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Record W4362581520 · doi:10.3390/ijms24076620

Cell-Free Supernatant (CFS) from Bacillus subtilis EB2004S and Lactobacillus helveticus EL2006H Cultured at a Range of pH Levels Modulates Potato Plant Growth under Greenhouse Conditions

2023· article· en· W4362581520 on OpenAlexaff
Levini A. Msimbira, Judith Naamala, Sowmyalakshmi Subramanian, Donald L. Smith

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsLactobacillus helveticusBacillus subtilisGreenhousePlant growthLactobacillusBiologyChemistryFood scienceMicrobiologyBacteriaBotanyFermentation

Abstract

fetched live from OpenAlex

Agriculture involving industrial fertilizers is another major human made contributing factor to soil pH variation after natural factors such as soil parent rock, weathering time span, climate, and vegetation. The current study assessed the potential effect of cell-free supernatant (CFS) obtained from Bacillus subtilis EB2004S and Lactobacillus helveticus EL2006H cultured at three pH levels (5, 7, and 8) on potato (var Goldrush) growth enhancement in a greenhouse pot experiment. The results showed that CFSs obtained from B. subtilis EB2004S and L. helveticus EL2006H cultured at pH 5 significantly improved photosynthetic rates, stomatal conductance, root fresh weight, and whole plant fresh weight. interactive effects of pot pH and that of CFSs obtained from pH 5 influenced chlorophyll, plant height, and shoot and whole plant fresh weight. Moreover, treatment 52EB2004S~0.4% initiated early tuberization for potato grown at pH 7 and 8. Potato grown at pH 5, which received a 72EB2004S~0.4% CFS treatment, had greater whole plant fresh and dry weight than that treated with L. helveticus EL2006H CFS and a positive control. Taken together, the findings of this study are unique in that it probed the effect of CFS produced under differing pH conditions which revealed a new possibility to mitigate stresses in plants.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.034
GPT teacher head0.260
Teacher spread0.226 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2023
Admission routes1
Has abstractyes

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