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Registro Completo |
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Biblioteca(s): |
Embrapa Pesca e Aquicultura. |
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Data corrente: |
20/10/2017 |
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Data da última atualização: |
10/10/2019 |
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Autoria: |
TORATI, L. S. |
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Afiliação: |
LUCAS SIMON TORATI, CNPASA. |
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Título: |
Reproductive physiology of Arapaima gigas (Schinz, 1822) and development of tools for broodstock management. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
2017 |
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Páginas: |
322 f. |
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Idioma: |
Inglês |
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Notas: |
Tese (Doutorado) - Institute of Aquaculture, University of Stirling, Escócia. |
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Conteúdo: |
Arapaima gigas is the largest scaled freshwater fish in the world reaching over 250 kg. With growth rates of 10 kg+ within 12 months, A. gigas is considered as a promising
candidate species for aquaculture development in South America. However, the lack of reproductive control in captivity is hindering the industry expansion. The work carried
out in this doctoral thesis therefore aimed to better understand the species? reproductive physiology, develop tools to identify gender and monitor gonad development, test
hormonal therapies to induce ovulation and spawning and characterise the cephalic secretion for its potential roles in pheromone release and during parental care. Initially, a
genomic study investigated the overall extent of polymorphism in A. gigas, which was found to be surprisingly low, with only 2.3 % of identified RAD-tags (135 bases long)
containing SNPs. Then, a panel with 293 single nucleotide polymorphism (SNP) was used to characterise the genetic diversity and structure of a range of Amazon populations.
Results revealed populations from the Amazon and Solimões appeared to be genetically different from the Araguaia population, while Tocantins population comprised individuals from both stocks. This data provided a tool for broodstock identification and future management. The PhD then aimed to evaluate the effects of slow-release mGnRH implants and different broodstock size pairings on maturation and spawning. Results showed that the implants stimulated the brain-pituitary-gonad axis resulting in increased plasma levels of testosterone (females) and 11-ketotestosterone in males, respectively regardless of pairing sizes. However, no spawning was observed. Results also showed the release of sex steroids with potential pheromonal action through the cephalic secretion, a biological fluid released from the adult head along the reproductive period. Thereafter, a non-surgical field endoscopy method was developed and validated for ovarian assessment and gender identification. The method was then used to describe the female gonopore and obtain biopsy of the ovary through cannulation which allowed the description of oogenesis in A. gigas. Importantly, oocytes obtained by cannulation confirmed that adult females under investigation were maturing with oocytes in final maturation stage but failed to ovulate/spawn. Another hormonal induction trial was therefore performed in which a combination of GnRHa (mGnRHa/sGnRHa) was used by injection to induce ovulation and spawning in selected maturing females with effects on oocyte maturation monitored post-induction through biopsy. However, this trial appeared to not be successful at inducing ovulation or spawning. Finally, the peptidome and proteome of the cephalic secretion was further characterised through the comparison between parental and non-parental fish. Results highlighted the complex role of this biological fluid including potential roles on the developing offspring during the parental care period. Overall, this doctoral thesis provided new basic and applied data on A. gigas reproduction and tools that can be used in future studies to better understand the environmental and hormonal control of oogenesis and spawning. MenosArapaima gigas is the largest scaled freshwater fish in the world reaching over 250 kg. With growth rates of 10 kg+ within 12 months, A. gigas is considered as a promising
candidate species for aquaculture development in South America. However, the lack of reproductive control in captivity is hindering the industry expansion. The work carried
out in this doctoral thesis therefore aimed to better understand the species? reproductive physiology, develop tools to identify gender and monitor gonad development, test
hormonal therapies to induce ovulation and spawning and characterise the cephalic secretion for its potential roles in pheromone release and during parental care. Initially, a
genomic study investigated the overall extent of polymorphism in A. gigas, which was found to be surprisingly low, with only 2.3 % of identified RAD-tags (135 bases long)
containing SNPs. Then, a panel with 293 single nucleotide polymorphism (SNP) was used to characterise the genetic diversity and structure of a range of Amazon populations.
Results revealed populations from the Amazon and Solimões appeared to be genetically different from the Araguaia population, while Tocantins population comprised individuals from both stocks. This data provided a tool for broodstock identification and future management. The PhD then aimed to evaluate the effects of slow-release mGnRH implants and different broodstock size pairings on maturation and spawning. Results showed that the implants stimulated the bra... Mostrar Tudo |
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Palavras-Chave: |
Araguaia; Solimões. |
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Thesagro: |
Arapauma gigas; Criação em cativeiro; Peixe de água doce; Pirarucu; Piscicultura; Polimorfismo genético; Recurso genético; Reprodução. |
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Thesaurus Nal: |
Amazonia. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 04030nam a2200265 a 4500
001 2077716
005 2019-10-10
008 2017 bl uuuu m 00u1 u #d
100 1 $aTORATI, L. S.
245 $aReproductive physiology of Arapaima gigas (Schinz, 1822) and development of tools for broodstock management.$h[electronic resource]
260 $a2017$c2017
300 $a322 f.
500 $aTese (Doutorado) - Institute of Aquaculture, University of Stirling, Escócia.
