| |
|
|
 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha : |
29/09/2014 |
|
Actualizado : |
15/10/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
VICENTE, E.; VARELA, P.; DE SALDAMANDO, L.; ARES, G. |
|
Afiliación : |
CARLOS ESTEBAN VICENTE CASTRO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PABLO NICOLAS VARELA PESSOLANO, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
|
Título : |
Evaluation of the sensory characteristics of strawberry cultivars throughout the harvest season using projective mapping. |
|
Fecha de publicación : |
2014 |
|
Fuente / Imprenta : |
Journal of the Science of Food and Agriculture, 2014, v.94, no.3, p.591-599. |
|
ISSN : |
0022-5142 |
|
DOI : |
10.1002/jsfa.6307 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received: 17 May 2013 / Revised: 20 June 2013 / Accepted article published: 18 July 2013 /Published online in: 9 August 2013. |
|
Contenido : |
ABSTRACT.
Strawberry breeding programs should be able to rely on valid and simple methodologies for evaluating sensory quality of new cultivars. In this context, the aim of the present work was to evaluate the applicability of a simple sensory methodology, named projective mapping, to evaluate the sensory characteristics of strawberry cultivars and advanced selections throughout the harvest season. Three strawberry cultivars and two advanced selections were evaluated by an untrained assessor panel using projective mapping in three different moments of the harvest season: June (early season), August (mid-season) and September (peak harvest). Instrumental measurements were also performed. RESULTS: Projective mapping enabled the identification of the main sensory characteristics of the strawberry cultivars and advanced selections, as well as the similarities and differences among them. Sensory characteristics of the five evaluated strawberry cultivars and advanced selections largely varied throughout the harvest season. Simple instrumental measurements were not able to predict the sensory characteristics of the strawberry cultivars, suggesting the importance of sensory methodologies for the evaluation of new cultivars in breeding programs. CONCLUSIONS: Projective mapping consisted of a quick alternative for the evaluation of new cultivars relative to standard commercial cultivars. Its main advantage is that a large number of cultivars can be screened with minimal investment of time and resources.
© 2013 Society of Chemical Industry. MenosABSTRACT.
Strawberry breeding programs should be able to rely on valid and simple methodologies for evaluating sensory quality of new cultivars. In this context, the aim of the present work was to evaluate the applicability of a simple sensory methodology, named projective mapping, to evaluate the sensory characteristics of strawberry cultivars and advanced selections throughout the harvest season. Three strawberry cultivars and two advanced selections were evaluated by an untrained assessor panel using projective mapping in three different moments of the harvest season: June (early season), August (mid-season) and September (peak harvest). Instrumental measurements were also performed. RESULTS: Projective mapping enabled the identification of the main sensory characteristics of the strawberry cultivars and advanced selections, as well as the similarities and differences among them. Sensory characteristics of the five evaluated strawberry cultivars and advanced selections largely varied throughout the harvest season. Simple instrumental measurements were not able to predict the sensory characteristics of the strawberry cultivars, suggesting the importance of sensory methodologies for the evaluation of new cultivars in breeding programs. CONCLUSIONS: Projective mapping consisted of a quick alternative for the evaluation of new cultivars relative to standard commercial cultivars. Its main advantage is that a large number of cultivars can be screened with minimal investment of... Presentar Todo |
|
Thesagro : |
FRAGARIA X ANANASSA DUCH; FRUTILLA; MEJORAMIENTO GENÉTICO DE FRUTILLA. |
|
Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
|
Marc : |
LEADER 02428naa a2200229 a 4500
001 1050708
005 2019-10-15
008 2014 bl uuuu u00u1 u #d
022 $a0022-5142
024 7 $a10.1002/jsfa.6307$2DOI
100 1 $aVICENTE, E.
245 $aEvaluation of the sensory characteristics of strawberry cultivars throughout the harvest season using projective mapping.$h[electronic resource]
260 $c2014
500 $aArticle history: Received: 17 May 2013 / Revised: 20 June 2013 / Accepted article published: 18 July 2013 /Published online in: 9 August 2013.
520 $aABSTRACT. Strawberry breeding programs should be able to rely on valid and simple methodologies for evaluating sensory quality of new cultivars. In this context, the aim of the present work was to evaluate the applicability of a simple sensory methodology, named projective mapping, to evaluate the sensory characteristics of strawberry cultivars and advanced selections throughout the harvest season. Three strawberry cultivars and two advanced selections were evaluated by an untrained assessor panel using projective mapping in three different moments of the harvest season: June (early season), August (mid-season) and September (peak harvest). Instrumental measurements were also performed. RESULTS: Projective mapping enabled the identification of the main sensory characteristics of the strawberry cultivars and advanced selections, as well as the similarities and differences among them. Sensory characteristics of the five evaluated strawberry cultivars and advanced selections largely varied throughout the harvest season. Simple instrumental measurements were not able to predict the sensory characteristics of the strawberry cultivars, suggesting the importance of sensory methodologies for the evaluation of new cultivars in breeding programs. CONCLUSIONS: Projective mapping consisted of a quick alternative for the evaluation of new cultivars relative to standard commercial cultivars. Its main advantage is that a large number of cultivars can be screened with minimal investment of time and resources. © 2013 Society of Chemical Industry.
