Response of Haricot Bean Varieties to Different Levels of Zinc Application in Selected Areas of Ethiopia
Bibliographic record
Abstract
Zinc is an essential trace element for plants, animals, and humans, and its deficiency is the fifth most important risk factor associated with illness and death in the developing world. The experiment was conducted in Taba, Halaba, and Butajira soils to evaluate the response of haricot bean varieties to different Zn levels. It was carried out in a quadruple factorial design on farmers’ fields and in a greenhouse with soils collected from the aforementioned locations. The two factors were the concentration of zinc fertilizer (0, 0.5, 1, or 1.5%) and the haricot bean variety (Nasir, Ibado, Hawassa Dume, or Sari-1). Zinc sulfate (ZnSO 4 ∙7H 2 O) was sprayed on the leaves, and nitrogen (N) and phosphorus (P) were applied to the soil equally for all treatments just before planting, using urea and triple super phosphate (TSP) respectively. Four haricot bean seeds/pot were sown and, later, two seedlings were thinned. For the field experiment, haricot beans were planted in rows with a spacing of 10 cm between plants and 40 cm between rows. Plant height, number of pods per plant, number of seeds per pot, 1000 seed weight, and biomass and grain yields were determined. Leaves and seeds from each treatment pot and plot were analyzed for their zinc contents. The results from pot and field experiments indicated that haricot bean production varied significantly among varieties both in yield parameters and tissue Zn concentrations, with the highest grain yield being produced by Nasir and Hawassa Dume. Nasir also produced the highest seed Zn; therefore, it was found to be the best variety both in quantity and quality. Haricot bean production also varied significantly among locations, with the highest grain yield at Butajira. The application of increasing levels of zinc fertilizer significantly increased tissue Zn concentrations. The growing season also significantly affected haricot bean production in terms of yield parameters and tissue Zn concentrations. The highest grain yield was observed during the belg (short growing) season, whereas the highest tissue Zn concentrations were recorded during the meher (long growing) season. Therefore, we can conclude that Zn fertilization and the consumption of haricot bean varieties with high levels of Zn could significantly improve the Zn status of people for whom haricot beans constitute a major component of their diet. Keywords: Haricot bean, leaf Zn concentration, seed Zn concentration, tissue Zn concentration, zinc fertilization
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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 | 0.001 |
| 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".