1. Introduction
Recently, there is increasing interest in forage sorghum grown in desert areas. Some of the advantages cultivating this crop include high water use efficiency than other forage crops, higher heat and drought tolerance, versatility, and potentially high-quality nutrients for cows, sheep, and camels [
1]. Compared to many forages, sorghum can produce more biomass and good feed quality if crop management practices are well optimized. In marginal and desertic areas, sorghum production is constrained by various abiotic stresses especially salt stress. Therefore, improved crop management and new varieties with increased tolerance to salinity can significantly increase their yields. However, the sorghum genera are very diverse genetically, phenotypically, and geographically and relatively few recognized species have been evaluated for potential forage selection.
Root growth and developmental flexibility may allow breeders to create crops with more resistant root system designs to abiotic stresses such as salt stress. However, this area remains underexplored in crop production systems. Thus, in this paper, we investigate the possible impact of diverse root characteristics on sorghum yield and performance under salt stress.
2. Materials and Methods
In this study, thirteen local sorghum varieties were used. The plants were cultivated in Laayoune, Morocco, under medium saline conditions (EC of 7884.5 S/cm) during the spring season of 2021 as part of an ongoing salt-tolerant forage germplasm phenotyping and genotyping project. Sampling for relative water content (RWC), chlorophyll content Chl), electrolyte leakage (EL), and total soluble carbohydrate (TSC) content was carried out during harvest. For root sampling, plants were removed, and roots scraped carefully to minimize damage at the soft dough stage when sorghum is apparently at the silage harvest maturity stage. The root data were processed for correlation analysis with other tested physiological parameters on SPSS (v.16, SPSS Inc., Chicago, IL, USA).
4. Discussion
The above-ground phenotypic traits measured in this study may be utilized as credible predictors of salt tolerance and forage yield. In terms of the physiological consequence of cellular water deficiency, the RWC, for example, is one of the most relevant markers of plant water status [
2]. As a result, it can predict sorghum water status in terms of cellular hydration while accounting for the effects of both leaf water potential and osmotic adjustment. The preservation of considerably greater RWC in some sorghum varieties can be attributed to the resistance to salt-induced physiological drought, which is consistent with our earlier findings that high RWC was related to salt resistance [
3]. Chlorophyll (a and b) functions as an intermediate in the transition of absorbed solar energy and its action in photosynthesis and organic compound production [
4]. As a result, it can be utilized as a plant health indicator under stressful conditions. The ability of sorghum varieties to maintain relatively higher total Chl contents reflects their ability to maintain higher photosynthetic efficiency, organic compound accumulation, and growth under salt stress, as evidenced by relatively higher digestible sugar contents, leaf area, and plant height in most of the varieties. This is also evidenced by a strong positive correlation between Chl, height, RWC, and soluble carbohydrate contents. The EL reflects the stability index of cellular membranes. Here, we observe a negative correlation between RWC, Chl, height, and leaf area with EL, indicating that salinity could not only damage membranes but also limit growth and photosynthetic capacity. Additionally, a negative correlation with all root parameters indicates that EL can be a reliable phenotypic marker for salt sensitivity in large sorghum varieties.
Soluble carbohydrates not only serve as vital nutritive molecules, but they can also serve as significant osmolytes in plants, helping to promote osmotic adjustment [
5]. A substantial correlation between soluble carbohydrates and RWC suggests that high soluble carbohydrate levels in sorghum had a favorable effect in water absorption and retention, which may boost photosynthesis and plant development. Roots play a vital role in plant response to stress and production. However, partly due to the difficulties in viewing them throughout the plant’s life cycle, they have received less attention than other organs. In this case, we see structural variety in traits such as MRL, LRN, MRV, and MRA in a sorghum population and various correlations with salt performance indices. This demonstrates the presence of a significant amount of flexibility in sorghum root system architecture (RSA) during salt stress. The positive connection between LRN and RWC suggests that the design in sorghum varieties with the greatest LRN and the shortest MRL may be related to sorghum salt tolerance. As a result, they might be used to simulate sorghum with more efficient roots to improve tolerance and yield.
