Introduction

Durum wheat (Triticum turgidum L. var. durum) accounts for about 6% of total wheat production, occupying approximately 20 million hectares worldwide (Guzmán et al. 2016). Global durum wheat production is estimated to be around 36 million tons. Most these areas have active breeding programs, which have created a large pool of modern durum wheat varieties with diverse characteristics to continue increasing grain yield and high quality (Wakeel et al. 2018). Durum wheat has been used for the preparation of diverse food products including bread, noodles and pasta. Hence, the selection and use of cultivars possessing optimal processing characteristics is imperative (Guzmán et al. 2016). High quality semolina can be obtained just from high quality grain (Rachoñ et al. 2012). Currently, over two billion people suffer from deficiency of micronutrients (Pandey et al. 2016). Humans need sufficient nutrients, such as micronutrients (copper, iron, manganese, zinc) and macronutrients (phosphorus, potassium, calcium, magnesium) for healthy nutrition (Bohra et al. 2019; Krishnan and Prabhasankar 2012). The chemical composition and micronutrients including minerals of wheat grain has necessary influence on its quality. Minerals are a group of compounds essential in human nutrition. However, the body’s organism is unable of producing them, therefore they must be supplied in suitable amounts with food (Rachoñ et al. 2012). Durum grain should be rich in proteins for the semolina. Lower rate of these components, the pasta will be brittle, fragile and therefore lower quality (Rachoñ and Kulpa 2004). Protein content have a many importance in durum wheat production and present the most important determinant of end-use quality, such as in pasta-making, in which high nutritional value and strong gluten are desirable. Quality and agronomical parameters have been commonly used in breeding programs, but determining quality and agronomic traits in genotypes needs various valuations to tend available results, since they are greatly affected by environmental conditions (Velu et al. 2014). Other factors which have been shown to affect durum wheat quality include genotype and the interaction between genotype and environment (Velu et al. 2014; Troccoli et al. 2000). Many investigations have been conducted to study particular quality chemical composition in durum wheat grain (Dinelli et al. 2013; Naseri et al. 2020). Sayaslan et al. (2012) with evaluation of the physical and chemical characteristics of some durum wheat cultivars demonstrated that in addition to color and protein properties, seed size and glassy endosperm are also important in the quality of durum wheat products. Fiore et al. (2019) investigated genetic diversity in a wheat collection from Sicily, using SNP markers and agro-morphological and quality traits. Their results showed that modern durum wheat cultivars showed lower grain protein content, compared to the older ones, as the wheat breeding programs are mainly focused on increasing the grain yield. Rachoñ et al. (2012) reported the superiority of spring durum wheat lines and cultivars in terms of total protein content and Zn compared to common wheat. The development of genotypes with grain quality in chemical compounds is useful for human health and knowledge of their genetic basis can be useful for breeding programs aimed at improving the nutritional properties of durum wheat (Velu et al. 2018; Koehler and Weiser 2013). This study aimed to determine relationships between the grain quality characteristics and agro-morphological traits, and to estimate genetic variability parameters of these traits in durum wheat genotypes, differing in genetic background, i.e., promising lines, local and old and recently developed varieties.

Materials and methods

Plant material

Fifteen durum wheat genotypes received from Dryland Agricultural Research Institute (DARI), Sararood branch, Kermanshah, Iran, were investigated at the research farm of Razi University, Kermanshah, Iran (latitude 34° 19′ N, longitude 47° 7′ E, and altitude 1322 m), during 2017–2018 and 2018–2019 cropping seasons. The durum wheat genotypes including promising lines, local and old and recently developed varieties (Table 1). Experimental field located in the west of Iran with moderate-cold and semi-arid climate and mean annual rainfall about 460 mm. The weather conditions during the experiments is described in Table 2.

