Analysis of germination data from agricultural experiments |
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| Institution: | 1. Statistics Group, Department of Basic Sciences and Environment, Faculty of Life Sciences, University of Copenhagen, Thorvaldsensvej 40, DK-1871 Frederiksberg C, Denmark;2. Weed Science, Department of Agriculture and Ecology, Faculty of Life Sciences, University of Copenhagen, Højbakkegård Allé 13, DK-2630 Taastrup, Denmark;1. Department of Life Science and Biotechnology, University of Ferrara, via L. Borsari 46, I-44121 Ferrara, Italy;2. Department of Agricultural and Environmental Sciences – Production, Landscape, Agroenergy, University of Milan, Via G. Celoria 2, 20133 Milan, Italy;1. College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi Province, 712100, PR China;2. Power china Northwest Engineering Corporation Limited, Xi’an City, Shaanxi Province, 710065, PR China;1. Departamento de Agronomía, Universidad Nacional Del Sur, San Andrés 800, 8000 Bahía Blanca, Argentina;2. Centro de Recursos Naturales Renovables de La Zona Semiárida (CERZOS), Universidad Nacional del Sur, CONICET, 8000 Bahía Blanca, Argentina;3. EEA INTA Bordenave, Bordenave, Buenos Aires 8187, Argentina;4. Instituto Nacional de Tecnología Agropecuaria, 8142 Hilario Ascasubi, Argentina;5. Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur, CONICET, 8000 Bahía Blanca, Argentina;1. INIA-CIFOR, Department of Forest Dynamics and Management, Madrid, Spain;2. Sustainable Forest Management Research Institute, Universidad de Valladolid & INIA, Palencia, Spain;3. INRA/AgroParisTech, Laboratoire d’Etude des Ressources Forêt-Bois (UMR 1092 LERFoB), 54042 Nancy, France;4. Centre Canadien sur la Fibre de Bois, Canadian Wood Fibre Centre Service Canadien des Forêts, Canadian Forest Service, 580 rue Booth, Ottawa, ON, Canada;1. Department of Crop Sciences, Research Institute of Organic Agriculture (FiBL), Frick, Switzerland;2. Getreidezüchtung Peter Kunz (gzpk), Feldbach, Switzerland;3. Institute of Phytomedicine, University of Hohenheim, Stuttgart, Germany;4. Department of Ecological Plant Protection, University of Kassel, Witzenhausen, Germany;5. Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland;6. Wageningen Plant Research, Wageningen University & Research (WUR), Wageningen, the Netherlands;7. Institute of Agrifood Research and Technology (IRTA), Lleida, Spain |
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| Abstract: | Expensive agricultural experiments deserve to be analyzed as efficiently as possible by extracting as much information as possible from the data while respecting the experimental design. We consider experiments where germination in response to time elapsed is used to characterize germination performance and vigour. We formulate statistical models in a biologically meaningful framework in such a way that the inherent data structure, which centers around repeatedly monitoring seeds over time, is duly incorporated in the statistical analysis. Consequently, estimation and model checking procedures are based on treating the data as event times, that is, to record the time it takes for germination (the event of interest) to occur. The key result is that the use of appropriate statistical models is important in order to get a better appreciation of the uncertainty that is present in germination experiments. |
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