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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
21/02/2014 |
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Actualizado : |
01/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
COZZOLINO, D.; DELUCCHI, M.I.; KHOLI, M.; VÁZQUEZ, D. |
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Afiliación : |
DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA INES DELUCCHI ZAPARRART, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MOHAM KHOLI, MOHAM, International Center for Wheat and Maize Improvement (CIMMYT).; DANIEL VÁZQUEZ PEYRONEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain. [Uso de la espectroscopía de reflectancia en el infrarrojo cercano para evaluar características de calidad en trigo]. |
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Fecha de publicación : |
2006 |
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Fuente / Imprenta : |
Agricultura Técnica, December 2006, Volume 66, Issue 4, Pages 370-375. |
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DOI : |
10.4067/S0365-28072006000400005 |
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Idioma : |
Inglés |
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Notas : |
Article history:Recibido: 17 de octubre de 2005/Aprobado: 30 de marzo de 2006. |
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Contenido : |
ABSTRACT:
The aim of this work was to explore the potential of visible (Vis) and near infrared reflectance (NIR) spectroscopy to measure quality characteristics in whole grain wheat (Triticum aestivum L.) as a tool in breeding programs. A total of 100 samples were analyzed by the reference methods for crude protein (CP), wet gluten (WG) and sodium dodecyl sulfate (SDS) sedimentation test. Whole grain samples were scanned in a NIR monochromator instrument (400-2500 nm) in reflectance. Partial least squares (PLS) were used to develop calibration equations for the quality characteristics in whole wheat. Calibration models were validated using an independent set of samples (n = 50) randomly selected from the population set. The uncertainty of the PLS models was evaluated by the standard error of prediction (SEP). The SEP obtained were 0.35% for CP, 2.04 for SDS and 4.14% for WG. It was concluded that NIR spectroscopy might be used as a screening tool to segregate early generations of wheat genotypes. At a later stage is needed to improve the accuracy of the NIR calibrations, broadening the calibration spectra with the incorporation of more genotypes and different crop years.
RESUMEN:
El objetivo de este trabajo fue explorar el potencial de la espectroscopía en el visible (Vis) e infrarrojo cercano (NIR) para medir características de calidad en el trigo (Triticum aestivum L.) para su uso en programas de mejoramiento. Cien muestras fueron analizadas por el método de referencia para proteína cruda (CP), gluten húmedo (WG) y sulfato de dodecil de sodio (SDS) o prueba de sedimentación. Las muestras de trigo se analizaron en un instrumento NIR (400-2500 nm) en reflectancia. El método de los cuadrados mínimos parciales (PLS) fue utilizado para desarrollar las ecuaciones de calibración para las características de calidad en trigo. Los modelos de calibración se validaron utilizando un conjunto independiente de muestras (n = 50) aleatoriamente escogido del conjunto de la población. La incertidumbre de los modelos PLS de calibración fue evaluada usando el error estándar de la predicción (SEP). El SEP obtenido fue de 0,35% para CP, 2,04 para SDS y 4,14% para WG. Se concluyó que la espectroscopía de NIR podría utilizarse como una herramienta de selección para segregar genotipos de trigo en generaciones tempranas. En una etapa posterior se necesita mejorar la precisión de los análisis NIR, ampliando el espectro de calibración con la incorporación de más genotipos y diferentes años de cultivo. MenosABSTRACT:
The aim of this work was to explore the potential of visible (Vis) and near infrared reflectance (NIR) spectroscopy to measure quality characteristics in whole grain wheat (Triticum aestivum L.) as a tool in breeding programs. A total of 100 samples were analyzed by the reference methods for crude protein (CP), wet gluten (WG) and sodium dodecyl sulfate (SDS) sedimentation test. Whole grain samples were scanned in a NIR monochromator instrument (400-2500 nm) in reflectance. Partial least squares (PLS) were used to develop calibration equations for the quality characteristics in whole wheat. Calibration models were validated using an independent set of samples (n = 50) randomly selected from the population set. The uncertainty of the PLS models was evaluated by the standard error of prediction (SEP). The SEP obtained were 0.35% for CP, 2.04 for SDS and 4.14% for WG. It was concluded that NIR spectroscopy might be used as a screening tool to segregate early generations of wheat genotypes. At a later stage is needed to improve the accuracy of the NIR calibrations, broadening the calibration spectra with the incorporation of more genotypes and different crop years.
