Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data

Costa, Alan Carlos; Balestre, Márcio; Botelho, Hortência Aparecida; Freitas, Rilke Tadeu Fonseca de; Gomes, Richardson Cesar da Silva; Campos, Sérgio Augusto de Sousa; Foresti, Fábio Porto; Hashimoto, Diogo Teruo; Martins, Danubia Batista; Prado, Fernanda Dotti do; Mendonça, Maria Andréia Corrěa

doi:10.1590/1678-992x-2016-0251

Cited by 7 publications

(6 citation statements)

References 20 publications

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“…The Pirapitinga Piaractus brachypomus neotropical fish species presents interesting productive attributes with desirable anatomical characteristics for consumers, and they are grown in several countries of South America, especially Brazil, Colombia, Peru and Venezuela, as well as in Asian countries such as China, Thailand, Vietnam (Costa et al, ; FAO, ; Mourad et al, ).…”

Section: Introductionmentioning

confidence: 99%

Associations between morphometric variables and weight and yields carcass in PirapitingaPiaractus brachypomus

et al. 2019

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The objective of this work was to evaluate the association between morphometric variables and carcass characteristics in Pirapitinga. We used a thousand specimens of Pirapitinga with an average weight of 1,200 g, which were stunned, slaughtered, weighed, measured, and processed for morphometric and processing yield analysis, to obtain weights, carcass and fillet yields. Initially, the linearity of the variables was verified. Pearson's simple and partial correlation tests were performed between all metrics. Track analysis was performed considering the weights and yields of carcass and filet as dependent variables and the others as independent variables. Ridge regression models were used to eliminate the effects of multicollinearity among the independent variables. Observations showed that the simple correlations between body weights and yields were superior to the partial ones in terms of magnitude. The length and circumference of the specimens were the measures most linearly associated with weight, carcass weight and fillet with rib weight. As for carcass yield and fillet yield, linear correlation coefficients were low and not significant when associated with body weights.With the path analysis, we could observe significant positive correlations between the morphometric measurements for weight, carcass weight and fillet with rib weight.The standard length, body circumference and body circumference/body height ratio are the most correlated. The latter are the most important variables in the evaluation of body weights in Pirapitinga fish. They can serve as criteria for indirect selection in searching for fish with better carcass characteristics. As for fillet and carcass yields, the morphometric variables have not shown to be efficient for indirect selection. K E Y W O R D Sbreeding fish, correlation, multivariate, path analysis, round fish

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Section: Introductionmentioning

confidence: 99%

Associations between morphometric variables and weight and yields carcass in PirapitingaPiaractus brachypomus

et al. 2019

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“…The method of Griffing () was adapted to a mixed models analysis proposed by Costa et al. (), with the environmental effects being estimated through an empirical best linear unbiased estimator and the genetic effects considered as random, to obtain the empirical best linear unbiased predictor of the GCA and SCA. However, since not all information about the parental generation is available, the diallel analysis was performed by the normal‐mixture mixed model which imputes the incidence matrices for the random effects (GCA and SCA) when the genetic composition of the animals is unknown (Costa et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…(), with the environmental effects being estimated through an empirical best linear unbiased estimator and the genetic effects considered as random, to obtain the empirical best linear unbiased predictor of the GCA and SCA. However, since not all information about the parental generation is available, the diallel analysis was performed by the normal‐mixture mixed model which imputes the incidence matrices for the random effects (GCA and SCA) when the genetic composition of the animals is unknown (Costa et al., ). To make inferences about the genetic composition of the sampled animals, the imputed incidence matrix of the GCA was considered because this gives an additive genetic effect in the model.…”

Section: Methodsmentioning

confidence: 99%

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General and specific combining ability in Serrasalmidae

et al. 2018

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This work was carried out to predict the combining abilities, both general and specific, for performance traits and bodily yields of Serrasalmidae. Ninety-six 30-day-old juveniles were purchased from two commercial fish farms, 12 of each of the following eight genetic groups: pacu, pirapitinga, tambaqui, tambacu, tambatinga, patinga, paqui and piraqui. Six fish from each genetic group were grown in 500-L fibreglass tanks (two tanks per genetic group) until they were 495 days old. At the end of the growth period fish were weighed, subjected to morphometric analysis and processed to obtain their bodily yields. Two nuclear markers and one mitochondrial marker were used to confirm the identity of the animals. Combining abilities were obtained using the method proposed by Griffing in 1956 (Australian Journal of Biological Science, 4, 463-493) adapted to a mixed models analysis, environmental effects were estimated by the empirical best linear unbiased estimator method and genetic effects (general and specific combining abilities) were estimated with the empirical best linear unbiased predictor. Predictions of the combining abilities of advanced hybrids were obtained by the mixed models mixture method with normal distributions. Tambaqui showed higher general and specific combining abilities than the other groups for most of the variables, making it the most important genetic group. General combining ability makes a greater contribution to phenotypic variance than specific combining ability for most variables, indicating a predominance of genes with an additive effect in the control of evaluated traits. K E Y W O R D SColossoma macropomum, diallel crossbreeding, fish breeding, Piaractus brachypomum, Piaractus mesopotamicus, round fish

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“…There are resources for the discrimination and classification of lambari species, such as taxonomy, but the methods are expensive and require technical knowledge. Separation and allocation by external morphology are unreliable when used as the single source of analysis, since it is based only on morphological characteristics (Chevassus, ; Costa et al, ; Mallet, ; Toledo‐Filho, Foresti, & Almeida‐Toledo, ). In this sense, the application of discriminant analysis using morphometric measures and ratios becomes a viable alternative for discriminating and classifying groups of a certain population.…”

Section: Introductionmentioning

confidence: 99%

Application of morphometric measures in estimation of body weight and discrimination ofAstyanax lacustrisandAstyanax fasciatus

et al. 2019

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The objective of this study was to verify the direct and indirect correlation between morphometric measures, ratios, body weight and yield in two lambari species Astyanax lacustris and Astyanax fasciatus and whether the discriminant analysis is capable of separating and allocating the species. We used 102 lambari yellow tail and 60 lambari red tail. The fish were weighed and submitted to the evaluation of the morphometric measurements. The direct and indirect effects were evaluated by the method of track analysis, considering weight at slaughter, weight of body parts and body yields as dependent variables and measures and morphometric ratios as explanatory variables. Astyanax lacustris presented higher height and body width, carcass yield and trunk, while A. fasciatus presented higher head yield and viscera weight. The discriminant analysis was able to classify 79.5% of the two species. Track analysis demonstrated that the morphometric measurements can be used for estimation of body and body components’ weight in A. lacustris and A. fasciatus. However, regarding the corporal yield; the morphometric measures were insufficient to explain the yield variations of the species.

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Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data

Cited by 7 publications

References 20 publications

Associations between morphometric variables and weight and yields carcass in PirapitingaPiaractus brachypomus

Associations between morphometric variables and weight and yields carcass in PirapitingaPiaractus brachypomus

General and specific combining ability in Serrasalmidae

Application of morphometric measures in estimation of body weight and discrimination ofAstyanax lacustrisandAstyanax fasciatus

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