Table 1 Fifteen durum wheat genotypes used in the study
Full size table
Table 2 Monthly rainfall and average temperature during two cropping seasons (2017–18 and 2018–19)
Full size table

The study was carried out as a randomized complete blocks design (RCBD) with three replications under rainfed condition. Plot size was five rows 3 m long, the rows were spaced at 22.5 cm apart and plant density was 400 grains per meter square. Five plants were randomly selected from each plot to measure the morphological and physiological traits. The aboveground biomass yield at both years was harvested from 1 m2 area from the middle three rows of each plots. The observations were recorded on five randomly selected plants in each entry for 29 traits including days to heading (DTH: days to 50% heading), days to anthesis (DTA: days to 50% anthesis), days to maturity (DTPM: the number of days from planting to 50% physiological maturity), flag-leaf length (FLL: flag leaf length, cm), flag-leaf width (FLW: flag leaf width, cm), flag leaf area (FLA: flag leaf width × flag leaf length × 0.7), kernel filling period (KFP: the number of days from anthesis to physiological maturity), kernel filling rate (KFR: the ratio weight of grain to kernel filling period in mg/day), weight of kernels per spike (WKPS: weight of kernels per spike, g), number of kernel per spike (NKPS: the number of kernel of the per spike), spike density (SD: the ratio number of spikelet to spike length), plant height (PH: plant height, cm), panicle length (PL: panicle length, cm), spike length (SL: spike length, cm), awn length (AL: awn length, cm), grain length (GL: grain length, mm), grain width (GW: grain width, mm), number of spike per m2 (NSP/m2: number of spike per 1m2), biological yield (BY: the weight of the biomass harvested from the 1m2 in g/m2), grain yield (GY: the weight of the grain yield harvested from the 1m2 in g/m2) and thousand kernel weight (TKW: 1000-kernel weight, g). Also, relative water content (RWC) was calculated using the method given by Barrs (1986). The SPAD reading was recorded for three flag leaves in each plot by the SPAD chlorophyll meter (Minolta Co. Ltd., Tokyo, Japan). Chlorophyll content (SPAD, Soil and Plant Analyzer Development), was measured on the flag-leaf according to the method of Chaves et al. (2002).

Soil experiment

To determine the physicochemical characteristics of the soil, composite soil samples were randomly selected from three different points of the field surfaces 0–30 cm. After transferring the sample to the laboratory, they were passed from a two-millimeter sieve properties such as saturated mud pH (McLean 1982), soil electrical conductivity (EC) (Rhoades 1982), soil texture (Gee and Bauder 1986), soil organic carbon (Walkley and Black 1934), calcium carbonate titration (Laitinen and Sympson 1954), absorbable phosphorus and potassium (Olsen et al. 1982), DTPA soil test for Zn, Fe, manganese and copper (Lindsay and Norvell 1978) were measured.

Chemical analysis

A whole grain sample of each genotype was ground to whole meal using a laboratory non-rust steel miller (IKA® A11 B, Germany). All chemical analysis was conducted on this sample. Moisture content of the flour sample was determined according to the AACC approved method 44-15 (AACC 2000). Ash content was determined using the approved AACC method (AACC 2000). Grain protein content (GPC) was measured by the Kjeldahl method (Bradstreet 1954) and expressed using the conversion factor (N × 5.75). Total soluble sugars and starch was conducted using the AACC method (AACC 2000). Fiber content percentage (FC) was determined by using the gravimetric method (Soest 1965). Fat percentage was measured using Soxhlet gravimetric method (Gulati et al. 1999). The grain Fe, Zn and Cd concentrations (GFeC, GZnC and GCdC) were determined by Atomic Absorption Spectrometer (SpectrAA-220, VARIAN, Australia).

Statistical analysis

Combined analysis of variance and mean comparisons using Least Significant Difference (LSD) test were done using SAS (Ver. 9.1) software. Genotypes were considered as fixed effect, and year was considered as random effect. Correlation analysis was performed using Past software (Ver. 4.03). Cluster analysis was performed using SYSTAT software (Ver. 13.2). The genetic variability parameters were estimation based on the method of Burton and DeVane (1953) and Johnson et al. (1955). Also, broad sense heritability (H) was calculated according to Nyquist (1991).

