He—Ne激光照射皮肤的几种现象的研究

本文研究了皮肤在大功率激光照射下,激光在皮肤组织中的传播情况及相应的温度,PH值的变化,并对产生的原因进行了初步分析和研究。     

梨遗传转化与遗传标记研究进展

用遗传转化的方法对梨进行遗传改良和用分子生物学的方法研究梨的遗传性状是当今梨科研的热点,基因型、抗菌肽的活性与稳定性、农杆菌的侵染力等是影响梨遗传转化的重要因素．DNA的提取方法决定DNA的数量和质量,直接影响分子生物学方法在梨中的应用和应用结果．本文综合有关文献综述了国内外梨遗传转化和遗传标记研究所取得的进展,并结合存在的问题对今后的工作重点提出了几点建议．     

A novel approach to the rapid assignment of 13C NMR spectra of major components of vegetable oils such as avocado,mango kernel and macadamia nut oils

Assignment of ¹³C nuclear magnetic resonance (NMR) spectra of major fatty acid components of South African produced vegetable oils was attempted using a method in which the vegetable oil was spiked with a standard triacylglycerol. This proved to be inadequate and therefore a new rapid and potentially generic graphical linear correlation method is proposed for assignment of the ¹³C NMR spectra of major fatty acid components of apricot kernel, avocado pear, grapeseed, macadamia nut, mango kernel and marula vegetable oils. In this graphical correlation method, chemical shifts of fatty acids present in a known standard triacylglycerol is plotted against the corresponding chemical shifts of fatty acids present in the vegetable oils. This new approach (under carefully defined conditions and concentrations) was found especially useful for spectrally crowded regions where significant peak overlap occurs and was validated with the well‐known ¹³C NMR spectrum of olive oil which has been extensively reported in the literature. In this way, a full assignment of the ¹³C{1H} NMR spectra of the vegetable oils, as well as tripalmitolein was readily achieved and the resonances belonging to the palmitoleic acid component of the triacylglycerols in the case of macadamia nut and avocado pear oil resonances were also assigned for the first time in the ¹³C NMR spectra of these oils. Copyright © 2009 John Wiley & Sons, Ltd.     

基于近红外漫反射光谱的香梨类别定性分析

基于近红外(near infrared, NIR)漫反射光谱分析技术对库尔勒香梨中的脱萼果和宿萼果进行了自动化判别试验研究。用对不同波段范围、不同光谱预处理方法(MSC、SNV、微分光谱)和不同主成分因子数对香梨类别判别结果的影响进行了对比分析,建立了香梨类别的定性判别模型。研究结果表明：用判别分析(discrimant analysis,DA)方法在9 091～4 000 cm-1范围结合原始光谱建立的DA判别模型最优,该方法对校正集正确分类率达100%,预测集正确分类率为95%。     

砀山酥梨果实发育与石细胞形成的动态研究

本实验以砀山酥梨为试材,研究了梨果实生长发育和石细胞形成的动态变化规律.结果表明:砀山酥梨果实生长发育过程中,果实鲜重和纵横径变化曲线均为“S”型,呈现慢—快—慢的生长规律;砀山酥梨石细胞是由果肉中薄壁细胞壁加厚,继则木质化而形成的;砀山酥梨石细胞形成的最高峰在梨花后第7周,其直径最大值出现于梨花后第11周,石细胞的形成于梨花后第11周停止.     

新型云母钛珠光颜料的研制

以白云母为基料，以ＴｉＯ２为包覆原料制备出了新型珠光颜料，本文首次提出以阶梯升温、ｐＨ递增和间歇加钛液的方法制备珠光颜料。用此法制得的样品与国内外同类样品经过ｘ射线衍射仪、扫描电镜和能谱仪的分析，表明其质量较佳。     

Eco-friendly and protective natural dye from red prickly pear (Opuntia Lasiacantha Pfeiffer) plant

New natural dye extracted from red prickly pear was used for dyeing wool with different types of mordents. The effect of mordant concentration on the color strength was discussed; the results obtained indicated that the color strength decreases with the increase of mordant concentration. The effect of the dye bath pH, salt concentration, dyeing temperature and dyeing time was also studied. The color strength and the dye uptake have exhibited high values. Good fastness properties of the dyed fabric were achieved.Antimicrobial activity of wool fabric dyed with this dye was tested according to diffusion agent. Test organisms as Escherichia coli, Bacillus subitilus, Pseudomons aeruginosa and Staphylococcus aureus were used and the results indicated that the samples exhibited a high inhibition zone.According to the available literature, this is the first report concerning a natural dye for fabric from fruits of red prickly pear plants.     

