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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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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
21/02/2014 |
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Actualizado : |
24/01/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
COZZOLINO, D.; CORBELLA, E. |
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Afiliación : |
DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; EDUARDO DANIEL CORBELLA GONZALEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Determination of honey quality components by near infrared reflectance spectroscopy. |
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Fecha de publicación : |
2003 |
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Fuente / Imprenta : |
Journal of Apicultural Research, 2003, volume 42, Issue 1-2, Pages 16-20. |
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DOI : |
10.1080/00218839.2003.11101081 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 19 Aug 2002 // Accepted 10 Dec 2002 // Published online: 24 Mar 2015. |
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Contenido : |
ABSTRACT.
Near infrared reflectance spectroscopy (NIRS) was used to assess the chemical composition of fresh honey samples. Samples (n = 110) from different locations across Uruguay were scanned in transreflectance (0.2 mm path?length) in a NIRS 6500 monochromator in both the visible and near infrared region (400?2500 nm). Prediction equations were developed using modified partial least squares and cross validation was applied to avoid overfitting. Calibrations for water content (g kg−1), pH, electrical conductivity (mS/cm), colour (mm Pfund) and hydroxymethylfurfural (mg kg−1) yielded a coefficient of determination in calibration (R2CAL) and standard error in cross validation of 0.96 (SECV: 31); 0.88 (SECV: 0.21); 0.94 (SECV: 0.07); 0.98 (SECV: 4.7) and 0.67 (SECV: 3.9), respectively. It is concluded that NIRS is a useful method to evaluate chemical composition on fresh honey samples.
© 2003 International Bee Research Association. |
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Palabras claves : |
COLOUR; ELECTRICAL CONDUCTIVITY; HMF; HONEY; NEAR INFRARED REFLECTANCE; PH; WATER CONTENT. |
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Thesagro : |
APICULTURA; MIEL. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 01800naa a2200265 a 4500
001 1002979
005 2019-01-24
008 2003 bl uuuu u00u1 u #d
024 7 $a10.1080/00218839.2003.11101081$2DOI
100 1 $aCOZZOLINO, D.
245 $aDetermination of honey quality components by near infrared reflectance spectroscopy.$h[electronic resource]
260 $c2003
500 $aArticle history: Received 19 Aug 2002 // Accepted 10 Dec 2002 // Published online: 24 Mar 2015.
520 $aABSTRACT. Near infrared reflectance spectroscopy (NIRS) was used to assess the chemical composition of fresh honey samples. Samples (n = 110) from different locations across Uruguay were scanned in transreflectance (0.2 mm path?length) in a NIRS 6500 monochromator in both the visible and near infrared region (400?2500 nm). Prediction equations were developed using modified partial least squares and cross validation was applied to avoid overfitting. Calibrations for water content (g kg−1), pH, electrical conductivity (mS/cm), colour (mm Pfund) and hydroxymethylfurfural (mg kg−1) yielded a coefficient of determination in calibration (R2CAL) and standard error in cross validation of 0.96 (SECV: 31); 0.88 (SECV: 0.21); 0.94 (SECV: 0.07); 0.98 (SECV: 4.7) and 0.67 (SECV: 3.9), respectively. It is concluded that NIRS is a useful method to evaluate chemical composition on fresh honey samples. © 2003 International Bee Research Association.
650 $aAPICULTURA
650 $aMIEL
653 $aCOLOUR
653 $aELECTRICAL CONDUCTIVITY
653 $aHMF
653 $aHONEY
653 $aNEAR INFRARED REFLECTANCE
653 $aPH
653 $aWATER CONTENT
700 1 $aCORBELLA, E.
773 $tJournal of Apicultural Research, 2003, volume 42, Issue 1-2, Pages 16-20.
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Registro original : |
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 : |
28/10/2024 |
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Actualizado : |
28/10/2024 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
LENA, H.; CAL, A.; PRECIOZZI, J. |
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Afiliación : |
HORACIO LENA, Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JAVIER PRECIOZZI, Universidad de la República, Facultad de Ingeniería Digital Sense, Uruguay. |
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Título : |
Sentinel-2 analysis for classification of winter crops in Uruguay. [Conference paper]. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp.4819-4823. https://doi.org/10.1109/IGARSS53475.2024.10641161 |
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ISBN : |
979-835036032-5 |
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Idioma : |
Inglés |
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Notas : |
Correspondence: Lena, H.; Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; email:horacio.lena@cienciassociales.edu.uy -- 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.- Crop type classification with satellite imageries is widely applied to support sustainable agricultural practices and for continuous crop monitoring [1], [2], [3]. In this work, we present a study for the classification of winter crops on a nationwide perspective for Uruguay. We have analyzed Uruguay's three most widely extended winter crops: wheat, barley, and rapeseed. We have trained a classifier based on XGBoost that uses temporal series built from Sentinel-2 image data. For training, we used the information from previous years and reported the results the following year. To our knowledge, this is the first work that proposes a clear and systematic way to classify winter crops in Uruguay based on historical data without needing samples of the actual year. We have obtained high precision and recall values for rapeseed and results comparable with other regions' work for wheat and barley. © 2024 IEEE. |
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Palabras claves : |
Crop classification; Decent work and economic growth - Goal 8; Remote sensing; Responsible consumption and production - Goal 12; SISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA; Sustainable Development Goals (SDGs); XGBoost; Zero hunger - Goal 2. |
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Asunto categoría : |
P40 Meteorología y climatología |
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Marc : |
LEADER 02234nam a2200253 a 4500
001 1064899
005 2024-10-28
008 2024 bl uuuu u01u1 u #d
020 $a979-835036032-5
100 1 $aLENA, H.
245 $aSentinel-2 analysis for classification of winter crops in Uruguay. [Conference paper].$h[electronic resource]
260 $aIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp.4819-4823. https://doi.org/10.1109/IGARSS53475.2024.10641161$c2024
500 $aCorrespondence: Lena, H.; Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; email:horacio.lena@cienciassociales.edu.uy -- Publisher: Institute of Electrical and Electronics Engineers Inc. -- Sponsors: The Institute of Electrical and Electronics Engineers, Geoscience and Remote Sensing Society (GRSS). --
520 $aABSTRACT.- Crop type classification with satellite imageries is widely applied to support sustainable agricultural practices and for continuous crop monitoring [1], [2], [3]. In this work, we present a study for the classification of winter crops on a nationwide perspective for Uruguay. We have analyzed Uruguay's three most widely extended winter crops: wheat, barley, and rapeseed. We have trained a classifier based on XGBoost that uses temporal series built from Sentinel-2 image data. For training, we used the information from previous years and reported the results the following year. To our knowledge, this is the first work that proposes a clear and systematic way to classify winter crops in Uruguay based on historical data without needing samples of the actual year. We have obtained high precision and recall values for rapeseed and results comparable with other regions' work for wheat and barley. © 2024 IEEE.
653 $aCrop classification
653 $aDecent work and economic growth - Goal 8
653 $aRemote sensing
653 $aResponsible consumption and production - Goal 12
653 $aSISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA
653 $aSustainable Development Goals (SDGs)
653 $aXGBoost
653 $aZero hunger - Goal 2
700 1 $aCAL, A.
700 1 $aPRECIOZZI, J.
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