Sclerotium rolfsii dynamics in soil as affected by crop sequences |
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| Institution: | 1. INIA Las Brujas, National Production and Environmental Sustainability Research Program and National Family Farm Production Research Program, Ruta 48km 10, Rincón del Colorado, Canelones CP:92000, Uruguay;2. Farming Systems Ecology, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands;3. Biometris, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands;4. Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de la República, Av. Garzón 809, CP 12900 Montevideo, Uruguay;5. Emerging Pathogens Institute and Department of Plant Pathology, University of Florida, Gainesville 32611, FL, USA;1. Department of Plant Science, University of Manitoba, 222 Agriculture Building, 66 Dafoe Road, Winnipeg, MB R3T 2N2, Canada;2. Department of Soil Science, University of Manitoba, 262 Ellice Building, 13 Feedman Crescent, Winnipeg, MB R3T 2N2, Canada;3. The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK;1. Chinese Academy of Meteorological Sciences, Beijing 10081, China;2. Luoyang Meteorological Administration, Henan 471000, China;1. Department of Geography and Environment, University of Geneva, Uni Mail, 40 Boulevard du Pont-d’Arve, 1211 Geneva, Switzerland;2. Institute for Environmental Sciences, University of Geneva, Uni Rondeau, Site de Battelle – Bâtiment D, 7 route de Drize, 1227 Carouge, Switzerland;1. Institute of Soil Biology, Na Sádkach 7, 370 05, ?eské Budějovice, Czech Republic;2. Institute for Environmental Studies, Faculty of Science, Charles University in Prague, Benátská 2, 128 44, Prague 2, Czech Republic;3. Department of Ecology, Faculty of Science, Charles University in Prague, Vini?ná 7, 128 44, Prague 2, Czech Republic;4. Department of Mycology, Crop Research Institute, Drnovská 507, 161 06, Prague 6–Ruzyně, Czech Republic;5. Department of Ecotoxicology, Crop Research Institute, ?ernovická 4987, 430 01, Chomutov, Czech Republic;6. CZ Biom, Pod Vě?í 2, 169 00, Prague 6, Czech Republic |
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| Abstract: | Crop rotation has been used for the management of soilborne diseases for centuries, but has not often been planned based on scientific knowledge. Our objective was to generate information on Sclerotium rolfsii dynamics under different crop or intercrop activities, and design and test a research approach where simple experiments and the use of models are combined to explore crop sequences that minimize Southern blight incidence.The effect of seventeen green manure (GM) amendments on sclerotia dynamics was analyzed in greenhouse and field plot experiments during two years. The relative densities of viable sclerotia 90 days after winter GM (WGM) incorporation were generally lower than after summer GM (SGM) incorporation, with average recovery values of 60% and 61% for WGM in the field, 66% and 43% for WGM in the greenhouse, and 162% to 91% for SGM in the greenhouse, in 2009 and 2010, respectively. Sclerotia survival on day d after GM amendment was described by the model Sf = Si × exp(?b × d), relating initial (Si) and final (Sf) sclerotia densities. Relative decay rates of the sclerotia (b) in SGM amended soil were largest for alfalfa (0.0077 ± 0.0031 day?1) and sudangrass (0.0072 ± 0.0030 day?1). In WGM amended soil, the largest b values were for oat (0.0096 ± 0.0024 day?1), wheat (0.0090 ± 0.0024 day?1) and alfalfa (0.0087 ± 0.0023 day?1).The effect of three cropping sequences (sweet pepper–fallow, sweet pepper–black oat and sweet pepper–onion) on sclerotia dynamics was analyzed in microplot experiments, and the data were used to calibrate the model Pf = Pi/(α + βPi), relating initial (Pi) and final (Pf) sclerotia densities. Median values for the relative rate of population increase at low Pi (1/α, dimension less) and the asymptote (1/β, number of viable sclerotia in 100 g of dry soil) were 8.22 and 4.17 for black oat (BO), 1.13 and 8.64 for onion (O), and 6.26 and 17.93 for sweet pepper (SwP).By concatenating the two models, sclerotia population dynamics under several crop sequences were simulated. At steady state, the sequence SwP–O–Fallow–BO resulted in the lowest long-term sclerotia density (7.09 sclerotia/100 g soil), and SwP–Fallow in the highest (17.89 sclerotia/100 g soil). The developed methodology facilitates the selection of a limited number of rotation options to be tested in farmers’ fields. |
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| Keywords: | Population dynamics Simulation model Crop rotation Green manure amendment |
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