Soil properties and the response of rice production to water regime and fertilizer source in low fertility soils of the Republic of Panama
Bibliographic record
Abstract
The System of Rice Intensification (SRI) is a resource-conserving rice production system that uses intermittent flooding and organic fertilization. The SRI is emerging as an alternative to conventional rice production systems that use continuous flooding and mineral fertilizer only, however yield improvements with SRI have been highly variable. The objective of this research was to determine if soil properties control the yield improvements with SRI and, if so, the underlying chemical and biological mechanisms. A meta-analysis of 72 SRI vs. conventional system trials from 16 countries found a significant yield response to SRI in low fertility soils (P<0.0001), but no difference between SRI and the conventional system in moderate and high fertility soils. These results were validated in a greenhouse study. Soils with low P availability (≤7.1 mg P kg-1) responded positively to intermittent flooding and organic fertilizer by increasing plant biomass, plant P uptake, available soil P and microbial P concentrations, compared to soils under continuous flooding and amended with mineral NPK fertilizer only. A field study investigating the interactive effects of water regime and fertilizer source found that, under conditions of P limitation, yields were greater with NPK + composted cow manure (compost) than NPK fertilizer alone in the intermittently flooded (6.6 t ha-1 vs. 4.9 t ha-1) and continuously flooded (6.8 t ha-1 vs. 6.2 t ha-1) soils. The available soil P concentration was significantly increased by compost and was correlated with yield (P=0.007). When N was the most limiting nutrient, according to the Diagnostic and Recommendation Integrated System (DRIS) analysis, yields were greater in the continuously flooded (5.2 t ha-1) than intermittently flooded (2.7 t ha-1) soils receiving NPK fertilizer only, but showed no difference when compost was applied. Compost had a positive effect on the crop nutrient balance according to DRIS analysis (P=0.0007). On-farm trials of SRI at 10 locations in Panama showed an average yield increase of 47% and 86% less water use. SRI is recommended as a rice production system to conserve water and improve rice yields under conditions of P limitation. Organic fertilization is recommended to improve crop nutrient balance and yield under intermittently flooded soil conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".