The laser-induced breakdown spectroscopy (LIBS) technique was applied to quantify nutrients (Mg, Ca, Na, and K) in spinach and rice and to discriminate pesticide-contaminated products in a rapid manner. Standard reference materials (spinach leaves and unpolished rice flour) were used to establish a relationship between LIBS intensity and the concentration of each element (Mg, Ca, Na, and K) (i.e., calibration line). The limits of detection (LODs) for Mg, Ca, Na, and K were found to be 29.63, 102.65, 36.36, and 44.46 mg/kg in spinach and 7.54, 1.76, 4.19, and 6.70 mg/kg in unpolished rice, respectively. Concentrations of those nutrient elements present in spinach and unpolished rice from a local market were determined by using the calibration lines and compared with those measured with ICP-OES, showing good agreement. The data also suggested that the LIBS technique with the chemometric method (PLS-DA) could be a great tool to distinguish pesticide-contaminated samples from pesticide-free samples in a rapid manner even though they have similar elemental compositions. Misclassification rates were found to be 0 and 2% for clean spinach and pesticide-contaminated spinach, respectively, by applying the PLS-DA model established from the training set of data to predict the classes of test samples.
We performed de novo transcriptome sequencing for Panax ginseng and Panax quinquefolius accessions using the 454 GS FLX Titanium System and discovered annotation-based genome-wide single-nucleotide polymorphism (SNPs) using next-generation ginseng transcriptome data without reference genome sequence. The comprehensive transcriptome characterization with the mature roots of four ginseng accessions generated 297,170 reads for 'Cheonryang' cultivar, 305,673 reads for 'Yunpoong' cultivar, 311,861 reads for the G03080 breeding line, and 308,313 reads for P. quinquefolius. In transcriptome assembly, the lengths of the sample read were 156.42 Mb for 'Cheonryang', 161.95 Mb for 'Yunpoong', 165.07 Mb for G03080 breeding line, and 166.48 Mb for P. quinquefolius. A total of 97 primer pairs were designed with the homozygous SNP presented in all four accessions. SNP genotyping using high-resolution melting (HRM) analysis was performed to validate the putative SNP markers of 97 primer pairs. Out of the 73 primer pairs, 73 primer pairs amplified the target sequence and 34 primer pairs showed polymorphic melting curves in samples from 11 P. ginseng cultivars and one P. quinquefolius accession. Among the 34 polymorphic HRM-SNP primers, four primers were useful to distinguish ginseng cultivars. In the present study, we demonstrated that de novo transcriptome assembly and mapping analyses are useful in providing four HRM-SNP primer pairs that reliably show a high degree of polymorphism among ginseng cultivars.
The soybean development goal in Korea has changed over time, but the pattern of genetic diversity in modern varieties has not yet been well characterized. In this study, 20 simple sequence repeat (SSR) markers are shown to generate a total of 344 alleles, where the number of alleles ranges from 7 to 29, with an average of 17.2 per locus, and the polymorphism informative content (PIC) values range from 0.6799 to 0.9318, with an average of 0.8675. Five different clusters are classified using the unweighted pair group mean arithmetic (UPGMA) method. The genetic distance between clusters I and V (0.3382) is the farthest, and that between clusters III and IV (0.0819) is the closest. The genetic distance between all pairings of groups, according to the time period of their release, is lowest (0.1909) between varieties developed in the 1990s and those from 2000 onward, and highest (0.5731) between varieties developed in the 1980s and those from 2000 onward. Model-based structure analysis revealed the presence of three sub-populations and 17 admixtures in the Korean soybean varieties. All 172 Korean soybean varieties were tested for discrimination using six SSR markers. The numbers of varieties that were clustered in each step are as follows: 7 (4.1%) in step 1 (Sat_076), 73 (42.4%) in step 2 (Sat_417), 69 (40.1%) in step 3 (Sat_043), 13 (7.6%) in step 4 (Satt197), 8 (4.6%) in step 5 (Satt434), and 2 (1.2%) in step 6 (Satt179). These results, based on the analysis of genetic resources, can contribute to the creation of a core collection for soybean conservation and breeding, as well as to the development of future varieties with useful traits.
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