MétaCan
Menu
Back to cohort

Seed germination behaviour of Quercus leucotrichophora (Banj oak) in Western Himalaya

2022· article· en· W4313068688 on OpenAlexaff
Sweata Bisht, L. S. Kandari, Vinod K. Bisht, Tripti Negi, Pragnesh Patel

Bibliographic record

VenueIndian Journal of Forestry · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsGerminationSowingSeedlingBiologyHorticulturePopulationBotanyAgronomy

Abstract

fetched live from OpenAlex

Quercus leucotrichophora A.Camus (Banj oak) is one of the keystone species in the mid-elevation forests across western and central Himalaya. Its regeneration in many parts is reported to be poor due to low germination and seedling emergence. Present study aims to investigate the germination behaviour of Quercus leucotrichophora. Seeds were collected from 5 different sites and sown in polybags under open, poly-house and shade-net-house conditions. Seed germination started in 20 days and was completed in 92 days. Higher seed germination was observed in poly-house conditions (76.66%-82.66%) followed by shade-net-house conditions (68.23-76.66%), while, minimum germination was observed in seeds placed under open conditions (61.66%-74.33%). Mean Germination Time was found rapid in poly-house conditions (8.4-10.13) followed by shade-net house conditions (8.79-12.71) and open conditions (20.39-24.66). Among all the sites, higher germination was recorded for the seeds collected from the mid altitude regions (1300-1400 m asl). A significant positive correlation (P<0.05) between seed size class with cumulative germination percentage was also noticed. The findings of the present study indicated that, site of seed collection can play a crucial role in seed germination. Thus, for raising quality planting material of Q. leucotrichophora, seed collection should be done from specific habitats that ultimately help in restoring the declining population.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueIndian Journal of ForestrySame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207