RESUMEN:
El objetivo de este trabajo fue explorar el potencial de la espectroscopía en el visible (Vis) e infrarrojo cercano (NIR) para medir características de calidad en el trigo (Triticum aestivum L.) para su uso en programas de mejoramiento. Cien muestras fueron analizadas por el método de refer... Presentar Todo |
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Palabras claves : |
GLUTEN HÚMEDO; GRAIN QUALITY; GRANO DE TRIGO; PROTEIN; SDS; WET GLUTEN; WHOLE WHEAT. |
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Thesagro : |
NIRS; PROTEÍNA; TRIGO; TRITICUM AESTIVUM. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13383/1/Uso-de-la-espectroscopia-de-reflectancia-en-el-inf.pdf
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Marc : |
LEADER 03624naa a2200313 a 4500
001 1034984
005 2019-10-01
008 2006 bl uuuu u00u1 u #d
024 7 $a10.4067/S0365-28072006000400005$2DOI
100 1 $aCOZZOLINO, D.
245 $aUse of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain. [Uso de la espectroscopía de reflectancia en el infrarrojo cercano para evaluar características de calidad en trigo].$h[electronic resource]
260 $c2006
500 $aArticle history:Recibido: 17 de octubre de 2005/Aprobado: 30 de marzo de 2006.
520 $aABSTRACT: The aim of this work was to explore the potential of visible (Vis) and near infrared reflectance (NIR) spectroscopy to measure quality characteristics in whole grain wheat (Triticum aestivum L.) as a tool in breeding programs. A total of 100 samples were analyzed by the reference methods for crude protein (CP), wet gluten (WG) and sodium dodecyl sulfate (SDS) sedimentation test. Whole grain samples were scanned in a NIR monochromator instrument (400-2500 nm) in reflectance. Partial least squares (PLS) were used to develop calibration equations for the quality characteristics in whole wheat. Calibration models were validated using an independent set of samples (n = 50) randomly selected from the population set. The uncertainty of the PLS models was evaluated by the standard error of prediction (SEP). The SEP obtained were 0.35% for CP, 2.04 for SDS and 4.14% for WG. It was concluded that NIR spectroscopy might be used as a screening tool to segregate early generations of wheat genotypes. At a later stage is needed to improve the accuracy of the NIR calibrations, broadening the calibration spectra with the incorporation of more genotypes and different crop years. RESUMEN: El objetivo de este trabajo fue explorar el potencial de la espectroscopía en el visible (Vis) e infrarrojo cercano (NIR) para medir características de calidad en el trigo (Triticum aestivum L.) para su uso en programas de mejoramiento. Cien muestras fueron analizadas por el método de referencia para proteína cruda (CP), gluten húmedo (WG) y sulfato de dodecil de sodio (SDS) o prueba de sedimentación. Las muestras de trigo se analizaron en un instrumento NIR (400-2500 nm) en reflectancia. El método de los cuadrados mínimos parciales (PLS) fue utilizado para desarrollar las ecuaciones de calibración para las características de calidad en trigo. Los modelos de calibración se validaron utilizando un conjunto independiente de muestras (n = 50) aleatoriamente escogido del conjunto de la población. La incertidumbre de los modelos PLS de calibración fue evaluada usando el error estándar de la predicción (SEP). El SEP obtenido fue de 0,35% para CP, 2,04 para SDS y 4,14% para WG. Se concluyó que la espectroscopía de NIR podría utilizarse como una herramienta de selección para segregar genotipos de trigo en generaciones tempranas. En una etapa posterior se necesita mejorar la precisión de los análisis NIR, ampliando el espectro de calibración con la incorporación de más genotipos y diferentes años de cultivo.
650 $aNIRS
650 $aPROTEÍNA
650 $aTRIGO
650 $aTRITICUM AESTIVUM
653 $aGLUTEN HÚMEDO
653 $aGRAIN QUALITY
653 $aGRANO DE TRIGO
653 $aPROTEIN
653 $aSDS
653 $aWET GLUTEN
653 $aWHOLE WHEAT
700 1 $aDELUCCHI, M.I.
700 1 $aKHOLI, M.
700 1 $aVÁZQUEZ, D.
773 $tAgricultura Técnica, December 2006, Volume 66, Issue 4, Pages 370-375.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
16/07/2020 |
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Actualizado : |
16/07/2020 |
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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 : |
HARRIS, P.; LANFRANCO, B.; LU, B.; COMBER, A. |
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Afiliación : |
PAUL HARRIS, Sustainable Agriculture Sciences, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK; BRUNO ANTONIO LANFRANCO CRESPO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; BINBIN LU, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; ALEXIS COMBER, School of Geography, University of Leeds, Leeds LS2 9JT, UK. |
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Título : |
Influence of geographical effects in hedonic pricing models for grass-fed cattle in Uruguay. [OPEN ACCESS]. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Agriculture, 2020, 10(7), 299; https://doi.org/10.3390/agriculture10070299 |
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ISSN : |
eISSN 2077-0472 |
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DOI : |
10.3390/agriculture10070299 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 27 June 2020 / Revised: 12 July 2020 / Accepted: 13 July 2020 / Published: 15 July 2020.
This article belongs to the Section Agricultural Economics, Policies and Rural Management.
The article contains supplementary material.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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Contenido : |
ABSTRACT.
