RESPONSE OF RICE VARIETY SARO 5 (TXD 306) TO P, Zn and Cu FROM DIFFERENT PHOSPHORUS SOURCES FERTILIZERS IN MBASA VILLAGE, KILOMBERO DISTRICT, TANZANIA
Bibliographic record
Abstract
The study is aimed at evaluating the response of rice variety fertilizer SARO (TXD 306) to P, Zn and Cu from different P sources fertilizers in selected rice growing areas in Kilombero district. Soil fertility analysis was conducted to determine physical and chemical properties of soil for suitability of rice growing. A screen house and field experiments were conducted to assess the response of rice variety SARO (TXD 306) to P, Zn and Cu from fertilizers sources (MPR, Minjingu mazao and DAP) and different levels of Zn and Cu using soils from Mbasa village. The results showed that the soils are acidic (pH 5.2 to 5.9), with low P (1.48 to 9.83 mg kg-1), low total N (0.11 to 0.22 mg kg-1), exchangeable Ca (< 10 cmol kg-1) and base saturation (2.38 to 5.54 %). The experimental results showed significant higher grain yield in all P sources (> 29.7 g pot-1) at (P<0.05) than the control (N alone) treatment (15.5 g pot-1) in P deficient Mbasa soil. Minjingu mazao did not differ (P < 0.05) from other P sources in terms of grain yield in soils under screen house conditions. Application of 2.5 mg kg-1 Zn in combination with DAP gave highest grain yields (39.23 g pot-1) but was statistically similar to Minjingu mazao. Under field condition in Mbasa Vijana 1 soil, all P sources resulted in significantly higher grain yield of 5.92 t ha-1 in Minjingu fertilizers and 6.94 t ha-1 in DAP than control 4.42 t ha-1. Application of Zn and Cu increased grain yield to a maximum of 6.38 in Minjingu and 7.51 t ha1 in DAP with all rate of Zn and 1.1 mgkg-1 Cu treatments. Minjingu mazao fertilizer was comparable to other P sources and has the ability to supply P as DAP fertilizer.
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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 | 0.000 |
| 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) | 0.001 | 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".