Plant Productions

Plant Productions

The Multivariate Statistical Methods to Study the Relationships among Safflower Traits under Normal Irrigation and Drought Stress Conditions

Document Type : Research Paper

Authors
Roghayeh Aminian 1
Khalil karimzadeh Asl 2
Farhad Habibzadeh 1
Abolfazl Baghbani Arani 3
1 Assistant Professor, Department of Genetics and Plant Breeding, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran
2 Assistant Professor, Research Institute of Forests and Rangelands and Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
3 Assistant Professor, Department of Agronomy Science, Faculty of Agriculture, Payam Noor University, Tehran, Iran
10.22055/ppd.2019.23810.1527
Abstract
Abstract
 
Background and Objectives
Drought stress is one of the most substantial environmental stresses affecting agricultural productivity around the world and may result in considerable yield reduction. The human population is expected to increase to over 8 billion by the year 2020. Therefore, providing adequate food and preventing crop yield reduction is essential. Plant breeding can solve this problem to some extent. Evaluating yield components and their inter-relationships as well as detecting suitable selection indices are very important in the safflower breeding program. The multivariate statistical analysis can provide more insights into the deep structure of data and traits’ relationships
 
Materials and Methods
In order to study the relationships between yield components of eight genotypes of safflowerunder normal irrigationand drought stress conditions and determine the high yield genotypes, a split-plot experiment was conducted in a randomized complete block design with three replications in the research field of Imam Khomeini International University, Qazvin. Irrigation regime included normal irrigation(irrigation after 60 mm evaporation from class A pan evaporation) and drought stress (watering until 50% flowering similar to normal irrigationand 50% flowering to maturity and irrigation after 100 mm evaporation from class A pan evaporation) were considered as main plots. Eight genotypes, including Kuseh Local, Sina, Isfahan Local, Mexican 88, Faraman, Soffeh, Goldasht, and Mexican 11 were used too.
 
Results
The analysis of the variance showed that the irrigation effect was significant for traits 1000 grain weight, flower weight, harvest index, and grain yield. There were significant differences among the genotypes for most of the measured traits, except boll diameter, boll number per plant, relative water content, and relative water loss. Plant height, shoot number, boll number, stem diameter, chlorophyll value, flower weight, biological yield, and harvest index positively correlated with the grain yield in both normal irrigation and drought stress conditions. Based on the results of stepwise regression and path analysis, biological yield and harvest index in both normal irrigation and drought stress conditions had the greatest effect on grain yield. Due to the high correlation between yield and harvest index and biological yield under stress conditions, the selection of varieties with high harvest index and biological yield can be very effective in achieving maximum yield under stress conditions. Factor analysis revealed that 4 factors accounted for approximately 82% variance changes in both normal irrigation and drought stress conditions. These factors were called yield, seed, boll size, and leaf water, respectively under normal irrigation, andplant vigor, yield, seed, boll size, and leaf water, respectively under drought stress conditions. Based on the seed yield factor and the biplot display, Faraman, Mahali Isfahan, Sina, and Mahali Kuseh were determined as high yield genotypes both in normal and drought stress conditions.
 
