Study on Relationships among Bread Wheat Landraces from Geographical Origins across Iran under Supplemental Irrigation and Rain-Fed Conditions

بوم شناسی کشاورزی

Article 5, Volume 13, Issue 4 - Serial Number 50, December 2022, Pages 653-668   

Document Type: Scientific - Research

DOI: 10.22067/jag.v13i4.88501

Authors

Hossein Hatamzade¹; Saber Golkari^{* 2}; Iraj Bernousi³; Reza Mohammadi⁴; Sukhwinder Singh⁵

¹Biometrical Genetic, Shirvan Dryland Agricultural Research Station, North Khorasan Agricultural and Natural Resources Research and Education Center, AREEO, Shirvan, Iran

²System Biology Department, Agricultural Biotechnology Research Institute of Iran, AREEO, Karaj, Iran.

³Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Urmia University, Urmia, Iran.

⁴Cereal Research Department, Dryland Agricultural Research Institute, AREEO, Kermanshah, Iran.

⁵Wheat scientist, Genetic Resources program, CIMMYT

Abstract

Introduction
Wheat is one of the most important crops worldwide and one of the most essential commodity in the global market. Many studies showed that it is necessary to increase global wheat production double before 2050 in order to meet the growing demands of the population, changing diets and consuming biofuels. In recent decades, climate changes have complicated the prediction of drought frequency and extent in the Mediterranean Basins. Therefore, more genetic sources are needed to identify lines carrying genes for tolerance and adaptation to drought conditions. One of the most important factors limiting growth, development, and productivity of crops is drought. Landraces breeds have become particularly important as genetic resources adapted to local conditions. An appropriate level of genetic variability in breeding materials and parental germplasm is vital for generating improved germplasm with desired traits that help to increase crop production and thus improve human nutrition. Landraces may facilitate to capture genetic recombination required for creating new genotypes tolerant to biotic and abiotic stresses. It is necessary to comprehend well the available genetic variation in primitive wheat, wild species, and landraces.
Materials and Methods
A core collection of 249 bread wheat landraces throughout Iran which belong to six different geographic origins were studied under supplemental irrigation and rainfed conditions at Sararood Agricultural Research Station in Kermanshah during 2016-17 growing seasons. Phonological, morphological and physiological traits were scored including days to heading (DTH), days to maturity (DTM), plant height (PH), peduncle length (PL), relative water content (RWC), number of seed per spike (NSPS), 1000 kernel weight (TKW), harvest index (HI), and grain yield (GY). Phonological, morphological and physiological traits were analyzed based on unbalanced combined completely randomization design. Two environments of supplemental irrigation and rain-fed were compared based on Hotelling T square test for the measured traits and multivariate analysis was also used to compare geographic origins in each environment separately. Shannon's index is employed to investigate diversity in germplasm and was utilized GT-bi-plot technique in order to depict relationships among diversity pattern for investigated traits and geographical origins of Iranian landraces.
Results and Discussion
The results of unbalanced analysis of combined variation and multivariate analyses revealed significant differences among geographical origins of Iran. Multivariate analysis showed significant differences among genotypes with different geographic origins in terms of Wilks’ lambda (0.69, 0.39), Pillai's trace (0.33, 0.81), Hotelling-Lawley trace (0.41, 1.1), and Roy’s greatest root (0.32, 0.57) for all traits at 1% probability level in supplemental irrigation and rainfed conditions, respectively. It means that the present population had high variegation. The results of bi-plot depicted significant differences between south geographic origins landraces and other geographic origins landraces for GY, HI, and TKW under the both supplemental irrigation and rainfed conditions. GT bi-plots revealed that the south landraces were early in flowering with high GY potential and also they indicated more compatibility to unpredictable situations in medium drought (supplemental irrigation) and severe drought (rainfed) conditions. The results indicated earliness (short DTM) as the most important phonologic trait affecting GY under rainfed conditions. South landraces can be suggested as highly valuable resources for using in breeding programs to develop new high yielding cultivars under unpredictable harsh environmental conditions. The examined Iranian wheat landraces showed high variations for important traits including GY, HI, TKW and earliness.
Conclusion
Our finding indicated that the explored variation play an important role in developing new cultivars and may be used in breeding programs aiming for adaptation to drought conditions. It is necessary to use a wide range of breeding strategies in order to gain present diversity in bread wheat which will lead to the expansion of the genetic basis of current cultivars and improvement of new wheat cultivars adapted to dryland conditions.
 