A series of non-spatial and spatial hedonic models of feeding and replacement cattle prices at video auctions in Uruguay (2002 to 2009) were specified with predictors measuring marketing conditions (e.g., steer price), cattle characteristics (e.g., breed) and agro-ecological factors (e.g., soil productivity, water characteristics, pasture condition, season). Results indicated that cattle prices produced under extensive production systems were influenced by all of predictor categories, confirming that found previously. Although many of the agro-ecological predictors were inherently spatial in nature, the incorporation of spatial effects into the estimation of the hedonic model itself, through either a spatially-autocorrelated error term or allowing the regression coefficients to vary spatially and at different scales, was able to provide greater insight into the cattle price process. Through the latter extension, using a multiscale geographically weighted regression, which was the most informative and most accurate model, relationships between cattle price and predictors operated at a mixture of global, regional, local and highly local spatial scales. This result is considered a key advance, where uncovering, interpreting, and utilizing such rich spatial information can help improve the geographical provenance of Uruguayan beef and is critically important for maintaining Uruguay´s status as a key exporter of beef with respect to the health and safety benefits of natural, open-sky, grass-fed production systems. MenosABSTRACT.
A series of non-spatial and spatial hedonic models of feeding and replacement cattle prices at video auctions in Uruguay (2002 to 2009) were specified with predictors measuring marketing conditions (e.g., steer price), cattle characteristics (e.g., breed) and agro-ecological factors (e.g., soil productivity, water characteristics, pasture condition, season). Results indicated that cattle prices produced under extensive production systems were influenced by all of predictor categories, confirming that found previously. Although many of the agro-ecological predictors were inherently spatial in nature, the incorporation of spatial effects into the estimation of the hedonic model itself, through either a spatially-autocorrelated error term or allowing the regression coefficients to vary spatially and at different scales, was able to provide greater insight into the cattle price process. Through the latter extension, using a multiscale geographically weighted regression, which was the most informative and most accurate model, relationships between cattle price and predictors operated at a mixture of global, regional, local and highly local spatial scales. This result is considered a key advance, where uncovering, interpreting, and utilizing such rich spatial information can help improve the geographical provenance of Uruguayan beef and is critically important for maintaining Uruguay´s status as a key exporter of beef with respect to the health and safety benefits of nat... Presentar Todo |
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Palabras claves : |
Beef cattle prices; MGWR; Multiscale; Provenance; Spatial regression. |
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Asunto categoría : |
A50 Investigación agraria |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/14550/1/Harris-et-al-2020-Agriculture-107-spatial-hedonic.pdf
https://www.mdpi.com/2077-0472/10/7/299/pdf
https://www.mdpi.com/2077-0472/10/7/299/s1
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Marc : |
LEADER 02758naa a2200253 a 4500
001 1061231
005 2020-07-16
008 2020 bl uuuu u00u1 u #d
022 $aeISSN 2077-0472
024 7 $a10.3390/agriculture10070299$2DOI
100 1 $aHARRIS, P.
245 $aInfluence of geographical effects in hedonic pricing models for grass-fed cattle in Uruguay. [OPEN ACCESS].$h[electronic resource]
260 $c2020
500 $aArticle history: Received: 27 June 2020 / Revised: 12 July 2020 / Accepted: 13 July 2020 / Published: 15 July 2020. This article belongs to the Section Agricultural Economics, Policies and Rural Management. The article contains supplementary material. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
520 $aABSTRACT. A series of non-spatial and spatial hedonic models of feeding and replacement cattle prices at video auctions in Uruguay (2002 to 2009) were specified with predictors measuring marketing conditions (e.g., steer price), cattle characteristics (e.g., breed) and agro-ecological factors (e.g., soil productivity, water characteristics, pasture condition, season). Results indicated that cattle prices produced under extensive production systems were influenced by all of predictor categories, confirming that found previously. Although many of the agro-ecological predictors were inherently spatial in nature, the incorporation of spatial effects into the estimation of the hedonic model itself, through either a spatially-autocorrelated error term or allowing the regression coefficients to vary spatially and at different scales, was able to provide greater insight into the cattle price process. Through the latter extension, using a multiscale geographically weighted regression, which was the most informative and most accurate model, relationships between cattle price and predictors operated at a mixture of global, regional, local and highly local spatial scales. This result is considered a key advance, where uncovering, interpreting, and utilizing such rich spatial information can help improve the geographical provenance of Uruguayan beef and is critically important for maintaining Uruguay´s status as a key exporter of beef with respect to the health and safety benefits of natural, open-sky, grass-fed production systems.
653 $aBeef cattle prices
653 $aMGWR
653 $aMultiscale
653 $aProvenance
653 $aSpatial regression
700 1 $aLANFRANCO, B.
700 1 $aLU, B.
700 1 $aCOMBER, A.
773 $tAgriculture, 2020, 10(7), 299; https://doi.org/10.3390/agriculture10070299
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