Effectiveness of Peanut Green Manure on Root Growth and Corn Yield in Alfisol Soil
Bibliographic record
Abstract
Addressing constraints associated with the low nutrient content of Alfisols used in agricultural practices, this study explored the potential of organic fertilizers in improving soil quality, health, and nutrient compositions.Specifically, the research examined the cultivation of corn on Alfisols supplemented with organic fertilizers, an approach aimed at addressing the growing demand for corn in Indonesia.Conducted from April 2022 to February 2023 at coordinates 07°38'07.04"S 110°57'00.7"E,this experimental study was structured according to a Randomized Complete Block Design with a single-factor treatment, consisting of six distinct doses of peanut green manure.The experiment was conducted with the following treatments: P0, which involved the use of inorganic fertilizer; P1, with the application of 2.5 tons/ha of peanut green manure; P2, with 5 tons/ha; P3, with 7.5 tons/ha; P4, with 10 tons/ha; P5, with 12.5 tons/ha.Each treatment was replicated thrice, yielding a total of 18 experimental units, each composed of 16 plants.The experimental plots were maintained within an area of 300 cm x 80 cm, with a planting distance of 100 cm × 50 cm.Data were subjected to an analysis of variance (ANOVA) at a 5% level, followed by Duncan's Multiple Range Test, also at a 5% level.A correlation analysis was performed to discern the relationships between the variables.The application of peanut green manure exhibited no significant differences in all variables, excluding root length.The longest root length (26.57cm) was observed in treatments involving inorganic fertilizers compared to those with peanut green manure.However, the root length exhibited a significant difference in response to various doses of peanut green manure.This investigation underscores the importance of cultivating corn on Alfisol soils, considering the increasing food demand and the decreasing availability of optimal lands for cultivation.The utilization of Alfisol soils could provide a viable solution to these challenges.
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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 | 0.000 |
| 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".