Optimal plot size and white rot incidence of sunflower evaluated in the southeastern of Buenos Aires Province
In Balcarce, AR, the white rot incidence by Sclerotinia sclerotiorum was evaluated in two sunflower F1 cultivars grown in uniformity trials during 2016 and 2017. At first year there were 165 minimum plots of 2m long and 0.7m wide (i.e. 1.4m2) with around seven plants each, by hybrid. In the second year, minimum plots reached 150. All capitula were inoculated with pathogen ascospores and white rot incidence was scored at each minimum plot. Adjacent minimum plots were combined to generate other plots with larger surfaces. The optimal size was detected by using the maximum curvature method in graphs where the coefficient of variation (%) was drawn in function of plot sizes. Combined analysis of variance detected significant effects of hybrids (H), years (Y) and HxY interaction on disease incidence. Results did not allow indicating a unique plot size, given that the optimum depended on the level of resistance of hybrid as well as the year of the experiment was made. During 2017, the most favorable one for white rot disease appearance, the optimum size was lower than in 2016 for both hybrids. Under our experimental conditions, the use of larger plots than the optimum detected herein would not cause a significant increase in the reliability of the disease incidence scoring per unit of resources employed.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | spa |
| Published: |
Facultad de Ciencias Agrarias y Forestales de la Universidad Nacional de La Plata
2019
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| Online Access: | https://revistas.unlp.edu.ar/revagro/article/view/7604 |
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| Summary: | In Balcarce, AR, the white rot incidence by Sclerotinia sclerotiorum was evaluated in two sunflower F1 cultivars grown in uniformity trials during 2016 and 2017. At first year there were 165 minimum plots of 2m long and 0.7m wide (i.e. 1.4m2) with around seven plants each, by hybrid. In the second year, minimum plots reached 150. All capitula were inoculated with pathogen ascospores and white rot incidence was scored at each minimum plot. Adjacent minimum plots were combined to generate other plots with larger surfaces. The optimal size was detected by using the maximum curvature method in graphs where the coefficient of variation (%) was drawn in function of plot sizes. Combined analysis of variance detected significant effects of hybrids (H), years (Y) and HxY interaction on disease incidence. Results did not allow indicating a unique plot size, given that the optimum depended on the level of resistance of hybrid as well as the year of the experiment was made. During 2017, the most favorable one for white rot disease appearance, the optimum size was lower than in 2016 for both hybrids. Under our experimental conditions, the use of larger plots than the optimum detected herein would not cause a significant increase in the reliability of the disease incidence scoring per unit of resources employed. |
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