Research Article

Phenotypic Characterization of Some Durum Wheat (Triticum durum Desf.) Genotypes Growing under Semi-Arid Conditions

Guendouz Ali, Hannachi Abderrahmane, Fellahi Zine El Abidine and Benalia Frih

  • Page No:  725 - 730
  • Published online: 31 Dec 2021
  • DOI : HTTPS://DOI.ORG/10.23910/1.2021.2487

  • Abstract
  •  guendouz.ali@gmail.com

Breeders are permanently looking for an efficient method of developing genotypes with improved yield. The aim of this study was to evaluate the performance of some durum wheat genotypes, the study of the correlations between traits and the direct effect of each trait on final grain yield. Twenty genotypes of durum wheat (Triticum durum Desf.) were planted in the experimental fields of INRAA, Setif, Algeria in (2016 –2017) crop season. The genotypes tested were grown in a randomized block design with three replications. The analyses of variance (ANOVA) demonstrate the existence of genetic diversity between genotypes tested. In addition, significant and positive correlations were registered between grain yield (GY) and days to heading (DH), number of spikes per square meter (NSM) and number of kernels per spike (NKS). The path analysis (PA) demonstrates positive and significant direct effects of the number of spikes per square meter (NSM), thousand kernels weight (TKW) and number of kernels per spike (NKS) on grain yield. Overall, the results proved that the genotypes Rezzak, Ofanto and BIDI 17 have the best ranking with the highest grain yield, and these can be recommended as the best genotypes for some in this area. In addition, the Principal Component Analysis (PCA) proved that the genotypes Rezzak, Bidi17, Ofanto, Kebir and Adnan 2 are very suitable genotypes for growing under semi-arid conditions.

Keywords :   Durum wheat, grain yield, path analysis, correlation, semi-arid

  • Introduction

    Durum wheat (Triticum turgidum subsp. durum Desf.) is a minor cereal crop representing 5% of the total wheat crop cultivated worldwide (about 17 mha) (Xynias et al., 2020). Durum wheat (Triticum durum Desf.) is one of the main crops consumed by humans and it is cultivated in different environments. Drought is the single largest abiotic stress factor leading to reduced crop yields. So, high-yielding crops, even in environmentally stressful conditions, are essential (Fleury et al., 2010). Total food use of wheat is forecast to approach 518 mt, up 1.1% and rising in close tandem with world population growth. However, large supplies and competitive prices are likely to drive up feed use of wheat by 2.8%, a faster rate than was projected earlier, while industrial use is also anticipated to register strong growth (Anonymous, 2019). Climate changes recorded changes in the composition and geographic redistribution of ecosystems in Algeria. This situation has resulted in a shift towards the north of the arid zones, until then confined between the Sahara and the high cereal plains (Haffaf et al., 2003). In Algeria, the actual production of cereals during the period 2010–2017 is estimated at 4.12 mt on average, an increase of 26% compared to the decade 2000–2009 when production is estimated on average at 32.6 million quintals. Production consists mainly of durum wheat and barley, which respectively represents 51% and 29% of all cereal production on average 2010–2017 (Anonymous, 2018). Drought is a meteorological term and is commonly defined as a period without significant rainfall. Generally, drought stress occurs when the available water in the soil is reduced and atmospheric conditions cause continuous loss of water by transpiration or evaporation. Drought stress tolerance is seen in almost all plants, but its extent varies from species to species and even within species (Jaleel et al., 2007). Tolerance to abiotic stresses is very complex, due to the intricacy of interactions between stress factors and various molecular, biochemical and physiological phenomena affecting plant growth and development (Razmjoo et al., 2008). Garcia del Moral et al. (1991) estimate that the grain yield of cereals is not influenced only by the components of the yield but also by the extension of the vegetative period and the filling of the grains. High yield potential under drought stress is the target of crop breeding. In many cases, high yield potential can contribute to yield in moderate stress environment (Blum, 1996). The most promising approach to increase agricultural productivity and satisfy human needs in the future is the genetic improvement of crops which requires a continuous allocation of new sources of genetic variation (Borner et al., 2000). Although breeders are continuing to improve the yield potential of wheat, the progress in increasing wheat yield in drought environments has been difficult to achieve. Grain yield is an environmental and genetic trait, it differs according to variety, soil fertility, soil moisture, temperature, diseases and pests. In defining a strategy for wheat breeding under drought tolerance, Rajaram et al. (1996) suggested that simultaneous evaluation of germplasm should be carried out under both near optimum conditions (to utilize high heritability and identify genotypes with high yield potential) and under stress conditions (to preserve alleles for drought tolerance). The objective of this study is to evaluate the performance of 20 durum wheat cultivars under semi-arid conditions based on different statistical methods.


