Corn Response to an Integrated Plant Nutrition System (IPNS) With Humic Acid and Biofertilizers
Bibliographic record
Abstract
Sustainable agriculture production depends on the development of methods that optimize nutrient cycling, minimize use of external inputs, and maximize input use efficiency according to the conditions of each region. The principle of an integrated plant nutrition system (IPNS) is to tailor plant nutrition and soil fertility management, taking advantage of the combined and harmonious use of inorganic, organic and biological resources. This greenhouse study investigated the individual and combined use of inorganic, organic and biological fertilizer resources for corn (Zea mays L.). We evaluated the effects of commercial synthetic fertilizer, humic acid products, compost/manure teas and bioinoculant as inorganic, organic and biological resources, respectively, and their synergy on corn growth and soil respiration parameters under a period of water stress. The pots were laid out in completely randomized design and the total of sixteen treatment combinations were replicated four times. In general, when comparing to the control values, the use of humic acid (HA), biofertilizers and the integration of both compounds generated significantly greater early season plant height, chlorophyll content, photosynthetic efficiency and shoot/root dry biomass. The soil substrate induced respiration was affected by only one biofertilizer product at two different rates. Though all pots received adequate synthetic fertilizer, the control plants were generally smaller and less vigorous compared to the plants receiving either HA or biofertilizer treatments, but no additive benefit was observed for the integrated practice compared to individual applications. Further studies addressing different types and levels of stress along with greater stress duration should be conducted to validate these findings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".