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Record W3206785413 · doi:10.1139/cjfr-2020-0351

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

2021· article· en· W3206785413 on OpenAlexvenueno aff
Said El Mrabet, Hanane Dounas, Adnane Bargaz, Robin Duponnois, Lahcen Ouahmane

Bibliographic record

VenueCanadian Journal of Forest Research · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsInoculationBiologySugarHorticultureGlomusDrought toleranceProlineStomatal conductanceBotanyPhotosynthesisFood science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.291
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

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