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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
08/06/2022 |
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Actualizado : |
08/06/2022 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
CAL, A.; PRECIOZZI, J.; MUSÉ, PABLO |
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Afiliación : |
ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JAVIER PRECIOZZI, IIE, Facultad de Ingeniería, Universidad de la Republica, Uruguay; Digital Sense, Uruguay; PABLO MUSÉ, IIE, Facultad de Ingeniería, Universidad de la Republica, Uruguay. |
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Título : |
Automatic Classification of Agricultural Summer Crops in Uruguay. [Conference paper] |
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Complemento del título : |
IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021, Brussels (Belgium) 12-16 July 2021. Code 176845. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
International Geoscience and Remote Sensing Symposium (IGARSS), 2021, pages 6520 - 6523. doi: http://doi.org/10.1109/IGARSS47720.2021.9555035 |
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DOI : |
10.1109/IGARSS47720.2021.9555035 |
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Idioma : |
Inglés |
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Notas : |
Publisher: Institute of Electrical and Electronics Engineers Inc. -- Sponsors: The Institute of Electrical and Electronics Engineers Geoscience and Remote Sensing Society (GRSS). |
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Contenido : |
ABSTRACT - In this work, we present a study for the classification of summer crops on a nationwide perspective. Using both optical and radar satellite images, we implement a time-series classification algorithm using XGBoost. Two datasets with farm-level information were used: one with ground truth obtained directly from farmers' production and the other with declared crops obtained at the government level. The crops analyzed were corn, soybean, sorghum, and pastures. When trained and validated with ground truth, the classifier yields a F1-Score performance of 99% for soybean, and values higher than 80% for corn and sorghum. Predictions performed with this model on the dataset of declared crops lead to F1-Score values of 54, 97, and 50%, for corn, soybean, and sorghum, respectively. These low values for corn and sorghum indicate the presence of mislabeled data in that dataset, which in turns may suggest issues with the declarations provided by the farmers. ©2021 IEEE. |
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Palabras claves : |
Data fusion; K-means; Laser radar; Radar imaging; Satellites; Soil preservation; Sustainable agriculture; XGBoost. |
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Asunto categoría : |
A50 Investigación agraria |
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Marc : |
LEADER 01977nam a2200253 a 4500
001 1063252
005 2022-06-08
008 2021 bl uuuu u01u1 u #d
024 7 $a10.1109/IGARSS47720.2021.9555035$2DOI
100 1 $aCAL, A.
245 $aAutomatic Classification of Agricultural Summer Crops in Uruguay. [Conference paper]$h[electronic resource]
260 $aInternational Geoscience and Remote Sensing Symposium (IGARSS), 2021, pages 6520 - 6523. doi: http://doi.org/10.1109/IGARSS47720.2021.9555035$c2021
500 $aPublisher: Institute of Electrical and Electronics Engineers Inc. -- Sponsors: The Institute of Electrical and Electronics Engineers Geoscience and Remote Sensing Society (GRSS).
520 $aABSTRACT - In this work, we present a study for the classification of summer crops on a nationwide perspective. Using both optical and radar satellite images, we implement a time-series classification algorithm using XGBoost. Two datasets with farm-level information were used: one with ground truth obtained directly from farmers' production and the other with declared crops obtained at the government level. The crops analyzed were corn, soybean, sorghum, and pastures. When trained and validated with ground truth, the classifier yields a F1-Score performance of 99% for soybean, and values higher than 80% for corn and sorghum. Predictions performed with this model on the dataset of declared crops lead to F1-Score values of 54, 97, and 50%, for corn, soybean, and sorghum, respectively. These low values for corn and sorghum indicate the presence of mislabeled data in that dataset, which in turns may suggest issues with the declarations provided by the farmers. ©2021 IEEE.
653 $aData fusion
653 $aK-means
653 $aLaser radar
653 $aRadar imaging
653 $aSatellites
653 $aSoil preservation
653 $aSustainable agriculture
653 $aXGBoost
700 1 $aPRECIOZZI, J.