  • Materials and Methods

    2.1.  Plant material and growth conditions

    Twenty genotypes of durum wheat (Triticum durum Desf.) were planted in the experimental fields of INRAA, Setif, Algeria, (5°37’E, 36°15’N) 981 masl in November 19, 2016. The genotypes tested were grown in a randomized block design with three replications, each plot consisted of 6 lines of 10 m long spaced of 0.2 m which made 12 m2 as plot area. The sowing density adjusted to 300 grains m–2. No specific treatment was administered.

    2.2.  Agronomical and physiological measurements

    At harvest, data was recorded on 1000-kernel weight (TKW) and grain yield (GY). In addition, some parameters such as number of spike m-2 (NS/m²) and kernels per spike (NK/S) were determined. The SPAD-502 measured the amount of chlorophyll (Chl) in the leaf, which is related to leaf greenness, by transmitting light from light emitting diodes (LED) through a leaf at wavelengths of 650 and 940 nm. In addition, the plant height and days to heading were determined.

    2.3.  Statistical analysis

    The analysis of variance was performed for agronomical and physiological traits, Fisher’s LSD multiple range test was employed for the mean comparisons by using Costat software. Linear correlation analysis was used to determine the relationships between the traits measured and the path analysis, and the Principal Component Analysis (PCA) was done using the Statistica software.


  • Results and Discussion

    The results of the analysis of variance demonstrated that the differences among genotypes were highly significant (p< 0.01) for all traits (Table 1).

    For the chlorophyll content (Chl), the values ranged from 44.53 for the genotype CHEN’S to 54.03 for Ofanto with a general mean of 48.44. In addition, the study of correlations showed no significant correlation between chlorophyll content and all traits. For the agronomic traits, such as Grain yield (GY), the values varied from 29.7 q ha-1 for Polonicum to 77.13 q ha-1for Ofanto. Significant and positive correlations were registered between GY and number of spikes per m² (NS/m²) and the number of kernels per spike (NK/S) (r=0.46*, r=0.73*, respectively) and a negative correlation was found between GY and days to heading (DH) (r=-0.66*) (Table 2).


    Ashraf (1998) reported that the productive spikes per plant contribute to the increasing of the grain yield under water deficit conditions. In addition, these correlations indicated that increase in grains per spike cause simultaneous increase in grain yield. The significant negative correlation between grain yield and number of days from sowing to heading (DH) confirms that the earliness has played a very important role in stability of durum wheat yield in dry areas which are characterized by excessive temperature and hot winds during the period of grain filling (Sharma and Smith, 1986). Some of these correlations among yield traits are in conformity with those of Gupta et al. (2001) who also noted a significant and positive correlation among grains per spike and grain yield and harvest index in their study. Correlation studies are also very useful to plant breeders for improving drought tolerance, in the sense that, any physiological or yield traits having high heritability could be used as indirect selection criteria to improve yield in water-deficit environments. The direct effects of all traits on the grain yield (Table 2) showed significant effect on number of spikes m-² (NS/m²), TKW and number of kernels per spike (NK/S) (PNSM/GY= 0.67***, PTKW/GY= 0.41***, PNKS/GY= 0.90***, respectively). Azimzadeh et al. (2000) showed that number of kernels and one-thousand weights were major components of yield, and with regard to direct effects and their meaningful and positive correlation with grain yield, based on these results, we can consider these two traits as selection criteria. Our results agree with those reported by Khaliq et al. (2004) and Guendouz et al. (2013), who found that kernels number per spike exerted a direct positive effect on grain yield. Based on the ranking test (Table 3) for all traits, the genotypes BIDI 17, Rezzak, Ofanto, Djenah Khotifa and MARTON DUR are the best genotypes under these conditions.


