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Genetic Control of Stagonospora Nodorum Blotch and Evaluation of a Digital Image Analysis Method to Estimate Fusarium Damaged Kernels in Wheat

Posted on:2014-10-06Degree:Ph.DType:Dissertation
University:North Carolina State UniversityCandidate:Maloney, Peter VincentFull Text:PDF
GTID:1458390005486030Subject:Agriculture
Abstract/Summary:
Stagonospora nodorum blotch Stagonospora nodorum leaf blotch is one of the major foliar diseases that affect wheat in the southeastern United States. This disease can cause substantial yield loss and can be difficult to chemically control. The objective of this study was to create a linkage map of the 'NC-Neuse' x 'AGS 2000' recombinant inbred population using multiple marker platforms and identify quantitative loci controlling resistance to Stagonospora nodorum leaf blotch. One-hundred-seventy-nine F5 --derived lines were evaluated in six inoculated environments in North Carolina and Virginia over three seasons, with two to three replications per environment. Over 1800 SSR, SNP, and DArT markers were utilized in creating the linkage map and identification of QTL.;Twelve QTL for Stagonospora nodorum blotch resistance were identified, as well as other QTL for Stagonospora nodorum host selective toxin resistance, heading date and plant height. The 12 QTL for SNB resistance traits accounted for 3 to 33 percent of the disease variation in the population and were found across nine different linkage groups. Resistance alleles were contributed by both parents. The largest QTL was located on linkage group 1A.1. It was associated with five out of the eight Stagonospora nodorum blotch resistance traits evaluated in the study. A QTL for host selective toxin resistance was aligned with a region associated with the Snn3 sensitivity gene and other QTL for SNB resistance aligned with regions associated with Snn4 and Snn1. Forty-four transgressive segregates exhibiting better resistance than NC-Neuse were identified and 23 of those lines contained all the resistance alleles for the snb_qtl_1A.1 QTL plus at least one other major QTL.;Digital Image Analysis of Fusarium Damaged Kernels Fusarium head blight (FHB), or head scab, causes a reduction in grain yield and quality, as well as, the formation of shriveled, dull-grey seeds called "tombstones" or Fusarium damaged kernels (FDK). FDK is commonly quantified on a percentage basis by visually separating damaged kernels from the healthy kernels following harvest, a process that is both time consuming and labor intensive. The objective of this study was to evaluate an alternative method for quantifying FDK through the use of digital imagery and the digital image analysis program ImageJ. The 'NC-Neuse' x 'AGS 2000' recombinant inbred population of 172 lines and the NC-Neuse x 'Bess' double-haploid population of 112 lines were used in this study. NC-Neuse and Bess were moderately resistant and AGS 2000 was susceptible to FHB. Both populations were evaluated under moderate to heavy FHB pressure in a total of five environments in North Carolina, Maryland and Missouri with two to three replications per environment. Wheat heads from each plot were harvested, dried, threshed, and cleaned by hand. Digital image analysis estimates were obtained by applying a hue, balance, and saturation filter in ImageJ to images captured using a standard digital SLR camera. The filter was set to exclude the less color saturated (grey) kernels. ImageJ would then output the proportionate area of damaged kernels.;Significant genetic variation was observed using both visual and digital image analysis methods to estimated FDK. Correlation values between methods ranged from 0.72 to 0.80 over all environments. A lower correlation value of 0.54 was observed in Columbia, MO because of cracked and broken kernels in the samples. Digital image analysis was three times faster than the visual method, and was able to estimate FDK on a larger per plot sample whereas labor and time constraints limited the sample size for the visual method. Digital image analysis was consistent over different samples and appears well suited as an alternative form of FDK detection in unbroken grain.
Keywords/Search Tags:Stagonospora nodorum, Digital image analysis, Damaged kernels, FDK, QTL, Method, Resistance, Over
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