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Article

Durum Wheat Seminal Root Traits within Modern and Landrace Germplasm in Algeria

1
Laboratoire d’Amélioration et de Développement de la Production Végétale et Animale (LADPVA), University of Ferhat ABBAS (UFAS-Sétif1), Setif 19000, Algeria
2
Biotechnology Research Center (CRBt), UV 03 BP E73, Nouvelle Ville Ali Mendjli, Constantine 25016, Algeria
3
Department of Biomedicine and Biotechnology, University of Alcalá, 28805 Alcalá de Henares, Spain
4
Estación Experimental de Aula Dei, EEAD-CSIC, Avenida Montañana 1005, 50059 Zaragoza, Spain
*
Authors to whom correspondence should be addressed.
Agronomy 2020, 10(5), 713; https://doi.org/10.3390/agronomy10050713
Submission received: 11 March 2020 / Revised: 14 May 2020 / Accepted: 14 May 2020 / Published: 16 May 2020
(This article belongs to the Special Issue Durum Wheat Breeding and Genetics)

Abstract

:
Seminal roots are known to play an important role in crop performance, particularly under drought conditions. A set of 37 durum wheat cultivars and local landraces was screened for variation in architecture and size of seminal roots using a laboratory setting, with a filter paper method combined with image processing by SmartRoot software. Significant genetic variability was detected for all root and shoot traits assessed. Four rooting patterns were identified, with landraces showing overall steeper angle and higher root length, in comparison with cultivars, which presented a wider root angle and shorter root length. Some traits revealed trends dependent on the genotypes’ year of release, like increased seminal root angle and reduced root size (length, surface, and volume) over time. We confirm the presence of a remarkable diversity of root traits in durum wheat whose relationship with adult root features and agronomic performance should be explored.

1. Introduction

The root system of wheat includes two main types, seminal (embryonic) and nodal roots, also known as the crown or adventitious roots [1,2]. Both types of roots play a crucial role in plant growth and are active throughout the whole plant life. Seminal roots, however, could be more important under specific circumstances, like drought conditions, as they penetrate deeper into the soil layers than nodal roots, making water in deep layers accessible to the plant [3,4,5]. Seminal roots also play a capital role during crop establishment, as they are the only roots existing before the emergence of the fourth leaf. Seminal roots include one primary root, two pairs of symmetric roots at each side, and, at times, a sixth central root [6].
The main features of root systems are encompassed under two categories, root system architecture (RSA) and morphology. RSA is related to the whole, or a large subset, of the root system, and may be described as topological or geometric measures of the root shape. Root morphology, as defined by J. Lynch, refers to “the surface features of a single root axis as an organ, including characteristics of the epidermis such as root hairs, root diameter, the root cap, the pattern of appearance of daughter roots, undulations of the root axis, and cortical senescence” [7]. The traits often used to describe wheat roots are total root length, root surface area, root volume, root angle, number of roots, and root diameter [8,9,10].
Roots are difficult to measure readily in natural conditions. Root trait determination has become accessible through the development of phenotyping methods in artificial systems, for instance, gel chambers [11], rolled germination paper [12], clear pots and growth pouches [13], “Termita” chamber and Whatman paper system [14], or growth pouches system [15]. Seminal roots can be phenotyped early and easily compared to the root system of mature plants [16,17], and for this reason, they have been proposed as good candidates to act as proxy traits in wheat [18] and maize [19,20]. Nevertheless, phenotyping these traits could be of interest only if they are useful to predict root growth and functioning in adult plants [21,22]. Indeed, several studies have found useful associations with traits in adult plants of wheat species [23,24,25,26]. For instance, the seminal root angle was correlated with nodal root angle [5,27], and with grain yield under drought conditions [28]. The seminal root number was correlated with thousand kernel weight (TKW) under stress, while the primary root length at the seedling stage was correlated with TKW under wetter conditions [25]. A steeper angle between the outermost roots and a higher root number in wheat seedlings have been linked to a more compact root system with more roots at depth in wheat [11,24,29].
Genotypic variation in root architecture has been reported within genotypes of different crop species [30,31,32], including wheat [13,21,25,33]. The presence of variation for the trait of interest is an essential requirement to improve the adaptability of crops under changing environmental conditions [34].
Local landraces are considered well adapted to the region where they were grown and contain large genetic diversity useful to improve crops like durum wheat [35]. These landraces were replaced by high yielding but more uniform semi-dwarf cultivars, better adapted to modern agriculture. However, scientists are convinced that local landraces still constitute a genetic resource useful to improve commercially valuable traits [36]. It is assumed that root traits enhance response to drought stress [37], but the realization of their contribution to superior grain yield depends on the type of drought and the agro-ecological conditions [38]. A deep rooting ideotype (“steep, cheap, and deep”) was proposed by [39] to optimize water and N acquisition, building on the assumption that deeper rooting genotypes will use water that is beyond reach for shallower rooting genotypes. Modern breeding has caused some shifts in the root system architecture of durum wheat, from shallower and densely rooted systems in landraces of Mediterranean origin to deeper and more evenly distributed systems throughout the soil depth in cultivars worldwide [5].
The current study aims at evaluating the diversity of seminal root traits, including root angle and depth, during early growth of a set of durum wheat genotypes, consisting of modern cultivars and local landraces which are representative of the germplasm adapted to the mostly semi-arid conditions of Algerian cereal-growing regions before and after the advent of modern breeding. The study aims to reveal morphological diversity that could have agronomic relevance and, therefore, interest breeders.

2. Materials and Methods

2.1. Plant Material

We studied thirty-seven genotypes (landraces and modern cultivars), representative of durum wheat (Triticum turgidum ssp. durum Desf.) grown in Algeria. Geographical origins were varied (Algeria, France, Italy, Spain, Tunisia), and included genotypes produced at international breeding programs addressing semi-arid areas, namely the International Maize and Wheat Improvement Center (CYMMIT), the International Center for Agricultural Research in the Dry Area (ICARDA) and the Arab Center for the Studies of Arid zones and Drylands (ACSAD). These genotypes are representative of different periods of agriculture in Algeria, before and after the Green Revolution (Table 1).

2.2. Root Phenotyping

2.2.1. Preparation of Seeds

Twelve seeds of uniform size and healthy aspects were visually selected from each genotype and surface sterilized in a sodium hypochlorite solution (1.25% + one detergent drop, Mistol Henkel Iberica®). Seeds of each genotype were soaked and shaken in the solution for 15–20 min. Then, they were rinsed four times with sterile deionized water, in sterile conditions. Twelve seeds of each genotype were placed in Petri dishes, each with two filter papers soaked with 4 mL of sterile water. Then the Petri dishes were placed in a dark room at 4 °C for four days, and then at 22 °C/18 °C in a growth chamber with a 12 h light/darkness photoperiod for about 16 h.
Finally, the pre-germinated grains were transferred to the rhizo-slide system, described in detail in the next section and Figure S1. The experiment was carried out at the Laboratory of Cellular Biology and Genetics, Department of Biomedicine and Biotechnology of the University of Alcalá, Spain.

