scholarly journals Genetic Diversity and Structure of Core Collection of Huangqi (Astragalus) Developed by Genomic Simple Sequence Repeat Markers

2022 ◽  
Author(s):  
Fanshu Gong ◽  
Yaping Geng ◽  
Pengfei Zhang ◽  
Feng Zhang ◽  
Xinfeng Fan ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Simulated Annealing ◽  
Core Collection ◽  
Phylogenetic Trees ◽  
Simulated Annealing Algorithm ◽  
Therapeutic Effects ◽  
Core Collections ◽  
The Core ◽  
Genetic Diversity And Structure ◽  
Annealing Algorithm

Abstract Huangqi (Astragalus) is a versatile herb that possesses several therapeutic effects against a variety of diseases, especially lung diseases. The aim of this study was to establish a core collection of Astragalus germplasm resources based on molecular 10 SSR markers. Based on 380 samples of Astragalus collected from different areas, five different methods were utilized to construct the core collection of Astragalus, including PowerCore-based M strategy, CoreFinder-based M strategy, Core Hunter-based stepwise sampling, PowerMarker-based simulated annealing algorithm based on allele maximization, and PowerMarker-based simulated annealing algorithm based on maximizing genetic diversity. Of the constructed Astragalus core collections, the CoreFinder-based M strategy was found to be the most suitable approach as it reserved all the alleles and most of the genetic diversity parameters were higher than those of the initial collection. Additional analyses demonstrated that the genetic diversity of the core collection matched the properties of the initial collection. Further, the phylogenetic trees indicated that the population structure of the core collection was similar to that of the initial collection. In addition, our results showed that the optimal grouping value of K was 2. The construction of a core collection is beneficial for the understanding, management, and utilization of Astragalus. Moreover, this study will act as a valuable reference for constructing core collections for other plants or fungi.

scholarly journals Comparing the efficiency of sampling strategies to establish a representative in the phenotypic-based genetic diversity core collection of orchardgrass (Dactylis glomerata L.)

2013 ◽  
Vol 49 (No. 1) ◽  
pp. 36-47 ◽  
Author(s):  
M. Studnicki ◽  
W. Mądry ◽  
J. Schmidt
Keyword(s):  
Genetic Diversity ◽  
Core Collection ◽  
Dactylis Glomerata ◽  
Sampling Strategy ◽  
Sampling Strategies ◽  
Core Collections ◽  
The Core ◽  
Entire Collection ◽  
The Mean ◽  
Dactylis Glomerata L

Establishing a core collection that represents the genetic diversity of the entire collection with a minimum loss of its original diversity and minimal redundancies is an important problem for gene bank curators and crop breeders. In this paper, we assess the representativeness of the original genetic diversity in core collections consisting of one-tenth of the entire collection obtained according to 23 sampling strategies. The study was performed using the Polish orchardgrass Dactylis glomerata L. germplasm collection as a model. The representativeness of the core collections was validated by the difference of means (MD%) and difference of mean squared Euclidean distance (d‒D%) for the studied traits in the core subsets and the entire collection. In this way, we compared the efficiency of a simple random and 22 (20 cluster-based and 2 direct cluster-based) stratified sampling strategies. Each cluster-based stratified sampling strategy is a combination of 2 clusterings, 5 allocations and 2 methods of sampling in a group. We used the accession genotypic predicted values for 8 quantitative traits tested in field trials. A sampling strategy is considered more effective for establishing core collections if the means of the traits in a core are maintained at the same level as the means in the entire collection (i.e., the mean of MD% in the simulated samples is close to zero) and, simultaneously, when the overall variation in a core collection is greater than in the entire collection (i.e., the mean of d‒D% in the simulated samples is greater than that obtained for the simple random sampling strategy). Both cluster analyses (unweighted pair group method with arithmetic mean UPGMA and Ward) were similarly useful in constructing those sampling strategies capable of establishing representative core collections. Among the allocation methods that are relatively most useful for constructing efficient samplings were proportional and D2 (including variation). Within the Ward clusters, the random sampling was better than the cluster-based sampling, but not within the UPGMA clusters.

A New Solution for Maxterm Problem in Trigonometric Functions by Simulated Annealing Algorithm

2013 ◽  
Vol 4 (2) ◽  
pp. 20-28
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Hadi Najafi ◽  
Kourosh Farahkhah
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Trigonometric Functions ◽  
Matlab Software ◽  
Annealing Algorithm ◽  
Do So

The present paper is an attempt to get total minimum of trigonometric Functions by Simulated Annealing. To do so the researchers ran Simulated Annealing. Sample trigonometric functions and showed the results through Matlab software. According the Simulated Annealing Solves the problem of getting stuck in a local Maxterm and one can always get the best result through the Algorithm.

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