轮台白杏叶片铁锰浓度光谱估算模型

建立基于光谱分析的轮台白杏叶片铁(Fe)、锰(Mn)元素浓度估算模型,为快速建立轮台白杏树体微量营养元素诊断体系提供技术途经。采用Unispec-SC光谱仪测定土壤肥力存在显著差异条件下轮台白杏果实不同生育时期叶片的光谱反射率,通过分析叶片中Fe和Mn元素浓度与Rλ和f′(Rλ)的相关性,筛选出光谱指示波段,并采用线性回归模型建立光谱估算模型以估算叶片Fe和Mn营养元素浓度。结果表明:轮台白杏果实不同生育时期叶片Fe元素的光谱敏感波段各不相同,果实坐果期和硬核期敏感波段分别为873和874nm,375和437nm。果实成熟期敏感波段为836和837nm而果实收后期敏感波段为325和1 054nm;轮台白杏果实四个生育时期Mn元素的光谱敏感波段分别为913和1 129nm,425和970nm,390和466nm,423和424nm;轮台白杏叶片Fe和Mn元素浓度均与光谱反射率一阶微分f′(Rλ)相关性最强,与之建立的线性光谱估算模型拟合度最高,且达到了显著或极显著水平。表明果实不同生育时期,轮台白杏叶片Fe和Mn元素的光谱指示波段不同,可根据双波段f′(Rλ)采用线性模型估算白杏叶片Fe和Mn元素浓度。     

Color Measurement in Leaf Diagnosis

Abstract

The paper presents for the first time in literature the use of color measurement in leaf diagnosis. It uses the data obtained in certain well- established conditions, in CIE 1976 system for quantifying the color changes of leaves in different sufference (plant or leaf damage) symptoms.

The data are presented for sugar beet plants, but the application can be easily extended to any crop, arboretums, or ecological systems.

As a further extension of the study, it can be used in the telediagnosis of plants' sufferences by plane or even by satellite.     

傅里叶变换红外光谱法研究核辐照对三七总皂苷粉成分的影响

采用傅里叶变换红外光谱(卷积谱)法对经不同剂量y-射线核辐照的三七总皂苷粉进行了对比研究.辐照剂量不高于9kGy时,三七总皂苷粉样品的化学成分几乎没有发生变化;三七总皂苷粉样品经15kGy及以上的辐照剂量辐照后,可能产生新的化学成分;经21kGy的剂量辐照,三七总皂苷粉产生了人参、三七粉所含的普通成分(非三七总皂苷成分...     

Effect of seasonal variation on dust samples of a winter fog affected urban environment of India,South East Asia

Physical and chemical characteristics of leaf dust (LD) samples, collected between 2011 and 2013, of a severely winter fog affected and polluted urban environment (Allahabad, India) of Indo-Gangetic plain are presented in this study. The weather changes in the study area are grouped into three effective annual seasonal periods – winter fog, pre-monsoon and post-monsoon. The pronounced impact of seasonal variations is observed in LD characteristics, as ~46% of the winter fog period samples ranges in size between 2.5 and 20 µm with high magnetic susceptibility (up to 938.22 × 10^?8 m³ kg^?1). In comparison, 35% of the LD from pre-monsoon period occurs in the size range of 100–300 µm with low magnetic susceptibility (up to 43.29 × 10^?8 m³ kg^?1). The fractal analysis involving submicroscopic clast dimension of LD also reveals a seasonal influence. The toxic metals (Pb, Zn, Cd, Cr and Ni) in LD belonging to winter fog and post-monsoon periods increase in comparison to samples from pre-monsoon time. Multivariate statistical analysis of trace element data suggests that the LD collected from winter fog and post-monsoon periods originate predominantly from anthropogenic source, whereas those collected during pre-monsoon owe their origin to crustal and anthropogenic sources, mainly. The present study has demonstrated the role of seasonal variation in controlling the physical and chemical properties of particulate matter based on multiple parameter analyses, and the derivation of the dust load from a mixed source (upper continental crust, anthropogenic and vehicular) for the study area for the first time.     

