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Record W4362702288 · doi:10.5539/jas.v15n5p67

Impact of Salinity on the Radiation Use Efficiency of Quinoa (Chenopodium quinoa Willd.) in Semi-arid Area in Tunisia

2023· article· en· W4362702288 on OpenAlexvenueno aff
Mourad Rezig, Neserine Ben Yahia, Mohamed Allani, Hassouna Bahrouni, Mohamed Ali Ben Abdallah, Ali Sahli

Bibliographic record

VenueJournal of Agricultural Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsAnthesisPhotosynthetically active radiationChenopodium quinoaSalinityHorticultureAgronomyBotanyBiologyPhotosynthesisCultivar

Abstract

fetched live from OpenAlex

The impact of three level of salinity (T0 = 1.2 dS m-1, T1 = 9.2 dS m-1 and T2 = 18 dS m-1) on photosynthetically active radiation intercepted (PARabs), Radiation Use Efficiency at pre-anthesis and post-anthesis (RUEPR and RUEPS), Radiation Use Efficiency of total dry biomass (RUETDM) and Radiation Use Efficiency of Grain Yield (RUEGY) at quinoa harvest were investigated during the growing season (2015). The RUE pre-anthesis (from transplanting to anthesis) has registered a decrease of 10.8 and 15.8% respectively in T1 (RUEPR = 4.62 g MJ-1) and T2 (RUEPR = 4.36 g MJ-1) compared to the control T0 (RUEPR = 5.18 g MJ-1). Likewise, the RUE post-anthesis was reduced by 8.9 and 32.1% in T1 (RUEPS = 1.23 g MJ-1) and in T2 (RUEPS = 0.91 g MJ-1), dissimilarity to T0 (RUEPS = 1.35 g MJ-1). The maximum RUETDM (3.2 g MJ-1) was manifested in (T0). However, the minimum RUETDM (2.8 g MJ-1) was observed in T2 (S = 18 dS m-1). A decline of 16.1% was observed in RUETDM due to the reduction on TDM from T0 (S = 1.2 dS m-1) to T2 (S = 18 dS m-1). As well, the RUEGY declined when salinity increased. The highest RUEGY (1.24 g MJ-1) was registered in T0. However, the lowest RUEGY (0.62 g MJ-1) was obtained in T2. A decrease of 50% in RUEGY due to the height reduction on yield was observed in the T2.

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)0.001
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 score0.788
Threshold uncertainty score0.151

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.030
GPT teacher head0.250
Teacher spread0.220 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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