Addition of biochar to acidic boreal podzolic soils enhances micronutrient availability and crop productivity
Bibliographic record
Abstract
Abstract Results of a recent multiyear experiment conducted on an agricultural plot that was recently converted from boreal forest (Labrador, Canada) suggested that NPK fertilizers contributed to better crop establishment and higher yield but only when it was applied along with biochar. The failure of fertilizer only treatments to allow crop establishment and desirable growth and yield could be related to the deficiency of one or more micronutrients. Consequently, a missing element trial with a number of micronutrients (Mn, Cu, Zn, and Mo) was initiated on the same soil to investigate whether biochar can facilitate the availability of one or more of these micronutrients, contributing to crop growth and yields. Results show that the incorporation of chemical fertilizers with biochar produced significantly higher yields than in the absence of biochar. Furthermore, in the absence of biochar, the addition of micronutrients (i.e., Mn, Cu, Zn, and Mo) did not significantly increase yield. On the other hand, among the treatments that included biochar, the absence of a micronutrient (i.e., only three of the four micronutrients included) had either no effect (e.g., absence of Mn or Zn) or was associated with the increased yields (i.e., absence of Cu or Mo). Thus, it is proposed that while all tested micronutrients were present in the podzolic soil, with Cu and Mo possibly oversupplied, co-application with biochar enhanced both macronutrient and micronutrient utilization by plants. The data on the availability of micronutrients in the soil, their concentration in plants, and total uptake also support this conclusion. Thus, biochar facilitates the plant uptake of both naturally occurring and added micronutrients, and associated crop productivity, in a podzolic soil typical for lands converted from forest to agricultural use in the boreal ecoregion of Labrador. These results also challenge the view that micronutrients must always be added to Podzols to achieve maximum productivity; biochar-mediated micronutrient plant uptake deserves consideration when managing Podzols.
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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 | 0.001 | 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".