2.2.2. The Rhizo-Slide System

The rhizo-slide system was constructed as a sandwich made with glass plate, black cardboard, filter paper, and a black plastic sheet. Sheets of A4-size black cardboard (180 g/m2, www.liderpapel.com) and filter papers were previously sterilized in an autoclave and then soaked in the nutritive solution Aniol [40]. The nutritive solution was prepared by dissolving 0.5550 g of Ca Cl2, 0.8215 g of KNO3, 0.6352 g of MgCl2·6H2O, 0.0165 g of (NH4)2SO, 0.0400 g of NH4NO3 in 100 mL of distilled water, to which 500 μL/L of Plant Preservative Mixture (PPMTM, Plant Cell Technology) at pH 5.8 was added. Each 8 mL was used to prepare 1 L of nutritive solution. Black cardboard with a nick made at the top center was placed on a glass plate with the same dimensions; then the pre-germinated grain (with embryonic part downward) was positioned just below the nick and covered by a filter paper. A black plastic sheet was used to cover the filter paper to ensure obscurity for roots, shifted ~2 cm upwards to allow better contact of the cardboard, and filter paper sheets with the nutritive solution. Two rhizo-slides were confronted to each other by the glass plate side, and the set was placed vertically in a glass box (internal dimensions of 32.2, 22, and 16 cm, length, width, and height) with two liters of the nutritive solution at the bottom, and then secured with two paper clips. Each glass box held 6 glass plates with two rhizoslides each, for a total of 12 seedlings, consisting of two genotypes, 6 seedlings for each (Figure S1). In total, each genotype was replicated 12 times. More details on the system are found in Ruiz et al. (2018) [25].
Once placed in the rhizoslides and the glass boxes, the seedlings were grown in a growth chamber for 7 days at 22/18 °C and 12/12 h photoperiod, day/night. The 37 genotypes were processed in batches of 6. Pre-germinated seeds of each 6 genotypes were placed into six glass boxes, each holding 6 seeds of two different genotypes. A complete batch comprised six boxes, three glass boxes prepared each Monday, and three each Thursday, every week. In total, 7 batches (14 runs) were performed until the experiment was completed (accounting for some seedlings that had to be replicated for various reasons). The set of genotypes for each run was selected randomly.
During the experiment, the boxes were replenished with distilled water every two days, to refill to the initial solution level. At the same time, to minimize seedling failure, each single seedling received 10 mL of the nutritive solution, applied with a pipette, near each seed. On the eighth day, the rhizo-slides were opened and shoots were immediately collected. The fresh roots were scanned using a Canon “LiDE210” scanner at 300 ppi to capture the first image then overlapped roots were manually separated and a second scan was done. The individual plant shoot dry weight (SDW) was obtained after oven-drying at 80 °C for six hours.

2.2.3. Image Analysis

The two images of a rhizo-slide were analyzed using SmartRoot software v.3.32 [41] plugin for ImageJ1.46R (http://imagej.nih.gov/ij/download.html). The first image was used to measure only root angles and the second one to assess the other root traits using manual and semi-automatic SmartRoot procedures. Each root of the seedling was traced, semi-automatically, and then SmartRoot automatically generated the corresponding traits. In total, ten variables from the Smartroot output were recorded for each seedling: total root length (TRL), primary root length (PRL), mean length of the other seminal roots (MRL), total root surface area (Surface), mean root diameter (Diameter), total root volume (Volume), root number (RN), and shoot dry weight (SDW). The root angle was determined for each root with respect to the vertical (90°). From this determination, we extracted the maximum vertical angle (MVA) represented by the root growing with the steepest angle, the least vertical angle (LVA) represented by the root growing with the widest angle, and mean vertical angle (MRA) of all the roots, for each seedling.

2.3. Statistical Analysis

The experiment was considered a completely randomized design, with 12 replicates per genotype. Statistical analyses were performed using the REML (Restricted maximum likelihood) procedure with Genstat 18 [42]. Genotypes were considered as fixed factors and replications were considered as a random factor. The “Genotype” factor (n-1 degrees of freedom) was broken down into a single degree of freedom comparison of landraces vs. cultivars (named “Type” effect), and a “within type” factor (n-2) which corresponds to the variation of genotypes within each type. Multiple means separation was carried out using LSD at 0.05 level, for variables in which the F-value for “Genotypes” was significant. A principal component analysis (PCA) and a hierarchical cluster analysis (HC) were performed using the R package FactoMineR [43]. The hcut function was used for tree cutting levels truncation. The R package Factoextra [44] was employed for extracting and visualizing the results. Broad-sense heritability (h2) was calculated on an entry mean basis using the REML procedure, as follows:
h2 = σ2g/(σ2g + (σ2e/r))
where σ2g is the genotypic variance, σ2e is the error variance and r is the number of replications.

3. Results

3.1. Genotypic Variability

We found remarkable genetic variability for all measured traits, as revealed by the highly significant differences among genotypes in the analyses of variance (Table 2). Significant differences were also found in the “type” comparison for most traits, except for Diameter and RN (Table 2). For the other traits, the mean squares for type were 4 to 12 times larger than those for genotypes.
The means of landraces showed higher or equal mean values compared to cultivars for all traits, except root angle (MRA, LVA, and MVA), which was higher in cultivars (Figure 1). It is worth mentioning that the landrace group presented higher root depth (PRL) than the cultivars.
All traits but SDW were root-related traits so, henceforward all the traits will be referred to generally as root traits unless stated otherwise. All traits (except RN) showed a near-normal distribution (Figure 1) which denotes their polygenic control. A wide range of phenotypic values was observed for most traits (Table 2). The landrace group showed a larger range of variation for TRL, Surface, Volume, and SDW than the cultivars. For the other traits, the cultivars had higher ranges of variation (Tables S1 and S2).
The coefficients of variation (CV) ranged from small values like 5.19 (Diameter) to 24.60 (MRA, Table 2). The exception was the large CV found for MVA, 59.82. When calculated separately for landraces and cultivars, slightly higher CV for most traits were found in landraces compared to cultivars (Table S2). All the traits exhibited high broad sense heritability (h2), ranging from 0.80 for MVA to 0.98 for MRA (Table 2).

