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Record W4311231255 · doi:10.5539/jas.v15n1p55

Introduction of Nutrient Solution of Silicon Sulfonated With Elemental Sulfur S8 for the Mini-tuber Production of Potato Cultivars from in vitro Micro-tuber

2022· article· en· W4311231255 on OpenAlexvenueno aff
Davoud Hassanpanah, Sayad Parastar Anzabi, Parviz Shirinzadeh Giglou, Ahmad Mousapour Gorji, Yousef Jahani Jelodar, Elham Parastar Anzabi, Hossein Hassanpanah

Bibliographic record

VenueJournal of Agricultural Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSilicon Effects in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarNutrientSulfurGreenhouseHorticultureAgronomyBiologyChemistry

Abstract

fetched live from OpenAlex

This study with aims to investigate the effect of nutrient solution sulfonated silicon with elemental sulfur S8 in the mini-tuber production of potato cultivars in the greenhouse of Potato Research Station of Ardabil Province, Iran was done during April till August of 2022. This experiment was carried out based on the factorial experimental design in two factors and three repetitions. The first factor with two levels including: 1. foliar spraying with nutrient solution sulfonated silicon with elemental sulfur S8 and 2. Control (without nutrient solution sulfonated silicon with elemental sulfur S8) and the second factor consists of micro-tubers of five cultivars in the name of Agria, Jelli, Anosha, T297 and Sheida. The foliar spraying with S-8 nutrient solution was done in five stages of vegetative growth, plant growth and development, tuberization, flowering and tuber development and tuber bulking. The results of analysis of variance showed that there was a significant difference between the levels of nutrient solution, cultivars and the interaction between nutrient solution and cultivars in terms of mini-tuber number and weight per square meter, mini-tuber number per plant and plant height. Anosha cultivar had the highest values in terms of mini-tuber number and weight per square meter and tuber number per plant traits by using nutrient solution and was placed in the group A. The Agria, Jelli, Sheida and T297 cultivars were placed in the group B and had the highest amount by using nutrient solution in terms of these characteristics. The Agria, Jelli and Anosh cultivars had the highest plant height by using nutrient solution. Based on the results, using sulfonated silicon nutrient solution with elemental sulfur S8 causing an increase mini-tuber number per square meter (515 numbers), mini-tuber number per plant (5 numbers), mini-tuber weight per square meter (47 kg) and plant height (92 cm) became.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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
Published2022
Admission routes1
Has abstractyes

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