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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
29/01/2024 |
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Actualizado : |
29/01/2024 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
DINI, M.; FRANZON, R.C.; RASEIRA, M.C.B; UENO, B.; MARCHI, P.M.; VIZZOTTO, M. |
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Afiliación : |
MAXIMILIANO ANTONIO DINI VIÑOLY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Universidade Federal de Pelotas, Faculdade de Agronomia Eliseu Maciel, Programa de Pós-Graduação em Agronomia, Rio Grande do Sul, Pelotas, Brazil; RODRIGO CEZAR FRANZON, Empresa Brasileira de Pesquisa Agropecuária, Embrapa Clima Temperado, Rio Grande do Sul, Pelotas, Brazil; MARIA DO CARMO BASSOLS RASEIRA, Empresa Brasileira de Pesquisa Agropecuária, Embrapa Clima Temperado, Rio Grande do Sul, Pelotas, Brazil; BERNARDO UENO, Empresa Brasileira de Pesquisa Agropecuária, Embrapa Clima Temperado, Rio Grande do Sul, Pelotas, Brazil; PRISCILA MONALISA MARCHI, Universidade Federal de Pelotas, Faculdade de Agronomia Eliseu Maciel, Programa de Pós-Graduação em Agronomia, Rio Grande do Sul, Pelotas, Brazil; Faculdade Santo Ângelo (FASA), Agronomia, Rio Grande do Sul, Santo Ângelo, Brazil; MARCIA VIZZOTTO, Empresa Brasileira de Pesquisa Agropecuária, Embrapa Clima Temperado, Rio Grande do Sul, Pelotas, Brazil. |
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Título : |
Blossom blight resistance in peach: phenotyping and antioxidants content in petals. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Brazilian Archives of Biology and Technology, 2023, Volume 66, e23220730. https://doi.org/10.1590/1678-4324-2023220730 -- OPEN ACCESS. |
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ISSN : |
1516-8913 |
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DOI : |
10.1590/1678-4324-2023220730 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 15 September 2022, Accepted 31 May 2023, Publication in this collection 30 October 2023, Date of issue 2023. -- Document type: Article Gold Open Access. -- Correspondence: Dini, M.; Universidade Federal de Pelotas, Faculdade de Agronomia Eliseu Maciel, Programa de Pós-Graduação em Agronomia, Rio Grande do Sul, Pelotas, Brazil; email:mdini@inia.org.uy -- Funding: This research was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES), through the first author's doctoral scholarship. -- Editor in Chief: Paulo Vitor Farago. -- Associate Editor: Jane Manfron Budel.-- License: Creative Commons Attribution (CC BY NC) license (https://creativecommons.org/licenses/by-nc/4.0/). |
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Contenido : |
ABSTRACT.- Brown rot and blossom blight caused by fungi of the genus Monilinia are the most important peach diseases. The increased concern with the environment and the health of workers and consumers, as well as the emergence of fungus isolates resistant to the main fungicide molecules favor control strategies such as genetic resistance. The objective of this study was to adjust a phenotyping protocol for evaluation of resistance/susceptibility to blossom blight in peach, as well as to quantify the antioxidant compounds present in the petals of these flowers and their correlation with the disease incidence and severity. The experiment was arranged in a randomized complete block split-split plot design, the plot being four concentrations of Monilinia fructicola conidia; the subplot two phenological flower stage; and the sub-subplot four peach genotypes. The quantification of antioxidant compounds and their correlation with susceptibility to blossom blight was performed in the four genotypes analyzed. Phenotyping was more efficient when concentrations between 400 and 4,000 conidia mL-1 were used, regardless of phenological flower stage. The phenolic compounds, anthocyanins and antioxidant activity are positively correlated among them, and negatively correlated with the blossom blight incidence and severity. In order to estimate the blossom blight susceptibility, it is recommended to use flowers at the pink or bloom stage, inoculum equivalent to 20-200 conidia per flower, and perform the evaluation at 96 hours after inoculation. This study suggests that more intense pink flowers have a higher content of antioxidant compounds and less blossom blight susceptibility. © 2023 by the authors. MenosABSTRACT.