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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
22/07/2015 |
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Actualizado : |
14/10/2019 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
GERMÁN, S. |
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Afiliación : |
SILVIA ELISA GERMAN FAEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Breeding malting barley under stress conditions in South America. |
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Fecha de publicación : |
2004 |
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Fuente / Imprenta : |
Czech Journal of Genetics and Plant Breeding, v. 40, n. 4, p. 140-147. |
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DOI : |
10.17221/3713-CJGPB |
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Idioma : |
Inglés |
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Contenido : |
Abstract: The annual average area sown with barley (Hordeum vulgare) in South America during 1999–2003 was 795 000 ha. In Argentina, Brazil, Chile and Uruguay, two-rowed spring cultivars are used mostly for malt production. Research has been developed in private malting companies and official institutions supported by the industry. In Argentina, tolerance to drought and heat stress during grain filling are important in drier areas. Yield and malt extract had been improved in cultivars released from 1940 to 1998. In Brazil, progress in grain yield, grain size,malting quality, early maturity, and resistance to net blotch, powdery mildew, and leaf rust has been achieved by EMBRAPA and malting companies. Higher tolerance to soil acidity and resistance to spot blotch are required. Since 1976, malting barley breeding in INIA-Chile has improved grain yield, grain size, beer production efficiency, and resistance to scald, net blotch, stripe rust, and leaf rust. Uruguay produces high quality malt exported mainly to Brazil. Malting companies have released locally bred and introduced cultivars since the early 1970’s. Initiated in
1988, INIA-Uruguay breeding program has improved yield, malting quality, and lodging and disease resistance. Fusarium head blight is a new challenge for research in Brazil and Uruguay. Information regarding malting barley production, the most important stresses in different areas of production, and breeding progress under South American conditions is provided. |
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Palabras claves : |
AMÉRICA DEL SUR; CHILE (PAÍS); CONDICIONES DE ESTRÉS; PLANT BREEDING; STRESS CONDITIONS. |
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Thesagro : |
ARGENTINA; BRASIL; CEBADA CERVECERA; CHILE; FITOMEJORAMIENTO; HORDEUM VULGARE; URUGUAY. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02284naa a2200277 a 4500
001 1053131
005 2019-10-14
008 2004 bl uuuu u00u1 u #d
024 7 $a10.17221/3713-CJGPB$2DOI
100 1 $aGERMÁN, S.
245 $aBreeding malting barley under stress conditions in South America.$h[electronic resource]
260 $c2004
520 $aAbstract: The annual average area sown with barley (Hordeum vulgare) in South America during 1999–2003 was 795 000 ha. In Argentina, Brazil, Chile and Uruguay, two-rowed spring cultivars are used mostly for malt production. Research has been developed in private malting companies and official institutions supported by the industry. In Argentina, tolerance to drought and heat stress during grain filling are important in drier areas. Yield and malt extract had been improved in cultivars released from 1940 to 1998. In Brazil, progress in grain yield, grain size,malting quality, early maturity, and resistance to net blotch, powdery mildew, and leaf rust has been achieved by EMBRAPA and malting companies. Higher tolerance to soil acidity and resistance to spot blotch are required. Since 1976, malting barley breeding in INIA-Chile has improved grain yield, grain size, beer production efficiency, and resistance to scald, net blotch, stripe rust, and leaf rust. Uruguay produces high quality malt exported mainly to Brazil. Malting companies have released locally bred and introduced cultivars since the early 1970’s. Initiated in 1988, INIA-Uruguay breeding program has improved yield, malting quality, and lodging and disease resistance. Fusarium head blight is a new challenge for research in Brazil and Uruguay. Information regarding malting barley production, the most important stresses in different areas of production, and breeding progress under South American conditions is provided.
650 $aARGENTINA
650 $aBRASIL
650 $aCEBADA CERVECERA
650 $aCHILE
650 $aFITOMEJORAMIENTO
650 $aHORDEUM VULGARE
650 $aURUGUAY
653 $aAMÉRICA DEL SUR
653 $aCHILE (PAÍS)
653 $aCONDICIONES DE ESTRÉS
653 $aPLANT BREEDING
653 $aSTRESS CONDITIONS
773 $tCzech Journal of Genetics and Plant Breeding$gv. 40, n. 4, p. 140-147.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
18/12/2018 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LOURENÇO, D. A. L.; FRAGOMENI, B.; LEGARRA, A.; AGUILAR, I.; LAWLOR, T. J. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Single-step genomic evaluations with 570K genotyped animals in US Holsteins. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Interbull Bulletin, 2015, v. 49, p. 85-89. |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a large number of genotyped animals. MenosABSTRACT.
The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a lar... Presentar Todo |
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Palabras claves : |
APY; SSGBLUP; VALIDATION. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12203/1/1382-2378-1-PB.pdf
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Marc : |
LEADER 02171naa a2200241 a 4500
001 1012457
005 2018-12-18
008 2015 bl uuuu u00u1 u #d
100 1 $aMASUDA, Y.
245 $aSingle-step genomic evaluations with 570K genotyped animals in US Holsteins.$h[electronic resource]
260 $c2015
520 $aABSTRACT. The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a large number of genotyped animals.
653 $aAPY
653 $aSSGBLUP
653 $aVALIDATION
700 1 $aMISZTAL, I.
700 1 $aTSURUTA, S.
700 1 $aLOURENÇO, D. A. L.
700 1 $aFRAGOMENI, B.
700 1 $aLEGARRA, A.
700 1 $aAGUILAR, I.
700 1 $aLAWLOR, T. J.
773 $tInterbull Bulletin, 2015$gv. 49, p. 85-89.
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