3.2. Relationships between Traits

Highly significant correlations were found between most traits (Table 2). TRL, Surface and Volume were highly and positively correlated among them. There were moderate positive correlations between TRL, surface, and Volume, with PRL, SDW, RN, and negative ones with root angle variables (seedlings with higher TRL, Surface, and Volume tended to have steeper root angles). Seedlings with higher RN tended to have roots with thinner root diameter, indicating that there could be some kind of compensation between these traits (more roots with a finer diameter and vice versa). Interestingly, seedlings with higher primary root length produced more shoot biomass. Performing correlations between traits within each group (cultivars and landraces) showed, in general, similar patterns to the correlations performed for the entire dataset (Table S2). The moderate relationship of PRL with MVA and RN disappeared in the landrace group, compared to the cultivars and the whole dataset (Table S2).

3.3. Time Trends of Root Traits

When the genotypic means were plotted against year of release of the genotypes, different trends were observed (Figure 2 and Figure S2), in which, all the traits presented significant regression coefficients except Diameter, RN and PRL (Table S3). This trend was largely influenced by the comparison of landraces vs. cultivars because landraces are older. The trend was positive or negative depending on the trait. Overall, cultivars reduced their seminal root length and developed a shallower root angle compared to landraces (Figure 2). The root surface and volume of root presented the same trend as root length, as they were highly correlated, as mentioned above. MVA and LVA showed the same trend as MRA. No substantial variation was observed for RN, Diameter, and PRL. Regarding the shoot, a remarkable and steady reduction in SDW over the years was detected (Figure 1 and Figure S2).

3.4. Grouping of Genotypes According to Root Traits

The first two principal components explained 69.63% of the total variation (Figure 3A). The first component (46%) was most related to Surface, TRL, Volume, and SDW, with the respective contributions of 20.19, 19.04, 18.16, and 11.51 (Table S4). MRA, LVA, and Diameter had the highest loadings for the second component (PC2). Correlations between these traits are discussed above (Table 2). Thus, the first axis (PC1) was related to root size traits and the second one to root architecture traits.
Genotypes were better distributed along with the first component, as a result of the contrasting position between landraces, many with large positive scores on PC1 (due to their higher root size and shoot weight) and the cultivars, with lower positive or negative scores in PC1, so the discrimination between these two groups was clear (Figure 3B). From the hierarchical classification, which was carried out based on the original data, four groups were created (G1 to G4) (Figure 3B). G1 was mostly formed by landraces. G2 was the largest one and was constituted by cultivars, and two landraces. This group was at a central position in the biplot graph (Figure 3B), presenting close to average values for most traits. G3 was located on the negative side of PC1, contrasting with G1 by having a relative smaller root size. Finally, the last group (G4) was formed by only three genotypes depicted on the negative quadrant, for both PC1 and PC2, having smaller values for both classes of root traits; fine, steeper root angle and reduced root traits related to biomass. This group included landrace Montpellier (genotype 9), which showed a special root system architecture compared to other landraces, with steeper root angle, and lower SDW, closer to two cultivars from Italy and ICARDA.

4. Discussion

The durum wheat collection used in this study was assembled to explore the seminal root variability present in a set of genotypes cultivated in Algeria, with a historical perspective on the possible changes caused by modern breeding. The method chosen enabled data acquisition and processing of 444 single plants, by one person, in two months. Its performance could be easily expanded by increasing the number of boxes and operators. Therefore, it is amenable to the scale needed for the type of studies carried out in plant genetics and breeding. Root number together with root length, the main results of this type of experiment, describe how extensively the seminal axes can potentially explore the rooting volume. These easily measurable traits at an early stage can have agronomic implications. For example, root spread angle is an additional feature whose variation can influence how crops cope with water-limited conditions and/or other environmental constraints, such as high pH, toxic ions, or low nutrient availability [45,46]. The root angular spread at an early growth stage can be used to predict the partitioning of root biomass in the soil profile at the adult plant stage [5,27,28], a feature relevant for water use efficiency in wheat [21,47]. Therefore, artificial systems are efficient at revealing phenotypic (and presumably genetic) variability, but its implications on agronomic performance must be validated later under field conditions.

4.1. Large Genotypic Variation for Seminal Root Traits

An overview of the results found in different studies sheds more light on the actual genetic variation available for seminal root traits, better than any single study. Differences among studies may be partly due to slight differences in the experimental methods, but also to the size and scope of the genetic material used. Nevertheless, some meaningful conclusions can be derived.
We found significant genetic variation for all traits. We found a range of values for the least vertical root angle (LVA) from 20.40° to 61.47°. Multiplying these values by two (range from 40.80° to 122.94°) allows the comparison of our study with others, in which the values of the total opening of the angle of the root system was reported. Our range was superior to those found by others in durum [47] and bread wheat [24,29]. Our wheat genotypes displayed similar low ranges of variation in mean root number as in similar studies in durum [47,48], with a slightly higher mean. In our genotypes, the sixth root was present in about a third of all genotypes, with no significant differences between landraces and cultivars. This is a similar proportion than found in a study of Mediterranean and North-American elite material [47], with the striking difference that in the former study they reported almost absence of the sixth seminal root in native Mediterranean materials [47]. Neither sample of landrace materials was large enough to derive definitive conclusions from these studies, but at least we can say that Algerian landraces are not more likely to lack the sixth seminal root than modern cultivars.
Based on the coefficients of variation, overall, landraces showed higher slightly variability for most traits, especially for root angle, even though the sample size was lower than for cultivars. Previous reports indicate that native Mediterranean landraces are likely to provide additional genetic variability for root architecture [46], particularly in wheat accessions that experienced long-term natural selection in drought-prone environments [49], and in barley [50]. Overall, the Algerian landraces showed sizeable genetic variation for most traits, indicating that they harbor relevant root morphology variation that should be further investigated by geneticists and breeders.