5. Conclusions
In this study, we see structural variety in root traits such as MRL, LRN, MRV, and MRA. This demonstrates the presence of a significant level of flexibility in sorghum RSA during salt stress. The positive connection between LRN and RWC suggests that the design in varieties with the greatest LRN and the shortest MRL may be related to sorghum salt tolerance and yield. As a result, they might be a target for developing and modeling sorghum with more efficient roots to improve tolerance and yield.
Author Contributions
Conceptualization, E.A., A.N., A.H. and A.O.; methodology, E.A., A.N. and K.P.D.; data collection, E.A., D.S.A., K.L. and A.N.; writing, editing, and reviewing, E.A., A.N., A.H., L.K., A.O., G.C. and M.E.G.; project administration, A.N.; funding acquisition, A.N. All authors have read and agreed to the published version of the manuscript.
Funding
This research is funded by OCP Phosboucraa Foundation, grant number FPB_SPA005_2020.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Acknowledgments
The authors acknowledge the OCP Phosboucraa Foundation for funding this project. Appreciation is extended to farmers for providing their farmlands to conduct the research trials and all field assistants.
Conflicts of Interest
The authors declare no conflict of interest.
References
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Table 1.
Means of tested root parameters.
Table 1.
Means of tested root parameters.
VARIETY | MRL 1 | MRV | MRA | LRN | LRL |
---|
1 | 61.56 | 11.82 | 12.74 | 77 | 74.74 |
2 | 73.91 | 26.70 | 13.63 | 112 | 144.37 |
3 | 114.30 | 24.09 | 23.40 | 248 | 355.34 |
4 | 57.27 | 13.42 | 4.24 | 95 | 92.37 |
5 | 72.37 | 15.38 | 17.21 | 193 | 134.32 |
6 | 133.20 | 9.731 | 6.00 | 104 | 161.33 |
7 | 48.05 | 26.49 | 1.79 | 63 | 70.68 |
8 | 95.16 | 23.84 | 10.94 | 124 | 177.64 |
9 | 60.85 | 12.67 | 7.84 | 108 | 158.32 |
10 | 60.46 | 18.18 | 10.60 | 142 | 140.86 |
11 | 29.36 | 5.80 | 18.43 | 77 | 112.93 |
12 | 18.84 | 21.28 | 123.00 | 129 | 289.18 |
13 | 121.10 | 31.15 | 33.99 | 247 | 301.49 |
Table 2.
Pearson correlation coefficients of tested parameters.
Table 2.
Pearson correlation coefficients of tested parameters.
| RWC | Height | EL | Chl | LL | LW | TSC | MRL | LRL | MRV | MRA | LRN | DW |
---|
RWC 1 | 1 | | | | | | | | | | | | |
Height | 0.184 | 1 | | | | | | | | | | | |
EL | −0.049 | −0.118 | 1 | | | | | | | | | | |
Chl | 0.083 | 0.400 * | −0.126 | 1 | | | | | | | | | |
LL | 0.430 ** | 0.520 ** | −0.056 | 0.360 * | 1 | | | | | | | | |
LW | 0.388 * | 0.387 * | −0.092 | 0.142 | 0.724 ** | 1 | | | | | | | |
TSC | 0.186 | 0.255 | −0.096 | 0.16 | 0.571 ** | 0.662 * | 1 | | | | | | |
MRL | 0.016 | 0.063 | −0.465 ** | 0.107 | 0.073 | 0.091 | 0.053 | 1 | | | | | |
LRL | 0.439 * | 0.042 | −0.224 | 0.105 | 0.014 | 0.012 | 0.144 | 0.843 ** | 1 | | | | |
MRV | 0.071 | 0.102 | −0.443 ** | 0.05 | 0.079 | 0.13 | 0.044 | 0.943 ** | 0.843 ** | 1 | | | |
MRA | 0.101 | 0.036 | −0.358 * | 0.087 | 0.157 | 0.207 | 0.103 | 0.901 ** | 0.775 ** | 0.794 ** | 1 | | |
LRN | 0.568 ** | 0.023 | −0.343 * | 0.091 | 0.03 | 0.034 | 0.12 | 0.954 ** | 0.920 ** | 0.900 ** | 0.909 ** | 1 | |
DW | 0.282 | 0.834 ** | −0.532 * | 0.301 | 0.654 ** | 0.417 * | 0.389 | 0.523 ** | 0.531 ** | 0.239 | 0.516 ** | 0.351 * | 1 |
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