghodrati G., Danaie A., Valipuor M.B. 2019. Stability study of seed yield in promising lines of spring oilseed rape in southern-worm regions of Iran. Journal of Crop Breeding 11(31): 42-54. https://doi.org/10.29252/jcb.11.31.42  
Baradaran R., MAJIDI H.E., Darvish F., Azizi M. 2007. Study of correlation relationships and path coefficient analysis between yield and yield components in rapeseed (Brassica napus L.).  
Canada C.C.o. 2013. Health Benefit of Canola Oil. Available on: www.canolacouncil.org/oileandemeal/canolaeoil/healthebenefitseofecanolaeoil/  
Diepenbrock W. 2000. Yield analysis of winter oilseed rape (Brassica napus L.). Field Crops Research 67(1):35-49.https://doi.org/10.1016/S0378-4290(00)000824  
FAO 2016. Food and Agriculture Organization of the United Nations. Food and Agricultural Commodities Production. Available on: http://www.fao.org/statistics/en/  
FAO 2018. Food and Agriculture Organization of the United Nations. Food and Agricultural Commodities Production. Available on: http://www.fao.org/statistics/en/  
Fischer R., Edmeades G.O. 2010. Breeding and cereal yield progress. Crop Science 50: S-85-S-98. https://doi.org/10.2135/cropsci2009.10.0564  
IPCC. 2007. Climate Change. The Physical Science Basis: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change: Summary for Policymakers and Technical Summary and Frequently Asked Questions. Cambridge University Press.  
Lobell D.B., Gourdji S.M. 2012. The influence of climate change on global crop productivity. Plant Physiology 160(4):1686-1697. https://doi.org/10.1104/pp.112.208298  
Moradi M., Soltani Hoveize M., Shahbazi E. 2017. Study the relations between grain yield and related traits in canola by multivariate analysis. Journal of Crop Breeding 9(23): 187-194.https://doi.org/10.29252/jcb.9.23.187  
Ortiz R., Sayre K.D., Govaerts B., Gupta R., Subbarao G., Ban T., Hodson D., Dixon J.M., Ortiz-Monasterio J.I., Reynolds M. 2008. Climate change: can wheat beat the heat? Agriculture, Ecosystems & Environment 126(1-2): 46-58.
https://doi.org/10.1016/j.agee.2008.01.019  
Roy D. 2000. Analysis and exploitation of variation. Alpha Science Int'l Ltd. Plant breeding  
Tahira A.R., Amjad M. 2013. Stability analysis of rapeseed genotypes targeted across irrigated conditions of Pakistan. International Journal of Agriculture Innovations and Research 2: 208-212.  
Thurling N. 1991. Application of the ideotype concept in breeding for higher yield in the oilseed brassicas. Field Crops Research 26(2): 201-219.
https://doi.org/10.1016/0378-4290(91)90036-U  
Thurling N., Kaveeta R. 1992. Yield improvement of oilseed rape (Brassica napus L.) in a low rainfall environment. I. Utilization of genes for early flowering in primary and secondary gene pools. Australian Journal of Agricultural Research 43(3): 609-622.
https://doi.org/10.1071/AR9920609  
Wu W., Ma B.-L. 2018. Assessment of canola crop lodging under elevated temperatures for adaptation to climate change. Agricultural and Forest Meteorology 248: 329-338. https://doi.org/10.1016/j.agrformet.2017.09.017