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 | Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha : |
21/02/2014 |
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Actualizado : |
24/09/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
GALETTA, M.A.; REINA, L.; RESQUÍN, F.; MANTERO, C.; GONZÁLEZ-PÉREZ, J.A.; ALMENDROS, G.; MENÉNDEZ, M.P.; GONZÁLEZ-VILADA, F.J. |
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Afiliación : |
Universidad de la República (UdelaR)/ Facultad de Química.; Universidad de la República (UdelaR)/ Facultad de Química.; JOSE FERNANDO RESQUIN PEREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Universidad de la República (UdelaR)/ Facultad de Agronomía.; Instituto de Recursos Naturales y Agrobiología de Sevilla, IRNAS-CSIC, Seville, Spaine.; SpaineMNCN-CSIC, Madrid, Spain.; Universidad de la República (UdelaR)/ Facultad de Química.; Instituto de Recursos Naturales y Agrobiología de Sevilla, IRNAS-CSIC, Seville, Spain. |
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Título : |
Chemometric appraisal of lignin pyrolytic assemblages from Eucalyptus woods relevant for pulping in Uruguay. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Journal of Analytical and Applied Pyrolysis, 2014, v. 109, p. 296-303. |
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DOI : |
10.1016/j.jaap.2014.08.001 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 5 January 2014 // Accepted 2 August 2014 // Available online 13 August 2014. |
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Contenido : |
Analytical pyrolysis (Py-GC/MS) at 500°C was applied to study wood composition of Eucalyptus species(Eucalyptus grandis, Eucalyptus dunnii and Eucalyptus benthamii) which are relevant for pulping inUruguay. Multivariate data treatments mainly principal component analysis and discriminant analy-sis were used to explore differences between the original wood cultivars. Multivariate analyses withautomatic backwards variable selection indicated that simplified methoxyphenol patterns (up to 10compounds) are sufficient for wood discrimination in terms of species and geographical origin butalso with purposes of forecasting the ease of delignification of the resulting pulps measured as activealkali. No additional chemotaxonomical accuracy was achieved when the data sets were enlarged withcarbohydrate-derived products. On the other side, discriminant or forecasting models (partial leastsquares and multiple linear regression) were much less significant when based on individual diag-nostic compounds, groups of compounds, or the classical syringyl-to-guaiacyl (S/G) ratio. Principalcomponent analysis indicated that the variability in lignin composition due to bioclimatic variations(spatial replications) was more significant than that due to phylogenetic differences (species andcultivars). |
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Palabras claves : |
ANALYTICAL PYROLYSIS; DISCRIMINANT ANALYSIS; FORESTACIÓN; LIGNIN METHOXYPHENOLS; MULTIPLE REGRESSION MODELS; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENT ANALYSIS. |
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Asunto categoría : |
K10 Producción forestal |
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Marc : |
LEADER 02390naa a2200313 a 4500
001 1017467
005 2019-09-24
008 2014 bl uuuu u00u1 u #d
024 7 $a10.1016/j.jaap.2014.08.001$2DOI
100 1 $aGALETTA, M.A.
245 $aChemometric appraisal of lignin pyrolytic assemblages from Eucalyptus woods relevant for pulping in Uruguay.$h[electronic resource]
260 $c2014
500 $aArticle history: Received 5 January 2014 // Accepted 2 August 2014 // Available online 13 August 2014.
520 $aAnalytical pyrolysis (Py-GC/MS) at 500°C was applied to study wood composition of Eucalyptus species(Eucalyptus grandis, Eucalyptus dunnii and Eucalyptus benthamii) which are relevant for pulping inUruguay. Multivariate data treatments mainly principal component analysis and discriminant analy-sis were used to explore differences between the original wood cultivars. Multivariate analyses withautomatic backwards variable selection indicated that simplified methoxyphenol patterns (up to 10compounds) are sufficient for wood discrimination in terms of species and geographical origin butalso with purposes of forecasting the ease of delignification of the resulting pulps measured as activealkali. No additional chemotaxonomical accuracy was achieved when the data sets were enlarged withcarbohydrate-derived products. On the other side, discriminant or forecasting models (partial leastsquares and multiple linear regression) were much less significant when based on individual diag-nostic compounds, groups of compounds, or the classical syringyl-to-guaiacyl (S/G) ratio. Principalcomponent analysis indicated that the variability in lignin composition due to bioclimatic variations(spatial replications) was more significant than that due to phylogenetic differences (species andcultivars).
653 $aANALYTICAL PYROLYSIS
653 $aDISCRIMINANT ANALYSIS
653 $aFORESTACIÓN
653 $aLIGNIN METHOXYPHENOLS
653 $aMULTIPLE REGRESSION MODELS
653 $aPARTIAL LEAST SQUARES REGRESSION
653 $aPRINCIPAL COMPONENT ANALYSIS
700 1 $aREINA, L.
700 1 $aRESQUÍN, F.
700 1 $aMANTERO, C.
700 1 $aGONZÁLEZ-PÉREZ, J.A.
700 1 $aALMENDROS, G.
700 1 $aMENÉNDEZ, M.P.
700 1 $aGONZÁLEZ-VILADA, F.J.
773 $tJournal of Analytical and Applied Pyrolysis, 2014$gv. 109, p. 296-303.
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INIA Tacuarembó (TBO) |
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
09/09/2014 |
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Actualizado : |
23/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; EZRA, E.; RON, M.; SHIRAK, A.; WELLER, J.I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Journal of Dairy Science, 2014, v.97, no.3, p.1742-1752. OPEN ACCESS. |
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ISSN : |
0022-0302 |
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DOI : |
10.3168/jds.2013-6916 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received September 10, 2013. / Accepted December 6, 2013. |
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Contenido : |
ABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy.
© 2014 American Dairy Science Association. MenosABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coe... Presentar Todo |
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Thesagro : |
MEJORAMIENTO GENÉTICO ANIMAL; MODELOS MATEMÁTICOS; SELECCIÓN DE GENOTIPOS; SELECCIÓN GENÓMICA. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3043/1/Aguilar-I.-2014-Jr.Dairy-Sci.-v.973-p.1742-1752.pdf
https://www.journalofdairyscience.org/article/S0022-0302(14)00052-6/pdf
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Marc : |
LEADER 03270naa a2200289 a 4500
001 1050061
005 2019-10-23
008 2014 bl uuuu u00u1 u #d
022 $a0022-0302
024 7 $a10.3168/jds.2013-6916$2DOI
100 1 $aLOURENCO, D.A.L.
245 $aMethods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses.$h[electronic resource]
260 $c2014
500 $aArticle history: Received September 10, 2013. / Accepted December 6, 2013.
520 $aABSTRACTS. Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy. © 2014 American Dairy Science Association.
650 $aMEJORAMIENTO GENÉTICO ANIMAL
650 $aMODELOS MATEMÁTICOS
650 $aSELECCIÓN DE GENOTIPOS
650 $aSELECCIÓN GENÓMICA
700 1 $aMISZTAL, I.
700 1 $aTSURUTA, S.
700 1 $aAGUILAR, I.
700 1 $aEZRA, E.
700 1 $aRON, M.
700 1 $aSHIRAK, A.
700 1 $aWELLER, J.I.
773 $tJournal of Dairy Science, 2014$gv.97, no.3, p.1742-1752. OPEN ACCESS.
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