Symbiotic interactions between a newly identified native mycorrhizal fungi complex and the endemic tree <i>Argania spinosa</i> mediate growth, photosynthesis, and enzymatic responses under drought stress conditions
Bibliographic record
Abstract
Water deficit or drought is the most important abiotic stress limiting plant growth performance and plant community development; this is typical in the Mediterranean area where plants are often severely and permanently water limited. Such is the case of the argan tree (Argania spinosa (L.) Skeels), one of the tree species most affected by desertification and global warming. To advance knowledge on how this tree can withstand drought stress, inoculation with a native complex of arbuscular mycorrhizal fungi (AMF), composed mainly of the genus Glomus, was studied in connection with a set of growth and physiological parameters. Under controlled conditions, inoculated and non-inoculated argan seedlings were grown for 3 months under three water regimens: 25%, 50%, and 75% relative to the field capacity of used soil substrate. The results showed that the argan tree had different growth abilities to develop and withstand the various applied water limitations. The AMF complex stimulated the growth and mineral nutrition of argan seedlings under the different imposed levels of water deficiency. Relative water content (RWC) in leaves, water potential, and stomatal conductance in argan leaves showed a general improvement in inoculated seedlings compared to non-inoculated ones. Soluble sugar and proline contents significantly increased in non-inoculated seedlings compared with inoculated seedlings under water-limiting conditions (25%). Similarly, oxidative enzyme (catalase, peroxidase, superoxide dismutase) activity increased significantly in drought-stressed seedlings. Non-inoculated seedlings showed the highest accumulation of these enzymes. Moreover, mycorrhizal symbiosis establishment positively correlated with argan tree seedlings in terms of growth, mineral nutrition, soluble sugar and proline contents, and enzymes activities. The main results from the current study suggest that AMF improve the ability of A. spinosa to tolerate drought by enhancing mineral nutrition and the transport of high levels of water by enhancing the RWC and water potential in leaves. Finally, the alleviation of the destructive effects of reactive oxygen species was modulated by enzymatic scavenging activity. Hence, the use of AMF in the technical process of argan seedlings production is highly recommended in different ecofriendly restoration strategies, with the aim of producing high quality seedlings capable of tolerating drought stress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".