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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
16/10/2018 |
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Actualizado : |
11/02/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
BORGES, A.; GONZÁLEZ-REYMUNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, L. |
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Afiliación : |
ALEJANDRA BORGES, Departamento de Estadística. Facultad de Agronomía, UdelaR.; AGUSTÍN GONZÁLEZ-REYMUNDEZ, Departamento de Estadística. Facultad de Agronomía, UdelaR.; OSVALDO, ERNST, Departamento de Producción de Cultivos. EEMAC, Facultad de Agronomía, UdelaR.; MÓNICA CADENAZZI, Departamento de Estadística. Facultad de Agronomía, UdelaR.; JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Department of Agronomy, University of Wisconsin. |
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Título : |
Can spatial modeling substitute experimental design in agricultural experiments? |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Crop Science, 2018, v. 59, no. 1, p. 1-10. |
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DOI : |
10.2135/cropsci2018.03.0177 |
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Idioma : |
Inglés |
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Notas : |
Article history: Accepted paper, posted 10/05/18. Published online December, 13. 2018. |
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Contenido : |
Abstract:
One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitute for good experimental design. MenosAbstract:
One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitut... Presentar Todo |
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Palabras claves : |
EFFICIENCY STATISTICS; EXPERIMENTAL DESIGN; FIELD VARIABILITY; SPATIAL MODELS; UNIFORMITY TRIAL. |
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Thesagro : |
DISENO ESTADISTICO; DISENO EXPERIMENTAL; MODELOS ESTADISTICOS; VARIABILIDAD. |
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Asunto categoría : |
U30 Métodos de investigación |
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Marc : |
LEADER 02512naa a2200313 a 4500
001 1059193
005 2019-02-11
008 2018 bl uuuu u00u1 u #d
024 7 $a10.2135/cropsci2018.03.0177$2DOI
100 1 $aBORGES, A.
245 $aCan spatial modeling substitute experimental design in agricultural experiments?$h[electronic resource]
260 $c2018
500 $aArticle history: Accepted paper, posted 10/05/18. Published online December, 13. 2018.
520 $aAbstract: One of the most critical aspects of agricultural experimentation is the proper choice of experimental design to control field heterogeneity, especially for large experiments. However, even with complex experimental designs, spatial variability may not be properly controlled if it occurs at scales smaller than blocks. Therefore, modeling spatial variability can be beneficial and some studies even propose spatial modeling instead of experimental design. Our goal was to evaluate the effect of experimental design, spatial modeling, and a combination of both under real field conditions using GIS and simulating experiments. Yield data from cultivars was simulated using real spatial variability from a large uniformity trial of one hundred independent locations and different sizes of experiments for four experimental designs: completely randomized design (CRD), randomized complete block design (RCBD), alpha-lattice incomplete block design (ALPHA), and partially replicated design (PREP). Each realization was analyzed using different levels of spatial correction. Models were compared by precision, accuracy, and the recovery of superior genotypes. For moderate and large experiment sizes, ALPHA was the best experimental design in terms of precision and accuracy. In most situations, models that included spatial correlation were better than models with no spatial correlation but they did not outperformed better experimental designs. Therefore, spatial modeling is not a substitute for good experimental design.
650 $aDISENO ESTADISTICO
650 $aDISENO EXPERIMENTAL
650 $aMODELOS ESTADISTICOS
650 $aVARIABILIDAD
653 $aEFFICIENCY STATISTICS
653 $aEXPERIMENTAL DESIGN
653 $aFIELD VARIABILITY
653 $aSPATIAL MODELS
653 $aUNIFORMITY TRIAL
700 1 $aGONZÁLEZ-REYMUNDEZ, A.
700 1 $aERNST, O.
700 1 $aCADENAZZI, M.
700 1 $aTERRA, J.A.
700 1 $aGUTIÉRREZ, L.
773 $tCrop Science, 2018$gv. 59, no. 1, p. 1-10.
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INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
10/07/2019 |
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Actualizado : |
10/07/2019 |
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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 : |
BESIL, N.; REZENDE, S.; ALONZO, N.; CESIO, M.V.; RIVAS, F.; HEINZEN, H. |
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Afiliación : |
NATALIA BESIL, Grupo de Análisis de Compuestos Traza (GACT), Departamento de Química del Litoral, Facultad de Química, CENUR Litoral Norte, Universidad de la República.; SOFÍA REZENDE, Grupo de Análisis de Compuestos Traza (GACT), Departamento de Química del Litoral, Facultad de Química, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay.; NOEL ALONZO, Grupo de Análisis de Compuestos Traza (GACT), Departamento de Química del Litoral, Facultad de Química, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay.; MARÍA VERÓNICA CESIO, Grupo de Análisis de Compuestos Traza (GACT), Departamento de Química del Litoral, Facultad de Química, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay.; CARLOS FERNANDO RIVAS GRELA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; HORACIO HEINZEN, Grupo de Análisis de Compuestos Traza (GACT), Departamento de Química del Litoral, Facultad de Química, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay. |
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Título : |
Analytical methods for the routinely evaluation of pesticide residues in lemon fruits and by products. |
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Complemento del título : |
Research article. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
SN Applied Sciences, 2019, 1: 618. |
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ISSN : |
2523-3971 |
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DOI : |
10.1007%2Fs42452-019-0626-x |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 10 October 2018 / Accepted: 16 May 2019 / Published online: 22 May 2019. |
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Contenido : |
ABSTRACT.
