基于叶片光学属性的作物叶片水分含量反演模型研究

叶片含水量是反映作物生理特性的一个重要参数, 对生态环境的研究具有重要意义。采用小波分析方法, 分析叶片含水量对反射率的影响特征, 建立综合利用多波段信息的作物叶片水分含量反演模型。基于PROSPECT模型的辐射传输理论, 推导出由叶片反射率光谱的小波系数反演叶片水分含量CW的理论模型。利用六种常用的小波函数, 对叶片组分水、干物质和白化基本层的吸收光谱进行小波分解。选取对水分变化最敏感, 同时对其他组分不敏感的分解尺度和波段位置, 找到能稳定突出水的光谱特征的小波系数。结果表明: bior1.5小波函数在尺度为200 nm, 波段位置为1 405和1 488 nm的小波系数具有上述特征。建立由叶片反射率光谱的bior1.5小波系数反演叶片水分含量CW的反演模型, 模型有两个转换系数a和Δ都受叶片结构参数N的影响。利用PROSPECT模型生成模拟光谱数据集, 校正建立的叶片水分含量反演模型中的两个转换系数a和Δ, 并与LOPEX93实验光谱数据集结合验证反演模型。结果表明: 反演模型不仅比传统基于植被指数的统计模型在精度上有提高(反演值与实测值的R2最高达到0.987), 而且更加稳定, 普适性更高。研究表明, 小波分析方法在利用高光谱数据反演作物叶片水分含量方面具有独特的优势。     

固相萃取-高效液相色谱法测定烟叶中吡虫啉农药残留量

建立了固相萃取-高校液相色谱法测定烟叶中吡虫啉农药残留量的方法。样品用乙腈提取,弗罗里硅土固相萃取柱净化.梯度洗脱方式分离,DAD二极管阵列检测器检测。吡虫啉加标回收率为87.83%—94.80%,相对标准偏差为1.64%,检出限为0.01μg/g。该方法灵敏、准确,适用烟草中吡虫啉农药残留的分析。     

利用偏最小二乘回归从冬小麦冠层光谱提取叶片含水量

通过人为控制灌溉水平,在冬小麦3个发育期(孕穗、开花、乳熟)测定了冠层光谱和叶片含水量(leaf water content,LWC)。针对每期数据,结合偏最小二乘回归和迭代特征去除,建立了基于诊断波段的LWC回归模型。结果表明,叶片水分的光谱响应及反演精度受小麦生长状态的影响。在孕穗、开花和乳熟3个发育阶段,回归模型中光谱数据的最佳利用形式分别为对数光谱、导数光谱和反射率光谱;重要光谱区间为SWIR,NIR和SWIR;模型交叉验证决定系数(R2_CV)为0.750,0.889和0.696。研究结论对今后监测冬小麦旱情和开发作物水分遥感产品具有重要的指导作用。     

Numerical analysis of pattern formation on the surface of transpiring leaves

The process of photosynthesis is facilitated by pores on the leaf surface called stomata. When a particular stoma is open, CO₂ is absorbed through its aperture, but H₂O is also lost due to evaporation. Thus a plant will seek a stomatal aperture that balances its need for CO₂ with its aversion to H₂O loss. In order to visualize a particular leaf’s stomatal aperture distribution and how it changes with time, fluorescence data is collected at regular intervals as digital images, resulting in a video sequence. It has been observed that stomatal apertures are often synchronized into spatially extended patches. In order objectively to analyze this phenomenon we have developed a technique to isolate patches via a three-dimensional PDE-based segmentation method. The resulting segmented data is then collapsed to a vector valued time series of much smaller dimension with a hybrid PCA-Archetypal Analysis approach. This allows for a unique interpretation of the data in terms of statistical measures of the motions of representative patches. The technique is illustrated with a data-set from a particularly complicated regime collected by the Complexity and Stomatal Behavior research lab at Utah State University.     

秦油2号油菜高产栽培中喷肥优化配方研究

采用二次饱和－Ｄ最优设计的方法，研究Ｓｒ（ＮＯ３）２（ｘ１）、ＫＨ２ＰＯ４（ｘ２）和Ｎａ２Ｂ４Ｏ７·１０Ｈ２Ｏ（ｘ３）叶面喷施对秦油２号油菜的产量效应，获得回归方程：ｙ＝２４７．４８５＋７．００４８ｘ１＋２．２９２４４ｘ２—９．８２６４６ｘ３—０．２５３５ｘ１ｘ２—１３．８５２４ｘ１ｘ３：—３．３７４７５ｘ２ｘ３＋２７．０５７５Ｘ２１—１６．３０３６ｘ２２—８．７６７８ｘ２３结果表明Ｓｔ（ＮＯ３）２。有明显的增产作用．ｘ１ｘ３的交互作用（效应）最大．通过计算机模拟．其最佳因子组合为Ｓｒ（ＮＯ３），０．１％、ＫＨ２ＰＯ４０．３％和硼砂０．０１％，预计产量可达２９６．４６ｋｇ／６６７ｍ２．     

Hydrogenation of 2,4-hexadienoic acid methyl ester

Hydrogenation of 2,4-hexadienoic acid methyl ester on supported metal catalysts (Pd/C, Pt/C, Rh/C and Ru/C) has been investigated. Methyl esters of 2-hexenoic and 3-hexenoic acids were formed and further hydrogenated to the methyl ester of hexanoic acid. Palladium was found to be the most active and selective catalyst for this reaction owing to the formation of intermediates.     

无人机高光谱波段选择的叶面积指数反演

叶面积指数(LAI)是评价作物长势和作物产量的重要参数.为有效利用高光谱信息,优选出最佳波段进而构建新型双波段指数来提高LAI估测精度,以冬小麦为研究对象,获取冬小麦孕穗期无人机高光谱数据和实测地面LAI数据,开展冬小麦LAI反演研究.首先采用连续投影算法(SPA)、最佳指数法(OIF)以及逐波段组合法(E)分别进行无...     

杂交稻不同时期喷施微量元素叶肥“稻多收”增产效果研究

“稻多收”是一种新型水稻专用叶肥，含多种微量元素，本文报道“稻多收”的施用方法、增产效果及原因，结果表明叶面喷施“稻多收”能使杂交稻增产16％～20％，每亩净增收入90．00～100．00元，是微量元素科学服务于农业生产的一个重要方面，从而为杂交稻栽培提供了一条经济有效的增产途径。     

Closest 4-leaf power is fixed-parameter tractable

The NP-complete Closest 4-Leaf Power problem asks, given an undirected graph, whether it can be modified by at most r edge insertions or deletions such that it becomes a 4-leaf power. Herein, a 4-leaf power is a graph that can be constructed by considering an unrooted tree—the 4-leaf root—with leaves one-to-one labeled by the graph vertices, where we connect two graph vertices by an edge iff their corresponding leaves are at distance at most 4 in the tree. Complementing previous work on Closest 2-Leaf Power and Closest 3-Leaf Power, we give the first algorithmic result for Closest 4-Leaf Power, showing that Closest 4-Leaf Power is fixed-parameter tractable with respect to the parameter r.