Discussion
Grain yield is a quantitative trait with a low broad sense heritability. Therefore, identifying the traits correlated with grain yield is a suitable strategy for the improvement and the indirect selection of grain yield. Stepwise regression and path analysis are efficient and useful statistical approaches for reaching the above aim. According to the results, the traits of the harvest index and biomass were recognized as the best suitable traits for indirect grain yield selection under normal and drought stress conditions.
Keywords
Biplot display
Factor Analysis
Moisture stress
Path analysis
Stepwise regression
Subjects
References
Acharya, S., Dhaduk, L. K. and Maliwal, G. L. (1994). Path analysis in safflower under conserved moisture conditions. Gujarat Agricultural University Research Journal, 20(1), 154-157.
Amini, F., Saeidi, Gh. and Arzani, A. (2008). The relationships between yield and its components in safflower genotypes (Carthamus tinctorius L.). Journal of Science and Technology of Agriculture and Natural Resources, 45(12), 525-535. [In Farsi]
Amiri, S., Noormohamadi, S. A. Jafari, A. and Chugan, R. (2009). Correlation, regression and path analysis for grain yield and yield components on early maturing hybrids of grain corn. Plant Productions, 16(2), 99-112. [In Farsi]
Asadi, A. and Mozaffari, A. K. (2006). Relationship among yield components and selection criteria for yield improvement in safflower (Carthamus tinctorius L.). Journal of Applied Sciences, 6(13), 2853-2855.
Aydin, N., Sermet, C., Zeki Mut, H., Bayramoglu, O. and Ozcan, H. (2010). Path analysis of yield and some agronomic and quality traits of bread wheat (Triticum aestivum L.) under different environments. African Journal of Biotechnology, 9(32), 5131-5134.
Bagheri, A., Yazdisamadi, B., Taeb, M. and Ahmadi, M. R. (2002). Study of correlations and relationships between plant yield and other quantitative and qualitative traits in safflower. Iranian Journal of Agricultural Sciences, 32(2), 307-295. [In Farsi]
Baybordi, A. (2008). Safflower plant nutrition. Tabriz: Parivar Press. [In Farsi]
Blum, A. (2010). Plant breeding for water-limited environments. New York, NY: Springer Publishing.
Dabiri, M., Bahramnejad, M. and Baghbanzadeh, M. (2009). Ammonium salt catalyzed multicomponent transformation: Simple route to functionalized spirochromenes and spiroacridines. Tetrahedron, 65(45), 9443-9447.
Diaz-Perez, J. C., Shackel, K. A and Sutter, E. G. (2006). Relative water content. Annals of Botany, 97(1), 85-96.
Falconer, D. S. (1960). Introduction to quantitative genetics. New York: The Ronald Press Company.
Fathian, Sh. and Ehsanzade, P. (2013). Association between some physiological characteristics and yield in spring safflower under two irrigation regimes. Iranian Journal of Filed Crop Science, 43(4), 649-659. [In Farsi]
Gavuzzi, P., Rizza, F., Palumbo, M., Campanile, R.C., Ricciardi, G.L. and Borghi, B. (1997). Evaluation of field and laboratory predictors of drought and heat tolerance in winter cereals. Canadian Journal of Plant Science, 77(4), 523-531.
Golkar, P., Arzani, A. and Rezaei, A.M. (2011). Genetic variation in safflower (Carthamus tinctorius L.) for seed quality-related traits and Inter-Simple Sequence Repeat (ISSR) Markers. International Journal of Molecular Sciences, 12(4), 2664-2677.
Golparvar, A. R. (2011). Assessment of relationship between seed and oil yield with agronomic traits in spring safflower cultivars under drought stress condition. Journal of Research in Agricultural Science, 7(2), 109-113.
Hatamzadeh, D. (2008). Study on Traits Related to Seed Yield in Safflower by Factor Analysis. Seed and Plant Improvement Journal, 24(3), 563-575. [In Farsi]
Johnson, R. A. and Wichern, D. W. (2007). Applied multivariate statistical analysis (6th Ed.). New Jersey, U.S.A.: Prentice-Hall, Inc.
Mahajan, S. and Tuteja, N. (2005). Cold, salinity and drought stresses: An overview. Archives of Biochemistry and Biophysics, 444(2), 139-158.
Majidi, M. M. and Mirlohi, A. F. (2009). Genetic variation, heritability and correlations of agro-morpholical traits in tall fescue (Festuca arundinacea). Euphytica, 167(3), 323-331.
Maleki Nejad, R. and Majidi, M. M. (2015). Association of seed yield, oil and related traits in safflower genotypes under normal and drought stress. Iranian Journal of Field Crops Research, 13(1), 109-119. [In Farsi]
Mokhtassi Bidgoli, A., Akbari, G. A., Mirhadi, M. J., Zand, E. and Soufizadeh, S. (2006). Path analysis of the relationships between seed yield and some morphological and phonological trait in safflower (Carthamus tinctorius L.). Euphytica, 148(3), 261-268.
Moosavi, S.S., Abdollahi, M.R., Ghanbari, F. and Kanouni, H. (2016). Detection and selection of effective traits on grain yield in chickpea (Cicer arientinum L.) under normal moisture condition. Plant Productions, 39(1), 119-131. [In Farsi]
Naserirad, H., Soleymanifard, A., Naseri, R. and Nasiri, S. (2013). Study of correlation between important agronomic traits and path analysis for grain and oil yield in Safflower. International Journal of Agronomy and Plant Production, 4(4), 670-673.
Paknejad, M. (2015). The effect of TiO2 Nano particles spraying on yield and physiological parameters of safflower under drought stress. M.Sc. thesis, Imam Khomeini International University (IKIU), Qazvin. [In Farsi]
Pourdad, S. S. (2008). Study on drought resistance indices in spring safflower. Acta Agronomica Hungarica, 56(2), 202-212.
Rafiei, F. and Saeidi, G.A. (2005). Genotypic and phenotypic relationships among agronomic traits and yield components in safflower (Carthamus tinctorius L.). Scientific Journal of Agriculture, 28(1), 137-149. [In Farsi]
Rahimi, M. H., Houshmand, S. and Khodambashi, M. (2016). Determination of the most important agronomic traits affecting seed yield in lentil (Lens culinaris Medik) recombinant inbred lines. Iranian Journal of Crop Sciences, 18(2), 161-177.
Reddy, A. R., Chaitanya, K. V. and Vivekandan, M. V. (2004). Drought induced responses of photosynthesis and antioxidant metabolism in higher plant. Journal of Plant. Physiology, 161(11), 1189-1202.
Salamati, M.S. (2012). Path analysis for seed yield in Iranian safflower (Carthamus tinctorius L.) genotypes. Agronomy Journal, 97(4), 105-111. [In Farsi]
Shiravand, R. and Majidi, M. M. (2013). Trait relationships in five species of Carthamus under normal and deficit irrigation. Journal of Crop Production and Processing, 3(8), 149-163.
Singh, V. and N. Nimbkar. (2007). Safflower (Carthamus tinctorius L.). In R. J. Singh (Ed.). Genetic resources, chromosome engineering, and crop improvement (pp. 167-194). London: CRC Press.
Tavakoli, V., Majidi, M. M., Mirlohi, A. F. and Sabzalian, M. R. (2012). Syudy of relationships between traits and path analysis in cultivated (Carthamus tinctorius) and wild (Carthamus oxyacanthus) safflower genotypes under normal and water deficit conditions. Electronic Journal of Crop Production, 5(3), 45-62. [In Farsi]
Tuncturk, M. and Ciftci, V. (2004). Relationships among traits using correlation and path coefficient analysis in safflower (Carthamus tinctorius L.). Asian Journal of Plant Sciences, 3(6), 683-686.
Zahedi, F., Mohammadi, M., Nabati Ahmadi, D. and Karimizadeh, R. (2016). Path analysis to study morpho-physiological traits, yield and traits related to yield of lentil genotypes under rain fed condition. Journal of Plant Production, 39(2), 71-89. [In Farsi]
Plant Productions
Volume 42, Issue 2
Spring 2019
Pages 211-226