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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
28/06/2021 |
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Actualizado : |
02/07/2021 |
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Tipo de producción científica : |
Poster |
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Autor : |
GARCIA-ROCHE, M.; CAÑIBE, G.; TALMÓN, D.; MENDOZA, A.; CASSINA, A.; QUIJANO, C.; CARRIQUIRY, M. |
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Afiliación : |
MERCEDES GARCIA-ROCHE, Departamento de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la República, Uruguay.; GUILLERMO CAÑIBE, Departamento de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la República, Uruguay.; DANIEL TALMÓN, Departamento de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la República, Uruguay.; ALEJANDRO FRANCISCO MENDOZA AGUIAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ADRIANA CASSINA, Centro de Investigaciones Biomédicas, Facultad de Medicina, Universidad de la República, Uruguay.; CELIA QUIJANO, Centro de Investigaciones Biomédicas, Facultad de Medicina, Universidad de la República, Uruguay.; MARIANA CARRIQUIRY, Departamento de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la República, Uruguay. |
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Título : |
Abundancia mitocondrial hepática en dos genotipos holstein en pastoreo. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
In: Jornadas Uruguayas de Buiatría, 48., 2021. Paysandú, Uruguay: Centro Médico Veterinario de Paysandú; Filial de la Sociedad de Medicina Veterinaria del Uruguaya; Sociedad Uruguaya de Buiatría, 31 de Mayo al 4 de Junio 2021. [Poster]. |
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Páginas : |
p.251-253. |
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Idioma : |
Español |
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Contenido : |
Resumen: El objetivo de este trabajo fue determinar la abundancia mitocondrial hepática en dos genotipos Holstein en un sistema pastoril durante lactancia media-tardía. Para este trabajo se utilizaron vacas del genotipo Holstein neozelandés y del genotipo Holstein norteamericano, las mismas pastorearon una pastura mixta de Medicago sativa y Dactylis glomerata y suplementadas con concentrados y reservas forrajeras. Se tomaron biopsias de hígado y
se analizó la expresión génica del factor de transcripción peroxisome proliferator-activated receptor gamma coactivator 1-alpha (controlador maestro de la biogénesis mitocondrial; PPARGC1A), la actividad citrato sintasa y la relación ADN mitocondrial / ADN nuclear. No se encontraron diferencias entre genotipos en la expresión de PPARGC1A, sin embargo, tanto la actividad citrato sintasa como la relación ADN mitocondrial / ADN nuclear fueron mayores para el genotipo Holstein neozelandés. Una mayor abundancia mitocondrial es clave para el mantenimiento de la homeostasis energética, elemento crucial para la mejor adaptación a los cambios fisiológicos.
Summary:The aim of this work was to determine the hepatic mitochondrial abundance in two Holstein genotypes in a pastoral system during mid-late lactation. For this study, cows of the New Zealand Holstein genotype and the North American Holstein genotype were used. Cows grazed a mixed pasture of Medicago sativa and Dactylis glomerata and were supplemented with concentrate and forage reserves. Liver biopsies were taken and the gene expression
of the peroxisome proliferator-activated receptor gamma coactivator 1-alpha – (a master regular of mitochondrial biogenesis, PPARGC1A) transcription factor, the citrate synthase activity, and the mitochondrial DNA / nuclear DNA ratio were analyzed. No differences were found be#2;tween genotypes in the expression of PPAR#2;GC1A, however, both citrate synthase activity and the mitochondrial DNA / nuclear DNA ra#2;tio were higher for the New Zealand Holstein
genotype. Greater mitochondrial abundance is key to maintaining energy homeostasis, a crucial element for a better adaptation to physiolo#2;gical changes. MenosResumen: El objetivo de este trabajo fue determinar la abundancia mitocondrial hepática en dos genotipos Holstein en un sistema pastoril durante lactancia media-tardía. Para este trabajo se utilizaron vacas del genotipo Holstein neozelandés y del genotipo Holstein norteamericano, las mismas pastorearon una pastura mixta de Medicago sativa y Dactylis glomerata y suplementadas con concentrados y reservas forrajeras. Se tomaron biopsias de hígado y
se analizó la expresión génica del factor de transcripción peroxisome proliferator-activated receptor gamma coactivator 1-alpha (controlador maestro de la biogénesis mitocondrial; PPARGC1A), la actividad citrato sintasa y la relación ADN mitocondrial / ADN nuclear. No se encontraron diferencias entre genotipos en la expresión de PPARGC1A, sin embargo, tanto la actividad citrato sintasa como la relación ADN mitocondrial / ADN nuclear fueron mayores para el genotipo Holstein neozelandés. Una mayor abundancia mitocondrial es clave para el mantenimiento de la homeostasis energética, elemento crucial para la mejor adaptación a los cambios fisiológicos.
Summary:The aim of this work was to determine the hepatic mitochondrial abundance in two Holstein genotypes in a pastoral system during mid-late lactation. For this study, cows of the New Zealand Holstein genotype and the North American Holstein genotype were used. Cows grazed a mixed pasture of Medicago sativa and Dactylis glomerata and were supplemented with concentrate and forage reser... Presentar Todo |
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Thesagro : |
PRODUCCION LECHERA; VACAS. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15707/1/JUB-no.48-2021.p.251-253.Mendoza.pdf
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Marc : |
LEADER 02991nam a2200217 a 4500
001 1062166
005 2021-07-02
008 2021 bl uuuu u00u1 u #d
100 1 $aGARCIA-ROCHE, M.