可见-近红外光谱的鸭梨黑心缺陷在线检测AdaBoost集成模型研究

黑心病是鸭梨贮藏期间发生的生理病害,其病变初期表现在内部果核处出现褐色斑块,而在果实外观上与正常果几乎没有任何差异,严重影响鸭梨的贮藏时间和品质,亟需一种快速无损的检测方法为鸭梨质量保驾护航。采用可见-近红外光谱法对鸭梨黑心缺陷进行在线检测和识别,结合平滑（Smoothing）、标准正态变量变换（SNV）、多元散射校正（MSC）、SG一阶导数（SG 1st-Der）以及小波变换（WT）预处理方法和主成分分析（PCA）、k近邻（kNN）、朴素贝叶斯（NBC）、支持向量机（SVM）以及基于Adaboost的集成学习等方法对鸭梨黑心病进行判别研究。Adaboost集成了kNN、NBC和SVM三个独立学习器。将120个健康鸭梨和165个黑心鸭梨共计285个样品划分为训练集和测试集进行模型的构建和评价,采用训练集的查准率/查全率的调和平均值（F-measure）和正确识别率（Accuracy）对分类模型进行优化和评价。研究结果表明：不同属性（正常和黑心）鸭梨样品光谱的前三主成分分布图相互交错,很难直观地对黑心鸭梨进行区分。样品光谱经小波变换（小波基为“Haar”）预处理的kNN模型训练集的F-measure和Accuracy分别为78.98%和82.62%;经过SG一阶导数预处理后的NBC模型训练集的F-measure和Accuracy分别为80.90%和82.11%;经过小波变换预处理后的SVM模型训练集的F-measure和Accuracy分别为90.24%和91.58%;经小波变换预处理的AdaBoost模型训练集的F-measure和Accuracy分别为91.46%和92.63%。通过测试集对模型进行验证可知：光谱经小波变换预处理后建立的Adaboost分类模型最优,分类的F-measure达到90.91%,较WT-kNN,SG 1st-Der-NBC和WT-SVM模型分别提高了11.39%,15.23%和2.30%;Accuracy达到92.63 ％,分别提高了10.52%,11.58%和2.10%;模型对测试集样品预测时的计算时间约为0.12s,满足在线分选要求。可见-近红外光谱结合AdaBoost分类方法,可以为鸭梨黑心病的在线检测提供一种快速简便的分析方法。     

高光谱成像技术的库尔勒梨早期损伤可视化检测研究

利用高光谱成像技术对库尔勒梨早期损伤进行快速识别检测。以60个库尔勒梨为研究对象,采集380～1 030 nm波段范围内完好样本和损伤后1～7天样本的480幅高光谱图像。提取图像中感兴趣区域(ROI)的平均光谱信息,利用小波变换(WT)对光谱数据进行去噪平滑,将去噪后的全部样本按2∶1的比例分成建模集(320个)和预测集(160个)。利用二阶导数从全谱信息中提取出19个特征波长,分别基于全谱和提取出的特征波长对建模集和预测集进行支持向量机(SVM)建模分析。结果表明,基于全谱和特征波长的判别分析模型中,两者预测集的识别率都达到93.75%,表明提取的特征波长包含了光谱数据中的关键信息。然后,基于特征波长运用波段比运算挑选最佳波段比,根据波段比F值的分布确定光谱图像分割的最佳波长684和798 nm。对最佳波段比(684/798 nm)下的图像,利用选择性搜索(SS)对高光谱图像中样本的完好和损伤区域进行分割,从分割结果来看,1～7天损伤样本的受损区域能够被准确检测出来。研究结果表明：基于高光谱成像技术对库尔勒梨进行损伤鉴别是可行的,该研究所获得的特征波长和波段比为研发在线实时的库尔勒梨损伤检测系统提供支撑。     

盐胁迫对不同苦瓜品种萌发及幼苗生长的影响

对海南常种的四个苦瓜品种（琼1号苦瓜、杂交一代金绿大肉苦瓜、一代交配槟城苦瓜和广研杂交苦瓜），在不同盐浓度下进行盐胁迫。结果表明广研杂交苦瓜在种子萌发及幼苗生长方面比其它三个品种耐盐。同时，当盐浓度为150mmol/L，各品种种子几乎不能萌发；当盐浓度为100mmol/L时，种子虽能萌发，但幼苗不能成活。