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Record W3095277260 · doi:10.3389/fpls.2020.586421

Selenium Biofortification and Interaction With Other Elements in Plants: A Review

2020· review· en· W3095277260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Plant Science · 2020
Typereview
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of British Columbia
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsBiofortificationSeleniumEssential nutrientCropBiologyNutrientBiotechnologyAgronomyChemistryMicronutrientEcology

Abstract

fetched live from OpenAlex

Selenium (Se) is an essential element for humans and animals and its deficiency in the diet is a global problem. Crop plants are the main source of Se for consumers. Therefore, there is much interest in understanding the factors that govern the accumulation and distribution of Se in the tissues of crop plants and the mechanisms of interaction of Se absorption and accumulation with other elements, especially with a view toward optimizing Se biofortification. An ideal crop for human consumption is rich in essential nutrient elements such as Se, while showing reduced accumulation of toxic elements in its edible parts. This review focuses on (a) summarizing the nutritional functions of Se and the current understanding of Se uptake by plant roots, translocation of Se from roots to shoots, and accumulation of Se in grains; and (b) discussing the influence of nitrogen (N), phosphorus (P), and sulfur (S) on the biofortification of Se. In addition, we discuss interactions of Se with major toxicant metals (Hg, As, and Cd) frequently present in soil. We highlight key challenges in the quest to improve Se biofortification, with a focus on both agronomic practice and human health.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.049
GPT teacher head0.325
Teacher spread0.276 · 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