245 $aAbundancia mitocondrial hepática en dos genotipos holstein en pastoreo.$h[electronic resource]
260 $aIn: Jornadas Uruguayas de Buiatría, 48., 2021. Paysandú, Uruguay: Centro Médico Veterinario de Paysandú; Filial de la Sociedad de Medicina Veterinaria del Uruguaya; Sociedad Uruguaya de Buiatría, 31 de Mayo al 4 de Junio 2021. [Poster].$c2021
300 $ap.251-253.
520 $aResumen: El objetivo de este trabajo fue determinar la abundancia mitocondrial hepática en dos genotipos Holstein en un sistema pastoril durante lactancia media-tardía. Para este trabajo se utilizaron vacas del genotipo Holstein neozelandés y del genotipo Holstein norteamericano, las mismas pastorearon una pastura mixta de Medicago sativa y Dactylis glomerata y suplementadas con concentrados y reservas forrajeras. Se tomaron biopsias de hígado y se analizó la expresión génica del factor de transcripción peroxisome proliferator-activated receptor gamma coactivator 1-alpha (controlador maestro de la biogénesis mitocondrial; PPARGC1A), la actividad citrato sintasa y la relación ADN mitocondrial / ADN nuclear. No se encontraron diferencias entre genotipos en la expresión de PPARGC1A, sin embargo, tanto la actividad citrato sintasa como la relación ADN mitocondrial / ADN nuclear fueron mayores para el genotipo Holstein neozelandés. Una mayor abundancia mitocondrial es clave para el mantenimiento de la homeostasis energética, elemento crucial para la mejor adaptación a los cambios fisiológicos. Summary:The aim of this work was to determine the hepatic mitochondrial abundance in two Holstein genotypes in a pastoral system during mid-late lactation. For this study, cows of the New Zealand Holstein genotype and the North American Holstein genotype were used. Cows grazed a mixed pasture of Medicago sativa and Dactylis glomerata and were supplemented with concentrate and forage reserves. Liver biopsies were taken and the gene expression of the peroxisome proliferator-activated receptor gamma coactivator 1-alpha – (a master regular of mitochondrial biogenesis, PPARGC1A) transcription factor, the citrate synthase activity, and the mitochondrial DNA / nuclear DNA ratio were analyzed. No differences were found be#2;tween genotypes in the expression of PPAR#2;GC1A, however, both citrate synthase activity and the mitochondrial DNA / nuclear DNA ra#2;tio were higher for the New Zealand Holstein genotype. Greater mitochondrial abundance is key to maintaining energy homeostasis, a crucial element for a better adaptation to physiolo#2;gical changes.
650 $aPRODUCCION LECHERA
650 $aVACAS
700 1 $aCAÑIBE, G.
700 1 $aTALMÓN, D.
700 1 $aMENDOZA, A.
700 1 $aCASSINA, A.
700 1 $aQUIJANO, C.
700 1 $aCARRIQUIRY, M.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
05/11/2020 |
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Actualizado : |
05/09/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
TREVISAN, R.; PÉREZ, O.; SCHMITZ, N.; DIERS, B.; MARTIN, N |
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Afiliación : |
RODRIGO TREVISAN, Department of Crop Sciences, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.; OSVALDO MARTIN PEREZ GONZALEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; NATHAN SCHMITZ, GDM Seeds Inc., Gibson City, IL 60936, USA.; BRIAN DIERS, Department of Crop Sciences, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA.; NICOLAS MARTIN, Department of Crop Sciences, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA. |
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Título : |
High-throughput phenotyping of soybean maturity using time Series UAV imagery and convolutional neural networks. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Remote Sensing, 2020, 12(21), 3617. OPEN ACCESS. DOI: https://doi.org/10.3390/rs12213617. |
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DOI : |
10.3390/rs12213617 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 18 September 2020 / Revised: 28 October 2020 / Accepted: 29 October 2020 / Published: 4 November 2020. |
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Contenido : |
Abstract: Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges.Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies
have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were
developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture developed solves limitations of previous research and can be used at scale in commercial breeding programs. MenosAbstract: Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges.Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies
have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were
developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture developed solves limitations of previ... Presentar Todo |
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Palabras claves : |
GLYCINE MAX (L.) MERR; MACHINE LEARNING; PHYSIOLOGICAL MATURITY; PLANT BREEDING; SOYBEAN PHENOLOGY. |
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Thesagro : |
MEJORAMIENTO GENETICO DE PLANTAS; SOJA. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/14789/1/remotesensing-12-03617.pdf
https://www.mdpi.com/2072-4292/12/21/3617/htm#
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Marc : |
LEADER 02555naa a2200277 a 4500
001 1061456
005 2022-09-05
008 2020 bl uuuu u00u1 u #d
024 7 $a10.3390/rs12213617$2DOI
100 1 $aTREVISAN, R.
245 $aHigh-throughput phenotyping of soybean maturity using time Series UAV imagery and convolutional neural networks.$h[electronic resource]
260 $c2020
500 $aArticle history: Received: 18 September 2020 / Revised: 28 October 2020 / Accepted: 29 October 2020 / Published: 4 November 2020.
520 $aAbstract: Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges.Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture developed solves limitations of previous research and can be used at scale in commercial breeding programs.
650 $aMEJORAMIENTO GENETICO DE PLANTAS
650 $aSOJA
653 $aGLYCINE MAX (L.) MERR
653 $aMACHINE LEARNING
653 $aPHYSIOLOGICAL MATURITY
653 $aPLANT BREEDING
653 $aSOYBEAN PHENOLOGY
700 1 $aPÉREZ, O.
700 1 $aSCHMITZ, N.
700 1 $aDIERS, B.
700 1 $aMARTIN, N
773 $tRemote Sensing, 2020, 12(21), 3617. OPEN ACCESS. DOI: https://doi.org/10.3390/rs12213617.
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