Development of the Nondestructive Leaf Area Estimation Model for Valeriana (Valeriana jatamansi Jones)

Leaf area (LA) is an important parameter related to plant growth and physiology. An allometric model was developed to estimate the LA of endangered medicinal plant Valeriana jatamansi using linear measurements such as leaf length (L) and width (W). LA and other leaf dimensions were measured using a laser leaf area meter. Leaves from seven accessions of valeriana were collected from the experimental site during 2015. Different regression models were developed between LA and other leaf components, viz. L, W, etc. The linear model having LW as an independent variable (y = 0.487 + 0.644 LW) provided the best estimation [coefficients of determination (R²) = 0.974, root mean square error (RMSE) = 2.222, coefficient of variation (CV) = 4.529]. Validation of the selected model showed a higher correlation between the actual leaf area (ALA) and the predicted leaf area (PLA) [R² = 0.956, RMSE = 2.310, CV = 5.319, predicted residual error sum of squares (PRESS) = 1067.352].     

荧光定量RT-PCR检测H5亚型禽流感病毒方法的建立与验证

根据H5亚型禽流感病毒HA基因上的保守序列,设计合成引物,以H5亚型禽流感病毒HA基因重组质粒为标准品绘制标准曲线,建立了荧光定量逆转录聚合酶链反应检测方法。结果表明,本试验建立的标准曲线循环阈值(Ct值)与模板浓度具有良好的线性关系,相关系数为0.995,灵敏度约为8拷贝/μL,相当于8个AIV颗粒,对新城疫病毒和其他禽病病毒无交叉反应,特异性好、重复性佳,为H5亚型禽流感病毒检测提供了一种特异、敏感、快速、低成本、高通量、生物安全性好的定量检测方法。对178份临床泄殖腔棉拭子样品的检测,该方法结果与经典病毒分离方法符合率大于90.0%,在禽流感病毒临床样品快速筛检、流行病学监测等方面显示了良好的应用前景。     

伊维菌素微乳无菌检查方法学的研究

本试验旨在对伊维菌素微乳制剂进行无菌检查方法学验证和无菌检查试验,确认本试验所用的方法适用于该制剂的无菌检查。按《中国兽药典》2005版一部(附录118)所载"无菌检查法"项下进行试验,通过对阳性对照菌、不同量冲洗液等条件的选择,采用薄膜过滤法对10瓶供试品(每种试验菌的样品量)进行检测,建立了无菌检查方法。经方法验证,用400mL 0.1%蛋白胨水溶液冲洗后,含供试品容器中的7个阳性菌试验组与阳性菌对照组相比均生长良好,说明供试品的该检验量在该检验条件下无抑菌作用或其抑菌作用可以忽略不计,可以用该方法进行供试品的无菌检查。对3批供试品进行无菌检查,阳性对照菌均在24h内生长良好,阴性对照均澄清,无菌生长,3批供试品均澄清,无菌生长,无菌检查试验结果符合规定。     

基于不同终点测定土壤中Zn的毒性阈值及其田间验证

利用Log-logistic剂量-效应函数模型,在实验室条件下分别利用大麦根伸长、西红柿及小白菜生长毒性及基质诱导硝化毒性测试方法,测定了16种不同性质土壤中Zn的毒性阈值,在此基础上建立了基于土壤性质主控因子的Zn的毒性预测模型,同时选取湖南祁阳酸性土和浙江嘉兴中性土验证了田间条件下土壤中Zn毒性阈值.结果表明:田间条件下,湖南祁阳土壤中Zn对玉米不同生长指标的EC10范围为37～51 mg· kg-1,EC50为127～312 mg·kg-1,不同测试指标的敏感性顺序为苗期叶面积＞秸秆生物量＞苗期株高＞籽粒产量;浙江嘉兴水稻土中Zn的毒性阈值EC10为213～332 mg·kg-1,EC50为682～922 mg·kg-1,不同测定指标间的敏感性顺序为孕穗期叶绿素含量＞秸秆生物量＞苗期株高＞籽粒产量.土壤中Zn的毒性阈值田间验证结果表明,实验室条件下基于不同评价终点测定的土壤中Zn的毒性阈值与田间条件下的吻合性在不同土壤间存在一定差异,相比而言,实验室条件下对偏中性的浙江嘉兴水稻土中Zn的毒性阈值测定结果与田间验证结果更接近;基于实验室条件下不同测试指标所测定的土壤中Zn毒性阈值与土壤主控因子间的预测模型能较好预测浙江嘉兴水稻土中Zn的毒性阈值,田间条件下所测定的ECx(x=10,50)值均在模型预测值的两倍的预测区间内;而对于偏酸性的湖南祁阳土壤,预测模型则低估了土壤中Zn的生态风险.     