Results

Variations in agronomic and grain quality characteristics of the studied durum wheat genotypes

According to ANOVA (Table 3), significant differences were observed between the genotypes for all the investigated traits. The year effect was also found to be significant for RWC, PH, PL, AL, GL, BY, NSP/m2, SL, SD, NKPS, GY, TKW, ash, GCdC, GPC and starch traits. Genotype × year interaction was significant for RWC, DTA, PL, GW, BY, NSP/m2, SL, NKPS, GY, TKW, ash, fat, GCdC, GPC, soluble sugar and starch traits. Finally, year (block) effect was significant difference for a number of agricultural traits (DTH, DTA, AL, GW and TKW) in durum wheat genotypes.

Table 3 Combined analysis of variance for agro-morphological traits and grain quality characteristics of 15 durum wheat genotypes during two years
Full size table

Descriptive statistics for the studied traits are presented in Table S1. Cultivar ‘Zahab’ had the highest mean yield. The local variety ‘Cheheldaneh’ had the highest mean values for FLA, AL, GL, SL and TKW. The ‘Saji’ cultivar showed the highest amounts of soluble sugar percentage and fat percentage. The highest amounts of moisture percentage and ash content belonged to genotype ‘Ammar-9’ (9.55% and 2.19 db%), and the lowest were in ‘Knd1149//68…’ (6.47% and 0.75 db%). The highest GPC was recorded for genotype 12 (‘SRN-1/…’ line) with 23.45%, and the lowest (13.42%) was recorded for genotype 7 (‘61–130/…’ line). ‘Geromtel-1’ expressed the highest amounts of GZnC and starch percentage. The highest amounts of WKPS, PH, FC and GFeC were found in Turkish durum wheat cultivar ‘G-1252’. The lowest GCdC was recorded for genotype 13 (‘G-1252/Kermanshah’ line) with 0.16 mg/kg. On the contrary, ‘G-1252’ was characterized by a high GCdC (0.81 mg/kg).

Estimation of genetic variability parameters

Maximum, minimum, mean, genotypic variance, genotypic coefficient of variance (GCV), phenotypic variance, phenotypic coefficient of variance (PCV) and broad-sense heritability (H2b), genetic advance (GA) and genetic advance as percentage of mean (GAM%) for all significant traits in analysis of variance are presented in Table 4. Biological yield and grain yield showed the highest genotypic and phenotypic variances. The lowest genotypic and phenotypic variances were recorded for KFR. The GCV was ranged from 2.34% (DTPM) to 91.30% (GCdC). Maximum GCV was observed for the Cd (91.30%). Among the grain quality characteristics, the highest genotypic and phenotypic coefficients of variation, (GCV = 91.30% and PCV = 108.70%) were observed for GCdC. GZnC showed the lowest amounts of genotypic and phenotypic coefficients of variation, (GCV = 6.62% and PCV = 8.16%). Among the agronomic traits, FLA showed the highest GCV (40.09%) value.

Table 4 Mean, maximum, minimum and genetic variability parameters for grain quality and agro-morphological characteristics of 15 durum wheat genotypes across two cropping seasons
Full size table

FC and GFeC showed heritability’s above 0.96. On the other hand, GW (0.04) and starch percentage (0.05) revealed the lowest heritability values. The genetic advance as percentage of mean for measured traits ranged from 0.02 to 143.94%. The highest genetic advance as percentage of mean was recorded for BY (143.94%), followed by GFeC (46.31%), GY (44.10%) and NSP/m2 (40.44%).

