Transpiration flow controls Zn transport in Brassica napus and Lolium multiflorum under toxic levels as evidenced from isotopic fractionation
Bibliographic record
Abstract
Stable zinc (Zn) isotope fractionation between soil and plant has been used to suggest the mechanisms affecting Zn uptake under toxic conditions. Here, changes in Zn isotope composition in soil, soil solution, root and shoot were studied for ryegrass ( Lolium multiflorum L.) and rape ( Brassica napus L.) grown on three distinct metal-contaminated soils collected near Zn smelters (total Zn 0.7–7.5%, pH 4.8–7.3). The Zn concentrations in plants reflected a toxic Zn supply. The Zn isotopic fingerprint of total soil Zn varied from −0.05‰ to +0.26 ± 0.02‰ ( δ 66 Zn values relative to the JMC 3-0749L standard) among soils, but the soil solution Zn was depleted in 66 Zn, with a constant Zn isotope fractionation of about −0.1‰ δ 66 Zn unit compared to the bulk soil. Roots were enriched with 66 Zn relative to soil solution ( δ 66 Zn root − δ 66 Zn soil solution = Δ 66 Zn root–soil solution = +0.05 to +0.2 ‰) and shoots were strongly depleted in 66 Zn relative to roots (Δ 66 Zn shoot–root = −0.40 to −0.04 ‰). The overall δ 66 Zn values in shoots reflected that of the bulk soil, but were lowered by 0.1–0.3 ‰ units as compared to the latter. The isotope fractionation between root and shoot exhibited a markedly strong negative correlation ( R 2 = 0.83) with transpiration per unit of plant weight. Thus, the enrichment with light Zn isotopes in shoot progressed with increasing water flux per unit plant biomass dry weight, showing a passive mode of Zn transport by transpiration. Besides, the light isotope enrichment in shoots compared to roots was larger for rape than for rye grass, which may be related to the higher Zn retention in rape roots. This in turn may be related to the higher cation exchange capacity of rape roots. Our finding can be of use to trace the biogeochemical cycles of Zn and evidence the tolerance strategies developed by plants in Zn-excess conditions.
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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) | 0.000 | 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".