650 $aFRAGARIA X ANANASSA DUCH
650 $aFRUTILLA
650 $aMEJORAMIENTO GENÉTICO DE FRUTILLA
700 1 $aVARELA, P.
700 1 $aDE SALDAMANDO, L.
700 1 $aARES, G.
773 $tJournal of the Science of Food and Agriculture, 2014$gv.94, no.3, p.591-599.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
| Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Treinta y Tres. |
|
Fecha actual : |
28/03/2016 |
|
Actualizado : |
24/09/2018 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
A - 1 |
|
Autor : |
BASSU, S.; BRISSON, N.; DURAND, J.L.; BOOTE, K.; LIZASO, J.; JONES, J.W.; ROSENZWEIG, C.; RUANE, A.C.; ADAM, M.; BARON, C.; BASSO, B.; BIERNATH, C.; BOOGAARD, H.; CONIJN, S.; CORBEELS, M.L; DERYNG, D.; SANTIS, G. DE; GAYLER, S.; GRASSINI, P.; HATFIELD, J.; HOEK, S.; IZAURRALDE, C.; JONGSCHAAP, R.; KEMANIAN, A.R.; KERSEBAUM, C.KIM, S-H.; KUMAR, N.; MAKOWSKI, D.; MÜLLER, C.; NENDEL, C.; PRIESACK, E.; PRAVIA, V.; SAU, F.; SHCHERBAK, I.; TAO, F.; TEXEIRA, E.; TIMLIN, D.; WAHA, K. |
|
Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Science, The Pennsylvania State University, USA. |
|
Título : |
How do various maize crop models vary in their responses to climate change factors? |
|
Fecha de publicación : |
2014 |
|
Fuente / Imprenta : |
Global Change Biology, 2014, v.20(7), p. 2301-2320. |
|
DOI : |
10.1111/gcb.12520 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014. |
|
Contenido : |
Abstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. MenosAbstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2]... Presentar Todo |
|
Palabras claves : |
AGMIP; CARBON DIOXIDE; CLIMATE; CO2; GRAIN YIELD; MAIZE; MODEL INTERCOMPARISON; MODELIZACIÓN DE CULTIVOS; SIMULATION MODELS; TEMPERATURE. |
|
Thesagro : |
CLIMA; DIOXIDO DE CARBONO; INCERTIDUMBRE; MAÍZ; MODELOS DE SIMULACIÓN; TEMPERATURA. |
|
Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
|
Marc : |
LEADER 03684naa a2200769 a 4500
001 1054517
005 2018-09-24
008 2014 bl uuuu u00u1 u #d
024 7 $a10.1111/gcb.12520$2DOI
100 1 $aBASSU, S.
245 $aHow do various maize crop models vary in their responses to climate change factors?$h[electronic resource]
260 $c2014
500 $aArticle history: Received 7 June 2013 and accepted 2 December 2013, published 2014.
520 $aAbstract: Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
650 $aCLIMA
650 $aDIOXIDO DE CARBONO
650 $aINCERTIDUMBRE
650 $aMAÍZ
650 $aMODELOS DE SIMULACIÓN
650 $aTEMPERATURA
653 $aAGMIP
653 $aCARBON DIOXIDE
653 $aCLIMATE
653 $aCO2
653 $aGRAIN YIELD
653 $aMAIZE
653 $aMODEL INTERCOMPARISON
653 $aMODELIZACIÓN DE CULTIVOS
653 $aSIMULATION MODELS
653 $aTEMPERATURE
700 1 $aBRISSON, N.
700 1 $aDURAND, J.L.
700 1 $aBOOTE, K.
700 1 $aLIZASO, J.
700 1 $aJONES, J.W.
700 1 $aROSENZWEIG, C.
700 1 $aRUANE, A.C.
700 1 $aADAM, M.
700 1 $aBARON, C.
700 1 $aBASSO, B.
700 1 $aBIERNATH, C.
700 1 $aBOOGAARD, H.
700 1 $aCONIJN, S.
700 1 $aCORBEELS, M.L
700 1 $aDERYNG, D.
700 1 $aSANTIS, G. DE
700 1 $aGAYLER, S.
700 1 $aGRASSINI, P.
700 1 $aHATFIELD, J.
700 1 $aHOEK, S.
700 1 $aIZAURRALDE, C.
700 1 $aJONGSCHAAP, R.
700 1 $aKEMANIAN, A.R.
700 1 $aKERSEBAUM, C.KIM, S-H.
700 1 $aKUMAR, N.
700 1 $aMAKOWSKI, D.
700 1 $aMÜLLER, C.
700 1 $aNENDEL, C.
700 1 $aPRIESACK, E.
700 1 $aPRAVIA, V.
700 1 $aSAU, F.
700 1 $aSHCHERBAK, I.
700 1 $aTAO, F.
700 1 $aTEXEIRA, E.
700 1 $aTIMLIN, D.
700 1 $aWAHA, K.
773 $tGlobal Change Biology, 2014$gv.20(7), p. 2301-2320.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Treinta y Tres (TT) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