Keywords

Bi-plot analysis; Breeding; Genetic resources

References

Ajmal, S.U., Minhas, N.M., Hamdani, A., Shakir, A., Zubair, M., and Ahmed, Z., 2013. Multivariate analysis of genetic divergence in wheat (Triticum aestivum) germplasm. Pakistan Journal of Botany 45: 1643-1648.

Bartual, R., Carbonell, E.A., and Green, D.E., 1985. Multivariate analysis of a collection of soybean cultivars for southeastern Spain. Euphytica 34: 113–123.

Belay, G., Tesemma, T., Bechere, E., and Mitiku, D., 1995. Natural and human selection for purple-grain tetraploid wheats in the Ethiopian highlands. Genetic Resources and Crop Evolution 42: 387–391.

Bhatt, E., 1976. An application of multivariate analysis to selection for quality characters in wheat. Australian Journal of Agricultural Research 27: 11–18.

Broich, S.L., and Palmer, R.G., 1980. A cluster analysis of wild and domesticated soybean phenotypes. Euphytica 29: 23–32.

Blum, A., 1997. Crop responses to drought and the interpretation of adaptation. Plant Growth Regulation 20:135-148.

Blum, A., Golan, G., Mayer, J., Sinmena, B., Shpiler, L., and Burra, J., 1989. The drought response of landraces of wheat from the northern Negev desert in Israel. Euphytica 43: 87–96.

Curtis, T., and Halford, N.G., 2014. Food security: the challenge of increasing wheat yield and the importance of not compromising food safety. Annals of Applied Biology 164: 354-372.

Egesi, C.N., Ilona, P., Ogbe, F.O., Akoroda, M., and Dixon, A., 2007. Genetic variation and genotype × environment interaction for yield and other agronomic traits in cassava in Nigeria. Agronomy Journal 99: 1137–1142.

Falconer, D.S., 1981. Introduction to Quantitative Genetics. 2^nd Edition. London: Longman Group Ltd., pp. 1-133.

Fernandez-Aparicio, M., Flores, F., and Rubiales, D., 2009. Field response of Lathyrus cicera germplasm to crenate broomrape (Orobanche crenata). Field Crops Research 113: 321–327.

Fisher Box, J., 1987. Guinness, gosset, fisher, and small samples. Statistical Science 2: 45–52.

Holden, J.H.W., 1984. The second ten years. In: Holden J.H.W., Williams J.T., (Eds.). Crop Genetic Resources: Conservation and Evaluation. London: George Allen and Unwin, pp. 177-185.

Hotelling, H., 1931. The generalization of student's ratio. Annals of Mathematical Statistics 2: 360–378.

Jaradat, A.A., 1992. Breeding potential of durum wheat landraces from Jordan. I. Phenotypic diversity. Hereditas 116: 301–304.

Mead, R., Curnow, R.N., and Hasted, A.M., 2002. Statistical methods in agriculture and experimental biology. 3^rd edition. Texts in Statistical Science Series. London: Chapman and Hall/CRC, pp. 406–418.

Mohammadi, R., and Amri, A., 2013. Phenotypic diversity and relationships among a worldwide durum wheat (Triticum turgidum L. var. durum) germplasm collection under rainfed conditions of Iran. Crop and Pasture Science 64: 87–99.

Mohammadi, S.A., and Prasanna, B.M., 2003. Analysis of genetic diversity in crop plants—salient statistical tools and considerations. Crop Science 43: 1235–1248.

Mohammadi, R., Sadeghzadeh, D., Armion, M., and Amri, A., 2011. Evaluation of durum wheat experimental lines under different climate and water regime conditions of Iran. Crop and Pasture Science 62: 137–151.

