Genotype by Environment Interaction and Stability of Chickpea (Cicer arietinum (L.)) Genotypes in Southern Ethiopia
Bibliographic record
Abstract
The production of chickpea in Ethiopia is being pushed into less favorable areas adjacent to and in the southern rift valley where it is exposed to severe moisture stress during the post-rainy growing season. Fifteen chickpea genotypes consisting of seven released varieties, six kabuli advanced lines obtained from ICARDA and two local checks, were tested in three replications of RCBD at three locations during 2012 and 2013 (six environments, E1 to E6) in southern Ethiopia. The objectives of the study were to determine the difference in grain yield between the genotypes and between the environments and investigate the magnitude and nature of G x E interaction, assess the stability of the chickpea genotypes and identify those with wide or narrow adaptation. Due to heterogeneity of errors over the six environments a transformation (Geometric mean x Log (Yield in Kg ha-1) was used. The Environment main effect and the GxE interaction were highly significant. Grain yield ranged between 31.8 and 68.7 units (0.66 and 5.2 tons ha-1) at E1 and E2, respectively; a reduction of 53.6% (87.3% in the original units, Kg ha-1) due to moisture stress. Univariate stability parameters identified four high yielding and stable genotypes, Ejeri, Mastewal, Wolayita Local and Habru for wide adaptation. There was no correlation between yield and stability; simultaneous selection for both high yield and stability is possible. Both AMMI and GGE put the lowest yielding environment, E1 as a distinct environment. Yield at E1 was negatively correlated with yield at other environments. AMMI and GGE identified the same four genotypes selected by Wi, (S2di), and ASVi for wide adaptation (Group I). Arerti, Butajira local, Cheffe and Naatolii (Group II) were adapted to high yielding environments similar to JolleAndegna (Butajira) and Taba in Wolayita. Shasho, FLIP03-28C and FLIP07-81C (Group III) were adapted to low yielding environments such as Halaba (Huletegna Choroko). Compared to Group II, genotypes in Group III had the highest mean yield under stress (E1) (8.8 vs 5.1), geometric mean yield (20.6 vs 17.4), Yield Stability Index (0.18 vs 0.08), Drought Resistance Index (0.24 vs 0.07), and the lowest percent yield reduction (81.7 vs 91.9%) and Drought Susceptibility Index (0.79 vs 0.91).
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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 | 0.000 | 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) | 0.000 | 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".