基于α_s-酪蛋白特异性的牛乳总蛋白质ELISA定量检测方法的建立

本研究旨在建立牛乳中总蛋白质的ELISA定量检测方法,并评价该方法在牛乳掺假辨识中的应用效果。首先用αs-酪蛋白标准品免疫新西兰白兔,制备αs-酪蛋白特异性抗血清,并建立αs-酪蛋白的间接ELISA检测方法,结果显示血清效价为1∶640,αs-酪蛋白检测的线性范围是25~600 ng/ml,R2=0.999 5,回收率是96.6%~105.2%。再应用乳成分分析仪,凯氏定氮法和所建立的ELISA法测定8份来源不同的原料乳中总蛋白和αs-酪蛋白含量,结果显示不同牛乳中总蛋白质含量在0.029 2~0.029 8 g/ml,αs-酪蛋白含量在0.008 4~0.009 2 g/ml,占牛乳总蛋白质的比例恒定,平均为0.3,并用该系数建立牛乳中总蛋白质的定量方法。最后对5份人为兑水稀释、添加尿素、BSA和三聚氰胺的模拟掺杂牛乳样品进行检测,测定结果表明基于αs-酪蛋白的ELISA方法比乳成分分析仪法和凯氏定氮法具有更高的灵敏性和特异性,含氮添加物对测定结果无显著影响(P0.05),更适合于作为原料乳及含乳产品中牛乳蛋白质的定量分析。     

栽培稻、斑点野生稻、药用野生稻基因组比较分析

以栽培稻总DNA为探针,对栽培稻(AA)自身、斑点野生稻(BB)以及药用野生稻(CC)体细胞染色体进行基因组荧光原位杂交(GISH),并以斑点野生稻总DNA为探针,对自身和药用野生稻体细胞染色体进行基因组荧光原位杂交,以此研究A、B、C 3个基因组型之间的关系.结果显示,A、B、C基因组之间都存在较高的同源性,其中AA与CC之间的信号最强,BB基因组与AA基因组次之,BB基因组与CC基因组的信号最弱.说明A、B、C 3个基因组之间的亲缘关系,A与C最近,B与C最远.     

拟建牛栏江象鼻岭水电站库区水生生物及鱼类资源调查

金沙江一级支流牛栏江,贵州省从未进行过水生生物资源调查,2005年10月、12月,经2次采样调查,共检出浮游植物116种,浮游动物15种,底栖动物9种,水生维管束植物1种,鱼类63种。对资源现状进行了评价,预测了建库后对水生生物及鱼类的影响。     

东北红豆杉性别相关的AFLP标记研究

利用AFLP技术,运用64个引物组合,检测雌雄东北红豆杉基因组DNA的多态性,筛选与东北红豆杉性别相关的分子标记.其中7对引物组合共提供了11个与东北红豆杉性别相关的分子标记,其中10个与东北红豆杉雌性相关的分子标记,仅1个与东北红豆杉雄性相关的分子标记.     

不同含水率速生杨木DMA图谱分析及应用

采用动态热机械分析仪对绝干、6％、12％、18％、30％、50％、100％和水饱和8种含水率速生杨木试件进行了动态黏弹性分析.动态力学分析参数为:温度扫描范围35～ 350℃,升温速度5℃·min-1,测量频率10Hz.储能模量的变化表明:各含水率试件在整个扫描温度范围内均出现2个明显的弹性转变过程,完成次级弹性转变的...     

