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Disease Progress Curve Parameters Help to Characterise the Types of Resistance to Late Blight Segregating in Cultivated Potato
Authors:Sylvie Marhadour  Roland Pellé  Jean-Marc Abiven  Frédérique Aurousseau  Hervé Dubreuil  Yves Le Hingrat  Jean-Eric Chauvin
Institution:1. FN3PT, 43-45 rue de Naples, 75008, Paris, France
2. INRA UMR 1349 IGEPP, Keraiber, 29260, Ploudaniel, France
3. Station de Création Variétale, Bretagne Plants, Kerlo?, 29260, Ploudaniel, France
4. Station de recherche du Comité Nord, 76110, Bretteville du Grand Caux, France
5. GROCEP, Station de Lavergne, 87370, Laurière, France
6. FN3PT, Roudouhir, 29460, Hanvec, France
Abstract:To decrease the environmental impact of treatments against late blight caused by Phytophthora infestans on potato, plant genetic resistance is a keystone in developing new culture strategies. Nonspecific resistance to late blight is a complex trait which is difficult to evaluate, while selection is both difficult and time consuming. However, we consider it is important to select for this type of resistance as it is a promising way to achieve durable resistance. In this study, parameters derived from disease progress curves (DPCs) were used to characterise the types of resistance among individuals of three tetraploid full-sib families named G1, B2, and K2. These families were composed of 280 (G1), 280 (B2), and 150 (K2) genotypes. Our aim was to avoid visual inspection of 5,710 DPCs and to identify genotypes exhibiting stable resistance. We used three parameters: the slope of the DPC, the date of appearance of the first symptoms in the tested genotypes compared with a susceptible standard, and the relative area under the disease progress curve (rAUDPC). Using an appropriate threshold for each parameter, we demonstrated that it is possible to classify the response of each genotype in one of the following categories: susceptible, non-specific resistance, specific resistance, non-specific resistance plus specific resistance (or specific resistance not overcome). Data were obtained each year from 2005 to 2007 under conditions of natural infection. According to the parameters analysed, non-specific resistance and specific resistance segregated in the families. The year effect was more than double the family effect for rAUDPC. Empirical adjustment of threshold values in a subsample of the tested genotypes led to an increase in the effectiveness of our classification method. Calculated classification enabled detection of stable genotypes in each family. The impact of the year effect differed with the family. In the G1 family, the distribution of genotypes in each category was relatively stable over the 3 years, whereas in K2, the proportion of genotypes demonstrating specific resistance alone increased, particularly in 2007. In the B2 family, the proportion of genotypes in the non-specific resistance category decreased from 40% to 15% from 2005 to 2006, and then remained stable in 2007. The heritabilities of the parameters ranged from 61% to 96% depending on the family and on the parameter concerned.
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