4.2. Classification of Durum Wheat Genotypes According to Root Morphology

Overall, genotypes with higher root length tended to have larger root number, as found in a previous study [47], and a narrower root angle. Other authors [24,51] found no correlation between root angle and root number. Sanguinetti et al. [47] also found no correlation of root angle with other traits and suggested that the root angle was controlled by an independent set of genes. In our study, however, given the negative correlation between MRA and root size traits, we cannot rule out that these two traits are controlled by the same set of genes.
We found that higher root length and Diameter were associated with higher SDW (r of 0.55 and 0.40, respectively, Table 2), suggesting a size effect that affected the whole plant. Rather similar observations were done in the Spanish core collection of tetraploid wheat, but the plant size effect was visible for subsp. dicoccon and turgidum, but not for durum [25]. Correlation between root length and volume and SDW was also found in hexaploid wheat [52]. We found no correlation between RN and MRA, in agreement with previous studies [24,51]. It seems that an overall plant size effect that affects harmonically roots and shoots is common in wheat species.
Our genotypes displayed different seminal root system patterns, from vigorous and steep to a small and shallow root system. These root patterns may be related to phylogenetic relationships, regional origin, and functional plant adaptation to different environments, as indicated in previous studies [53]. There were differences in the length of the seminal roots of single plants. This was made evident by calculating the difference between the length of the primary root (PRL), and the average of the rest (MRL). G2 and G3 had a higher difference between PRL and the mean length of other roots (MRL), compared to groups G1 and G4, which had roots with more similar lengths (Table S5). G2 genotypes combined a significantly longer primary root (Table S5) with the largest difference between it and the other seminal roots (together with G3). This rooting pattern, based on dissimilar growth of the roots, could have an impact on overall soil exploring capacity that should be explored further, particularly its usefulness in semi-arid environments, to access to stored water at deep layers at critical periods (flowering and grain filling), while keeping enough shallow roots to take advantage of in-season precipitations.
Two groups (G1 and G3) showed the highest contrast in the multivariate analysis (Figure 3). G1, with a majority of landraces, displayed a vigorous seminal root system, in contrast with G3, formed entirely by cultivars with small root systems. Our finding was in agreement with the study of a collection of 160-durum wheat landraces [33] in terms of larger seminal root size. This study found that landraces coming from the eastern Mediterranean region (Turkey), the driest and warmest areas considered in the study, showed the largest seminal root size and widest root angle compared to landraces from eastern Balkan countries. The authors claimed that these differences were due to the adaptations of landraces to the contrasting environmental conditions of these two regions. The larger root size and wider root angle from Turkish landraces would allow better exploration of the full soil profile and better water capture. Among the four groups found in this study, no one combined the highest MRA and TRL, comparable to Turkish landraces. Therefore, there could be room for improvement for the root systems of durum wheat for Algeria. Crosses to combine these traits in a single genotype should be devised, and Turkish landraces could be tested in Algerian conditions, to assess their potential.
In our germplasm, the landraces showed on an average narrower angle and higher root size. Previous studies on Mediterranean durum wheat [33] found that the genotypes with the narrowest angle came from the western Mediterranean region and that they also had heavier grains [54,55]. Additionally, it was reported that Triticum turgidum subsp. dicoccon landraces coming from cooler and wetter zones had shallower seminal root systems than those from warmer and drier areas [25]. The subsp. durum landraces, developed in warmer and drier areas, tended to have larger and steeper root patterns than landraces coming from cooler and wetter zones. Accordingly, the root system architecture of the Algerian landraces would indicate adaptation to a warm and dry environment. Other studies have found different root morphologies in apparent adaptation to stressful conditions. For instance, the drought-tolerant bread wheat cv. SeriM82 has a compact root system [21], associated with a limited water use early in the season, facilitating access to stored water later in the reproductive phase. Contrary to our landraces, SeriM82 exhibited less vigorous shoot growth. In contrast with our findings, a study of bread wheat germplasm grown historically in the semi-arid northwestern of China [56] found that breeding caused a narrowing of the seminal root angle, reduced root number, and increase of primary seminal root length. In that study “newer cultivars produced higher yields than older ones only at the higher sowing density, showing that increased yield results from changes in competitive behavior.” This view was confirmed and expanded later [57], confirming that the advantage of new Chinese wheat cultivars came from the attenuation of inter-plant competition and increased plasticity in root morphology. A seminal root architecture with fewer, longer seminal roots with narrower root angle, would overlap less with neighbors, leading to less competition between individuals [58], and these trends agree with the hypothesis of weakening of “selfish” traits [59].
The shift in root morphology observed in Algeria in the step from landraces to modern cultivars does not conform to the scenario described in those works. There was a reduction of overall root length and volume after the advent of modern breeding, which could be consistent with the reduction of inter-plant competition but combined with the widening of the root angle, which does not bode well with that hypothesis. It seems that wheat breeding may have resulted in different trends for root morphology in different parts of the world. This could be the result of the adaptation of Algerian landraces to agronomic conditions different from current agriculture. The difference in rooting patterns between landraces from different geographical areas and cultivars may lie in the agronomic environments in which they were developed. In general, modern durum wheat cultivars were bred under high plant densities [57], whereas landraces were grown in stands with density adapted to the environment. The morphology of Algerian landraces (long seminal roots growing in steep angles) conforms to the “steep, cheap, and deep root ideotype” [60], and could be the result of adaptation to accessing water in deep soil layers. Further studies with adult plants are needed to evaluate if root features of seedlings are maintained when the competition between individuals for root growth is increased (as the seminal and nodal roots require more space and resources than just the seminal roots of the seedlings). A shovelomics experiment is being carried out with the same genotypes, which could elucidate this issue at least for some measurable traits like root angle.
The high SDW of our durum landraces compared to cultivars could be related to the lack of dwarfing genes in the landraces. This hypothesis was already confirmed previously for bread and durum wheat for some height reducing genes [61], which reduced the first seedling leaf growth in Rht genotypes compared with the corresponding tall wheat lines.

4.3. Conclusions and Perspectives

We have found wide genetic variability in a collection of durum wheat genotypes cultivated in Algeria and unraveled a possible historic trend that sheds light on the outcomes of modern breeding. An important issue is to what extent this variability found at the seedling stage can reflect the variability in the field with the same genetic material, more precisely, which traits can be consistent across plant phases (seedling and adult plant), enabling the selection at the early seedling stage. If this relationship is not found, then the room for the testing of seminal root traits is very limited. Experiments to evaluate this relationship are ongoing.
Overall, landraces showed a larger root size and steeper root angle. These two traits could be involved in the adaptation of landraces to water-stressed environments. The dwarfing genes seem to influence biomass partitioning; screening the current germplasm for these genes would elucidate this issue. The root size and shape in our data indicated some independence that would open opportunities to design cultivars with the desired combinations of traits.
Overall, the current genotypes present a diverse root system architecture, from compact deep-rooting to wide shallow one. This opens the opportunity to test the four different root ideotypes found (G1–G4) for functional implications under water and nutrient-limited environments. Based on the above results, we hypothesize that root architecture difference between cultivars, landraces (or steep deep vs. shallow root systems) may result in different strategies of adaptation to the availability of water and nutrients over the soil profile.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4395/10/5/713/s1, Table S1. Mean values and standard errors (12 replications) of the seminal root traits for the 37 durum wheat genotypes. Table S2: Descriptive statistics and correlation coefficients for seedling traits, calculated separately for the cultivar and landrace groups. Table S3: Results of linear regressions of traits over years of release. Table S4: Contribution (%) of the traits to the first two principal components (PC1, PC2), as represented in Figure 3A. Table S5: Means comparison between groups formed by hierarchical clustering for the traits assessed. Figure S1. (A) One-week-old durum wheat seedlings in the rhizoslide system; (B) pictures of two genotypes contrasting for root angle, landrace Gloire de Montgolfier (left) and cultivar Oued El Berd (right); (C) schematic representation of a glass box, holding 6 glass plates, each holding two rhizoslides. Figure S2: Time trend of seminal root traits over the year of release.

