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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
21/02/2014 |
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Actualizado : |
30/07/2019 |
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Autor : |
BAIGORRI, H.E.J.; GIORDA, L.M. (Ed.). |
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Título : |
Reconocimiento de enfermedades, plagas y malezas de la soja. |
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Fecha de publicación : |
1998 |
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Fuente / Imprenta : |
Marcos Juárez, Córdoba, AR: INTA, 1998. |
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Páginas : |
124 p. |
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Serie : |
(Agro de Córdoba, 5) |
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ISSN : |
0329-0077 |
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Idioma : |
Español |
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Palabras claves : |
AMV; CERCOSPORA KIKUCHII; CORYNESPORA CASSIICOLA; DAMPING OFF; DEFICIENCIAS MINERALES; DIAPORTHE PHASEOLORUM VAR. MERIDIONALIS; ENFERMEDADES BACTERIANAS; ENFERMEDADES FÚNGICAS; ENFERMEDADES VIRÓSICAS; FITOTOXICIDAD POR HERBICIDAS; GEMINIVIRUS; MACROPHOMINA PHASEOLINA; MICROSPHAERA DIFFUSA; NECROSIS DEL BROTE; PERONOSPORA MANSHURICA; PHIALOPHORA GREGATA; PHOMOPSIS SOJAE; PMV; PSEUDOMONAS SYRINGAE PV. GLYCINEA; PSEUDOMONAS SYRINGAE PV. TABACI; SCLEROTIUM ROLFSII; SEPTORIA GLYCINES; SMV; TSV; VIRUS DEL MOSAICO DE LA ALFALFA; VIRUS DEL MOSAICO DE LA SOJA; VIRUS DEL MOTEADO DEL MANÍ; XANTHOMONAS CAMPESTRIS PV. GLYCINES. |
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Thesagro : |
COLLETOTRICHUM; ENFERMEDADES DE LAS PLANTAS; FUSARIUM SOLANI; GLYCINE; PHYTOPHTHORA SOJAE; SCLEROTINIA SCLEROTIORUM; SOJA. |
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Asunto categoría : |
H20 Enfermedades de las plantas |
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Marc : |
LEADER 01679nam a2200565 a 4500
001 1035615
005 2019-07-30
008 1998 bl uuuu u00u1 u #d
022 $a0329-0077
100 1 $aBAIGORRI, H.E.J.
245 $aReconocimiento de enfermedades, plagas y malezas de la soja.
260 $aMarcos Juárez, Córdoba, AR: INTA$c1998
300 $a124 p.
490 $a(Agro de Córdoba, 5)
650 $aCOLLETOTRICHUM
650 $aENFERMEDADES DE LAS PLANTAS
650 $aFUSARIUM SOLANI
650 $aGLYCINE
650 $aPHYTOPHTHORA SOJAE
650 $aSCLEROTINIA SCLEROTIORUM
650 $aSOJA
653 $aAMV
653 $aCERCOSPORA KIKUCHII
653 $aCORYNESPORA CASSIICOLA
653 $aDAMPING OFF
653 $aDEFICIENCIAS MINERALES
653 $aDIAPORTHE PHASEOLORUM VAR. MERIDIONALIS
653 $aENFERMEDADES BACTERIANAS
653 $aENFERMEDADES FÚNGICAS
653 $aENFERMEDADES VIRÓSICAS
653 $aFITOTOXICIDAD POR HERBICIDAS
653 $aGEMINIVIRUS
653 $aMACROPHOMINA PHASEOLINA
653 $aMICROSPHAERA DIFFUSA
653 $aNECROSIS DEL BROTE
653 $aPERONOSPORA MANSHURICA
653 $aPHIALOPHORA GREGATA
653 $aPHOMOPSIS SOJAE
653 $aPMV
653 $aPSEUDOMONAS SYRINGAE PV. GLYCINEA
653 $aPSEUDOMONAS SYRINGAE PV. TABACI
653 $aSCLEROTIUM ROLFSII
653 $aSEPTORIA GLYCINES
653 $aSMV
653 $aTSV
653 $aVIRUS DEL MOSAICO DE LA ALFALFA
653 $aVIRUS DEL MOSAICO DE LA SOJA
653 $aVIRUS DEL MOTEADO DEL MANÍ
653 $aXANTHOMONAS CAMPESTRIS PV. GLYCINES
700 1 $aGIORDA, L.M.
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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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