Relationships among agronomic and grain quality traits

Pearson’s correlation coefficients between agro-morphological and grain quality traits are given in Fig. 1. The GY had negative or non-significant correlations with the most of grain quality characteristics except fat, FC, GFeC and GZnC. Among the grain quality traits, GPC was positively correlated with DTH (0.62), DTA (0.67), DTPM (0.57), KFP (0.57), BY (0.70) and it was significantly and negatively (P < 0.05) associated with GY (− 0.50), WKPS (− 0.54) and PH (− 0.51). Relationships between the measured characteristics revealed that grain GZnC only had a negative significant correlation (P < 0.05) with FC (− 0.51). GFeC negatively correlated (P < 0.05) with AL (− 0.56). GCdC positively correlated (P < 0.05) with FC (0.63) and NKPS (0.63), but negatively correlated with RWC (− 0.73) and AL (− 0.53). Soluble sugar percentage negatively correlated (P < 0.05) with FLL (− 0.51); and starch percentage positively correlated (P < 0.01) with GW (0.73).

Fig. 1
figure 1

Genotypic correlations between agro-morphological and quality traits in 15 durum wheat genotypes, significant correlations are marked inside the box

Full size image

Flag leaf length (FLL) had a significant positive correlation (P < 0.01) with FLW (0.83), FLA (0.90), PL (0.70), AL (0.75) and GL (0.74). DTH and DTPM had significant positive correlation (P < 0.01) with DTA (0.97) and KFP (0.96) but negatively correlated with KFR (− 0.70) and WKPS (− 0.92). AL and GL showed significant and positive correlation (P < 0.01) with GL (0.87) and TKW (0.70). Also, there was no correlation between TKW and GY with GFeC and GZnC.

Classifying the durum wheat genotypes

Cluster analysis using Ward method and based on square Euclidean distance matrix classified fifteen genotypes into three groups (Fig. 2). The first group consisted of genotypes ‘Germotel-1’ ‘61–130/…’ ‘Haurani’ ‘Knd1149//68…’ ‘BCRIS/BICUM…’ ‘Saji’ ‘Ammar-9’ and ‘G-1252/Kermanshah’. This group had the lowest TKW, NKPS, WKPS, DTH, DTA, BY, PL, ash content and in terms of GCdC, GPC and starch percentage, middling values compared to other groups. Also, in this group, some of the analyzed cultivars exhibited low GCdC concentration. Between them, ‘G-1252/Kermanshah’ line was the most suitable option in terms of low GCdC. The second group comprised three Iranian cultivars ‘Zardak’ ‘Cheheldaneh’ and ‘Zahab’ two Turkish cultivars ‘G-1252’ and ‘Imren’ and breeding line ‘Rascon_…’. Genotypes in this group were distinguished from other groups by having high values for FLW (2.3 cm), FLL (30.5 cm), FLA (51.1), PH (129.7 cm), PL (54.5 cm), GL (14.3 mm), TKW (53.2 g), GY (520.5 g/m2), FC (4.2%) and GFeC (148.7 mg/kg). ‘Zahab’ cultivar with the highest GY was in the second group, while ‘SRN-1/KILL//2*FOLTA-1’ with the highest GPC (23.4%) classified in the third group (Fig. 3).

Fig. 2
figure 2

Validity index plot for clustering 15 durum wheat genotypes

Full size image
Fig. 3
figure 3

Cluster analysis using Ward method and based on square Euclidean distance matrix for the studied traits on fifteen durum wheat genotypes

