Integrated Application of Organic and Blended Mineral Fertilizers Improves Potato Productivity and Income for Smallholder Farmers in Acidic Soils
Bibliographic record
Abstract
Potato (Solanum tuberosum) is the world’s third most important food crop. However, potato productivity is very low in acidic soils that cover about 50% of the arable land in the world. Therefore, the aim of this study was to evaluate the effect of sole and integrated farmyard manure (FYM) and different types mineral fertilizers on yield, yield components and economic returns of potato in acidic soil of Ethiopia. Six treatments: 1) Control (without fertilizer), 2) sole application of the recommended NP (RNP) fertilizer (11 kg/ha N and 40 kg/ha P), 3) sole FYM (28.8 t/ha FYM), 4) half dose of recommended NP fertilizer and half dose of the FYM, 5) blended fertilizer formulated as 17.3 kg N, 34.7 kg P2O5, 7.41 kg S, 2.23 kg Zn, 0.3 kg B + 100 kg/ha), and 6) half blended and half FYM, were arranged in a randomized complete block design. The results revealed that potato plants amended with sole blended fertilizer, and integrated FYM and mineral fertilizers doubled fresh tuber yield as compared to the control. The RNP fertilizer gave the lowest (α < 0.05) marketable potato yields of all the fertilizer treatments. Applications of sole blended or integrated FYM and mineral fertilizers resulted in the highest net benefit with acceptable marginal rate of return. Integrated use of FYM and mineral fertilizers is crucial for improved and sustained smallholder potato production in acidic soils. Further studies are required to examine the long-term effects of blended fertilizers on soil properties.
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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".