Ainfo Consulta

Catálogo de Información Agropecuaria

Bibliotecas INIA

 

Botón Actualizar


Botón Actualizar

Registro completo
Biblioteca (s) :  INIA Las Brujas.
Fecha :  07/05/2021
Actualizado :  06/09/2022
Tipo de producción científica :  Artículos en Revistas Indexadas Nacionales
Autor :  GONZÁLEZ, M.; RESQUÍN, F.; BALMELLI, G.
Afiliación :  MILENA GONZÁLEZ CHAVEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE FERNANDO RESQUIN PEREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUSTAVO DANIEL BALMELLI HERNANDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay.
Título :  Performance of Eucalyptus tereticornis provenances in subtropical climate. [Comportamiento productivo de orígenes de Eucalyptus tereticornis en clima subtropical.]. [Comportamento produtivo de origens de Eucalyptus tereticornisem clima subtropical.]
Complemento del título :  Forest science and Landscape managemet.
Fecha de publicación :  2021
Fuente / Imprenta :  Agrociencia Uruguay, Apr 2021, vol. 25, no. 1, e322. DOI: https://doi.org/10.31285/AGRO.25.322
ISSN :  e-ISSN: 2730-5056
DOI :  10.31285/AGRO.25.322
Idioma :  Inglés
Notas :  Article history: Received 13 Feb 2020; Accepted 18 Nov 2020; Published 12 Apr 2021. Editor: Jaime González Talice (Universidad de la República, Montevideo, Uruguay ). Correspondence: Gustavo Balmelli - Email: gbalmelli@inia.org.uy
Contenido :  ABSTRACT. - Eucalyptus tereticornis has a wide natural geographic distribution from Papua New Guinea to South Australia (6º-38º S), therefore, it is expected the existence of important differences among provenances. Although differ-ences in performance among provenances have been reported in several countries, the existing information is insufficient to allow the choice of the most appropriate provenance as a source of seeds for commercial planta-tions for humid subtropical climates. In order to evaluate the performance of 20 provenances of E. tereticornisin Uruguay and to generate information that contributes to the identification of the best provenances for humid subtropical climates, survival, individual tree volume, stem straightness and forking were assessed at 9-years-old in 4 sites in the center, north and northeast of Uruguay. Significant differences among provenances for all traits and significant provenance by site interaction for survival, individual tree volume and forking were found. No provenance was best in all sites. The Buckenbowra provenance had simultaneously high volume and sur-vival. The absence of a clear regionalization, coupled with a significant provenance-by site interaction, suggests that local evaluation of different provenances is essential to identify appropriate seed sources, both for tree breeding and for use in commercial plantations. .-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-. RESUMEN. - Eucalyptus tereticornis es una especie que t... Presentar Todo
Palabras claves :  Forking; Genotype by environment interaction; Interação genótipo-ambiente; Presença de bifurcações; Retidão do fuste; Sobrevivência; Stem straightness; Survival; Volume.
Thesagro :  INTERACCION GENOTIPO POR AMBIENTE; PRESENCIA DE BIFURCACIONES; RECTITUD DE FUSTE; SUPERVIVENCIA; VOLUMEN.
Asunto categoría :  K01 Ciencias forestales - Aspectos generales
URL :  http://www.ainfo.inia.uy/digital/bitstream/item/16742/1/Agrociencia-UY-2021-25-N1-322.pdf
Marc :  Presentar Marc Completo
Registro original :  INIA Las Brujas (LB)
Biblioteca Identificación Origen Tipo / Formato Clasificación Cutter Registro Volumen Estado
LB102652 - 1PXIAP - DDPP/AGROCIENCIA URUGUAY/2021 (1)

Volver


Botón Actualizar


Botón Actualizar

Registro completo
Biblioteca (s) :  INIA La Estanzuela.
Fecha actual :  05/11/2020
Actualizado :  05/09/2022
Tipo de producción científica :  Artículos en Revistas Indexadas Internacionales
Circulación / Nivel :  Internacional - --
Autor :  TREVISAN, R.; PÉREZ, O.; SCHMITZ, N.; DIERS, B.; MARTIN, N
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.
Título :  High-throughput phenotyping of soybean maturity using time Series UAV imagery and convolutional neural networks.
Fecha de publicación :  2020
Fuente / Imprenta :  Remote Sensing, 2020, 12(21), 3617. OPEN ACCESS. DOI: https://doi.org/10.3390/rs12213617.
DOI :  10.3390/rs12213617
Idioma :  Inglés
Notas :  Article history: Received: 18 September 2020 / Revised: 28 October 2020 / Accepted: 29 October 2020 / Published: 4 November 2020.
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 previ... Presentar Todo
Palabras claves :  GLYCINE MAX (L.) MERR; MACHINE LEARNING; PHYSIOLOGICAL MATURITY; PLANT BREEDING; SOYBEAN PHENOLOGY.
Thesagro :  MEJORAMIENTO GENETICO DE PLANTAS; SOJA.
Asunto categoría :  F30 Genética vegetal y fitomejoramiento
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#
Marc :  Presentar Marc Completo
Registro original :  INIA La Estanzuela (LE)
Biblioteca Identificación Origen Tipo / Formato Clasificación Cutter Registro Volumen Estado
LE103236 - 1PXIAP - DDPP/Remote Sensing/2020
Volver
Expresión de búsqueda válido. Check!
 
 

Embrapa
Todos los derechos reservados, conforme Ley n° 9.610
Política de Privacidad
Área Restricta

Instituto Nacional de Investigación Agropecuaria
Andes 1365 - piso 12 CP 11100 Montevideo, Uruguay
Tel: +598 2902 0550 Fax: +598 2902 3666
bibliotecas@inia.org.uy

Valid HTML 4.01 Transitional