玉米粉淀粉含量近红外模型建立与优化

以230份玉米自交系为样本，采用旋光法与一阶导数及去一条直线的光谱预处理法，构建玉米粉样淀粉含量的近红外分析（NIRS）模型。研究标明，该模型可显著提高子粒淀粉含量预测的准确性。该模型的定标标准偏差（RMSEE）、交叉验证标准偏差（RMSECV）、外部验证标准偏差（RMSEP）、定标相关系数（R_cal²）、交叉验证相关系数（R_cv²）、外部验证相关系数（R_cv²）分别为0.609、0.722、0.738、0.909、0.864和0.854。建立的玉米粉样NIRS模型可将预测值与化学值偏差控制在1.7%内，能够准确定量分析玉米子粒淀粉含量，应用于育种材料早期筛选及群体水平粗淀粉分析。     

EC细网格模式2m气温预报产品在崂山地区的验证

选取2015—2019年青岛市崂山区10个气象自动站的日气温数据和EC细网格模式2 m气温预报产品,验证EC细网格模式2 m气温预报产品最低温度和最高温度在青岛崂山地区的准确率,同时分析崂山地区温度的时间、空间分布特征,对预报产品进行订正,在实际业务中进行推广,提高预报的准确率,做好公众气象服务。结果表明,气温存在年变化差异和季节内差异,同一种温度下,春季和夏季的区域分布比较类似,秋季和冬季的区域分布比较类似;崂山区内EC细网格24 h最低温度预报值偏高,最高温度预报值偏低,最低温度的预报总体准确率比最高温度的预报总体准确率要高,西部地区的预报准确率要高于东部地区的准确率;通过订正后,发现最低温度4个季节的预报准确率都在50%以上,最高温度订正后的准确率,除夏季59%以外,其他各季节均在75%以上。     

紫外分光光度法测定陈皮类茶饮料的酶解效果

[目的]使用紫外分光光度测定陈皮类茶饮料的酶解效果。[方法]全波长扫描,确定陈皮类茶饮料样品的吸收峰,再用紫外分光光度法确定样品OD值并换算出T值,研究酶解效果。[结果]方法精密度的相对标准偏差为0.086%,方法稳定性的相对标准偏差为0.210%,灵敏度比感官评价至少高125倍。[结论]用紫外分光光度法研究酶解效果的方法具有较好的精密度、较高的灵敏度和较好的稳定性。     

蔬菜幼苗叶面积快速测定方法筛选与优化

为得到一种快速且准确测定蔬菜幼苗叶面积的方法,以番茄幼苗为试材,以方格法为对照,研究扫描分析法、叶面积仪法、打孔称重法测定叶面积的准确性、精确性与测定速度,然后采用黄瓜、辣椒叶片及纸片的面积对测定结果进行验证,最后基于不同扫描分辨率对筛选出的方法进行优化。结果表明,相比叶面积仪法和打孔称重法,扫描分析法测定结果更接近真实值,且精度更高,用时更短。扫描分析法不同分辨率下测定结果无显著差异,且扫描分辨率越低所需测定时间越短。扫描分辨率50 dpi下的扫描分析法可作为一种快速准确测定蔬菜幼苗叶面积的方法。     

新构形齿轮刀具安装参数对齿形精度的影响

以加工直齿轮为例，根据齿廓啮合原理及齿廓法线建立数学模型，进行理论推导分析及上机电算，探讨了新构形恨具３个安装参数－－中心距Ａ、刀具安装倾角ψ和偏距Ｂ存在误差时，对加工齿轮齿形精度的影响；通过切齿了实验验证。为切齿机床调整提供了理论依据。     

三平移并联机器人机构的精度分析

针对一种具有相似平台的3-TPT型三平移并联机器人，根据该机器人的位置反解方程，利用全微分理论建立了该机器人精度分析的数学模型；通过计算机仿真研究了机器人的驱动杆杆长误差、结构尺寸变化和位姿变化对机器人精度的影响，为该机器人机构的实际误差补偿与控制提供了理论依据。     

Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain

We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔG(AG) ), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii) a positive interaction exists between the use of genotypic information and a short generation interval on ΔG(AG) and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔG(AG) if genotypic information about the breeding goal trait is known. We examined four breeding schemes with or without genomic selection and with or without intensive use of young bulls using pseudo-genomic stochastic simulations. The breeding goal consisted of a milk production trait and a functional trait. The two breeding schemes with genomic selection resulted in higher ΔG(AG) , greater contributions of the functional trait to ΔG(AG) and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information on ΔG(AG) . Hence, a breeding scheme with genomic selection and with intensive use of young bulls (a turbo scheme) seems to offer the greatest potential. The third hypothesis was disproved as inclusion of genomically enhanced breeding values (GEBV) for an indicator trait in the selection index increased ΔG(AG) in the turbo scheme. Moreover, it increased the contribution of the functional trait to ΔG(AG) , and it decreased ΔF. Thus, indicator traits may still be profitable to use even when GEBV for the breeding goal traits are available.     

Investigation of the Effect of Mesh Size on the Effectiveness of Hotplate Aqua Regia Extractions

Aqua regia extractions with subsequent inductively coupled plasma determinations are a very common method of elemental analysis of soils and sediments. Before extraction, the material must be dried and sieved. Small variations in this early step can have a significant impact on the later outcomes, especially for unassisted (for example, without ultrasonic or microwave) extraction procedures. Therefore the impact of mesh size on the sieving process was investigated. A mesh size of 2.0 mm or greater yielded unacceptably high variations between the subsamples and a very poor recovery rate when compared to a 0.063-mm sieve. A mesh size of 0.3 mm resulted in the best outcomes, losing nearly no material in the fine sediment samples and about a tenth in the coarse samples. The precision was high for the 0.3-mm samples as well, only negligibly surpassed by the 0.1-mm samples for some materials.     

基于TM数据的MODIS雪盖产品精度分析

采用玛纳斯河流域2003年1月1日EOS/MODIS八日合成的雪盖数据和2003年1月4日TM雪盖图进行对比分析,通过TM数据的验证,MOD10A2的精度为95%,精度较高,MOD10A2对积雪进行监测可有效降低云层对遥感影像的影响,在一段时间内可有效对地面实施监测。