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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
08/06/2022 |
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Actualizado : |
01/12/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LARZABAL, J.; RODRIGUEZ, M.; YAMANAKA, N.; STEWART, S. |
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Afiliación : |
JHON LARZABAL PÉREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Magíster en Ciencias Agrarias, Facultad de Agronomía, Universidad de La República, Montevideo, Uruguay.; MARCELO JULIAN RODRIGUEZ ALONZO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; NAOKI YAMANAKA, Biological Resources and Post-harvest Division, Japan International Research Center for Agricultural Sciences (JIRCAS), 1-1 Ohwashi, Tsukuba, Ibaraki, 305-8686, Japan.; SILVINA MARIA STEWART SONEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Pathogenic variability of Asian soybean rust fungus within fields in Uruguay. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Tropical Plant Pathology, 2022, Volume 47, Issue 4, Pages 574-582. doi: https://doi.org/10.1007/s40858-022-00511-2 |
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DOI : |
10.1007/s40858-022-00511-2 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 20 January 2022/ Accepted 04 May 2022/ Published 26 May 2022.This study was partly financially supported by the National Institute for Agricultural Research (INIA) and partly by the Japan International Research Center for Agricultural Sciences (JIRCAS) research project ?Development of resilient crops and production technologies. |
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Contenido : |
Abstract:
Asian soybean rust (ASR) caused by Phakopsora pachyrhizi is one of the most threatening diseases in soybean, the most important agricultural crop in Uruguay. Resistance to ASR is conditioned by major genes called Rpps. So far, at least 12 Rpp genes and/or alleles have been identified and mapped to seven loci in the soybean genome. To enhance genetic improvement and reduce yield losses in Uruguay, it is essential to know the pathotypes that interact with Rpp-carrying soybeans, their dynamics and diversity. Five commercial fields were sampled in different regions of the country during two seasons in order to determine the number of pathotypes to which soybeans are locally exposed. Three to 19 single-lesion isolates per field were obtained. Based on the number of uredinia per lesion and the sporulation level, avirulent/virulent phenotype was determined for each isolate by inoculating onto a differential set. Twenty-eight pathotypes were differentiated from a total of 50 isolates, 17 were unique, and 11 were recurrently isolated up to five times. The most frequent pathotype was found in one field only, while several pathotypes were shared among fields. Mayor genes Rpp1-b, Rpp5, and Rpp6 had resistant interactions with many of the isolates, while Rpp1-b and the soybean line with Rpp2, Rpp4, and Rpp5 stacked genes showed resistance to all isolates. In contrast, Rpp1 and Rpp3 showed susceptible reactions to all isolates. Pathogenic variability was higher within fields than among fields; thus, soybean cultivars can be exposed to up to 13 different pathotypes within a single field. This high diversity should be considered when breeding for resistance to this pathogen; thus, pyramiding mayor genes and introducing horizontal resistance should be considered. © 2022, The Author(s), under exclusive license to Sociedade Brasileira de Fitopatologia. MenosAbstract:
Asian soybean rust (ASR) caused by Phakopsora pachyrhizi is one of the most threatening diseases in soybean, the most important agricultural crop in Uruguay. Resistance to ASR is conditioned by major genes called Rpps. So far, at least 12 Rpp genes and/or alleles have been identified and mapped to seven loci in the soybean genome. To enhance genetic improvement and reduce yield losses in Uruguay, it is essential to know the pathotypes that interact with Rpp-carrying soybeans, their dynamics and diversity. Five commercial fields were sampled in different regions of the country during two seasons in order to determine the number of pathotypes to which soybeans are locally exposed. Three to 19 single-lesion isolates per field were obtained. Based on the number of uredinia per lesion and the sporulation level, avirulent/virulent phenotype was determined for each isolate by inoculating onto a differential set. Twenty-eight pathotypes were differentiated from a total of 50 isolates, 17 were unique, and 11 were recurrently isolated up to five times. The most frequent pathotype was found in one field only, while several pathotypes were shared among fields. Mayor genes Rpp1-b, Rpp5, and Rpp6 had resistant interactions with many of the isolates, while Rpp1-b and the soybean line with Rpp2, Rpp4, and Rpp5 stacked genes showed resistance to all isolates. In contrast, Rpp1 and Rpp3 showed susceptible reactions to all isolates. Pathogenic variability was higher within fields tha... Presentar Todo |
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Palabras claves : |
Pathotype; PHAKOPSORA PACHYRHIZI; Urediniospore. |
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Thesagro : |
ENFERMEDADES DE LAS PLANTAS; SOJA. |
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Asunto categoría : |
H20 Enfermedades de las plantas |
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Marc : |
LEADER 02980naa a2200241 a 4500
001 1063250
005 2022-12-01
008 2022 bl uuuu u00u1 u #d
024 7 $a10.1007/s40858-022-00511-2$2DOI
100 1 $aLARZABAL, J.
