Effect of water soluble humic acid applied to potato foliage on plant growth, photosynthesis characteristics and fresh tuber yield under different water deficits
Bibliographic record
Abstract
Abstract Water scarcity is the main limiting factor in agricultural crop production in arid and semi-arid areas in northern China. Humic acid could improve the plant resistance to mitigate the abiotic drought damages, which is a potential strategy to improve the crop production in these regions. An experiment to investigate the effect of water soluble humic acid on plant growth, photosynthesis characteristics and fresh tuber yield of potato under different water deficits was carried out under greenhouse conditions in 2014 and 2015. Treatments included foliar application of fresh water (FW), humic acid diluted with water 500 times (HA) and control (CK), and the water deficits included 45%, 60% and 75% of the field water holding capacity. The HA treatment showed highly significant (P ≤ 0.01) effect on dry biomass, root/shoot ratio and photosynthesis parameters, improved the dry biomass above ground (DM-AG) by 14.12–36.63%, 11.62–36.26% and 7.85–20.85% over the whole growing season at water deficits of 45%, 60% and 75% of the field water holding capacity respectively in 2014 and 2015; decreased the root/shoot (R/S) ratio in the early growing season and increased the R/S ratio in the later growing season; showed an improved effect on leaf soil plant analysis development (SPAD), photosynthesis rate (Pn) and stomatal conductance (Gs) and decreased transpiration rate (Tr) and intercellular CO2 concentration (Ci) compared with the control. HA usually showed a better effect on photosynthesis parameters in 60% of the field water holding capacity than 45% and 75% except on Pn. Compared with control, HA increased fresh tuber yield by 34.47–63.48%, 35.95–37.28% and 23.37–27.15% at 45%, 60% and 75% of the field water holding capacity respectively. HA enhanced the potato plant growth, and improved photosynthesis parameters and fresh tuber yield under different water deficits under green house conditions, and represents an opportunity to improve crop production and sustainability of agriculture in arid and semiarid regions.
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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) | 0.001 | 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".