Nogueira, A.M., Ferreira, M.F.S., Guilhen, J.H.S., and Ferreira, A., 2014. Multivariate analysis in a genetic divergence study of Psidium guajava. Genetics and Molecular Research: GMR 13: 10657-10668.

Ogunbodede, B.A., 1997. Multivariate analysis of genetic diversity in Kenaf, Hibiscus cannabinus (L.). African Crop Science Journal 5: 127–134.

Ortiz, R., Braun, H.J., Crossa, J., Crouch, J.H., Davenport, G., Dixon, J., Dreisigacker, S., Duveiller, E., Huerta-Espino, J., Joshi, A.K., Kishii, M., Kosina, P., Manes, Y., Mezzalama, M., Morgounov, A., Murakami, J., Nicol, J., Ortiz-Ferrara, G., Ortiz-Monasterio, J., Payne, T.S., Javier Peña, R., Reynolds, M.P., Sayre, K.D., Sharma, R.C., Singh, R.P., Wang, J., Warburton, M., Wu, H., and Iwanaga, M., 2008. Wheat genetic resources enhancement by the international maize and wheat improvement center (CIMMYT). Genetic Resources and Crop Evolution 55: 1095–1140.

Ortiz, R., Madsen, S., and Vuylsteke, D., 1998. Classification of African plantain landraces and banana cultivars using a phenotypic distance index of quantitative descriptors. Theoretical and Applied Genetics 96: 904–911.

Ray, D.K., Mueller, N.D., West, P.C., and Foley, J.A., 2013. Yield trends are insufficient to double global crop production by 2050. PLOS ONE 8: e66428.

Rencher, A.C., and Christensen, W.F., 2012. Methods of Multivariate Analysis. 3^rd edition. New Jersey, USA: John Wiley and Sons.

Shannon, C.E., 1948. A mathematical theory of communication. The Bell System Technical Journal 27: 379–423.

Shukla, S., Bhargava, A., Chatterjee, A., Srivastava, A., and Singh, S.P., 2006. Genotypic variability in vegetable amaranth (Amaranthus tricolor L.) for foliage yield and its contributing traits over successive cuttings and years. Euphytica 151: 103–110.

Singh, S.P., Nodari, R., and Gepts, P., 1991. Genetic diversity in cultivated common bean: I. Allozymes. Crop Science 31: 19–23.

Taehoon, K., 2015. T test as a parametric statistic. Korean Journal of Anesthesiology 68: 540–546.

Tambussi, E.A., Nogues, S., and Araus, J.L., 2005. Ear of durum wheat under water stress: Water relations and photosynthetic metabolism. Planta 221: 446–458.

Tesemma, T., Tsegaye, S., Belay, G., Bechere, E., and Mitiku, D., 1998. Stability of performance of tetraploid wheat landraces in the Ethiopian highland. Euphytica 102: 301–308.

Van Hintum, T.H.L.J., Brown, A.H.D., Spillane, C., and Hodgkin, T., 2000. Core collections of plant genetic resources. Ipgri Technical Bulletin 3: 1-48.

Vidya, C., Oommen, S.K., and Kumar, V., 2002. Genetic variability and heritability of yield and related characters in yard-long bean. Journal of Tropical Agriculture 40: 11–13.

Villa, T.C.C., Maxted, N., Scholten, M.A., and Ford-Lloyd, B.V., 2005. Defining and identifying crop landraces. Plant Genetic Resources 3: 373–384.

William, G.H., and Mackay, T.F.C., 2004. D.S. falconer and introduction to quantitative genetics. Genetics 167(4): 1529-1536.

Yan, W., and Rajcan, I., 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science 42: 11–20.

Yan, W., and Frégeau-Reid, J., 2008. Breeding line selection based on multiple traits. Crop Science 48: 417–423.

Zhang, H., Zhang, D., Wang, M., Sun, J., Qi, Y., Li, J., Wei, X., Han, L., Qiu, Z., Tang, S., and Li, Z., 2011. A core collection and mini core collection of Oryza sativa L in China. Theoretical and Applied Genetics 122: 49–61.