- Brown rot and blossom blight caused by fungi of the genus Monilinia are the most important peach diseases. The increased concern with the environment and the health of workers and consumers, as well as the emergence of fungus isolates resistant to the main fungicide molecules favor control strategies such as genetic resistance. The objective of this study was to adjust a phenotyping protocol for evaluation of resistance/susceptibility to blossom blight in peach, as well as to quantify the antioxidant compounds present in the petals of these flowers and their correlation with the disease incidence and severity. The experiment was arranged in a randomized complete block split-split plot design, the plot being four concentrations of Monilinia fructicola conidia; the subplot two phenological flower stage; and the sub-subplot four peach genotypes. The quantification of antioxidant compounds and their correlation with susceptibility to blossom blight was performed in the four genotypes analyzed. Phenotyping was more efficient when concentrations between 400 and 4,000 conidia mL-1 were used, regardless of phenological flower stage. The phenolic compounds, anthocyanins and antioxidant activity are positively correlated among them, and negatively correlated with the blossom blight incidence and severity. In order to estimate the blossom blight susceptibility, it is recommended to use flowers at the pink or bloom stage, inoculum equivalent to 20-200 conidia per flower, and ... Presentar Todo |
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Palabras claves : |
Anthocyanins; Antioxidant activity; Monilinia fructicola (Winter) Honey; Phenolic compounds; Prunus persica (L.) Batsch; SISTEMA VEGETAL INTENSIVO - INIA. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/17478/1/Dini-eta-2023-BABT-1678-4324-2023220730.pdf
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Marc : |
LEADER 03401naa a2200289 a 4500
001 1064442
005 2024-01-29
008 2023 bl uuuu u00u1 u #d
022 $a1516-8913
024 7 $a10.1590/1678-4324-2023220730$2DOI
100 1 $aDINI, M.
245 $aBlossom blight resistance in peach$bphenotyping and antioxidants content in petals.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 15 September 2022, Accepted 31 May 2023, Publication in this collection 30 October 2023, Date of issue 2023. -- Document type: Article Gold Open Access. -- Correspondence: Dini, M.; Universidade Federal de Pelotas, Faculdade de Agronomia Eliseu Maciel, Programa de Pós-Graduação em Agronomia, Rio Grande do Sul, Pelotas, Brazil; email:mdini@inia.org.uy -- Funding: This research was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES), through the first author's doctoral scholarship. -- Editor in Chief: Paulo Vitor Farago. -- Associate Editor: Jane Manfron Budel.-- License: Creative Commons Attribution (CC BY NC) license (https://creativecommons.org/licenses/by-nc/4.0/).
520 $aABSTRACT.- Brown rot and blossom blight caused by fungi of the genus Monilinia are the most important peach diseases. The increased concern with the environment and the health of workers and consumers, as well as the emergence of fungus isolates resistant to the main fungicide molecules favor control strategies such as genetic resistance. The objective of this study was to adjust a phenotyping protocol for evaluation of resistance/susceptibility to blossom blight in peach, as well as to quantify the antioxidant compounds present in the petals of these flowers and their correlation with the disease incidence and severity. The experiment was arranged in a randomized complete block split-split plot design, the plot being four concentrations of Monilinia fructicola conidia; the subplot two phenological flower stage; and the sub-subplot four peach genotypes. The quantification of antioxidant compounds and their correlation with susceptibility to blossom blight was performed in the four genotypes analyzed. Phenotyping was more efficient when concentrations between 400 and 4,000 conidia mL-1 were used, regardless of phenological flower stage. The phenolic compounds, anthocyanins and antioxidant activity are positively correlated among them, and negatively correlated with the blossom blight incidence and severity. In order to estimate the blossom blight susceptibility, it is recommended to use flowers at the pink or bloom stage, inoculum equivalent to 20-200 conidia per flower, and perform the evaluation at 96 hours after inoculation. This study suggests that more intense pink flowers have a higher content of antioxidant compounds and less blossom blight susceptibility. © 2023 by the authors.
653 $aAnthocyanins
653 $aAntioxidant activity
653 $aMonilinia fructicola (Winter) Honey
653 $aPhenolic compounds
653 $aPrunus persica (L.) Batsch
653 $aSISTEMA VEGETAL INTENSIVO - INIA
700 1 $aFRANZON, R.C.
