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Record W2783344948 · doi:10.5539/jas.v10n2p195

Breeding Progress for Grain Yield and Yield Related Characters of Kabuli Chickpea (Cicer arietinum L.) in Ethiopia Using Regression Analysis

2018· article· en· W2783344948 on OpenAlexvenueno aff
Megersa Tadesse, Assefa Funga, Asnake Fikre, Tulu Degefu, Million Eshete, Lijalem Korbu, N Girma, Dagnachew Bekele, Ridwan Mohamed, Zewdie Bishaw, Pooran M. Gaur, Chris O. Ojiewo

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
FundersBill and Melinda Gates Foundation
KeywordsYield (engineering)Randomized block designCroppingBiologyAgronomyCropGrain yieldPlant breedingCrop yieldAgricultureEcology

Abstract

fetched live from OpenAlex

The genetic progress in seed yield and yield related characters of 10 kabuli chickpea varieties released by the Ethiopian Chickpea Crop Improvement Program from 1974 to 2017 was assessed during the main cropping season. The varieties were evaluated in the Randomized Complete Block design at Debrezeit Agricultural Research Center experimental research farm. The overall increase in seed yield over the local check, DZ-10-4, was estimated to be 739 kg/ha (38.9%). On station grain yield increased from 1900 to 3250 kg/ha during the last 43 years and the overall increase in seed yield of the Arerti variety over the oldest variety DZ-10-4 was estimated to be 1350 kg/ha or 71.1%. Based on the regression analysis, the estimated average annual rate of increase in grain yield potential was 10.87kg/ha/year with an annual relative genetic change of 0.57%/year. Genotypic change was an important source for increased grain yield potential during the studied period. Positive genetic gains were observed for the yield traits (grain yield and yield components). The average cumulative gains over 43 years of breeding was, therefore, 445.67 kg (23.37%) for seed yield, and 30.26 g for hundred seeds weight (297.7%). Hundred seed weight revealed the most dramatic response to breeding for the last 43 years. It is, therefore, strategically advisable that breeding efforts in the future should give due attention to yield related traits of kabuli chickpea varieties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.254
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2018
Admission routes1
Has abstractyes

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