Carbon balance and greenhouse gas emissions from horticultural plants grown in peat-based growing media
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.
Bibliographic record
Abstract
Peat-based growing substrates are commonly used in specialty crop production. The decomposition rates of peat and the respiration dynamics of plants grown in peat mixtures are poorly understood. We grew lettuce ( Lactuca sativa ) and petunia ( Petunia sp.), representing food and ornamental plant growth, in peat-based media and measured the exchange of carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ) over 3 to 4 months. We used radiocarbon isotopes to partition ecosystem respiration (ER) into autotrophic respiration (AR) and heterotrophic respiration (HR) and estimated the priming effect of roots to enhance peat HR. Average (± standard deviation) N 2 O emissions were 2.69 ± 3.47 mg m −2 day −1 , while CH 4 emissions were variable and small. HR measured from peat alone was on average 0.28 ± 0.15 g CO 2 -C m −2 day −1 . Average net ecosystem exchange (NEE) and ER measurements for pots containing lettuce were −1.17 and 2.09 g CO 2 -C m −2 day −1 , respectively, and NEE and ER for pots containing petunia were −0.62 and 2.96 g CO 2 -C m −2 day −1 , respectively. Without considering the priming effect, HR contributed 9% and 13% to the total ER in lettuce and petunia, respectively. Radiocarbon partitioning of ER revealed that HR contributes 10% and 18% for lettuce and petunia, showing a statistically significant positive priming ( p = 0.007) effect in petunia but not in lettuce. Our measurements provide a basis for the reporting of GHG emissions from horticultural plants grown in peat-based growing media.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it