    In addition, the ranking based on the traits which have significant direct effect on grain yield (NSM, TKW and NKS) showed that the genotypes Rezzak, Ofanto, BIDI 17, Adnan 2 and Kebir are the best genotypes. Combination ranking between NSM, TKW, NKS and GY showed that the genotypes Rezzak, Ofanto and BIDI 17 have the best ranking (TOP) with highest grain yield under semi-arid conditions. Data presented in Table 4 and graphically shown in Figure 1 proved that an increase in the number of PCs was associated with a decrease in Eigenvalues. Accordingly, it is reasonable to assume that the PCs analysis had grouped the studied durum-wheat traits into three main components that altogether accounted for 75% of the total observed variation. Principal component analysis (PCA) showed that NKS and GY were well correlated with the first component PC1 which represented 36.49% of the information.


    In addition, mean-while, the second PC correlated with NSM and DH traits and accounted for 22.97 % of the detected total variation, while the third PC correlated with TKW and Chl traits and accounted for 15.87 % of the total survived variation (Table 4).

    Relatively similar results were reported by Frih et al. (2021) and Moragues et al. (2006) who stated that the first two PCs were related to the GY components. As shown in the Figure 1, the distribution of the genotypes tested via the first and the second PC classified the genotypes into three groups, and the first group which includes five genotypes (Rezzek, Bidi17, Ofanto, Kebir and Adnan 2) is characterised by high productivity; the second group, which includes the local landrace, Oued Zenati, Belioni, Polonicum, Djenah Khotifa and Guemgoum Rkhem, has high TKW and long days to heading (Tardive genotypes). Increasing GY potential could enable plant breeders to realise the desired increment in drought-stressed tolerance of durum wheat genotypes. The results illustrated in Figure 1 proved that the genotypes Rezzek, Bidi17, Ofanto, Kebir and Adnan 2 are very suitable as parents in the future programmes of durum wheat ameliorations under semi-arid conditions.


  • Conclusion

    Path analysis revealed that NSM, TKW and NKS had a positive direct effect on GY. Our results demonstrate that the genotypes Rezzak, Ofanto and BIDI 17 have the highest grain yield and can be recommended for cultivation under semi-arid conditions. Based on the Principal Components Analysis, the five genotypes Rezzek, Bidi17, Ofanto, Kebir and Adnan 2 are the preferable genotypes for growing under the semi-arid conditions.


  • Reference
  • Anonymous, 2018. Statistiques serie B-Ministere de l’agriculture et du developpement rural. MARD. Available at http://madrp.gov.dz/agriculture/statistiques-agricoles/.Accessed on March 15, 2021.

    Anonymous, 2019.Food and Agriculture Organization [FAO] .2019. Food Outlook - Biannual Report on Global Food Markets - November. Rome. Available at https://www.fao.org/documents/card/en/c/CA6911EN/. Accessed on March 20, 2021.

    Ashraf, M.Y., 1998. Yield and yield components response of wheat (Triticum aestivum L.) genotypes grown under different soil water deficit conditions. Acta Agronomica Hungarica 46, 45–51.

    Azimzadeh, C.M., Rashed mohassel, M.H., 2000. Determination of pattern growth in three wheat cultivars and to barley cultivars. Iranian Journal of Crop Sciences 1(4), 42–54.

    Blum, A., 1996. Crop response to drought and the interpretation of adaptation. Journal of Plant Growth Regulation 20, 135–148.

