Isotopic fractionation of zinc in field grown tomato
Bibliographic record
Abstract
Many of the world’s soils are deficient in zinc (Zn), and this has implications for plant and human nutrition. Consequently, there is a need to better understand plant uptake and allocation of Zn. Natural abundances of stable isotopes have been used to gain insight into uptake, assimilation, and allocation of various elements by plants. Inductively coupled plasma mass spectrometry was used to study the fractionation of Zn isotopes in the shoots and fruits of mature tomato plants (Solanum lycopersicum L.) grown on an organic farm. Effects of mycorrhizal colonization of roots on Zn fractionation were studied by growing a tomato mutant with reduced mycorrhizal colonization, and its mycorrhizal wild-type progenitor. Fruits of both genotypes were enriched in 64Zn and 66Zn and depleted in 67Zn and 68Zn isotopes, based on calculations that expressed the concentration of each isotope as a percentage of total Zn. The reverse was true of the shoots. Furthermore, shoots of the mycorrhizal genotype were very slightly enriched in 64Zn and 66Zn isotopes relative to those of the reduced mycorrhizal colonization genotype. Possible explanations for fractionation of Zn between shoots and fruits, including differential bonding of Zn to cellular components, processes affecting Zn–phytate–protein complexes, and Zn transport and translocation processes are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".