基于优化面积光谱指数的玉米叶片叶绿素值估测

综合使用光谱技术对作物养分进行实时、有效诊断,有助于作物的精准管理、保障产量和减少环境污染,提高肥料利用率,并且为定量估测作物生化组分状况提供了一种新的途径.光谱指数是进行作物叶片叶绿素实时估测的重要指标,然而由于受到环境条件及内在生化成分的影响,估测结果不尽满意.为了进一步提高光谱指数在估测作物叶片叶绿素含量时的抗干...     

T1 THEOREM FOR BESOV SPACES ON NONHOMOGENEOUS SPACES

Suppose μ is a Radon measure on Rd, which may be non doubling. The only condition assumed on μ is a growth condition, namely, there is a constant Co ＞ 0 such that for all x ∈ supp(μ) and r ＞ 0,μ(B(x,r)) ≤ Corn, where 0 ＜ n ≤ d. We prove T1 theorem for non doubling measures with weak kernel conditions. Our approach yields new results for kernels satisfying weakened regularity conditions, while recovering previously known Tolsa's results. We also prove T1 theorem for Besov spaces on nonhomogeneous spaces with weak kernel conditions given in [7].     

An economic and environmental comparison of a biochemical and a thermochemical lignocellulosic ethanol conversion processes

With the world’s focus on rapidly deploying second generation biofuels technologies, there exists today a good deal of interest in how yields, economics, and environmental impacts of the various conversion processes of lignocellulosic biomass to transportation fuels compare. Although there is a good deal of information regarding these conversion processes, this information is typically very difficult to use on a comparison basis because different underlying assumptions, such as feedstock costs, plant size, co-product credits or assumed state of technology, have been utilized. In this study, a rigorous comparison of different biomass to transportation fuels conversion processes was performed with standard underlying economic and environmental assumptions so that exact comparisons can be made. This study looked at promising second-generation conversion processes utilizing biochemical and thermochemical gasification technologies on both a current and an achievable state of technology in 2012. The fundamental finding of this study is that although the biochemical and thermochemical processes to ethanol analyzed have their individual strengths and weaknesses, the two processes have very comparable yields, economics, and environmental impacts. Hence, this study concludes that based on this analysis there is not a distinct economic or environmental impact difference between biochemical and thermochemical gasification processes for second generation ethanol production.     

非离子型表面活性剂辅助酶水解玉米秸杆蒸爆渣

研究纤维素酶对蒸汽爆破预处理玉米秸杆的水解过程. 实验结果表明,玉米秸杆蒸爆渣中的木质素对纤维素酶存在非生产性吸附,降低了纤维素酶对玉米秸杆蒸爆渣的水解率;通过添加非离子型表面活性剂PEG 6000,减少纤维素酶的非生产性吸附,改善纤维素酶对玉米秸杆蒸爆渣的水解性能;在pH值为4.8,温度为50℃,PEG 6000浓度为3.5g/L的优化条件下,纤维素酶水解玉米秸杆蒸爆渣48h,还原糖水解率和葡萄糖水解率分别为83.61%和64.15%.     

Application of off-line pyrolysis with dynamic solid-phase microextraction to the GC–MS analysis of biomass pyrolysis products

Pyrolysis coupled with dynamic solid-phase micro extraction (Py-SPME) followed by GC–MS analysis was applied to the determination of volatile compounds evolved by a micro-scale off-line pyrolysis apparatus, in order to extend the information affordable with this type of analytical equipment. The Py-SPME method with a carboxen/PDMS fiber working in the retracted mode was tested on four biomass samples (switchgrass, sweet sorghum, corn stalk and poplar) for qualitative analysis of semi-volatile pyrolysis products and quantitative determination of main volatiles (C₁–C₄) pyrolysis products. The developed procedure allowed capturing and analysis of all GC analyzable compounds, without memory effects and with good peak resolution also for early GC-eluting compounds. Twelve main volatile pyrolysis products, including hydroxyacetaldehyde and acetic acid, were successfully quantified; in spite of the intrinsic variability introduced by dynamic SPME sampling, results were relatively accurate and consistent with literature data on bench pyrolysis reactors.     