Author Contributions

Conceptualization, E.I.; methodology, J.M.G.; formal analysis, R.B. and E.I.; investigation, R.B. and E.I.; resources, A.M.; software, J.M.G.; supervision, J.M.G., A.M., and E.I.; data curation, R.B.; visualization, J.M.G.; writing—original draft preparation, R.B. and J.M.G.; writing—review and editing, R.B., J.M.G., A.M., A.M.C., and E.I.; project administration, A.M.C.; funding acquisition, R.B.; A.M.; A.M.C., and E.I. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by University of Alcalá Project CCGP2017-EXP/007. E.I. and A.M.C. acknowledge funding from the Spanish Ministry of Economy and Competitiveness and the Agencia Estatal de Investigación (Project AGL2016–80967-R), and the European Regional Development Fund.

Acknowledgments

R.B. is a recipient a PhD grant in the framework of Programme National Exceptionel (PNE 2018/2019) funded by Algerian Ministry of Higher Education and Scientific Research.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chochois, V.; Vogel, J.P.; Rebetzke, G.J.; Watt, M. Variation in adult plant phenotypes and partitioning among seed and stem-borne roots across Brachypodium distachyon accessions to exploit in breeding cereals for well-watered and drought environments. Plant Physiol. 2015, 168, 953–967. [Google Scholar] [CrossRef] [Green Version]
  2. Sinha, S.K.; Rani, M.; Kumar, A.; Kumar, S.; Venkatesh, K.; Mandal, P.K. Natural variation in root system architecture in diverse wheat genotypes grown under different nitrate conditions and root growth media. Theor. Exp. Plant Physiol. 2018, 30, 223–234. [Google Scholar] [CrossRef]
  3. Araki, H.; Iijima, M. Deep rooting in winter wheat: Rooting nodes of deep roots in two cultivars with deep and shallow root systems. Plant Prod. Sci. 2001, 4, 215–219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Manske, G.G.B.; Vlek, P.L.G. Root Architecture-Wheat as a Model Plant. In Plant Roots: The Hidden Half, 3rd ed.; Waisel, Y., Eshel, A., Beeckman, T., Kafkafi, U., Eds.; Marcel Dekker: New York, NY, USA, 2002; pp. 249–259. [Google Scholar]
  5. Maccaferri, M.; El-Feki, W.; Nazemi, G.; Salvi, S.; Canè, M.A.; Colalongo, M.C.; Stefanelli, S.; Tuberosa, R. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat. J. Exp. Bot. 2016, 67, 1161–1178. [Google Scholar] [CrossRef] [PubMed]
  6. Esau, K. Plant Anatomy, 2nd ed.; John Wiley: New York, NY, USA, 1965; 767p. [Google Scholar]
  7. Lynch, J. Root architecture and plant productivity. Plant Physiol. 1995, 109, 7–13. [Google Scholar] [CrossRef] [PubMed]
  8. Ahmadi, J.; Pour-Aboughadareh, A.; Fabriki-Ourang, S.; Mehrabi, A.A.; Siddique, K.H.M. Screening wheat germplasm for seedling root architectural traits under contrasting water regimes: Potential sources of variability for drought adaptation. Arch. Agron. Soil Sci. 2018, 64, 1351–1365. [Google Scholar] [CrossRef]
  9. York, L.M.; Slack, S.; Bennett, M.J.; Foulkes, M.J. Wheat shovelomics I: A field phenotyping approach for characterizing the structure and function of root systems in tillering species. BioRxiv 2018, 280875. [Google Scholar] [CrossRef]
  10. Nguyen, V.L.; Stangoulis, J. Variation in root system architecture and morphology of two wheat genotypes is a predictor of their tolerance to phosphorus deficiency. Acta Physiol. Plant. 2019, 41, 109. [Google Scholar] [CrossRef] [Green Version]
  11. Bengough, A.G.; Gordon, D.C.; Al-Menaie, H.; Ellis, R.P.; Allan, D.; Keith, R.; Thomas, W.T.B.; Forster, B.P. Gel observation chamber for rapid screening of root traits in cereal seedlings. Plant Soil 2004, 262, 63–70. [Google Scholar] [CrossRef]
  12. Watt, M.; Moosavi, S.; Cunningham, S.C.; Kirkegaard, J.A.; Rebetzke, G.J.; Richards, R.A. A rapid, controlled-environment seedling root screen for wheat correlates well with rooting depths at vegetative, but not reproductive, stages at two field sites. Ann. Bot. 2013, 112, 447–455. [Google Scholar] [CrossRef] [Green Version]
  13. Richard, C.A.; Hickey, L.T.; Fletcher, S.; Jennings, R.; Chenu, K.; Christopher, J.T. High-throughput phenotyping of seminal root traits in wheat. Plant Methods 2015, 11, 13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. González, J.M.; Friero, E.; Selfa, L.; Froilán, S.; Jouve, N.A. Comparative study of root system architecture in seedlings of Brachypodium spp. using three plant growth supports. Cereal Res. Commun. 2016, 44, 69–78. [Google Scholar] [CrossRef] [Green Version]
  15. Adeleke, E.; Millas, R.; McNeal, W.; Faris, J.; Taheri, A. Variation analysis of root system development in wheat seedlings using root phenotyping system. Agronomy 2020, 10, 206. [Google Scholar] [CrossRef] [Green Version]
  16. Richard, C.; Christopher, J.; Chenu, K.; Borrell, A.; Christopher, M.; Hickey, L. Selection in early generations to shift allele frequency for seminal root angle in wheat. Plant Genome 2018, 11, 170071. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. El Hassouni, K.; Alahmad, S.; Belkadi, B.; Filali-Maltouf, A.; Hickey, L.T.; Bassi, F.M. Root system architecture and its association with yield under different water regimes in durum wheat. Crop Sci. 2018, 58, 2331–2346. [Google Scholar] [CrossRef] [Green Version]
  18. Bai, C.; Liang, Y.; Hawkesford, M.J. Identification of QTLs associated with seedling root traits and their correlation with plant height in wheat. J. Exp. Bot. 2013, 64, 1745–1753. [Google Scholar] [CrossRef] [Green Version]
