Screening Cover Crops for Utilization in Irrigated Vineyards: A Greenhouse Study on Species’ Nitrogen Uptake and Carbon Sequestration Potential
Bibliographic record
Abstract
This study examines the potential of 23 plant species, comprising 10 legumes, 9 grasses, and 4 forbs, as cover crops to enhance carbon (C) sequestration and soil nitrogen (N) in vineyards. After a 120-day evaluation period, cover crop biomass was incorporated into the soil, and grapevine seedlings were planted in its place. Among the established cover crops, the C input potential ranged from 0.267 to 1.69 Mg ha−1, and the N input potential ranged from 12.3 to 114 kg ha−1. Legume species exhibited up to threefold greater shoot dry weight (SDW) compared to grass species. Ladino white clover, Dutch white clover, and Clover blend were superior in SDW, total dry weight (TDW), total C content, and total N content. Legumes exhibited slightly higher root dry weight (RDW) than grasses, with the exception of Fall rye leading at 15 g pot−1, followed by Ladino white clover and Dutch white clover at an average of 12 g pot−1. Legumes, particularly clover blend and Alsike clover, displayed high shoot N concentration at an average of 2.95%. Root N concentration in Legumes (Fabaceae) were significantly higher at 1.82% compared to other plant families at 0.89%, while their root C/N ratio was lower at 18.3, contrasting with others at 27.7, resulting in a faster turnover. Biomass production exhibited a negative relationship (R2 = 0.51) with soil residual NO3−. Fall rye, Winfred brassica, and buckwheat had the highest N utilization efficiency (NUtE) values (ava. 121 g g−1). Alsike clover, Ladino white clover, and clover blend showed the highest N uptake efficiency (NUpE) values (ava. 75%). The Readily Available N (RAN) Reliance Index (RANRI) is introduced as a novel indicator for quantifying the extent to which a plant relies on RAN for its total N requirement. The RANRI value represents the percentage of the plant’s total N sourced from RAN, ranging from 11% for legumes to 86% for grasses. This implies a substantial influx of nitrogen through a pathway independent of RAN in legumes. Grape shoot N concentration positively correlated with soil NO3− (R2 = 0.31) and cover crop C/N ratio (R2 = 0.17) but negatively correlated with cover crop TDW (R2 = 0.31). This study highlights legume plants as more effective in C and N assimilation during establishment but cautions about potential soil mineral N depletion before reaching their full biological N fixation capacity.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".