Improving Soil Fertility and Maize Growth in Suboptimal Land Through Application of Humic Acid
Bibliographic record
Abstract
Humic acid (HA) has been reported to increase plant growth and crop yields, as well as improve soil fertility. However, the potential utilization of HA extracted from various organic waste composts as organic amendment in suboptimal soils has not been studied in depth. The experiment used a two-factor Completely Randomized Design (CRD) with three replications. Four types of HA were used, namely bagasse HA (BHA), water hyacinth HA (WHA), market waste HA (MHA), and commercial HA (CHA). It also comprised of four doses HA i.e., 0.05, 0.10, 0.15 and 0.20% (of soil on w/w base). The results revealed that fluctuations in soil pH and nutrient release with the HA application had a variable quadratic response pattern. Organic carbon increased by 17%, while total N and available P decreased by 5% and 38.6% during the last weeks of incubation. The HA application could improve the growth response and nutrient uptake of maize significantly. CHA0.20% was the best interaction treatment which had the highest average value on dry weight and NPK uptake, which were 98.0 g pot-1, 178.8 mg plant-1, 27.4 mg plant-1 and 216.9 mg plant-1, respectively. The scanning electron microscopic (SEM) showed that HA could increase in the length and density of maize root hairs. Furthermore, the HA application significantly increased pH, CEC, C-organic content and availability of soil nutrients.
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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".