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VIEW ARTICLE
Genetics
Inheritance of Resistance to Leaf Freckles and Wilt Caused by Clavibacter michiganense subsp. nebraskense in Early Maturing Maize Inbred Lines. E. N. Ngong-Nassah, Former graduate student, Plant Science Department, South Dakota State University, Brookings 57007; M. L. Carson(2), and Z. W. Wicks, III(3). (2)(3)Associate professors, Plant Science Department, South Dakota State University, Brookings 57007. (2)Present address: Research plant pathologist, USDA-ARS, Box 7616, Department of Plant Pathology, North Carolina State University, Raleigh 27695-7616. Phytopathology 82:142-146. Accepted for publication 11 September 1991. This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. The American Phytopathological Society, 1992. DOI: 10.1094/Phyto-82-142.
The inheritance of resistance to leaf freckles and wilt was studied in two greenhouse and two field trials of a set of diallel crosses between 10 early maturing maize inbred lines. Inheritance of resistance in six F2 populations derived from resistant × susceptible and intermediate × susceptible crosses was also studied in the greenhouse and field. General combining ability was much more important than specific combining ability for disease resistance. General combining ability effects were generally consistent between trials, whereas specific combining ability effects were not. Additive genetic effects accounted for most of the variation among generation means in populations derived from resistant × susceptible crosses, and less so in populations from intermediate × susceptible crosses. Broad-sense heritabilities were high, and estimates of gene numbers were low in F2 populations derived from resistant × susceptible crosses. Resistance to leaf freckles and wilt in the more resistant inbred lines appears to be controlled by relatively few genes (3–5) acting in a mostly additive manner. Development of resistant germ plasm using a variety of breeding methods, including pedigree, bulk, backcross, and recurrent selection methods, should be successful, particularly if material is evaluated in more than one environment.
Additional keywords: corn, Goss’s wilt, Zea mays.
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