700 1 $aRASEIRA, M.C.B
700 1 $aUENO, B.
700 1 $aMARCHI, P.M.
700 1 $aVIZZOTTO, M.
773 $tBrazilian Archives of Biology and Technology, 2023, Volume 66, e23220730. https://doi.org/10.1590/1678-4324-2023220730 -- OPEN ACCESS.
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INIA Las Brujas (LB) |
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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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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha actual : |
12/11/2015 |
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Actualizado : |
09/10/2019 |
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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 : |
MARCAIDA, M.; ASSENG, S.; EWERT, F.; BASSU, S.; DURAND, J.L.; LI, T.; MARTRE, P.; ADAM, M.; AGGARWAL, P.K.; ANGULO, C.; BARON, C.; BASSO, B.; BERTUZZI, P.; BIERNATH, C.; BOOGAARD, H.; BOOTE, K.J.; BOUMAN, B.; BREGAGLIO, S.; BRISSON, N.; BUIS, S.; CAMMARANO, D.; CHALLINOR, A.J.; CONFALONIERI, R.; CONIJN, J.G.; CORBEELS, M.; DERYNG, D.; DE SANCTIS, G.; DOLTRA, J.; FUMOTO, T.; GAYDON, D.; GAYLER, S.; GOLDBERG, R.; GRANT, R.F.; GRASSINI, P.; HATFIELD, J.L.; HASEGAWA, T.; HENG, L.; HOEK, S.; HOOKER, J.; HUNT, L.A.; INGWERSEN, J.; IZAURRALDE, R.C.; JONGSCHAAP, R.E.E.; JONES, J.W.; KEMANIAN, R.A.; KERSEBAUM, K.C.; KIM, S.-H.; LIZASO, J.; MÜLLER, C.; NAKAGAWA, H.; NARESH KUMAR, S.; NENDEL, C.; O'LEARY, G.J.; OLESEN, J.E.; ORIOL, P.; OSBORNE, T.M.; PALOSUO, T.; PRAVIA, V.; PRIESACK, E.; RIPOCHE, D.; ROSENZWEIG, C.; RUANE, A.C.; RUGET, F.; SAU, F.; SEMENOV, M.A.; SHCHERBAK, I.; SINGH, B.; SINGH, U.; SOO, H.K.; STEDUTO, P.; STÖCKLE, C.; STRATONOVITCH, P.; STRECK, T.; SUPIT, I.; TANG, L.; TAO, F.; TEIXEIRA, E.I.; THORBURN, P.; TIMLIN, D.; TRAVASSO, M.; RÖTTER, R.P.; WAHA, K.; WALLACH, D.; WHITE, J.W.; WILKENS, P.; WILLIAMS, J.R.; WOLF, J.; YIN, X.; YOSHIDA, H.; ZHANG, Z.; ZHU, Y. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. |
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ISSN : |
0168-1923 |
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DOI : |
10.1016/j.agrformet.2015.09.013 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. |
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Contenido : |
ABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2].
© 2015 Elsevier B.V. All rights reserved. MenosABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in... Presentar Todo |
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Palabras claves : |
Climate change; CROP MODEL; Emulator; MAIZE; Meta-model; MODELIZACIÓN DE LOS CULTIVOS; RICE; Statistical model; WHEAT; Yield. |
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Thesagro : |
ARROZ; CAMBIO CLIMÁTICO; MAÍZ; MODELOS ESTADISTICOS; TRIGO. |
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Asunto categoría : |
A50 Investigación agraria |
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Marc : |
LEADER 05363naa a2201417 a 4500
001 1053856
005 2019-10-09
008 2015 bl uuuu u00u1 u #d
022 $a0168-1923
024 7 $a10.1016/j.agrformet.2015.09.013$2DOI
100 1 $aMARCAIDA, M.
245 $aA statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration.
260 $c2015
500 $aArticle history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015.
520 $aABSTRACT. Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2]. © 2015 Elsevier B.V. All rights reserved.
