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Caracterização molecular de germoplasma de batata (Solanum tuberosum L.) por microssatélites

2009· dissertation· pt· W1591589630 on OpenAlexaboutno aff
Patrícia Favoretto

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsUPGMAGermplasmSolanum tuberosumGenetic diversityCultivarBiologyGenetic similarityMicrosatelliteBreeding programCropSelection (genetic algorithm)HorticultureJaccard indexBiotechnologyAgronomyMathematicsGenetic variationComputer scienceAlleleStatisticsGeneticsPopulationCluster analysis

Abstract

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Molecular characterization of commercial cultivars of potato using SSR markersThe cultivation of potato (Solanum tuberosum L) is becoming increasingly important from the point of view of producers, researchers and consumers, for representing one of the food protein mostly consumed in the world.However, Brazil depends on imported varieties, originated from temperate climate which does not complies with our conditions, thus reflecting in lower productivity and quality.Despite the great progress that this crop presented in all these years of cultivation, it is necessary to search for more productive, adapted and resistant materials.The conventional breeding programs are important for the selection of new parents, but the time spent to develop and launch a new variety is quite long.In this scenario, new approaches are being increasingly used in the identification of germplasm banks and most promising cultivars.The objective of this study was to evaluate, using microsatellite markers, 108 accessions of five potato collections containing commercial varieties, clones for breeding programs and organic farming varieties, aiming at the genetic characterization, identification of duplicates and possible parents to be used in potato breeding programs.For the molecular characterization, 10 specific primers were used, generating a total of 50 alleles (bands) which were analyzed as binary data, and from this data a similarity matrix was obtained using the Jaccard coefficient of similarity.With this coefficient and the UPGMA method, cluster analysis were carried out using the NTSYSpc software and bootstraps analyses, generating dendrograms which allowed the genetic distinction between accessions.The polymorphism information content (PIC) and expected heterozygosity (H e ) were both significant, with the highest values (0.8594 and 0.8725, respectively) obtained for primer STM0019a.On average, the number of alleles per locus was five, ranging from two alleles for primers STM 1053 and STM 1104 to 13 alleles per locus for primer STM0019a.To facilitate the visualization of the results, in addition to being evaluated as a whole, the 108 accessions were divided into groups according to the collections (commercial varieties, clones and organic farming), where the highest variation for the Jaccard coefficient (0.39 -0.93) was found for the 57 accessions of organic and commercial cultivars collections.When assessing the 108 accessions together, the Jaccard coefficient ranged from 0.42 to 0.93, showing a high genetic variability between accessions of the five collections.Six possible duplicates were found ['ATLANTIC (Canada) and ATLANTIC (Chile); 67-2 and 17-10 (clones CNPH 1 ); Color and AGATE (EPAMIG); 253 E 266 (clones CNPH 2 ); MELODY and APTA 21-54 (organic farming); and 387-1 (E1) and VOYAGER], and also the more genetically distant accessions [clone 383-19 (Embrapa-CNPH 1 ) and the commercial cultivar HPC-7B] were identified, thereby enabling the identification of potential parents for breeding programs.High levels of polymorphism observed for Solanum tuberosum suggest that microsatellite markers can be a useful tool to detect the genetic differences between potato cultivars.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

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Citations0
Published2009
Admission routes1
Has abstractyes

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