基于DS算法的玉米近红外定性分析光谱校正方法研究

从校正的角度出发,研究了近红外定性分析中模型稳定性问题。以13个玉米品种为研究对象,针对数据采集时间不同带来的模型失效问题,借鉴近红外光谱定量分析中两台仪器间模型传递的思想,将直接模型传递(Direct Standardization)算法用于校正同一仪器不同时间采集的光谱, 使得一次建立的品种鉴别模型,能用于其余时间测试数据的鉴别。首先采用Kennard/Stone算法在主光谱集中选取校正样品集,按照对应的编号从从光谱集中取出对应的数据,然后对校正样品集采用DS算法求取两组数据间的变换关系,再对剩余的从光谱集进行相应的变换得到适用于模型的光谱。实验中对比了校正样本数和模型校正位置对校正结果的影响,分别从品种定性鉴别准确性和校正前后主光谱数据和从光谱数据分布距离两方面分析了实验结果。结果表明,该方法能有效地解决同一仪器随着采样时间推移产生的光谱偏移现象,对采样时间不同的测试集均得到较高的识别率,提高了模型的鲁棒性和适用范围,由实验结果可见,校正位置处于特征提取之后时,校正效果最佳。     

玉米品种近红外光谱鉴别技术中的参数漂移问题研究

以13个玉米品种鉴别为研究对象,提出了一种解决光谱仪参数漂移问题的有效方法。使用同一台光谱仪分不同时间重复采集数据,用一天数据建模,其余测试,发现不同时间采集的数据有较大偏移,严重时正确识别率仅为7.69%。为此,提出一种有监督学习特征提取的多天联合建模方法,首先挑选具有代表性的多个时间段样本数据共同组成建模集,其次采用PLS+LDA特征提取算法,提取出与仪器参数漂移无关的品种特征信息, 然后采用BPR方法建立品种鉴别模型。实验结果表明,该方法对于不同时间数据的偏移均能有较好的校正效果,得到较高的识别率和稳定性。     

重金属铅离子胁迫下玉米叶片光谱弱差信息的DSAT甄别模型

光谱间微弱信息测度是当今高光谱遥感研究难点之一,传统光谱测度方法难以区分光谱信息的微弱差异。研究设计了不同浓度的铅(Pb)污染实验,并测量了不同浓度铅离子(Pb2+)胁迫下玉米叶片的高光谱反射率、叶绿素含量及Pb2+含量,但是从所测结果得出,不同浓度Pb2+胁迫下的光谱相似性相关系数均达到0.999,难以区分不同浓度Pb2+胁迫引发的光谱间微弱信息差异和污染程度。针对这一情况,基于光谱微分处理、正切函数增强、光谱角量度与波谱分段检测等,提出了一种新型的相似光谱测度方法,即微分光谱角正切(derivative spectral angle tangent,DSAT)法。为了验证DSAT在区分相关系数达0.99以上相似光谱的可行性和有效性,将DSAT用于不同浓度Pb2+胁迫玉米叶片的整体波形与光谱区间子波形的信息差异性度量与检测。实验结果得到,波形差异信息与玉米叶片中叶绿素相对浓度与Pb2+含量显著相关。进而也证明DSAT法在甄别较高相似性光谱间差异上具有更好的实用性和优越性。     

基于高光谱技术的玉米种子可视化鉴别研究

种子纯度是衡量种子品质的重要指标。提出一种基于近红外(874～1 734 nm)高光谱技术实现玉米种子可视化鉴别的方法。采集4个品种共384个玉米种子样本的高光谱图像数据,随机选择288个样本作为建模集,剩余96个样本作为预测集。对玉米种子光谱曲线进行分析后,通过连续投影算法（SPA）选取7个特征波段作为输入,结合偏最小二乘法判别分析(PLS-DA)模型,对预测集进行预测,获得较好的分类效果,其中R_C=0.917 7,RMSECV=0.444 2; R_CV=0.911 5,RMSECV=0.459 9,建模集和预测集的总体鉴别率分别为78.5%和70.8%。通过图像处理技术提取高光谱图像中每个玉米颗粒的平均光谱数据,输入建立的SPA-PLS-DA模型,在计算生成的鉴别图中以不同颜色标识不同类别,实现了混杂玉米种子样本的可视化鉴别。对3份不同组成的混杂种子样本进行鉴别,达到了较好的可视化效果。结果表明,通过可视化鉴别技术,可以直观方便地观察混杂种子样本中不同品种种子的分布和数量,为农业生产中种子的纯度鉴别和筛选提供了帮助。