Effect of Shrimp-Based Cropping Systems on Salinity and Soil Fertility in a Coastal Area of Bangladesh: A Village-Level Study
Bibliographic record
Abstract
The present study analysed soil salinity and some essential soil nutrients for rice plant as affected by a shrimp-based cropping system in a coastal area of Bangladesh. The study was conducted in a village located in Satkhira district. Two main cropping systems, the shrimp-boro rice cropping system and the aman rice-boro rice cropping system, are mainly practised by local farmers in the study village. Soil and water samples were collected from the plots of these cropping systems and chemical analysis was done to measure the salinity level of the soil and water as well as to find out the nutrient status of the soil. The data was also collected for economic analysis and estimated rice and shrimp yield from the local farmers. The results revealed that the soil salinity level of the shrimp-boro rice cropping system was higher than that of aman rice-boro over the consecutive years of 2010, 2011 and 2012. The soil was found to be moderately saline. The organic matter content, potassium, calcium, magnesium and sulphur levels of the soil in the shrimp-boro rice system were increased, while the total nitrogen, phosphorus, boron and zinc availability decreased. It was also found that the yield of boro rice was 4,950 kg/ha whereas the aman rice yield was 3,020 kg/ha and that for shrimp the yield was calculated as 268 kg/ha for one growing season (six months). The total income from boro rice, aman rice and shrimp was calculated as 127,760 Tk, 87,118 Tk and 149,476 Tk, respectively. The paper concludes that although some nutrient elements were available in adequate amounts, salinity kept these nutrients from being taken up by the rice plants since salinity changes the osmotic pressure of the soil solution system. This may ultimately lead to a reduction in rice yield and threaten the sustainability of the local shrimp-boro rice cropping system.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".