Citrus fruits and their by-products such as concentrated juices and essential oils are important intermediate by-products in the food industry that can selectively accumulate plant protection agrochemicals employed in their production. They are very difcult matrices for pesticide residue analysis due their high number and concentration of phytochemicals that could hamper the determinations. The fruit processing leads to the concentration/dilution or elimination of some of these natural products that change totally the nature of the matrix where the pesticides partition unevenly. Looking at the industrial process of the fruit, a unifed vision for the pesticide residues analysis throughout the lemon fruit chain production, useful for the routine analysis of the above mentioned three matrices is presented. The driven concept is the minimization of matrix efects through sample dilution of the concentrated by-products, either after sample treatment or not. This approach will contribute to the maintenance of the whole instrumental system. QuEChERS AOAC 2007.01 was selected as the most suitable protocol for routine determination of, residues of 16 the pesticides most commonly used in the fruits during the citrus production through liquid chromatography coupled to tandem mass spectrometry (LC?MS/MS). The same protocol was applied for pesticide residue analysis in concentrated juice after diluting 4 times the sample to minimize the matrix efects. For the analysis of lemon essential oils, the dilution and shoot procedure proved to be useful for LC?MS/MS and gas chromatography?mass spectrometry determination. The three methodologies were validated following SANTE guidelines, with quantitation limits below the established European Union and Codex Alimentarius maximum residue limits. The developed methodologies are useful tools for the routine control analysis of pesticide residues in lemon matrices, allowing high sample throughput and enhancing labs productivity.
© Springer Nature Switzerland AG MenosABSTRACT.
Citrus fruits and their by-products such as concentrated juices and essential oils are important intermediate by-products in the food industry that can selectively accumulate plant protection agrochemicals employed in their production. They are very difcult matrices for pesticide residue analysis due their high number and concentration of phytochemicals that could hamper the determinations. The fruit processing leads to the concentration/dilution or elimination of some of these natural products that change totally the nature of the matrix where the pesticides partition unevenly. Looking at the industrial process of the fruit, a unifed vision for the pesticide residues analysis throughout the lemon fruit chain production, useful for the routine analysis of the above mentioned three matrices is presented. The driven concept is the minimization of matrix efects through sample dilution of the concentrated by-products, either after sample treatment or not. This approach will contribute to the maintenance of the whole instrumental system. QuEChERS AOAC 2007.01 was selected as the most suitable protocol for routine determination of, residues of 16 the pesticides most commonly used in the fruits during the citrus production through liquid chromatography coupled to tandem mass spectrometry (LC?MS/MS). The same protocol was applied for pesticide residue analysis in concentrated juice after diluting 4 times the sample to minimize the matrix efects. For the analysis of lemon e... Presentar Todo |
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Palabras claves : |
CONCENTRATED LEMON JUICE; ESSENTIAL OILS; GC–MS; LC–MS/MS; LEMON FRUIT; PESTICIDE RESIDUES. |
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Asunto categoría : |
F01 Cultivo |
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Marc : |
LEADER 02922naa a2200289 a 4500
001 1059939
005 2019-07-10
008 2019 bl uuuu u00u1 u #d
022 $a2523-3971
024 7 $a10.1007%2Fs42452-019-0626-x$2DOI
100 1 $aBESIL, N.
245 $aAnalytical methods for the routinely evaluation of pesticide residues in lemon fruits and by products.$h[electronic resource]
260 $c2019
500 $aArticle history: Received: 10 October 2018 / Accepted: 16 May 2019 / Published online: 22 May 2019.
520 $aABSTRACT. Citrus fruits and their by-products such as concentrated juices and essential oils are important intermediate by-products in the food industry that can selectively accumulate plant protection agrochemicals employed in their production. They are very difcult matrices for pesticide residue analysis due their high number and concentration of phytochemicals that could hamper the determinations. The fruit processing leads to the concentration/dilution or elimination of some of these natural products that change totally the nature of the matrix where the pesticides partition unevenly. Looking at the industrial process of the fruit, a unifed vision for the pesticide residues analysis throughout the lemon fruit chain production, useful for the routine analysis of the above mentioned three matrices is presented. The driven concept is the minimization of matrix efects through sample dilution of the concentrated by-products, either after sample treatment or not. This approach will contribute to the maintenance of the whole instrumental system. QuEChERS AOAC 2007.01 was selected as the most suitable protocol for routine determination of, residues of 16 the pesticides most commonly used in the fruits during the citrus production through liquid chromatography coupled to tandem mass spectrometry (LC?MS/MS). The same protocol was applied for pesticide residue analysis in concentrated juice after diluting 4 times the sample to minimize the matrix efects. For the analysis of lemon essential oils, the dilution and shoot procedure proved to be useful for LC?MS/MS and gas chromatography?mass spectrometry determination. The three methodologies were validated following SANTE guidelines, with quantitation limits below the established European Union and Codex Alimentarius maximum residue limits. The developed methodologies are useful tools for the routine control analysis of pesticide residues in lemon matrices, allowing high sample throughput and enhancing labs productivity. © Springer Nature Switzerland AG
653 $aCONCENTRATED LEMON JUICE
653 $aESSENTIAL OILS
653 $aGC–MS
653 $aLC–MS/MS
653 $aLEMON FRUIT
653 $aPESTICIDE RESIDUES
700 1 $aREZENDE, S.
700 1 $aALONZO, N.
700 1 $aCESIO, M.V.
700 1 $aRIVAS, F.
700 1 $aHEINZEN, H.
773 $tSN Applied Sciences, 2019, 1: 618.
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