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Record W2170693538 · doi:10.5539/jps.v3n1p91

Effect of Size of Polybag on Survival and Growth of Mango Grafts

2014· article· en· W2170693538 on OpenAlexvenueno aff
P. M. Haldankar, YR Parulekar, M. M. Kulkarni, K. E. Lawande

Bibliographic record

VenueJournal of Plant Studies · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEpicotylSproutingRandomized block designHorticultureBiologyGermination

Abstract

fetched live from OpenAlex

Mango is the most important fruit crop of India’s western coast. Mango is commercially propagated by epicotyl grafting. Presently, epicotyl grafts are prepared in 6” × 8” poly bags which restrict root growth and such grafts take longer time for establishment in the field and growth is reduced. Hence, experiment was conducted for optimizing the size of poly bag for cv. Alphonso and Kesar for vigorous growth of epicotyl grafts. The investigation was undertaken in Randomized Block Design with four treatments viz. T1-10” × 14” bags (Alphonso grafts), T2-10” × 14” bags (Kesar grafts), T3-6’’ × 8’’ bags (Alphonso grafts), T4-6’’ × 8’’ bags (Kesar grafts) replicated five times with a unit of 200 grafts per treatment per replication. The sprouting and survival percentage was not affected by size of bags. Among all the treatments, the larger size bags of T1 and T2 improved the vigour of grafts remarkably by producing longer tap root, greater root spread and more number of secondary roots with increased plant height, girth at collar, number of leaves per graft and plant spread over the small sized bags in treatment T3 and T4. The RGR recorded in T1 and T2 was better than that of T3 and T4.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.117

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 science0.0000.000
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 head0.015
GPT teacher head0.243
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

Citations4
Published2014
Admission routes1
Has abstractyes

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