一粒小麦染色体高分辨显带

AMD 法显带技术对一粒小麦的染色体进行染色体高分辨显带,经过放线菌素 D 预处理、Ohnuki′s 溶液低渗、固定液中捣碎涂片法制片、Wright-Giemsa 染色等显带程序,可以在一粒小麦的所有染色体上成功地显示丰富的高分辨带纹,并对其进行了分析与配对,平均每条染色体上有20多条深带,整个染色体组共显143条带纹。这将对一粒小麦染     

基于ESTARFM模型的区域农田高时空分辨率影像产生与应用

多时相遥感影像特别是关键生育期数据是农业物候、长势及产量监测的重要数据源,然而可见光影像易受云雨干扰,在特定区域关键时间窗口缺少高时空分辨率数据的现实情况下,遥感影像时空数据融合方法变得尤为重要。增强型自适应反射率时空融合模型 ESARFM (Enanced Spaial and emporal Adapive Reflecance Fusion Model)是一种小区域合成高时空分辨率影像的较好方法,该算法在我国不同农业种植区的适应性及应用工作尚未充分展开。本文以河北、黑龙江、新疆典型农区为研究区域进行大面积应用检验分析,基于 MODIS 与 Landsa 影像,利用ESARFM 生成具有高时空特征的 Landsa 模拟影像,将其与真实 Landsa 影像进行对比,并在新疆地区展开ESARFM 算法在 NDVI 方面的应用。结果表明, ESARFM 对 3 个不同区域状况的地区都有较好的影像预测能力,并且在新疆地区可以很好地生成 30 m 空间分辨率的多时相 NDVI,用于作物分类和长势监测。     

Quantitation Overcoming Matrix Effects of Lipophilic Toxins in Mytilus galloprovincialis by Liquid Chromatography-Full Scan High Resolution Mass Spectrometry Analysis (LC-HR-MS)

The analysis of marine lipophilic toxins in shellfish products still represents a challenging task due to the complexity and diversity of the sample matrix. Liquid chromatography coupled with mass spectrometry (LC-MS) is the technique of choice for accurate quantitative measurements in complex samples. By combining unambiguous identification with the high selectivity of tandem MS, it provides the required high sensitivity and specificity. However, LC-MS is prone to matrix effects (ME) that need to be evaluated during the development and validation of methods. Furthermore, the large sample-to-sample variability, even between samples of the same species and geographic origin, needs a procedure to evaluate and control ME continuously. Here, we analyzed the toxins okadaic acid (OA), dinophysistoxins (DTX-1 and DTX-2), pectenotoxin (PTX-2), yessotoxin (YTX) and azaspiracid-1 (AZA-1). Samples were mussels (Mytilus galloprovincialis), both fresh and processed, and a toxin-free mussel reference material. We developed an accurate mass-extracted ion chromatogram (AM-XIC) based quantitation method using an Orbitrap instrument, evaluated the ME for different types and extracts of mussel samples, characterized the main compounds co-eluting with the targeted molecules and quantified toxins in samples by following a standard addition method (SAM). An AM-XIC based quantitation of lipophilic toxins in mussel samples using high resolution and accuracy full scan profiles (LC-HR-MS) is a good alternative to multi reaction monitoring (MRM) for instruments with HR capabilities. ME depend on the starting sample matrix and the sample preparation. ME are particularly strong for OA and related toxins, showing values below 50% for fresh mussel samples. Results for other toxins (AZA-1, YTX and PTX-2) are between 75% and 110%. ME in unknown matrices can be evaluated by comparing their full scan LC-HR-MS profiles with those of known samples with known ME. ME can be corrected by following SAM with AM-XIC quantitation if necessary.     

新乡市北站工厂污泥中重金属污染状况研究

[目的]研究北站工厂污泥中的重金属污染状况。[方法]采用HNO3-HF-HClO4消解土壤样品,用原子吸收光谱法对北站工厂污泥样品中重金属Cr、Zn、Cd、Ni、Cu的含量进行了分析测定。[结果]与我国污泥农用标准相比,铬,镉,镍,铜4种重金属在3种污泥样品中的含量都没有超过允许的水平,但锌在黄泥中的含量严重超标,在白泥和黑泥均达到标准。[结论]为预测和防治污泥重金属污染提供理论依据     

