Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

META-R:A software to analyze data from multi-environment plant breeding trials

META-R(multi-environment trial analysis in R)is a suite of R scripts linked by a graphical user interface(GUI)designed in Java language.The objective of META-R is to accurately analyze multi-environment plant breeding trials(METs)by fitting mixed and fixed linear models from experimental designs such as the randomized complete block design(RCBD)and the alpha-lattice/lattice designs.META-R simultaneously estimates the best linear and unbiased estimators(BLUEs)and the best linear and unbiased predictors(BLUPs).Additionally,it computes the variance-covariance parameters,as well as some statistical and genetic parameters such as the least significant difference(LSD)at 5%significance,the coefficient of variation in percentage(CV),the genetic variance,and the broad-sense heritability.These parameters are very important in the selection of top performing genotypes in plant breeding.META-R also computes the phenotypic and genetic correlations among environments and between traits,as well as their statistical significance.The genetic correlations between environments or traits can be visualized in a biplot graph or a tree diagram(dendrogram).Genetic correlations are very important for identifying environments with similar behavior or making indirect selection and identifying the most highly associated traits.META-R performs multi-environment analyses by using the residual maximum likelihood(REML)method;these analyses can be done by environment,across environments by grouping factors(stress conditions,nitrogen content,etc.)and across environments;the analyses across environments can be done with a pre-defined degree of heritability.

Wheat Yield Response to Foliar Fungicide Application against Leaf Rust Caused by Puccinia triticina

A study was conducted on reducing the yield loss of wheat due to leaf rust caused by Puccinia triticina with foliar application of fungicides during the 2014-2015 and 2015-2016 growing seasons at the Wheat Research Institute in Faisalabad, Pakistan. Three fungicides： Folicur （tebuconazole） at 300 mL/ha, Nativo （tebuconazole ＋ trifloxystrobin） at 300 g/ha and Tilt （propiconazole） at 500 mL/ha were applied single or two times to Morocco and Sehar-06 wheat varieties used in the trial. The trial plots were first sprayed at the Zadok＇s scale （ZS） 3 stage and second sprayed between ZS 4.3 and 5.4 stages. The greenness of the trial crop was measured using GreenSeeker. Foliar application of fungicides significantly reduced the loss of grain yield and 1,000-grain weight （TGW） of wheat due to leaf rust in comparison to the control without fungicides application. Of the three fungicides, two times spray of Nativo reduced the grain yield loss of leaf rust susceptible mega wheat variety Sehar-06 by 45%-56% and the loss of TGW by 42%, also giving the highest marginal return in the trial. Single application of Nativo was equally effective as two times spray of Folicur in reducing the loss of wheat grain yield. Two times spray of Folicur was found to be the second choice of fungicide for reducing the yield loss of wheat. The research identified suitable fungicides for reducing the yield loss of wheat due to leaf rust and also generated important scientific knowledge required to manage a sudden outbreak of leaf rust to ensure food security.