HEAVY METAL CONTENT IN SOILS OF SELECTED HOP PLANTATIONS IN RELATION TO THEIR NATURAL BACKGROUND
Bibliographic record
Abstract
Heavy metals (HM) are present in soil naturally [1], due to weathering of the element-rich parent rock and anthropogenic sources (industry, agriculture, traffic, energy production) [2–4]. The agricultural source of the increased HM concentrations in soil are HM-containing fertilisers and pesticides. Agricultural soils are often considered polluted, and are, therefore, subject to soil contamination monitoring for food safety reasons. Permanent crops are particularly at risk, due to the intensive and traditional (over)use of pesticides and fertilisers. Hop plantations are a special type of economically important permanent crop in the Lower Savinja region. The product, the dried hop cones, is mainly exported. The cultivation of hops requires intensive soil tillage, fertilisation, and, above all, constant protection of the hop plant by usage of pesticides. According to Slovenian legislation [5], the HM concentration is considered elevated if the HM concentration in the soil is above the limit immission value (LIV), polluted if it is above the warning immission value (WIV), and critically polluted if it is above the critical immission value (CIV). The HM content was analysed in the soils of 10 hop plantations in the Lower Savinja region. The soil samples were dried, ground and sieved in the FVO laboratory, and analysed by Bureau Veritas Commodities (Canada) using Aqua Regia extraction to determine the 'pseudo-total content' for 37 elements (Ag, Al, As, Au, B, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, Hg, K, La, Mg, Mn, Mo, Na, Ni, P, Pb, S, Sb, Sc, Se, Sr, Te, Th, Ti, TI, U, V, W, and Zn), 10 of which (in the frames) are considered common HM soil contaminants. The HM concentrations in the soils of the hop plantations were within the natural background values [1] (below the LIV), with the exception of Cd, Cu and Zn, which were above the LIV in some cases. The Cd concentration was elevated in 90 % (it exceeded the LIV). The hop fields were not contaminated with Cd – as the concentration did not exceed the WIV. The Cu concentration was within the natural background values in 20 % of the hop plantations (well below the LIV), 30 % were elevated (exceeded the LIV), while 50 % were polluted with Cu (the Cu exceeded the WIV). The Zn concentration was below the LIV value in 80 % of the hop plantations, 10 % exceeded the LIV value, while 10 % of the hop plantations were considered to be polluted with Zn (the Zn exceeded the WIV value) [6]. As expected, we found that the soils of the hop plantations contained significantly increased, and, in some places, exceeded quantities of Cu and Zn, and in some cases also Cd. Elevated concentrations of HM may also be reflected in other parts of the environment, while the effects on food quality were not detected (i.e., elevated concentrations in beer).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".