Assessment of genetic relationships among Spring Dendrobium cultivars and varietal materials using amplified fragment length polymorphism (AFLP) analysis

Spring Dendrobiums have been largely produced as one of the top grade ornamental pot plants due to their various flower colors, multitudinous flowers and graceful flower shape as well as their long period of florescence. Genetic relationships among Spring Dendrobium cultivars, however, have not been documented. This study analyzed the genetic relatedness of 30 commonly grown cultivars or varietal materials using amplified fragment length polymorphism (AFLP) markers with near-infrared fluorescence-labeled primers. Eight EcoRI + 3 bases/MseI + 3 bases primer set combinations were used in this investigation. Each selected primer set generated 113 to 158 scorable fragments. A total of 1102 AFLP fragments were detected, of which 778 were polymorphic (70.6%). An unweighted pair-group method of the arithmetic averages (UPGMA), principal coordinate analysis (PCOA), and bootstrap analysis were used to analyze the genetic relationships. The 30 cultivars were separated into five clusters. Cluster I contains 6 cultivars that are either from Senlan No.1 or Senlan No. 6 with Jaccardfs similarity coefficients ranging from 0.70 to 0.80. All of these 6 cultivars came from Taiwan, and were derived from somaclonal variants or sports. Just 3 cultivars were positioned in cluster II ranging from 0.71 to 0.76, and also originated from Taiwan. Cluster III included 13 cultivars, Jaccardfs similarity coefficients varied from 0.69 to 0.84. Seven cultivars from Senlan No. 15 or eSnowboy Romancef were situated in cluster IV with Jaccardfs similarity coefficients ranging from 0.69 to 0.82. Only eSantana Canaryf was positioned in cluster ‡X with Jaccardfs similarity coefficient at 0.62. This study established the genetic relationships of these commonly cultivated Spring Dendrobiums, and raised a concern over genetic vulnerability of cultivars in this study because of their close genetic similarities.Key words: Spring Dendrobium, amplified fragment length polymorphism (AFLP), genetic relationship, cultivars and varietal materials

A Comparative Study on Improved Arrhenius-Type and Artificial Neural Network Models to Predict High-Temperature Flow Behaviors in 20MnNiMo Alloy

The stress-strain data of 20MnNiMo alloy were collected from a series of hot compressions on Gleeble-1500 thermal-mechanical simulator in the temperature range of 1173∼1473 K and strain rate range of 0.01∼10 s−1. Based on the experimental data, the improved Arrhenius-type constitutive model and the artificial neural network (ANN) model were established to predict the high temperature flow stress of as-cast 20MnNiMo alloy. The accuracy and reliability of the improved Arrhenius-type model and the trained ANN model were further evaluated in terms of the correlation coefficient (R), the average absolute relative error (AARE), and the relative error (η). For the former, R and AARE were found to be 0.9954 and 5.26%, respectively, while, for the latter, 0.9997 and 1.02%, respectively. The relative errors (η) of the improved Arrhenius-type model and the ANN model were, respectively, in the range of −39.99%∼35.05% and −3.77%∼16.74%. As for the former, only 16.3% of the test data set possesses η-values within ±1%, while, as for the latter, more than 79% possesses. The results indicate that the ANN model presents a higher predictable ability than the improved Arrhenius-type constitutive model

Detecting Cosmic 21 cm Global Signal Using an Improved Polynomial Fitting Algorithm

Detecting the cosmic 21 cm signal from Epoch of Reionization (EoR) has always been a difficult task. Although the Galactic foreground can be regarded as a smooth power-law spectrum, due to the chromaticity of the antenna, additional structure will be introduced into the global spectrum, making the polynomial fitting algorithm perform poorly. In this paper, we introduce an improved polynomial fitting algorithm - the Vari-Zeroth-Order Polynomial (VZOP) fitting and use it to fit the simulation data. This algorithm is developed for the upcoming Low-frequency Anechoic Chamber Experiment (LACE), yet it is a general method suitable for application in any single antenna-based global 21 cm signal experiment. VZOP defines a 24-hour averaged beam model that brings information about the antenna beam into the polynomial model. Assuming that the beam can be measured, VZOP can successfully recover the 21 cm absorption feature, even if the beam is extremely frequency-dependent. In real observations, due to various systematics, the corrected measured beam contains residual errors that are not completely random. Assuming the errors are frequency-dependent, VZOP is capable of recovering the 21 cm absorption feature even when the error reaches 10%. Even in the most extreme scenario where the errors are completely random, VZOP can at least give a fitting result that is not worse than the common polynomial fitting. In conclusion, the fitting effect of VZOP depends on the structure of the error and the accuracy of the beam measurement.Comment: 14 pages, 15 figures, Accepted for publication in MNRA