Evaluation of ultrasonic sensor for variable-rate spray applications

Automatic variable-rate sprayers require accurate measurement of canopy size. An estimate of canopy size is made by measuring the distance to the canopy at several elevations above the ground; an ultrasonic sensor was used to determine canopy distance in this study. It is sometimes necessary to conduct spray operations during harsh operating conditions. In this study ultrasonic sensors were subjected to simulated environmental and operating conditions to determine their durability and accuracy. Conditions tested included exposure to extended cold, outdoor temperatures, cross winds, temperature change, dust clouds, travel speeds and spray cloud effects. The root mean square (RMS) error in a series of measurements of the distance to a simulated plant canopy was used to test for significant difference among treatments. After exposure to outdoor cold conditions for 4 months, the RMS error in distance measured by the ultrasonic sensor increased from 3.31 to 3.55 cm, which was not statistically significant. Neither the presence of dust cloud nor the changes in cross-wind speeds over a range from 1.5-7.5 m/s had significant effects on the mean RMS errors. Varying sensor travel speed from 0.8 to 3.0 m/s had no significant influence on sensor detection distances. Increasing ambient temperature from 16.7 to 41.6 °C reduced the detection distance by 5.0 cm. The physical location of the spray nozzle with respect to the ultrasonic sensor had a significant effect on mean RMS errors. The mean RMS errors of sensor distance measurements ranged from 2.3 to 83.0 cm. The RMS errors could be reduced to acceptable values by proper controlling the sensor/spray nozzles spacing on a sprayer. In addition, multiple-synchronized sensors were tested for their measurement stability and accuracy (due to possible cross-talk errors) when mounted on a prototype sprayer. It was found that isolating the pathway of the ultrasonic wave of each sensor reduced detecting interference between sensors during multiple sensor operation. Test methods presented herein may be useful in the design of standardized testing protocols for field use distance sensors.     

Hyperspectral species mapping for automatic weed control in tomato under thermal environmental stress

This work studied the impacts of variations in environmental temperature on hyperspectral imaging features in the visible and near infrared regions for robust species identification for weed mapping in tomato production. Six major Californian processing tomato cultivars, black nightshade (Solanum nigrum L.) and redroot pigweed (Amaranthus retroflexus L.) were grown under a variety of diurnal temperature ranges simulating conditions common in the Californian springtime planting period and one additional treatment simulating greenhouse growing conditions. The principal change in canopy reflectance with varying temperature occurred in the 480-670 and 720-810 nm regions. The overall classification rate ranged from 62.5% to 91.6% when classifiers trained under single temperatures were applied to plants grown at different temperatures. Eliminating the 480-670 nm region from the classifier’s feature set mitigated the temperature effect by stabilizing the total crop vs. weed classification rate at 86.4% over the temperature ranges. A site-specific recalibration method was also successful in alleviating the bias created by calibrating the models on the extreme temperatures and increased the classification accuracy to 90.3%. A global calibration method, incorporating all four temperature conditions in the classifier feature space, provided the best average total classification accuracy of 92.2% out of the methods studied, and was fairly robust to the varying diurnal temperature conditions.     

水稻稻瘟病图像识别预处理方法研究

为了实现计算机对水稻稻瘟病病害的自动识别,研究了水稻稻瘟病病斑图像的预处理和形状特征提取方法。试验中利用灰度变换、直方图均衡化及中值滤波法有效去除了噪声和增强了图像,利用拉氏算子对病斑图像进行边缘检测,准确提取了病斑的形状特征,实现了稻瘟病图像目标分割。这些研究为进一步的特征参数提取及最终病害确定打下基础。     

基于Meta分析的猪后腿性状QTL整合定位

【目的】通过Meta分析,利用数学模型整合与优化猪后腿腿臀质量、腿臀肉质量和腿臀比性状的QTL,提高QTL定位的准确度和有效性,为猪后腿性状QTL的精细定位和分子辅助育种奠定基础。【方法】收集猪后腿腿臀质量,腿臀肉质量和腿臀比性状的QTL及其相关信息,利用BioMercator2.1,将原始QTL映射到美国肉畜研究中心（USDA-MARC 2.0）公布的猪遗传连锁图谱,构建新的整合图谱,分析得到QTL簇。进一步对各QTL簇进行Meta分析,定位“真实”QTL（MQTL）,缩短95%置信区间,减少定位误差。【结果】收集了93个猪后腿性状的QTL及其相关信息,经比对、映射,构建了新的整合图谱,发现19个QTL簇。通过Meta分析,得到19个MQTL,其图距比原平均图距缩短16.19%～78.96%,其中,MQTL1、MQTL5、MQTL6、MQTL8、MQTL9、MQTL10、MQTL11、MQTL12和MQTL17等9个MQTL图距的缩短比例均超过50%。【结论】Meta分析得到的MQTL图距均有不同程度缩短,最小的仅1.75 cM,缩短比例最大可达78.96%,提高了QTL定位的准确度和有效性。