650 $aARROZ
650 $aCAMBIO CLIMÁTICO
650 $aMAÍZ
650 $aMODELOS ESTADISTICOS
650 $aTRIGO
653 $aClimate change
653 $aCROP MODEL
653 $aEmulator
653 $aMAIZE
653 $aMeta-model
653 $aMODELIZACIÓN DE LOS CULTIVOS
653 $aRICE
653 $aStatistical model
653 $aWHEAT
653 $aYield
700 1 $aASSENG, S.
700 1 $aEWERT, F.
700 1 $aBASSU, S.
700 1 $aDURAND, J.L.
700 1 $aLI, T.
700 1 $aMARTRE, P.
700 1 $aADAM, M.
700 1 $aAGGARWAL, P.K.
700 1 $aANGULO, C.
700 1 $aBARON, C.
700 1 $aBASSO, B.
700 1 $aBERTUZZI, P.
700 1 $aBIERNATH, C.
700 1 $aBOOGAARD, H.
700 1 $aBOOTE, K.J.
700 1 $aBOUMAN, B.
700 1 $aBREGAGLIO, S.
700 1 $aBRISSON, N.
700 1 $aBUIS, S.
700 1 $aCAMMARANO, D.
700 1 $aCHALLINOR, A.J.
700 1 $aCONFALONIERI, R.
700 1 $aCONIJN, J.G.
700 1 $aCORBEELS, M.
700 1 $aDERYNG, D.
700 1 $aDE SANCTIS, G.
700 1 $aDOLTRA, J.
700 1 $aFUMOTO, T.
700 1 $aGAYDON, D.
700 1 $aGAYLER, S.
700 1 $aGOLDBERG, R.
700 1 $aGRANT, R.F.
700 1 $aGRASSINI, P.
700 1 $aHATFIELD, J.L.
700 1 $aHASEGAWA, T.
700 1 $aHENG, L.
700 1 $aHOEK, S.
700 1 $aHOOKER, J.
700 1 $aHUNT, L.A.
700 1 $aINGWERSEN, J.
700 1 $aIZAURRALDE, R.C.
700 1 $aJONGSCHAAP, R.E.E.
700 1 $aJONES, J.W.
700 1 $aKEMANIAN, R.A.
700 1 $aKERSEBAUM, K.C.
700 1 $aKIM, S.-H.
700 1 $aLIZASO, J.
700 1 $aMÜLLER, C.
700 1 $aNAKAGAWA, H.
700 1 $aNARESH KUMAR, S.
700 1 $aNENDEL, C.
700 1 $aO'LEARY, G.J.
700 1 $aOLESEN, J.E.
700 1 $aORIOL, P.
700 1 $aOSBORNE, T.M.
700 1 $aPALOSUO, T.
700 1 $aPRAVIA, V.
700 1 $aPRIESACK, E.
700 1 $aRIPOCHE, D.
700 1 $aROSENZWEIG, C.
700 1 $aRUANE, A.C.
700 1 $aRUGET, F.
700 1 $aSAU, F.
700 1 $aSEMENOV, M.A.
700 1 $aSHCHERBAK, I.
700 1 $aSINGH, B.
700 1 $aSINGH, U.
700 1 $aSOO, H.K.
700 1 $aSTEDUTO, P.
700 1 $aSTÖCKLE, C.
700 1 $aSTRATONOVITCH, P.
700 1 $aSTRECK, T.
700 1 $aSUPIT, I.
700 1 $aTANG, L.
700 1 $aTAO, F.
700 1 $aTEIXEIRA, E.I.
700 1 $aTHORBURN, P.
700 1 $aTIMLIN, D.
700 1 $aTRAVASSO, M.
700 1 $aRÖTTER, R.P.
700 1 $aWAHA, K.
700 1 $aWALLACH, D.
700 1 $aWHITE, J.W.
700 1 $aWILKENS, P.
700 1 $aWILLIAMS, J.R.
700 1 $aWOLF, J.
700 1 $aYIN, X.
700 1 $aYOSHIDA, H.
700 1 $aZHANG, Z.
700 1 $aZHU, Y.
773 $tAgricultural and Forest Meteorology, 2015$gv.214-215, p. 483-493.
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