  19. Tuberosa, R.; Salvi, S.; Sanguineti, M.C.; Landi, P.; Maccaferri, M.; Conti, S. Mapping QTLs regulating morpho-physiological traits and yield: Case studies, shortcomings and perspectives in drought-stressed maize. Ann. Bot. 2002, 89, 941–963. [Google Scholar] [CrossRef] [Green Version]
  20. Tuberosa, R.; Sanguineti, M.C.; Landi, P.; Giuliani, M.M.; Salvi, S.; Conti, S. Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes. Plant Mol. Biol. 2002, 48, 697–712. [Google Scholar] [CrossRef]
  21. Manschadi, A.M.; Christopher, J.; De Voil, P.; Hammer, G.L. The role of root architectural traits in adaptation of wheat to water-limited environments. Funct. Plant Biol. 2006, 33, 823–837. [Google Scholar] [CrossRef] [Green Version]
  22. Paez-Garcia, A.; Motes, C.M.; Scheible, W.R.; Chen, R.; Blancaflor, E.B.; Monteros, M.J. Root traits and phenotyping strategies for plant improvement. Plants 2015, 4, 334–355. [Google Scholar] [CrossRef]
  23. Løes, A.K.; Gahoonia, T.S. Genetic variation in specific root length in Scandinavian wheat and barley accessions. Euphytica 2004, 137, 243–249. [Google Scholar] [CrossRef]
  24. Manschadi, A.M.; Hammer, G.L.; Christopher, J.T.; Devoil, P. Genotypic variation in seedling root architectural traits and implications for drought adaptation in wheat (Triticum aestivum L.). Plant Soil 2008, 303, 115–129. [Google Scholar] [CrossRef]
  25. Ruiz, M.; Giraldo, P.; González, J.M. Phenotypic variation in root architecture traits and their relationship with eco-geographical and agronomic features in a core collection of tetraploid wheat landraces (Triticum turgidum L.). Euphytica 2018, 214, 54. [Google Scholar] [CrossRef]
  26. Li, T.; Ma, J.; Zou, Y.; Chen, G.; Ding, P.; Zhang, H.; Yang, C.; Mu, Y.; Tang, H.; Liu, Y.; et al. Quantitative trait loci for seeding root traits and the relationships between root and agronomic traits in common wheat. Genome 2020, 63, 27–36. [Google Scholar] [CrossRef] [PubMed]
  27. Alahmad, S.; El Hassouni, K.; Bassi, F.M.; Dinglasan, E.; Youssef, C.; Quarry, G.; Able, J.A.; Christopher, J.A. Major root architecture QTL responding to water limitation in durum wheat. Front. Plant Sci. 2019, 10, 436. [Google Scholar] [CrossRef] [Green Version]
  28. Ali, M.L.; Luetchens, J.; Nascimento, J.; Shaver, T.M.; Kruger, G.R.; Lorenz, A.J. Genetic variation in seminal and nodal root angle and their association with grain yield of maize under water-stressed field conditions. Plant Soil 2015, 397, 213–225. [Google Scholar] [CrossRef]
  29. Nakamoto, T.; Oyanagi, A. The direction of growth of seminal roots of Triticum aestivum L. and experimental modification thereof. Ann. Bot. 1994, 73, 363–367. [Google Scholar] [CrossRef]
  30. Masi, C.E.A.; Maranville, J.W. Evaluation of sorghum root branching using fractals. J. Agric. Sci. 1998, 131, 259–265. [Google Scholar] [CrossRef]
  31. Liao, H.; Rubio, G.; Yan, X.; Cao, A.; Brown, K.M.; Lynch, J.P. Effect of phosphorus availability on basal root shallowness in common bean. Plant Soil 2001, 232, 69–79. [Google Scholar] [CrossRef]
  32. Lynch, J.P.; Brown, K.M. Topsoil foraging–an architectural adaptation of plants to low phosphorus availability. Plant Soil 2001, 237, 225–237. [Google Scholar] [CrossRef]
  33. Roselló, M.; Royo, C.; Sanchez-Garcia, M.; Soriano, J.M. Genetic dissection of the seminal root system architecture in Mediterranean durum wheat landraces by genome-wide association study. Agronomy 2019, 9, 364. [Google Scholar] [CrossRef] [Green Version]
  34. El-Beltagy, A.; Madkour, M. Impact of climate change on arid lands agriculture. Agric. Food Secur. 2012, 1, 3. [Google Scholar] [CrossRef] [Green Version]
  35. Nazco, R.; Villegas, D.; Ammar, K.; Pena, R.J.; Moragues, M.; Royo, C. Can Mediterranean durum wheat landraces contribute to improved grain quality attributes in modern cultivars? Euphytica 2012, 185, 1–17. [Google Scholar] [CrossRef]
  36. Lopes, M.S.; El-Basyoni, I.; Baenziger, P.S.; Singh, S.; Royo, C.; Ozbek, K.; Aktas, H.; Ozer, E.; Ozdemir, F.; Manickavelu, A.; et al. Exploiting genetic diversity from landraces in wheat breeding for adaptation to climate change. J. Exp. Bot. 2015, 66, 3477–3486. [Google Scholar] [CrossRef]
  37. Araujo, S.S.; Beebe, S.; Crespi, M.; Delbreil, B.; González, E.M.; Gruber, V.; Lejeune-Henaut, I.; Link, W.; Monteros, M.J.; Prats, E.; et al. Abiotic stress responses in legumes: Strategies used to cope with environmental challenges. Crit. Rev. Plant Sci. 2015, 34, 237–280. [Google Scholar] [CrossRef]
  38. Rao, I.M.; Beebe, S.E.; Polania, J.; Grajales, M.; Cajiao, C.; Ricaurte, J.; García, R.; Rivera, M. Evidence for genotypic differences among elite lines of common bean in the ability to remobilize photosynthate to increase yield under drought. J. Agric. Sci. 2017, 155, 857–875. [Google Scholar] [CrossRef]
  39. Lynch, J.P. Steep, cheap and deep: An ideotype to optimize water and N acquisition by maize root systems. Ann. Bot. 2013, 112, 347–357. [Google Scholar] [CrossRef] [Green Version]
  40. Aniol, A. Induction of aluminum tolerance in wheat seedlings by low doses of aluminum in the nutrient solution. Plant Physiol. 1984, 75, 551–555. [Google Scholar] [CrossRef] [Green Version]
  41. Lobet, G.; Pagès, L.; Draye, X. A novel image-analysis toolbox enabling quantitative analysis of root system architecture. Plant Physiol. 2011, 157, 29–39. [Google Scholar] [CrossRef] [Green Version]
  42. Payne, R.W.; Murray, D.A.; Harding, S.A.; Baird, D.B.; Soutar, D.M. GenStat for Windows Introduction, 12th ed.; VSN International: Hemel Hempstead, UK, 2009. [Google Scholar]