Full size image

Discussion

The chemical and mineral composition of wheat grain has important influence on its quality. Minerals are a group of compounds necessary in human nutrition. The human organism is incapable of producing them, hence they must be supplied in appropriate amounts with food (Rachoñ et al. 2012). So, improvement of durum wheat grain quality through agronomic bio-fortification transforms into a prioritized research area and an effective pathway for combating malnutrition (Melash and Mengistu 2020). The analysis of agro-morphological and biochemical characteristics of the examined genotypes of durum wheat revealed significant variations in all of the studied traits (Table 3). Therefore, the existing difference can indicate the presence of genetic diversity and the availability of the opportunity to select suitable parents (Alahmad et al. 2023). The present study demonstrated that grain yield, its components and grain quality traits were influenced by the environment, specifically the variation in the cropping season. This finding aligns with the results reported by Shirvani et al. (2021) and Mohammadi et al. (2018), who also observed that the grain yield and quality parameters of durum wheat varieties are influenced by the weather conditions prevailing during the experimental year. In this study, the cultivar ‘Zahab’ exhibited the highest mean yield among the tested cultivars. On the other hand, the ‘Saji’ cultivar demonstrated the highest percentage of soluble sugar. Carbohydrates and soluble sugars play crucial roles in various physiological processes within organisms. They are involved in the synthesis of metabolic compounds, providing energy, maintaining membrane balance, regulating gene expression, and acting as signaling molecules (Himani and Madan 2018). The color of semolina obtained from durum wheat grain is very important, because synthetic colors are not used in the production of pasta. It is desirable for durum wheat grain to have low levels of ash since a relatively high ash content can result in a darker color of pasta (Zalewski and Bojarczuk 2004; Rachoñ et al. 2012). In our study, genotype ‘Ammar-9’ exhibited the highest ash content with a value of 2.18 db%. Durum wheat is well-known for its high grain protein content, which is considered one of its distinguishing qualities (Rachoñ et al. 2012). Numerous studies have reported higher protein content in durum wheat grain compared to common wheat (Colasuonno et al. 2021; Rachoñ and Szumi£o 2009). Grain protein content is indeed a quantitative trait, as it is influenced by environmental factors. Therefore, it is important to measure grain protein content in replicated trials to account for variations in the environment and ensure accurate and reliable measurements. The grain of genotype 12 (‘SRN-1/…’ line) exhibited the highest protein content, reaching 23.5%. It is crucial for organisms to have an adequate supply of basic nutrients, including micronutrients, such as iron and zinc, which are often required in trace amounts. Wheat grain serves as an important source of these micronutrients (Velu et al. 2018). Zinc is an essential element that plays a vital role in various biological processes. It is required for the synthesis of carbohydrates and proteins, as well as for the functioning of growth-regulating hormones like auxin and chlorophyll biosynthesis (Begum et al. 2016). Iron is another crucial trace element that plays a significant role in plant development, as well as in determining the quantity and quality of the final product. Iron deficiency can have adverse effects on plant growth and development, leading to reduced yields and compromised product quality (Briat et al. 2015). In this study ‘Geromtel-1’ exhibited the highest starch content, while ‘G-1252’ demonstrated the highest of GZnC and GFeC among the genotypes tested (Table S1). Tiwari et al. (2016) and Melash and Mengistu (2020) also support the finding of higher zinc content in durum wheat compared to common wheat. Additionally, Amiri et al. (2020) conducted genetic analysis on bread wheat and reported that populations with high genetic diversity possess unique alleles that can be utilized for genetic enhancement of GFeC and GZnC in wheat. Therefore, the utilization of recurrent selection can be recommended to combine the additive gene effects for breeding improved levels of these micronutrients. Additionally, starch, as one of the key components of wheat endosperm, significantly influences the quality of wheat. The identification of genes responsible for starch synthesis and understanding the inheritance patterns of starch-related traits can provide valuable insights into manipulating starch functionality in various products and improving nutritional quality. By studying the genes involved in starch metabolism and their expression patterns, researchers can gain a better understanding of how to modulate starch properties and optimize its utilization in different food and non-food applications. This knowledge can contribute to developing improved varieties with enhanced starch functionality and nutritional characteristics (Labuschange et al. 2009; Himani and Madan 2018). The presence of heavy metals, such as cadmium (Cd), in soil poses a significant threat to crop productivity and food-chain contamination. Cd is particularly hazardous due to its potential for bioaccumulation in the food chain. It can be taken up by plants and subsequently consumed by humans and animals, leading to health risks and environmental concerns (Vergine et al. 2017). According to Table