MétaCan
Menu
Back to cohort
Record W2808000859 · doi:10.22077/escs.2017.595.1127

تأثیر تنش شوری و روشهای مختلف پرایمینگ بذر بر سبز شدن و خصوصیات گیاهچه کینوا (Chenopodium quinoa Willd.)

2018· article· fa· W2808000859 on OpenAlexaboutno aff
معصومه صالحی, ولی سلطانی, فرهاد دهقانی

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languagefa
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsChenopodium quinoaChenopodiumChenopodiaceaeBotanyBiologyHorticultureChemistry

Abstract

fetched live from OpenAlex

]Introduction The main limiting factor for food security in Iran and world is water qualitative and quantitative. Agriculture sector is the main consumer of water and more vulnerable section from water crisis. In order to improve food security calorie requirement of growing population should be provided from nonsaline water resources. Quinoa (Chenopodium quinoa) is diploeid, allotetraploied, C3 and facultative halophyte from Amaranthace family and categorized in pseudo cereal group. This plant has cultivated 5000 years in Ands, and the highest cultivated area is in Bolivia near salt flats. This plant can grow successfully in different countries such as, Europe countries, USA, Canada, Africa, Morocco, Pakistan and India. Protein content is between 13.81-21.9% and flour is gluten free and provides all essential amino acid of human. Because of high potential of quinoa for providing human calories and high salt and drought tolerance it could be considered for saline and marginal area. Quinoa was selected for cultivation with saline water because of salt tolerance and economic production with saline water which are not use for conventional crop. The main problem of quinoa is emergence and stand establishment with saline water. The aim of this study is evaluation of salinity stress on plant emergence and priming effect of emergence improvement under saline condition. Materials and methods In order to evaluate salinity stress on emergence and establishment of quinoa an experiment was conducted based on CRD design with 5 levels of salinity (0, 4, 8, 12 and 16 dS/m) with four replication in soil and cocopit. Emergence recorded daily and finally plant height and dry weight was measured. Two piece and modified discount function model was fitted to emergence percent. In order to improve emergence under saline condition an experiment was conducted with three treatments (Gibberlic acid (10 ppm), H2O and Ascorbic acid (3 ppm)) and four levels of salinity (0, 4 and 8 dS/m) with three replications based on CRD design with factorial arrangement. Coefficent of equation was estimated with SAS software based on NLIN and REG procedure. Results and discussion Result showed that quinoa is sensitive in emergence stage is depends to substrate and 50 % of emergence reduction in soil and cocopit occurred at 6.35 and 15.04 dS/m. Threshold in soil and cocopit was 9.52 and 0.03 dS/m. Emergence rate and percentage of seeds under saline condition in cocpit did not have significant differences up to 12 dS/m and salinity above 4 dS/m delay emergence. Seedling emergence index under nonsaline condition was 0.96 but at 4, 8 and 12 dS/m in soil had 24, 48 and 84 % reduction. Seedling height in soil and cocopit at 12 dS/m reduced 91 and 30 %, respectively. Priming could not improve quinoa emergence although hydroprime improve emergence to some extent (8%). Quinoa is sensitive to salinity at seedling stage but after this stage could produce 2-3 t ha-1 seed yield with 15 dS/m saline water in Yazd. Since, in saline area farmers don’t have fresh water and quinoa is sensitive to saline water during emergence and early establishment. It would be better use transplanting method or not coverage of seed with soil.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
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 score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0080.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0840.001

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 head0.268
GPT teacher head0.520
Teacher spread0.252 · 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.

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicSeed and Plant BiochemistryFrench-language works237,207