  43. Le, S.; Josse, J.; Husson, F. FactoMineR: An R Package for Multivariate Analysis. J. Stat. 2008, 25, 18. [Google Scholar]
  44. Kassambara, A.; Mundt, F. Package ‘factoextra’. Extr. Vis. Results Multivar. Data Anal. 2017, 76. Available online: http://www.sthda.com/english/rpkgs/factoextra (accessed on 2 March 2020).
  45. Devaiah, B.N.; Nagarajan, V.K.; Raghothama, K.G. Phosphate homeostasis and root development in Arabidopsis is synchronized by the zinc finger transcription factor ZAT6. Plant Physiol. 2007, 145, 147–159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Da Silva, A.; Bruno, I.P.; Franzini, V.I.; Marcante, N.C.; Benitiz, L.; Muraoka, T. Phosphorus uptake efficiency, root morphology and architecture in Brazilian wheat cultivars. J. Radioanal. Nucl. Chem. 2016, 307, 1055–1063. [Google Scholar] [CrossRef]
  47. Sanguineti, M.C.; Li, S.; Maccaferri, M.; Corneti, S.; Rotondo, F.; Chiari, T.; Tuberosa, R. Genetic dissection of seminal root architecture in elite durum wheat germplasm. Ann. Appl. Biol. 2007, 151, 291–305. [Google Scholar] [CrossRef]
  48. Cane, M.A.; Maccaferri, M.; Nazemi, G.; Salvi, S.; Francia, R.; Colalongo, C.; Tuberosa, R. Association mapping for root architectural traits in durum wheat seedlings as related to agronomic performance. Mol. Breed. 2014, 34, 1629–1645. [Google Scholar] [CrossRef] [Green Version]
  49. Robertson, B.M.; Waines, J.G.; Gill, B.S. Genetic variability for seedling root number in wild and domesticated wheats. Crop Sci. 1979, 19, 843–847. [Google Scholar] [CrossRef]
  50. Grando, S.; Ceccarelli, S. Seminal root morphology and coleoptile length in wild (Hordeum vulgare ssp. spontaneum) and cultivated (Hordeum vulgare ssp. vulgare) barley. Euphytica 1995, 86, 73–80. [Google Scholar]
  51. O’Brien, L. Genetic variability of root growth in wheat (Triticum aestivum L.). Aust. J. Agric. Res. 1979, 30, 587–595. [Google Scholar] [CrossRef]
  52. Narayanan, S.; Mohan, A.; Gill, K.S.; Prasad, P.V. Variability of root traits in spring wheat germplasm. PLoS ONE 2014, 9, e100317. [Google Scholar] [CrossRef]
  53. Bodner, G.; Leitner, D.; Nakhforoosh, A.; Sobotik, M.; Moder, K.; Kaul, H.P. A statistical approach to root system classification. Front. Plant Sci. 2013, 4, 292. [Google Scholar] [CrossRef] [Green Version]
  54. Royo, C.; Nazco, R.; Villegas, D. The climate of the zone of origin of Mediterranean durum wheat (Triticum durum Desf.) landraces affects their agronomic performance. Genet. Resour. Crop Evol. 2014, 61, 1345–1358. [Google Scholar] [CrossRef] [Green Version]
  55. Soriano, J.M.; Villegas, D.; Aranzana, M.J.; Del Moral, L.F.G.; Royo, C. Genetic structure of modern durum wheat cultivars and Mediterranean landraces matches with their agronomic performance. PLoS ONE 2016, 11, e0160983. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Zhu, Y.H.; Weiner, J.; Yu, M.X.; Li, F.M. Evolutionary agroecology: Trends in root architecture during wheat breeding. Evol. Appl. 2019, 12, 733–743. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Song, L.; Zhang, D.W.; Li, F.M.; Fan, X.W.; Ma, Q.; Turner, N.C. Drought stress: Soil water availability alters the inter- and intra-cultivar competition of three spring wheat cultivars bred in different eras. J. Agron. Crop Sci. 2010, 196, 323–335. [Google Scholar] [CrossRef]
  58. De Parseval, H.; Barot, S.; Gignoux, J.; Lata, J.; Raynaud, X. Modelling facilitation or competition within a root system: Importance of the overlap of root depletion and accumulation zones. Plant Soil 2017, 419, 97–111. [Google Scholar] [CrossRef] [Green Version]
  59. Weiner, J.; Du, Y.L.; Zhang, C.; Qin, X.L.; Li, F.M. Evolutionary agroecology: Individual fitness and population yield in wheat (Triticum aestivum). Ecology 2017, 98, 2261–2266. [Google Scholar] [CrossRef] [Green Version]
  60. Kembel, S.W.; Cahill, J.F. Independent evolution of leaf and root traits within and among temperate grassland plant communities. PLoS ONE 2011, 6, e19992. [Google Scholar] [CrossRef]
  61. Ellis, M.H.; Rebetzke, G.J.; Chandler, P.; Bonnett, D.; Spielmeyer, W.; Richards, R.A. The effect of different height reducing genes on the early growth of wheat. Funct. Plant Biol. 2004, 31, 583–589. [Google Scholar] [CrossRef]
Figure 1. Boxplots for root traits for the cultivar (red) and landrace (blue) groups. Horizontal lines splitting the boxes indicate the median values; box limits indicate the 25th and 75th percentiles; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles; outliers are represented by dots. Variable names coded as in Table 2. Genotype mean values are in Table S1.
Figure 1. Boxplots for root traits for the cultivar (red) and landrace (blue) groups. Horizontal lines splitting the boxes indicate the median values; box limits indicate the 25th and 75th percentiles; whiskers extend 1.5 times the interquartile range from the 25th and 75th percentiles; outliers are represented by dots. Variable names coded as in Table 2. Genotype mean values are in Table S1.
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Figure 2. Time trends for total root length (TRL) and mean root angle (MRA) in seedlings of 37 durum wheat varieties. Yellow symbols correspond to landraces; blue symbols correspond to cultivars. The coefficients of determination (R2) of the regression lines are indicated in each graph.
