Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/124192
DC Field | Value | Language |
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dc.contributor.author | Shin,Hyun Suk | en_US |
dc.contributor.author | Montachana Chimborazo, Magaly Elizabeth | en_US |
dc.contributor.author | Escobar Rivas, Jakie Melissa | en_US |
dc.contributor.author | Lorenzo Felipe,Alvaro | en_US |
dc.contributor.author | Martínez Soler, Marina | en_US |
dc.contributor.author | Zamorano Serrano, María Jesús | en_US |
dc.contributor.author | Fernández Martín, Jesús | en_US |
dc.contributor.author | Ramírez Artiles, Juan Sebastián | en_US |
dc.contributor.author | Peñate Sánchez, Adrián | en_US |
dc.contributor.author | Lorenzo Navarro, José Javier | en_US |
dc.contributor.author | Intriago Díaz, Walter | en_US |
dc.contributor.author | Torres, Ricardo | en_US |
dc.contributor.author | Reyes Abad, Eduardo | en_US |
dc.contributor.author | Afonso López, Juan Manuel | en_US |
dc.date.accessioned | 2023-08-29T08:14:15Z | - |
dc.date.available | 2023-08-29T08:14:15Z | - |
dc.date.issued | 2023 | en_US |
dc.identifier.issn | 2352-5134 | en_US |
dc.identifier.other | Scopus | - |
dc.identifier.uri | http://hdl.handle.net/10553/124192 | - |
dc.description.abstract | This study aimed to estimate the genetic parameters of growth-related traits (weight and length), morphological traits (cephalothorax, abdomen, length, height, segment width and volume), and the correlated response of weight traits via the selection for morphological traits to evaluate the relative efficiency of indirect selection in P. vannamei from a selective breeding growth programme, PMG-BIOGEMAR®, under industrial production conditions in Ecuador. A total of 595 shrimps from 89 full-sibling families were reared under an extensive culturing system (estuaries) (PRODUMAR, Duran, Ecuador), and were evaluated for genetic parameters at harvest size. The heritability of growth traits was moderate-medium (0.25–0.34), whereas it was quite variable for morphological traits (0.01–0.77). Among the morphological traits, Sixth Segment Width (SW6) (0.77) and Sixth Segment Volume (SV6) (0.35) had medium-high heritability, and genetic correlations between almost all morphological and growth traits were high and positive, except those corresponding to the fourth segment. According to these genetic parameters, SW6 and SV6 as the correlated response to weight are 9.7% and 5.8%, respectively, being more efficient than direct selection for weight. Thus, the sixth segment should be considered an indirect selection criterion for growth in future breeding programmes as it is a precise, non-invasive, and low-cost morphological trait for growth improvement in the industrial sector. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Aquaculture Reports | en_US |
dc.source | Aquaculture Reports[EISSN 2352-5134],v. 31, (Agosto 2023) | en_US |
dc.subject | 2409 Genética | en_US |
dc.subject.other | Correlated Response | en_US |
dc.subject.other | Genetic Parameters | en_US |
dc.subject.other | Growth | en_US |
dc.subject.other | Morphology | en_US |
dc.subject.other | Penaeus Vannamei | en_US |
dc.title | Genetic parameters for growth and morphological traits of the Pacific white shrimp Penaeus vannamei from a selective breeding programme in the industrial sector of Ecuador | en_US |
dc.type | info:eu-repo/semantics/Article | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/j.aqrep.2023.101649 | en_US |
dc.identifier.scopus | 85166671305 | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.orcid | NO DATA | - |
dc.contributor.authorscopusid | 58522048100 | - |
dc.contributor.authorscopusid | 58187581400 | - |
dc.contributor.authorscopusid | 58522179500 | - |
dc.contributor.authorscopusid | 57224353358 | - |
dc.contributor.authorscopusid | 58187901400 | - |
dc.contributor.authorscopusid | 58521665300 | - |
dc.contributor.authorscopusid | 58522302100 | - |
dc.contributor.authorscopusid | 58521797600 | - |
dc.contributor.authorscopusid | 26421312300 | - |
dc.contributor.authorscopusid | 15042453800 | - |
dc.contributor.authorscopusid | 58187847800 | - |
dc.contributor.authorscopusid | 58521536400 | - |
dc.contributor.authorscopusid | 58187581500 | - |
dc.contributor.authorscopusid | 57201126472 | - |
dc.identifier.eissn | 2352-5134 | - |
dc.relation.volume | 31 | en_US |
dc.investigacion | Ciencias de la Salud | en_US |
dc.type2 | Artículo | en_US |
dc.utils.revision | Sí | en_US |
dc.date.coverdate | Agosto 2023 | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-VET | en_US |
dc.description.sjr | 0,823 | |
dc.description.jcr | 3,2 | |
dc.description.sjrq | Q1 | |
dc.description.jcrq | Q1 | |
dc.description.scie | SCIE | |
dc.description.miaricds | 10,3 | |
item.fulltext | Con texto completo | - |
item.grantfulltext | open | - |
crisitem.author.dept | GIR Grupo de Investigación en Acuicultura | - |
crisitem.author.dept | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.dept | GIR Grupo de Investigación en Acuicultura | - |
crisitem.author.dept | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.dept | GIR Grupo de Investigación en Acuicultura | - |
crisitem.author.dept | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.dept | GIR Grupo de Investigación en Acuicultura | - |
crisitem.author.dept | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.dept | Departamento de Patología Animal, Producción Animal, Bromatología y Tecnología de Los Alimentos | - |
crisitem.author.dept | GIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR Grupo de Investigación en Acuicultura | - |
crisitem.author.dept | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.dept | Departamento de Patología Animal, Producción Animal, Bromatología y Tecnología de Los Alimentos | - |
crisitem.author.orcid | 0000-0002-1649-5613 | - |
crisitem.author.orcid | 0000-0003-1569-9152 | - |
crisitem.author.orcid | 0000-0003-2876-3301 | - |
crisitem.author.orcid | 0000-0002-2834-2067 | - |
crisitem.author.parentorg | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.parentorg | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.parentorg | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.parentorg | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.parentorg | IU de Investigación en Acuicultura Sostenible y Ec | - |
crisitem.author.fullName | Shin, Hyun Suk | - |
crisitem.author.fullName | Lorenzo Felipe,Alvaro | - |
crisitem.author.fullName | Martínez Soler, Marina | - |
crisitem.author.fullName | Zamorano Serrano, María Jesús | - |
crisitem.author.fullName | Peñate Sánchez, Adrián | - |
crisitem.author.fullName | Lorenzo Navarro, José Javier | - |
crisitem.author.fullName | Afonso López, Juan Manuel | - |
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