S1, ‘G-1252/Kermanshah’ exhibited the lowest GCdC. This may be attributed to the genotype’s ability to store high levels of Cd in the roots, thereby preventing its translocation to the shoots and ultimately the grains. This mechanism of sequestering Cd in the roots helps minimize its accumulation in the edible parts of the plant and reduces the potential for food-chain contamination (Vergine et al. 2017). Therefore, this promising line, ‘G-1252/Kermanshah’ can be recommended for inclusion in breeding programs aimed at developing durum wheat varieties with improved human feed quality. Its ability to limit the accumulation of Cd in edible parts makes it a desirable candidate for ensuring food safety and reducing the risk of heavy metal contamination in the food chain. In the investigation of genetic variability parameters, PCV exhibited a similar trend as GCV. This indicates that selection can be effectively applied to these traits to identify and isolate more promising genotypes. The similarity in trends between PCV and GCV suggests that the observed variability is largely of genetic origin, providing a solid foundation for selecting genotypes with desired traits in breeding programs (Ahsan et al. 2015). There was a strong agreement between GCV and PCV for the majority of the recorded characteristics. This close correspondence suggests that these traits are less influenced by environmental factors and have a stronger genetic basis. These findings align with the results reported by Mohammadi et al. (2018), supporting the notion that these traits exhibit a higher degree of genetic control and are less affected by environmental fluctuations. The trait DTPM exhibited the lowest values for both GCV and PCV. This indicates that there is limited variability for this trait within the studied population. To make improvements in this trait, breeders should focus on identifying and utilizing sources with high variability for DTPM (Do Thi Ha and Ravikesavan 2006). The broad-sense heritability (h2b) values for all traits ranged from 0.04 to 0.97, as shown in Table 4. The low heritability values observed in several studies indicate that environmental factors play a substantial role in causing phenotypic variations for these traits. Consequently, relying solely on the screening of genotypes based on these traits may not be highly effective, as their expression is heavily influenced by the environment. It becomes essential to consider additional factors and traits in breeding programs to achieve more reliable and effective selection of superior genotypes (Steinsaltz et al. 2020). In each plant population, the observed diversity is influenced by both genetic and environmental factors. While genetic diversity can be inherited from one generation to the next, heritability alone does not provide an indication of the expected benefit in the next generation. It must be considered together with genetic advance. Characters with high heritability and substantial genetic advance are considered valuable traits in the selection process. These traits are predominantly controlled by genes and are less influenced by environmental factors (Panse and Sukhatme 1995). Consequently, they are highly reliable during the selection of genotypes (Ahsan et al. 2015). Most of the agronomic traits were inversely correlated with grain quality traits (Fig. 1). In accordance with our findings, several studies including Sourour et al. (2018), Amiri et al. (2018) and Blanco et al. (2012) have also reported a negative correlation between grain protein content and GY. Therefore, the negative association between yield and high quality should be a major concern for breeders aiming to simultaneously increase the yield and quality of durum wheat grain. The investigated genotypes could serve as a platform for parental selection in breeding programs, aiming to develop high-yielding and high-quality durum wheat lines, as well as for genetic mapping studies. No correlation was observed between TKW and GY with GFeC and GZnC, which is consistent with the findings of Velu et al. (2012) and Amiri et al. (2018). This may indicate an ineffective concentration of these minerals due to the small grain size, as suggested by Velu et al. (2014). The genotypes and promising lines can be considered as potential parents in the development of durum wheat genotypes with high grain quality characteristics. Finally, the locally adapted cultivar ‘Zardak’ variety from Kermanshah and the Turkish cultivar ‘G-1252’ can be considered as parents for developing new durum wheat genotypes. It should be noted that these cultivars exhibit high yield and high grain quality characteristics. This project is currently underway. The broad-sense heritability of GZnC, GFeC and GPC was observed to be high, indicating that these important traits can be effectively selected through bio-enhancement breeding programs. These results suggest that breeding efforts can lead to improvements in the levels of micronutrients and grain protein in durum wheat. The present study has identified several promising lines that possess specific traits, particularly high protein content, iron and zinc concentrations. These lines hold potential value in durum wheat breeding programs aiming to combine high micronutrient content with high nutritional protein content, without compromising grain yield. The utilization of these cultivars/lines in breeding programs has the potential to enhance the nutritional, health, and commercial quality of durum wheat. This approach could contribute to improving the resilience of durum wheat varieties.