Figure 2. Time trends for total root length (TRL) and mean root angle (MRA) in seedlings of 37 durum wheat varieties. Yellow symbols correspond to landraces; blue symbols correspond to cultivars. The coefficients of determination (R2) of the regression lines are indicated in each graph.
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Figure 3. Biplot of the first two principal components (A) and dendrogram resulting from hierarchical clustering (B) based on seedling traits for 37 durum wheat genotypes. Ellipses in (A) encompass the individuals according to the clustering presented in (B). Yellow symbols correspond to landraces; blue symbols correspond to cultivars. Genotypes coded with numbers as in Table 1.
Figure 3. Biplot of the first two principal components (A) and dendrogram resulting from hierarchical clustering (B) based on seedling traits for 37 durum wheat genotypes. Ellipses in (A) encompass the individuals according to the clustering presented in (B). Yellow symbols correspond to landraces; blue symbols correspond to cultivars. Genotypes coded with numbers as in Table 1.
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Table 1. Name, type of cultivar, origin, and year of release of 37 genotypes of durum wheat used in the experiment.
Table 1. Name, type of cultivar, origin, and year of release of 37 genotypes of durum wheat used in the experiment.
GenotypeType/PedigreeOriginYear of Release
1BeliouniLandraceAlgeria1958
2Bidi 17LandraceAlgeria1930
3Djenah KhotifaLandraceNorth Africa1955
4Gloire de MontgolfierLandraceAlgeria1960
5Guemgoum R’ khemLandraceAlgeria1960
6Hedba 3LandraceAlgeria1921
7LangloisLandraceAlgeria1930
8Mohammed Ben Bachir (MBB)LandraceAlgeria1930
9MontpellierLandraceAlgeria1965
10Oued Zenati 368LandraceAlgeria1936
11Acsad 65Gerardo-vz-469/3/Jori-1//Nd-61-130/LeedsACSAD1984
12Altar 84Ruff/Flamingo,mex//Mexicali-75/3/ShearwaterCYMMIT1984
13Ammar 6Lgt3/4/Bicre/3/Ch1//Gaviota/StarkeICARDA2010
14BousselemHeider//Martes/Huevos de oroICARDA2007
15BoutalebHedba 3/OfantoAlgeria2013
16CapeitiEiti*6/Senatore-CappelliItaly1940
17Chen’sShearwater(sib)/(sib)Yavaros-79CYMMIT1983
18CiccioAppulo/Valnova(f6)//(f5)Valforte/PatrizioItaly1996
19CirtaHedba-3/Gerardo-vz-619Algeria2000
20CorePlatani/GianniItaly2008
21GTA DurCrane/4/Polonicum PI185309//T.glutin enano/2* Tc60/3/GllCIMMYT1972
22INRAT 69Mahmoudi/(bd-2777)KyperoundaTunisia1969
23KoriflaDurum-dwarf-s-15/Crane//GeierICARDA1987
24MansourahBread wheat/MBBAlgeria2012
25MassinissaOfanto/BousselemAlgeria2012
26MegressOfanto/Waha//MBBAlgeria2007
27Mexicali 75Gerardo-vz-469/3/Jori(sib)//Nd-61-130/LeedsCIMMYT1975
28OfantoAdemelio/AppuloItaly1990
29Oued El BerdGta dur/OfantoAlgeria2013
30PolonicumTriticum polinicum/Zenati boulette 1953-58France1973
31SahellCit”s”/4/Tace/4*tc//2*zb/wls/3/aa”s’’/5/Ruff”s”/Albe”s”CYMMIT1977
32SimetoCapeiti-8/ValnovaItaly1988
33SitifisBousselam/OfantoAlgeria2011
34VitronTurkey77/3/Jori/Anhinga//FlamingoSpain1987
35WahaPlc/Ruff//Gta’s/3/RoletteICARDA1986
36WahbiBidi 17/Waha//Bidi 17Algeria2002
37ZB × FgZb/fg‘‘s’’ lk/3/ko 120/4/Ward cs 10604Algeria1983
*: Backcross.
Table 2. Descriptive statistics, broad sense heritability (h2), ANOVA summary, and correlation coefficients for the root traits assessed in 37 durum wheat cultivars.
Table 2. Descriptive statistics, broad sense heritability (h2), ANOVA summary, and correlation coefficients for the root traits assessed in 37 durum wheat cultivars.
Descriptive Statistics ANOVACorrelation
TraitsMinMeanMaxCVh2GenotypeTypeTRLSurfaceVolumeDiameterPRLSDWMRALVAMVARN
TRL (cm)54.2898.49137.2213.510.90******1******ns*****************
Surface (cm2)8.2516.7724.8214.740.90******0.951***************ns******
Volume (cm3)0.09620.23260.372117.030.90******0.830.971************ns*****
Diameter (cm)0.04470.05380.06205.190.87***ns0.080.380.591***************
PRL (cm)14.3226.5132.0610.760.90******0.550.550.520.171***ns*****ns
SDW (g)5.7014.7223.5018.660.94******0.550.630.640.400.581ns***ns
MRA (°)1.2030.3645.6924.600.98******−0.39−0.32−0.230.20−0.010.001******ns
LVA (°)20.4042.7161.4717.810.92******−0.28−0.23−0.180.120.080.010.761***ns
MVA (°)0.0014.1043.4959.820.80******−0.25−0.20−0.150.12−0.27−0.130.620.251**
RN (no.)4.005.326.009.130.87***ns0.370.320.26−0.22−0.010.06−0.090.02−0.141
*, **, ***: sources of variation in the analyses of variance or correlation coefficients significant at p < 0.05, 0.01, and 0.001, respectively. TRL: Total root length, Surface: total root surface area, Volume: Total root volume, Diameter: mean root diameter, PRL: Primary root length, SDW: Shoot dry weight, MRA: Mean root angle, LVA: Least vertical angle, MVA: Maximum vertical angle, RN: Root number.

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Boudiar, R.; González, J.M.; Mekhlouf, A.; Casas, A.M.; Igartua, E. Durum Wheat Seminal Root Traits within Modern and Landrace Germplasm in Algeria. Agronomy 2020, 10, 713. https://doi.org/10.3390/agronomy10050713

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Boudiar R, González JM, Mekhlouf A, Casas AM, Igartua E. Durum Wheat Seminal Root Traits within Modern and Landrace Germplasm in Algeria. Agronomy. 2020; 10(5):713. https://doi.org/10.3390/agronomy10050713

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Boudiar, Ridha, Juan M. González, Abdelhamid Mekhlouf, Ana M. Casas, and Ernesto Igartua. 2020. "Durum Wheat Seminal Root Traits within Modern and Landrace Germplasm in Algeria" Agronomy 10, no. 5: 713. https://doi.org/10.3390/agronomy10050713

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