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Record W2612469505 · doi:10.5539/jas.v9n6p13

Alkaloids in White Lupin and Their Effects on Symbiotic N Fixation

2017· article· en· W2612469505 on OpenAlexvenueno aff
Kristina D. Staples, Anwar A. Hamama, Regina Knight-Mason, Harbans L. Bhardwaj

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
Fundersnot available
KeywordsLupinusBiologyPoint of deliveryAlkaloidHorticultureBotanyInoculation

Abstract

fetched live from OpenAlex

Seeds of white lupin (Lupinus albus L.), known to potentially fix 150 to 200 kg/ha N via Symbiotic N Fixation (SNF), are classified as sweet or bitter based on their alkaloid contents: sweet lupins contain very low whereas bitter lupins contain high contents of alkaloids. However, precise information about effects of alkaloid content on SNF is not very well unknown. Experiments were conducted to determine if alkaloid content in the seed is related to that in other plant tissue such as leaves and pod shells, characterization of relationship between alkaloid concentration and SNF, and to study variation among 126 white lupin accessions for concentration of alkaloids. In the first experiment, the Dragendorff test, a colorimetric test, was used to categorize field-grown lupin lines into 6 categories: 0, 1, 2, 3, 4, and 5 with 0 representing sweet and 5 representing extreme bitterness with bitterness increasing from 0 to 5. In the second experiment, ten lupin lines differing in their Dragendorff score from 0 to four were inoculated with seven bradyrhizobial strains and studied for SNF in a greenhouse. A numerical scale from 0 to 4 with 1 representing absence of nodules and 4 representing many functional nodules was used as a measure of SNF. In the third experiment, concentrations of alkaloids (Dragendorff scores), oil, and protein were studied in 126 accessions.Results indicated that all progenies with Dragendorff score of 1 for the seeds also had the same score for leaves and pod shells. However, this was not true for other progenies. In the case of progenies with Dragendorff scores of 0, 2, 3, or 4 in the seed, the Dragendorff scores for leaves and pod shells were above and below the seed scores indicating existence of variation for alkaloids in various tissues of the lupin plant. Alkaloid content also had significant effects on root nodulation. The interaction between alkaloid categories and bradyrhizobial strains was non-significant. The root nodulation score for lupin lines in alkaloid categories 0, 3, and 4 were similar, indicating that the same bradyrhizobial strain could be used to effectively inoculate sweet and bitter white lupin lines. The root nodulation induced by the seven bradyrhizobial strains were statistically different. It was observed that S96-A15, S96-A19, and S96-B9 were more efficient bradyrhizobial strains whereas S96-A5 was observed to be less efficient for root nodulation. Significant variation existed among 126 white lupin accessions for Dragendorff score and concentrations of oil and protein. The alkaloid content did not affect oil content in the seed, however, alkaloid content significantly affected protein content. The results indicated that bitter seeds had higher protein content.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2017
Admission routes1
Has abstractyes

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