基于参数优化的最小二乘支持向量机触电电流检测方法

针对如何从低压电网总泄漏电流中检测出生物体触电电流信号的难题,提出了一种基于网格搜索和交叉验证的最小二乘支持向量机的触电电流信号检测方法。首先在剩余电流动作保护装置触电物理试验系统平台上通过故障录波器获得生物体在3个典型时刻(电源电压最大时刻、电源电压过零时刻及电源电压任意时刻)发生触电过程的总泄漏电流和触电电流波形,并截取触电前1个周期和触电后3个周期共800个采样点的信号数据作为触电试验样本数据;然后将触电试验样本数据进行滤波预处理,预处理后的多个样本采样点的总泄漏电流组合成特征向量输入最小二乘支持向量机(least square-support vector machine,LS-SVM),相应样本采样点的触电电流作为其输出,并通过网格搜索与交叉验证相结合的方法来优化最小二乘支持向量机参数,利用输出最优参数组合对触电电流与总泄漏电流的关系进行训练,从而建立了触电电流的检测模型;最后利用该方法对10组测试样本数据进行了检测,检测结果为:当训练样本数据为20组时,检测均方误差为14.0040,当训练样本数据为40组时,检测均方误差为11.7469,当训练试验数据为65组时,检测均方误差为11.1849。与径向基(radial basis function,RBF)神经网络方法相比,最小二乘支持向量机方法比径向基神经网络方法检测均方误差分别低3.7272、1.9132、0.1556,从而可较准确地从总泄漏电流中检测出生物体触电电流信号,为开发新一代基于生物体触电电流分量而动作的自适应型剩余电流保护装置提供理论依据。     

Across-breed validation study confirms and identifies new loci associated with sexual precocity in Brahman and Nellore cattle

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10^–3) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10^–3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.     

Analysis of the Mycosporine-Like Amino Acid (MAA) Pattern of the Salt Marsh Red Alga Bostrychia scorpioides

This study presents the validation of a high-performance liquid chromatography diode array detector (HPLC-DAD) method for the determination of different mycosporine-like amino acids (MAAs) in the red alga Bostrychia scorpioides. The investigated MAAs, named bostrychines, have only been found in this specific species so far. The developed HPLC-DAD method was successfully applied for the quantification of the major MAAs in Bostrychia scorpioides extracts, collected from four different countries in Europe showing only minor differences between the investigated samples. In the past, several Bostrychia spp. have been reported to include cryptic species, and in some cases such as B. calliptera, B. simpliciuscula, and B. moritziana, the polyphyly was supported by differences in their MAA composition. The uniformity in the MAA composition of the investigated B. scorpioides samples is in agreement with the reported monophyly of this Bostrychia sp.     

Investigations on Cambodian soils

Basic information on the nature of soils, their potentialities, and their limitations is necessary to evaluate Cambodian agriculture properly, and to develop a program for increasing food and other crops. Suitable information has, however, been limited, especially as there is not to be found in any report much data relating to soils of different origins over the whole country. There is, needless to say, some information on confined areas of Cambodia.     

基于优化支持向量机的采煤机故障诊断技术

为了对采煤机故障进行准确诊断研究,本文提出了一种基于优化支持向量机的采煤机故障诊断新方法,首先采用主成分分析法(PCA)对采煤机故障特征参数进行特征提取,其次应用特征数据进行基于支持向量机(SVM)的采煤机故障诊断模型训练,再次采用交叉验证方法对SVM模型参数进行优化,建立最优SVM采煤机故障诊断模型,最后通过对比实验,验证了基于优化SVM采煤机故障诊断模型的可行性和优越性。