245 $aPathogenic variability of Asian soybean rust fungus within fields in Uruguay.$h[electronic resource]
260 $c2022
500 $aArticle history: Received 20 January 2022/ Accepted 04 May 2022/ Published 26 May 2022.This study was partly financially supported by the National Institute for Agricultural Research (INIA) and partly by the Japan International Research Center for Agricultural Sciences (JIRCAS) research project ?Development of resilient crops and production technologies.
520 $aAbstract: Asian soybean rust (ASR) caused by Phakopsora pachyrhizi is one of the most threatening diseases in soybean, the most important agricultural crop in Uruguay. Resistance to ASR is conditioned by major genes called Rpps. So far, at least 12 Rpp genes and/or alleles have been identified and mapped to seven loci in the soybean genome. To enhance genetic improvement and reduce yield losses in Uruguay, it is essential to know the pathotypes that interact with Rpp-carrying soybeans, their dynamics and diversity. Five commercial fields were sampled in different regions of the country during two seasons in order to determine the number of pathotypes to which soybeans are locally exposed. Three to 19 single-lesion isolates per field were obtained. Based on the number of uredinia per lesion and the sporulation level, avirulent/virulent phenotype was determined for each isolate by inoculating onto a differential set. Twenty-eight pathotypes were differentiated from a total of 50 isolates, 17 were unique, and 11 were recurrently isolated up to five times. The most frequent pathotype was found in one field only, while several pathotypes were shared among fields. Mayor genes Rpp1-b, Rpp5, and Rpp6 had resistant interactions with many of the isolates, while Rpp1-b and the soybean line with Rpp2, Rpp4, and Rpp5 stacked genes showed resistance to all isolates. In contrast, Rpp1 and Rpp3 showed susceptible reactions to all isolates. Pathogenic variability was higher within fields than among fields; thus, soybean cultivars can be exposed to up to 13 different pathotypes within a single field. This high diversity should be considered when breeding for resistance to this pathogen; thus, pyramiding mayor genes and introducing horizontal resistance should be considered. © 2022, The Author(s), under exclusive license to Sociedade Brasileira de Fitopatologia.
650 $aENFERMEDADES DE LAS PLANTAS
650 $aSOJA
653 $aPathotype
653 $aPHAKOPSORA PACHYRHIZI
653 $aUrediniospore
700 1 $aRODRIGUEZ, M.
700 1 $aYAMANAKA, N.
700 1 $aSTEWART, S.
773 $tTropical Plant Pathology, 2022, Volume 47, Issue 4, Pages 574-582. doi: https://doi.org/10.1007/s40858-022-00511-2
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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 : |
29/03/2021 |
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Actualizado : |
15/06/2022 |
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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 : |
SCHILLACI, C; PEREGO, A.; VALKAMA, E.; MÄRKER, M.; SAIA, S.; VERONESI, F.; LIPANI, A.; LOMBARDO, L.; TADIELLO, T.; GAMPER, H. A.; TEDONE, L.; MOSS, C.; PAREJA-SERRANO, E.; AMATO, G.; KÜHL, K.; DAMATIRCA, C.; COGATO, A.; MZID, N.; EESWARAN, R.; REBELO, M.; SPERANDIO, G.; BOSINO, A.; BUFALINI, M.; TUNÇAY, T.; DING, J.; FIORENTINI, M.; TISCORNIA, G.; CONRADT, S.; BOTTA, M.; ACUTIS, M. |
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Afiliación : |
CALOGERO SCHILLACI, Department of Agricultural and Environmental Science, University of Milan, Milan, Italy; ALESSIA PEREGO, Department of Agricultural and Environmental Science, University of Milan, Milan, Italy; ELENA VALKAMA, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Jokioinen, Finland; MICHAEL MÄRKER, Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy; SERGIO SAIA, Department of Veterinary Sciences, University of Pisa,Pisa, Italy; FABIO VERONESI, Water Research Centre Limited, Frankland Road, Blagrove, Swindon, England, UK; ALDO LIPANI, Department of Web Intelligence Group, University College London (UCL), London, England, UK; LUIGI LOMBARDO, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, the Netherlands; TOMMASO TADIELLO, Department of Agricultural and Environmental Science, University of Milan, Milan, Italy; HANNES A. GAMPER, Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy; LUIGI TEDONE, Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy; CAMI MOSS, Department of Population Health, London School of Hygiene & Tropical Medicine, London, UK; ELENA PAREJA-SERRANO, NRAE-UMR EMMAH, Domaine Saint Paul - Site Agroparc, Avignon, France; GABRIELE AMATO,, Applied Physics Institute, Nello Carrara - National Research Council of Italy (IFAC-CNR), Sesto Fiorentino (FI), Italy; KERSTEN KÜHL, Department