|
|
Registro completo
|
Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
05/11/2020 |
Actualizado : |
05/09/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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 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 |
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 : |
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.
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA La Estanzuela (LE) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
Registros recuperados : 13 | |
2. | | BENTANCOR, L.; RUIZ, A.; CASTAÑO, V.; DURÁN, P. Medición de agua y transmisión de datos en sistemas de riego por gravedad. ln: JORNADA ANUAL ARROZ, 2016, INIA TREINTA Y TRES, TREINTA Y TRES, UY. Arroz: resultados experimentales 2015-2016. Treinta y Tres, (Uruguay): INIA, 2016. cap. 2, p. 23-25. (INIA Serie Actividades de Difusión; 765)Biblioteca(s): INIA Tacuarembó; INIA Treinta y Tres. |
| |
5. | | BENTANCOR, L.; HERNÁNDEZ, J.; DEL PINO, A.; CALIFRA, A.; RESQUÍN, F.; GONZÁLEZ-BARRIOS, P. Evaluation of the biomass production, energy yield and nutrient removal of Eucalyptus dunnii Maiden grown in short rotation coppice under two initial planting densities and harvest systems. Biomass and Bioenergy, 2019, v. 122, p. 165-174. Article history: Received 31 August 2018 // Received in revised form 18 January 2019 // Accepted 21 January 2019.Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
Biblioteca(s): INIA Tacuarembó. |
| |
7. | | BENTANCOR, L.; HERNÁNDEZ, J.; DEL PINO, A.; CALIFRA, A.; GONZÁLEZ, P.; RESQUÍN, F. Nutrient removal with harvest of biomass of Eucalyptus dunnii maiden grown in short rotation coppice for bioenergy. In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo: FAGRO, 2019. p. 71 Trabajo originalmente publicado en: Hernández J., Bentancor L., del Pino A., Califra A., González P. & Resquin F. 2018. 21st World Soil Science Congress (Presenta trabajo, 12/08/2018). Nutrient extraction by the biomass of Eucalypts...Tipo: Abstracts/Resúmenes |
Biblioteca(s): INIA Tacuarembó. |
| |
8. | | GIMÉNEZ, L.; PUPPO, L.; BENTANCOR, L.; HAYASHI, R.; SAWCHIK, J.; GARCIA, C. (Ed.). Riego en cultivos y pasturas. 3er. Seminario Internacional, 2014, Paysandú (Uruguay). Montevideo : INIA, 2014. 137 p. Instituciones: Grupo de Desarrollo de Riego (GDR), Facultad de Agronomía (FAGRO); Instituto Nacional de Investigación Agropecuaria (INIA). - Edición a cargo de: Luis Giménez, Lucía Puppo, Lisette Bentancor, Raquel Hayashi, Jorge Sawchik,...Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
| |
9. | | RESQUÍN, F.; BENTANCOR, L.; CARRASCO-LETELIER, L.; RACHID, C.; NAVARRO-CERRILLO, R.M. Rotation length of intensive Eucalyptus plantations: how it impacts on productive and energy sustainability. Biomass and Bioenergy, 2022, Volume 166, article 106607. doi: https://doi.org/10.1016/j.biombioe.2022.106607 Article history: Received 11 April 2022; Received in revised form 31 August 2022; Accepted 18 September 2022; To be published November 2022.
Corresponding author: Fernando Resquin, Route 5 km 368, CP45000, INIA Tacuarembó, Uruguay. E-mail...Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
Biblioteca(s): INIA Las Brujas. |
| |
10. | | MÁRMOL, S.; BENTANCOR, L.; FRANCIA, M.; HIRIGOYEN, A.; PÉREZ BIDEGAIN, M.; BLANCO, G.; PÉREZ, M.M. Verification of deep root exploration of Eucalyptus grandis to permian sedimentary rocks of northeastern Uruguay. [Verificación de exploración radicular profunda de Eucalyptus grandishasta rocas sedimentarias pérmicas del noreste uruguayo]. [Verificação da exploração de raízes profundas de Eucalyptus grandisaté rochas sedimentares Permianas do nordeste do Uruguai]. Agrociencia Uruguay, 2022, vol. 26, NE1, e508. https://doi.org/10.31285/AGRO.26.508 Article history: Received 19 Jan 2021, Accepted 13 Nov 2021, Published 27 May 2022.
Special issue in homage to Prof. Jorge Bossi (1934-2020). [Número especial en homenaje al Prof. Jorge Bossi].
Editores: Antonella Celio, Universidad de la...Tipo: Artículos en Revistas Indexadas Nacionales | Circulación / Nivel : Nacional - -- |
Biblioteca(s): INIA Las Brujas. |
| |
11. | | CASTILLO, A.; ASHFIELD, R.; BENTANCOR, M.; BENTANCOR, L.; BONILLA, B.; CEPPA, M.; FRANCO, R.; SILVA, N.; CABRERA, D.; RODRIGUEZ, P.; ZOPPOLO, R. Micropropagación de plantas en biorreactores de inmersión temporal (BIT). Revista INIA Uruguay, 2019, no. 56, p. 88-91. (Revista INIA; 56)Tipo: Artículos en Revistas Agropecuarias |
Biblioteca(s): INIA Treinta y Tres. |
| |
12. | | DELPIAZZO, R.; BARCELLOS, M.; BARROS, S.; BENTANCOR, L.; FRAGA, M.; GIL, J.; IRAOLA, G.; MORSELLA, C.; PAOLICCHI, F.; PÉREZ, R.; RIET-CORREA, F.; SANGUINETTI, M.; SILVA, A.; SILVEIRA, C.S.; CALLEROS, L. Accurate and fast identification of Campylobacter fetus in bulls by real-time PCR targeting a 16S rRNA gene sequence. Veterinary and Animal Science, January 2021, vol.11 no. 100165, 5 p. OPEN ACCESS. Doi: https://doi.org/10.1016/j.vas.2020.100163 Article history: Received 21 October 2020 / Received in revised form 20 December 2020 / Accepted 22 December 2020 / available online 24 December 2020.
Corresponding author: laurabet@higiene.edu.uyTipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
Biblioteca(s): INIA Treinta y Tres. |
| |
13. | | SILVEIRA, L.; CHRETIES, CH.; ALONSO, J.; AMORÍN, C.; DE IZAGUIRRE, P.; CRISCI, M.; SYMONDS, S.; MARTÍNEZ, L.; GARCÍA, M.; GARCÍA, F.; DELGADO, S.; CLÉRICI, C.; BENTANCOR, L.; HILL, M.; ALLIAUME, F.; CABRAL, P.; AUDICIO, P.; IROUMÉ, A.; HUBER, A.; SCHIPILOV, A. Efectos de la actividad forestal sobre los recursos suelos y aguas Montevideo (UY): INIA, 2011. 41 p. (Serie FPTA-INIA; 32) "Proyecto FPTA 210: "Efecto de la actividad forestal sobre los recursos suelos y aguas, en microcuencas similares sometidas a distinto manejo". Período de Ejecución: Mar. 2007-Jun. 2010Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
Registros recuperados : 13 | |
|
Expresión de búsqueda válido. Check! |
|
|