Diversity of Pepper (Capsicum spp.) Genotypes from Eritrea Assessed by Morphological Traits
Bibliographic record
Abstract
<p>Diversity in plant genetic resources provides an opportunity for plant breeders to develop new and improved cultivars with desirable characteristics. The purpose of this study was to assess the diversity of Eritrean pepper germplasm in order to obtain information for improving it. A total of 60 pepper (<em>Capsicum</em> spp.) seed sample collections were obtained from farmers and institutions in Eritrea. The collections were evaluated at two sites located in two different agro-climatic regions of the country. The collections were assessed using 16 quantitative and 23 qualitative descriptors. A Randomized Complete Block Design was used for the evaluation. Quantitative and qualitative data of the two sites were subjected to Principal Component Analysis, Principal Coordinate Analysis, Hierarchal clustering, Analysis of variance and Correlation. The distribution of characters of the different quantitative and qualitative traits and the performance of the collections showed the existece of variable characters distributed among the collections indicating considerable diversity. For quantitative variables, the first three components were able to explain 61%, 58% and 67% of the total variation in Hamelmalo, Asmara and combined data of the two sites respectively. While for the qualitative variables the first three components were able to explain a variation of 58% in Hamelmalo, 49%, in Asmara and 55% combined data of the two sites. Phenological attributes and fruit characteristics were found to contribute more to the variation. The majority of the traits evaluated were significant and the highest Coefficient of Variation was related to fruit characteristics. The results of this study showed that there is sufficient variability within the Eritrean pepper genotypes that could be used in future breeding and crop improvement programs.</p>
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".