基于AMSR-E与MODIS数据海表面温度遥感反演研究

海洋表面温度是海洋环境的重要参数。遥感技术是进行海表面温度研究的有效手段之一。以印度洋北部海域为研究区域,利用Aqua卫星上的微波数据（AMSR-E）和光学数据（MODIS）,进行了海表温度反演研究。首先对AMSR-E L2A数据和MODIS-L1B数据进行预处理,然后将AMSR E的各极化通道亮温数据与实测海表温度进行相关性分析,通过多元线性回归建立AMSR-E海表温度的反演模型,而MODIS海表温度则通过采用线性多通道算法得到,最后以AMSR-E亮温数据为主,MODIS海表温度数据为辅,采用多元线性回归的方法建立了海表温度反演模型。利用该模型反演印度洋北部海域海表温度,反演结果与实测数据相比,其均方根误差为0.323 97 ℃。     

自模式曲线分辨红外光度法用于咖啡碱—茶碱混合物的不分离定量测定

本文研究了自模式曲线分辩红外光度法及其在多组分结构相似混合物同时定量测定中的应用.测定不同配比(10:1至1:10)咖啡碱—茶碱混合物组分,平均回收率分别为99.2±3.6%与99.1±2.8%,测定雀巢咖啡中咖啡碱的结果为3.37±0.093%.     

Scaling simulation models for spatially heterogeneous ecosystems with diffusive transportation

The behavioral dependence of vegetation simulation models for spatially heterogeneous grasslands on simulation resolution was investigated. The dependence can be largely attributed to the non-linearity of the models. We showed that increasing scale or decreasing spatial resolution tended to overestimate the changing rate of an ecosystem using our landscape simulation model for alkaline grasslands in northeast China. A technique for scaling up simulation models with diffusive transportation was developed in this study by means of expanding the nonlinear driving functions in the model. The analysis showed that a simulation model for spatially heterogeneous landscapes might necessitate modification of both its mathematical structure and parameterization when applied to different scales. The scaling coefficients derived in this study were shown to be proportional to the variances or covariance of the spatially referenced variables, and can be estimated by running the model at a fine resolution for selected samples of the coarser grid cells. The technique was applied to a grassland landscape in northeast China and the results were compared with five-year observations on community succession. The comparison indicated that the proposed technique could effectively reduce overall scaling error of the model by as much as 80%, depending on the scaling difference between the fine and the coarse resolutions as well as the sampling scheme used.     

Characterizing Fine-scale Patterns of Alternative Agricultural Landscapes with Landscape Pattern Indices

Landscape pattern indices are common tools of landscape ecologists, affording comparisons of different study areas, or the same study area at different times. Since the advent of popular index-calculating software, more landscapes can be analyzed in short amounts of time, yet the behaviour of landscape pattern indices can vary for different contexts or data characteristics, complicating interpretation. I applied a selected set of landscape pattern indices to fine-resolution (3 m) data representing a highly fragmented landscape – Corn Belt Iowa agriculture – to investigate the performance of landscape pattern indices. Indices measured pattern attributes that affect the viability of small mammal populations, namely habitat proportion and connectivity and landscape grain size and heterogeneity. Results showed that the performance of indices for fine-resolution data can be highly variable, depending upon data and contextual issues like the presence of linear elements and the amount of habitat. For these Corn Belt landscapes good habitat proportions and patch sizes were small (commonly less than 10% and less than 1 ha, respectively), and connectivity was variable depending on the measure. Aggregation and mean nearest neighbour indices performed better than other connectivity indices. Fine-resolution data representing highly fragmented landscapes can raise difficulties for indices of landscape configuration. Landscape pattern indices require improvement to perform better for increasingly available fine-resolution data representing common landscape types.     

酶法拆分DL-茶氨酸及其分离纯化

将DL-茶氨酸乙酰化为N-乙酰-DL-茶氨酸,利用本实验室筛选的有较高氨基酰化酶活性的真菌刺孢小克银汉霉9980（Cunnighamella echinulata 9980）对DL-茶氨酸进行拆分并对拆分条件进行摸索。结果表明：反应最适温度50℃,最适pH7.0,底物浓度0.5mol/L,湿菌体量4g/100βml,拆分时间30h,拆分率可达92％。产物经JK008阳离子交换树脂氨性柱分离,L-茶氨酸收率84.3％,[α] =8.1(c=2,H₂O), 符合JP2000药典。     

崂山林场林分生物量遥感反演估算研究

以Landsat TM影像和高分一号影像为数据源,结合外业实测数据,利用遥感影像和实测数据建立崂山林场生物量多元线性反演模型,比较分析不同数据源下反演出的模型精度,估测了崂山林场森林生物量。研究发现,利TM遥感影像作为数据源的崂山林场森林生物量反演模型平均精度为77.12%。高分一号遥感数据反演的生物量模型平均反演精度达到80.75%,高于TM数据源下的生物量反演模型精度。分别根据TM遥感影像和高分一号遥感影像林分生物量估测模型,估测的崂山林场2009年的林分生物量为401185.62t,2013年的林分生物量为402485.44t。