    Borner, A., Chebotar, S.,Korzun, V., 2000. Molecular characterization of the genetic integrity of wheat (Triticum aestivum L.) germplasm after long-term maintenance. Theoretical and Applied Genetics 100, 494–497.

    Fleury, D., Jefferies, S., Kuchel, H., Langridge, P., 2010. Genetic and genomic tools to improve drought tolerance in wheat. Journal of Experimental Botany 61, 3211–3222.

    Frih, B., Oulmi, A., Guendouz, A., Bendada, H., Selloum, S., 2021.  Statistical analysis  of  the  relationships  between  yield  and  yield  components  in  some  durum  wheat  (Triticum  durum  desf.)  Genotypes Growing under Semi-Arid  Conditions.  International Journal of Bio-resource  and  Stress  Management 12(4),  385–392. HTTPS://DOI.ORG/10.23910/1.2021.2431.

    Jaleel, C.A., Manivannan, P., Kishorekumar, A., Sankar, B., Gopi, R., Somasundaram, R., Panneerselvam, R., 2007. Alterations in osmoregulation, antioxidant enzymes and indole alkaloid levels in Catharanthusroseus exposed to water deficit.Colloids and Surfaces B-Biointerfaces 59, 150–157.

    Garcia del Moral, L., Ramos, F.J.M., Garcia del Moral, N.B., Jimeneztejada, M.P., 1991. Otogenetic approach to grain production in spring barley based on path-coefficient analysis. Crop Science 31, 1179–1185.

    Guendouz, A., Guessoum, S., Maamri, K., Benidir, M., Hafsi, M., 2013. Performance of ten durum wheat (Triticum durum Desf.) cultivars under semi-arid conditions (north Africa-Algeria). Indian Journal of Agricultural Research 47(4), 317–322.

    Gupta, N.K., Gupta, S., Kumar, A., 2001. Effect of water stress on physiological attributes and their relationship with growth and yield in wheat cultivars at different growth stages. Journal of Agronomy 86, 1437–1439.

    Haffaf, A., Labdi, M., Hammou, M., 2003. Tolerance a la secheresse, une realite dans le developpement de la cerealiculture et l utilisation des espaces productifs en zones semi-arides. Cerealiculture 40, 20–24.

    Khaliq, I., Parveen, N., Chowdhry, M.A., 2004. Correlation and path coefficient analyses inbread wheat. International Journal of Agriculture and Biology 6(4), 633–635.

    Moragues, M., Garcia Del Moral, L.F., Moralejo, M., Royo, C., 2006. Yield formation strategies of durum wheat landraces with distinct pattern of dispersal within the Mediterranean basin I: Yield components. Field Crops Research 95, 194–205.

    Rajaram, S., Braun, H.J., Ginkel, M.V., 1996. CIMMYT’s approach to breed for drought tolerance. Euphytica (Netherlands) 92, 147–153.

    Razmjoo, K., Heydarizadeh, P., Sabzalian, M.R., 2008. Effect of salinity and drought stresses on growth parameters and essential oil content of Matricaria chamomila. International Journal of Agriculture and Biology 10, 451–454.

    Sharma R.C., Smith, E.L., 1986. Selection for high and low harvest index in three winter population. Crop Science26, 1147–1150.

    Xynias, I.N., Mylonas, I., Korpetis, E., Ninou, E.,Tsaballa, A., Avdikos, I., Mavromatis, A.2020. Durum wheat breeding in the mediterranean region: current status and future prospects. Agronomy 10, 432.


People also read

Short Research

Preference Towards Online Mode of Distance Education Courses–conjoint Analysis

M. Malarkodi, V. M. Indumathi and S. Praveena

Conjoint analysis, distance education, preference, online learning

Published Online : 07 Feb 2018

Review Article

Cereal Residues - Not a Waste Until We Waste it: A Review

Amit Anil Shahane and Yashbir Singh Shivay

Cereal residue, ecological services, energy source, residue burning

Published Online : 07 Feb 2016