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Record W2017424391 · doi:10.5539/jps.v3n2p45

Induction of Flowering by Girdling in Jamun cv. Konkan Bahadoli

2014· article· en· W2017424391 on OpenAlexvenueno aff
P. M. Haldankar, N. V. Dalvi, YR Parulekar, K. E. Lawande

Bibliographic record

VenueJournal of Plant Studies · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGirdlingBark (sound)HorticultureBiologyRandomized block designSyzygiumBotany

Abstract

fetched live from OpenAlex

Jamun (Syzygium cuminii) is an underexploited fruit crop gifted with abundant nutritional and medicinal values. In spite of its greater economic value, farmers are reluctant to establish jamun orchards as flowering is the major constraint. The prebearing age of jamun is fairly long even in grafts. It takes about 6 to 7 years for commencement of flowering and many times this period is extended up to 10 years. An experiment was therefore undertaken under two distinct locations having different weather conditions to study the efficiency of girdling for induction of flowering in jamun under Maharashtra conditions. The experiment was conducted in Randomized Block Design with five treatments viz. T1- Deep cut on secondary branches, T2 – Deep cut on tertiary branches, T3- Removal of 3 mm bark on secondary branches, T4- Removal of 3 mm bark on tertiary branches and T5- Control (No girdling). Results indicated that girdling was beneficial in jamun for induction of flowering, greater flowering intensity, more number of flowers and fruits per branchlet, reduced period from flowering to harvesting and higher yield as compared to control plants. Tertiary branches were found to be more appropriate location for girdling than secondary branches. Girdling with deep cut without removal of bark was more beneficial than the removal of bark. T2 was the best treatment of girdling in jamun.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.111

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 head0.034
GPT teacher head0.242
Teacher spread0.209 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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