of Geography, Ludwig-Maximilians-Universität München (LMU Munich), Germany; CLAUDIA DAMATIRCA, Department of Agricultural, Forest and Food Sciences, University of Torino, Grugliasco, Italy; ALESSIA COGATO, Department of Land, Environmental, Agriculture and Forestry, University of Padova, Legnaro, Italy; NADA MZID, Department of Agriculture Forestry and Nature (DAFNE), University of Tuscia, Viterbo, Italy; RASU EESWARAN, Department of Plant, Soil and Microbial Sciences, Michigan State University, MI, USA; MARYA REBELO, Department of Agriculture, Food and Environment, University of Pisa, Pisa, Italy; GIORGIO SPERANDIO, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy; ALBERTO BOSINO, Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy; MARGHERITA BUFALINI, University of Camerino, School of Science and Technology-Geology Division, Camerino, Italy; TÜLAY TUNÇAY, Soil Fertilizer and Water Resources Central Research Institute, Ankara, Turkey; JIANQI DING, Department of Biological and Ecological Sciences DEB, Università della Tuscia, Viterbo, Italy; MARCO FIORENTINI, Department of Agricultural, Food and Environmental Sciences (D3A), Marche Polytechnic University, Ancona, Italy; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SARAH CONRADT, SCOR SE, Zurich Branch, Switzerland; MARCO BOTTA, Department of Agricultural and Environmental Science, University of Milan, Milan, Italy; MARCO ACUTIS, Department of Agricultural and Environmental Science, University of Milan,Milan, Italy. |
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Título : |
New pedotransfer approaches to predict soil bulk density using WoSIS soil data and environmental covariates in Mediterranean agro-ecosystems. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Science of The Total Environment, 2021, Volume 780, Article 146609. Doi: https://doi.org/10.1016/j.scitotenv.2021.146609 |
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DOI : |
10.1016/j.scitotenv.2021.146609 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 26 December 2020; Revised 24 February 2021; Accepted 16 March 2021; Available online 19 March 2021.
Incluye Supplementary data.
Editor: Manuel Esteban Lucas-Borja |
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Contenido : |
ABSTRACT.
For the estimation of the soil organic carbon stocks, bulk density (BD) is a fundamental parameter but measured data are usually not available especially when dealing with legacy soil data. It is possible to estimate BD by applying pedotransfer function (PTF). We applied different estimation methods with the aim to define a suitable PTF for BD of arable land for the Mediterranean Basin, which has peculiar climate features that may influence the soil carbon sequestration. To improve the existing BD estimation methods, we used a set of public climatic and topographic data along with the soil texture and organic carbon data. The present work consisted of the following steps: i) development of three PTFs models separately for top (0?0.4 m) and subsoil (0.4?1.2 m), ii) a 10-fold cross-validation, iii) model transferability using an external dataset derived from published data.
The development of the new PTFs was based on the training dataset consisting of World Soil Information Service (WoSIS) soil profile data, climatic data from WorldClim at 1 km spatial resolution and Shuttle Radar Topography Mission (SRTM) digital elevation model at 30 m spatial resolution.
The three PTFs models were developed using: Multiple Linear Regression stepwise (MLR-S), Multiple Linear Regression backward stepwise (MLR-BS), and Artificial Neural Network (ANN).
The predictions of the newly developed PTFs were compared with the BD calculated using the PTF proposed by Manrique and Jones (MJ) and the modelled BD derived from the global SoilGrids dataset.
© 2021 Published by Elsevier B.V. MenosABSTRACT.
For the estimation of the soil organic carbon stocks, bulk density (BD) is a fundamental parameter but measured data are usually not available especially when dealing with legacy soil data. It is possible to estimate BD by applying pedotransfer function (PTF). We applied different estimation methods with the aim to define a suitable PTF for BD of arable land for the Mediterranean Basin, which has peculiar climate features that may influence the soil carbon sequestration. To improve the existing BD estimation methods, we used a set of public climatic and topographic data along with the soil texture and organic carbon data. The present work consisted of the following steps: i) development of three PTFs models separately for top (0?0.4 m) and subsoil (0.4?1.2 m), ii) a 10-fold cross-validation, iii) model transferability using an external dataset derived from published data.