520 $aArapaima gigas is the largest scaled freshwater fish in the world reaching over 250 kg. With growth rates of 10 kg+ within 12 months, A. gigas is considered as a promising candidate species for aquaculture development in South America. However, the lack of reproductive control in captivity is hindering the industry expansion. The work carried out in this doctoral thesis therefore aimed to better understand the species? reproductive physiology, develop tools to identify gender and monitor gonad development, test hormonal therapies to induce ovulation and spawning and characterise the cephalic secretion for its potential roles in pheromone release and during parental care. Initially, a genomic study investigated the overall extent of polymorphism in A. gigas, which was found to be surprisingly low, with only 2.3 % of identified RAD-tags (135 bases long) containing SNPs. Then, a panel with 293 single nucleotide polymorphism (SNP) was used to characterise the genetic diversity and structure of a range of Amazon populations. Results revealed populations from the Amazon and Solimões appeared to be genetically different from the Araguaia population, while Tocantins population comprised individuals from both stocks. This data provided a tool for broodstock identification and future management. The PhD then aimed to evaluate the effects of slow-release mGnRH implants and different broodstock size pairings on maturation and spawning. Results showed that the implants stimulated the brain-pituitary-gonad axis resulting in increased plasma levels of testosterone (females) and 11-ketotestosterone in males, respectively regardless of pairing sizes. However, no spawning was observed. Results also showed the release of sex steroids with potential pheromonal action through the cephalic secretion, a biological fluid released from the adult head along the reproductive period. Thereafter, a non-surgical field endoscopy method was developed and validated for ovarian assessment and gender identification. The method was then used to describe the female gonopore and obtain biopsy of the ovary through cannulation which allowed the description of oogenesis in A. gigas. Importantly, oocytes obtained by cannulation confirmed that adult females under investigation were maturing with oocytes in final maturation stage but failed to ovulate/spawn. Another hormonal induction trial was therefore performed in which a combination of GnRHa (mGnRHa/sGnRHa) was used by injection to induce ovulation and spawning in selected maturing females with effects on oocyte maturation monitored post-induction through biopsy. However, this trial appeared to not be successful at inducing ovulation or spawning. Finally, the peptidome and proteome of the cephalic secretion was further characterised through the comparison between parental and non-parental fish. Results highlighted the complex role of this biological fluid including potential roles on the developing offspring during the parental care period. Overall, this doctoral thesis provided new basic and applied data on A. gigas reproduction and tools that can be used in future studies to better understand the environmental and hormonal control of oogenesis and spawning.
650 $aAmazonia
650 $aArapauma gigas
650 $aCriação em cativeiro
650 $aPeixe de água doce
650 $aPirarucu
650 $aPiscicultura
650 $aPolimorfismo genético
650 $aRecurso genético
650 $aReprodução
653 $aAraguaia
653 $aSolimões
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Registro original: |
Embrapa Pesca e Aquicultura (CNPASA) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sul. Para informações adicionais entre em contato com cppsul.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pecuária Sul. |
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Data corrente: |
03/02/2021 |
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Data da última atualização: |
03/02/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FERREIRA, J. S. de A.; FERREIRA, A. P. L.; PEREZ, N. B. |
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Afiliação: |
Jean Samarone de Almeida Ferreira, UNIPAMPA; Ana Paula Lüdtke Ferreira, UNIPAMPA; NAYLOR BASTIANI PEREZ, CPPSUL. |
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Título: |
A hidden Markov chain approach to crop yield forecasting. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
International Journal on Computer Science and Information Systems, v. 15, n. 2, p. 148-160, 2020. |
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ISSN: |
1646-3692 |
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Idioma: |
Inglês |
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Conteúdo: |
Prediction of harvest yield is an important and challenging problem. Attempts to solve this problem rely usually rely on regression techniques highly dependent on local factors. This paper presents a hidden Markov model approach for forecasting weight production. The model can deal with any culture or provided data. Results show that the model can capture both spatial and temporal harvest variability. Model analysis can help determine causes of variability, differently from regression or more straightforward Markov chain approaches. The resulting structure can benefit from statistical techniques for model tuning and model fitting. |
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Palavras-Chave: |
Cadeia de Markov. |
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Thesagro: |
Agricultura de Precisão; Colheita. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01236naa a2200193 a 4500
001 2129773
005 2021-02-03
008 2020 bl uuuu u00u1 u #d
022 $a1646-3692
100 1 $aFERREIRA, J. S. de A.
245 $aA hidden Markov chain approach to crop yield forecasting.$h[electronic resource]
260 $c2020
520 $aPrediction of harvest yield is an important and challenging problem. Attempts to solve this problem rely usually rely on regression techniques highly dependent on local factors. This paper presents a hidden Markov model approach for forecasting weight production. The model can deal with any culture or provided data. Results show that the model can capture both spatial and temporal harvest variability. Model analysis can help determine causes of variability, differently from regression or more straightforward Markov chain approaches. The resulting structure can benefit from statistical techniques for model tuning and model fitting.
650 $aAgricultura de Precisão
650 $aColheita
653 $aCadeia de Markov
700 1 $aFERREIRA, A. P. L.
700 1 $aPEREZ, N. B.
773 $tInternational Journal on Computer Science and Information Systems$gv. 15, n. 2, p. 148-160, 2020.
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