700 1 $aMUSÉ, PABLO
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
28/11/2018 |
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Actualizado : |
28/11/2018 |
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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 : |
SALINAS, L.M.; BALSEIRO, A.; JIRÓN, W.; PERALTA, A.; MUÑÓZ, D.; FAJARDO, J.; GAYO, E.; MARTÍNEZ, I.Z.; RIET-CORREA, F.; GARDNER, D.R.; GARCÍA MARÍN, J.F. |
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Afiliación : |
LUIS MANUEL SALINAS, Universidad Internacional Antonio de Valdivieso (UNIAV), Rivas, Nicaragua; Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain.; ANA BALSEIRO, Servicio Regional de Investigación y Desarrollo Agroalimentario (SERIDA), Centro de Biotecnología Animal, Gijón, Asturias, Spain.; WILLIAM JIRÓN, Universidad Nacional Autónoma de Nicaragua (UNAN), León, Nicaragua.; ANA PERALTA, Universidad Nacional Autónoma de Nicaragua (UNAN), León, Nicaragua.; DAVID MUÑÓZ, Universidad Nacional Autónoma de Nicaragua (UNAN), León, Nicaragua.; JORGE FAJARDO, Universidad Nacional Autónoma de Nicaragua (UNAN), León, Nicaragua.; ELENA GAYO, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain.; ILEANA ZORHAYA MARTÍNEZ, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain; Universidad Popular Autónoma del Estado de Puebla (UPAEP), Mexico.; FRANKLIN RIET-CORREA AMARAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DALE R. GARDNER, Poisonous Plant Research Laboratory, Logan, UT, United States.; JUAN FRANCISCO GARCÍA MARÍN, Facultad de Veterinaria, Universidad de León, Campus de Vegazana, León, Spain. |
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Título : |
Neurological syndrome in goats associated with Ipomoea trifida and Ipomoea carnea containing calystegines. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Toxicon, January 2019, Volume 157, Pages 8-11. |
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ISSN : |
0041-0101 |
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DOI : |
10.1016/j.toxicon.2018.11.291 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 16 September 2018 // Received in revised form 7 November 2018 // Accepted 9 November 2018 // Available online 14 November 2018.
This work was partially supported by a grant from Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria ( INIA , Spain), reference number E-RTA2013-00013-C04-04 (FEDER co-funded). |
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Contenido : |
ABSTRACT.
A disease characterized by ataxia, tremors and nystagmus had been observed in goats in Nicaragua. The main histologic lesions were loss and neuronal vacuolation of Purkinje cells and Wallerian-like degeneration mainly in the cerebellum, suggesting a glycoprotein storage disease. Ipomoea carnea and Ipomoea trifida found in the paddocks were negative for swainsonine, but contained calystegines at 0.02% and 0.06% suggesting that the disease was caused by these substances, which are competitive inhibitors of β-glucosidase and α-galactosidase activities.
© 2018 Elsevier Ltd |
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Palabras claves : |
CALYSTEGINES; GOAT; IPOMOEA CARNEA; IPOMOEA TRIFIDA; NICARAGUA; POISONING. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 01903naa a2200349 a 4500
001 1059313
005 2018-11-28
008 2018 bl uuuu u00u1 u #d
022 $a0041-0101
024 7 $a10.1016/j.toxicon.2018.11.291$2DOI
100 1 $aSALINAS, L.M.
245 $aNeurological syndrome in goats associated with Ipomoea trifida and Ipomoea carnea containing calystegines.$h[electronic resource]
260 $c2018
500 $aArticle history: Received 16 September 2018 // Received in revised form 7 November 2018 // Accepted 9 November 2018 // Available online 14 November 2018. This work was partially supported by a grant from Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria ( INIA , Spain), reference number E-RTA2013-00013-C04-04 (FEDER co-funded).
520 $aABSTRACT. A disease characterized by ataxia, tremors and nystagmus had been observed in goats in Nicaragua. The main histologic lesions were loss and neuronal vacuolation of Purkinje cells and Wallerian-like degeneration mainly in the cerebellum, suggesting a glycoprotein storage disease. Ipomoea carnea and Ipomoea trifida found in the paddocks were negative for swainsonine, but contained calystegines at 0.02% and 0.06% suggesting that the disease was caused by these substances, which are competitive inhibitors of β-glucosidase and α-galactosidase activities. © 2018 Elsevier Ltd
653 $aCALYSTEGINES
653 $aGOAT
653 $aIPOMOEA CARNEA
653 $aIPOMOEA TRIFIDA
653 $aNICARAGUA
653 $aPOISONING
700 1 $aBALSEIRO, A.
700 1 $aJIRÓN, W.
700 1 $aPERALTA, A.
700 1 $aMUÑÓZ, D.
700 1 $aFAJARDO, J.
700 1 $aGAYO, E.
700 1 $aMARTÍNEZ, I.Z.
700 1 $aRIET-CORREA, F.
700 1 $aGARDNER, D.R.
700 1 $aGARCÍA MARÍN, J.F.
773 $tToxicon, January 2019, Volume 157, Pages 8-11.
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