Klebsiella jilinsis 2N3 promotes maize growth and induces resistance to northern corn leaf blight

2021 ◽  
Vol 156 ◽  
pp. 104554
Author(s):  
Meng Zhang ◽  
Cheng Zhang ◽  
Sisheng Zhang ◽  
Huilin Yu ◽  
Hongyu Pan ◽  
...  
Keyword(s):  
Leaf Blight ◽  
Northern Corn Leaf Blight ◽  
Maize Growth ◽  
Corn Leaf Blight

Morphological and molecular markers based screening of maize hybrids against northern corn leaf blight

2020 ◽  
Vol 53 (1) ◽  
Author(s):  
Sadaf Naeem ◽  
Muhammad Tahir ◽  
Kiramat Khan ◽  
Amjad Hasan ◽  
Rafiq Ahmad
Keyword(s):  
Molecular Markers ◽  
Leaf Blight ◽  
Maize Hybrids ◽  
Northern Corn Leaf Blight ◽  
Corn Leaf Blight

scholarly journals A Quantitative Disease Severity Rating Scale for Northern Corn Leaf Blight

2016 ◽  
Vol 17 (1) ◽  
pp. 49-50 ◽  
Author(s):  
Trey Price ◽  
Myra Purvis ◽  
Hunter Pruitt
Keyword(s):  
United States ◽  
Disease Severity ◽  
Rating Scale ◽  
The United States ◽  
Leaf Blight ◽  
Analysis Software ◽  
Northern Corn Leaf Blight ◽  
Severity Rating ◽  
Corn Leaf Blight

Northern corn leaf blight (NCLB) is an annual issue for corn producers throughout the United States. Consequently, researchers are constantly evaluating hybrids for resistance and fungicides for efficacy. In most cases, NCLB severity is evaluated by visually estimating the percentage of affected foliage. Perceptions of disease severity are variable among stakeholders; therefore, a rating scale was created using photo analysis software that may be used to increase accuracy of disease severity estimations. Accepted for publication 15 March 2016. Published 28 March 2016.

qNCLB7.02, a novel QTL for resistance to northern corn leaf blight in maize

2018 ◽  
Vol 38 (5) ◽  
Author(s):  
Jianjun Wang ◽  
Zhennan Xu ◽  
Jing Yang ◽  
Xiaohuan Lu ◽  
Zhiqiang Zhou ◽  
...  
Keyword(s):  
Leaf Blight ◽  
Northern Corn Leaf Blight ◽  
Corn Leaf Blight

scholarly journals Genetic Mapping And Genomic Prediction For Northern Corn Leaf Blight (Exserohilum Turcicum (Pass.) Leonard And Suggs) Resistance

2021 ◽  
Author(s):  
D.C. Balasundara ◽  
H. C. Lohithaswa ◽  
M. Rahul ◽  
R. L. Ravikumar ◽  
Anand Pandravada ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Combining Ability ◽  
Inbred Lines ◽  
Leaf Blight ◽  
Environment Interaction ◽  
Exserohilum Turcicum ◽  
Northern Corn Leaf Blight ◽  
Polymorphic Snps ◽  
Corn Leaf Blight ◽  
Two Populations

Abstract Background: Northern corn leaf blight (NCLB) of maize caused by Exserohilum turcicum is a serious foliar disease. Resistance to NCLB is complexly inherited and the highly significant genotype x environment interaction effect makes selection of resistant genotypes difficult through conventional breeding methods. Hence an attempt was made to identify the genomic regions associated with NCLB resistance and perform genomic selection (GS) in two F2:3 populations derived from the crosses CM212 × MAI172 (Population-1) and CM202 × SKV50 (Population-2). Results: Two populations, each comprising of 366 progenies, were phenotyped at three different locations in the disease screening nurseries. Linkage analysis using 297 polymorphic SNPs in Population-1 and 290 polymorphic SNPs in Population-2 revealed 10 linkage groups spanning 3623.88cM and 4261.92cM with an average distance of 12.40 cM and 14.9 cM, respectively. Location-wise and pooled data across locations indicated that QTL expression was population and environment specific. The genomic prediction accuracies of 0.83 and 0.79 were achieved for NCLB Population 1 and Population 2, respectively. The resistant progenies from both populations were advanced to derive inbred lines and crossed with four different testers in line x tester mating design to test for their combining ability. High overall general combining ability was exhibited by 21 inbred lines. Among crosses 48 % were assigned high overall specific combining ability status. Out of 136 single crosses, seven recorded significant positive standard heterosis over the best check for grain yield. The clustering pattern of inbred lines developed from the two populations revealed high molecular diversity. Conclusions: In this study, comparatively better genomic prediction accuracies were achieved for NCLB and the worth of F3 progenies with high genomic predictions was proved by advancing them to derive inbred lines and establishing their higher combining ability for yield and yield related traits.

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