The development of the new PTFs was based on the training dataset consisting of World Soil Information Service (WoSIS) soil profile data, climatic data from WorldClim at 1 km spatial resolution and Shuttle Radar Topography Mission (SRTM) digital elevation model at 30 m spatial resolution.
The three PTFs models were developed using: Multiple Linear Regression stepwise (MLR-S), Multiple Linear Regression backward stepwise (MLR-BS), and Artificial Neural Network (ANN).
The predictions of the newly developed PTFs were compared with the BD calculated using the PTF proposed by Manrique and Jones (MJ) an... Presentar Todo |
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Palabras claves : |
Agriculture; Bulk density (BD); Pedotransfer functions; PTFs; Soil carbon; Soil carbon sequestration; Soil organic carbon stocks; Soil texture. |
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Asunto categoría : |
P36 Erosión conservación y recuperación del suelo |
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Marc : |
LEADER 03433naa a2200589 a 4500
001 1061870
005 2022-06-15
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1016/j.scitotenv.2021.146609$2DOI
100 1 $aSCHILLACI, C
245 $aNew pedotransfer approaches to predict soil bulk density using WoSIS soil data and environmental covariates in Mediterranean agro-ecosystems.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 26 December 2020; Revised 24 February 2021; Accepted 16 March 2021; Available online 19 March 2021. Incluye Supplementary data. Editor: Manuel Esteban Lucas-Borja
520 $aABSTRACT. For the estimation of the soil organic carbon stocks, bulk density (BD) is a fundamental parameter but measured data are usually not available especially when dealing with legacy soil data. It is possible to estimate BD by applying pedotransfer function (PTF). We applied different estimation methods with the aim to define a suitable PTF for BD of arable land for the Mediterranean Basin, which has peculiar climate features that may influence the soil carbon sequestration. To improve the existing BD estimation methods, we used a set of public climatic and topographic data along with the soil texture and organic carbon data. The present work consisted of the following steps: i) development of three PTFs models separately for top (0?0.4 m) and subsoil (0.4?1.2 m), ii) a 10-fold cross-validation, iii) model transferability using an external dataset derived from published data. The development of the new PTFs was based on the training dataset consisting of World Soil Information Service (WoSIS) soil profile data, climatic data from WorldClim at 1 km spatial resolution and Shuttle Radar Topography Mission (SRTM) digital elevation model at 30 m spatial resolution. The three PTFs models were developed using: Multiple Linear Regression stepwise (MLR-S), Multiple Linear Regression backward stepwise (MLR-BS), and Artificial Neural Network (ANN). The predictions of the newly developed PTFs were compared with the BD calculated using the PTF proposed by Manrique and Jones (MJ) and the modelled BD derived from the global SoilGrids dataset. © 2021 Published by Elsevier B.V.
653 $aAgriculture
653 $aBulk density (BD)
653 $aPedotransfer functions
653 $aPTFs
653 $aSoil carbon
653 $aSoil carbon sequestration
653 $aSoil organic carbon stocks
653 $aSoil texture
700 1 $aPEREGO, A.
700 1 $aVALKAMA, E.
700 1 $aMÄRKER, M.
700 1 $aSAIA, S.
700 1 $aVERONESI, F.
700 1 $aLIPANI, A.
700 1 $aLOMBARDO, L.
700 1 $aTADIELLO, T.
700 1 $aGAMPER, H. A.
700 1 $aTEDONE, L.
700 1 $aMOSS, C.
700 1 $aPAREJA-SERRANO, E.
700 1 $aAMATO, G.
700 1 $aKÜHL, K.
700 1 $aDAMATIRCA, C.
700 1 $aCOGATO, A.
700 1 $aMZID, N.
700 1 $aEESWARAN, R.
700 1 $aREBELO, M.
700 1 $aSPERANDIO, G.
700 1 $aBOSINO, A.
700 1 $aBUFALINI, M.
700 1 $aTUNÇAY, T.
700 1 $aDING, J.
700 1 $aFIORENTINI, M.
700 1 $aTISCORNIA, G.
700 1 $aCONRADT, S.
700 1 $aBOTTA, M.
700 1 $aACUTIS, M.
773 $tScience of The Total Environment, 2021, Volume 780, Article 146609. Doi: https://doi.org/10.1016/j.scitotenv.2021.146609
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