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。     

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。     

改进的QGA-ELM算法水稻叶面积指数反演模型

为了通过植被指数（VI）准确、可靠的获取不同施肥梯度、不同品种的水稻叶面积指数（LAI）,提出了一种基于改进的QGA-ELM算法应用于水稻LAI反演。首先通过8折交叉验证确定极限学习机(ELM)最佳的隐含层神经元个数与隐含层激活函数类型,再通过引入组合动态旋转角策略、单点混沌交叉操作、混沌变异操作、确定性选择策略、量子灾变操作对量子遗传算法（QGA）进行改进,最后使用改进后的QGA算法优化ELM神经网络输入层到隐含层的连接权值和隐含层的阈值。为了验证该模型普适性和有效性,依次建立多元线性回归、BP、ELM、QGA-ELM、改进的QGA-ELM算法5种模型,并在不同数据集上进行反演效果比较,结果表明：（1）对比QGA-ELM算法和改进的QGA-ELM算法进化过程,改进的算法能有效提升模型寻优能力,避免算法早熟,且能寻得更优结果。（2）对比五种算法在不同数据集上的反演效果,验证了NDVI,RVI与LAI之间主要为非线性关系,且ELM神经网络模型反演效果要优于BP神经网络模型和多元线性回归模型。（3）对比五种算法在不同数据集上的反演效果,改进的QGA-ELM算法绝大部分情况下拥有最高的反演精度和最低的误差,改进后的算法反演精度得到了明显提升,泛化性能也得到了增强。（4）改进的QGA-ELM算法在各种施肥梯度上均具有最高反演精度和最低误差,且精度较高,能为不同生长状况水稻LAI反演提供依据。（5）五种模型对庆和香LAI反演精度均要高于龙稻18,而改进的QGA-ELM算法在不同水稻品种上依然具有较高的反演精度,且在不同水稻品种上反演精度相差极小,远低于其他四种模型,能很好适应不同水稻品种LAI反演要求,极大提升模型的稳定性性,为不同水稻品种反演提供参考意义。     

低温胁迫下香蕉叶片Chla荧光动力学参量的变化及其品种差异性

低温胁迫下,广东2号香蕉品种和巴西香蕉品种Williams的叶绿素(Chla)荧光动力学参量F_Ⅴ/F_m、ΔF_Ⅴ/F_T以及williams品种的F_IV/F_Ⅴ均呈下降趋势,两个品种的荧光上升半时间T_1/2及广东2号的F_IV/F_Ⅴ呈上升趋势.其中,Williams的F_Ⅴ/F_m、ΔF_Ⅴ/F_T和T_1/2的变化幅度小于广东2号,表明低温胁迫通过抑制光合电子传递速度和PSⅡ无活性中心含量的提高使香蕉叶片PSⅡ原初光能转换效率下降,相同低温对广东2号的影响大于对Williams的影响.F_Ⅴ/F_m和ΔF_Ⅴ/F_T可以作为评价香蕉幼苗抗冷性的物理指标.     

Proteomic analysis of a spring wheat cultivar in response to prolonged cold stress

Cold represents one of the major abiotic factors influencing plant growth and development worldwide. We analysed the long-term responsiveness of an Iranian spring wheat (cv. Kohdasht) to cold from a proteomic point of view, in order to unravel the molecular mechanisms helping a cold-sensitive cultivar to survive exposure to suboptimal temperatures. Plants were grown at 20 or 4°C until entering the reproductive stage and a cross-comparison on the leaf proteomes was performed. Quantitative analyses on protein alterations occurring upon low-temperature exposure showed a reinforcement in ascorbate recycling (dehydroascorbate reductase, ascorbate peroxidase) and protein processing (proteasome subunit, cysteine proteinase), as well as the accumulation of the enzyme devoted to tetrapyrrole resynthesis (glutamate semialdehyde aminomutase). In contrast, among proteins down-regulated after cold stress, we could identify some key Krebs cycle enzymes (isocitrate dehydrogenase, malate dehydrogenase), together with many photosynthesis-related proteins (oxygen-evolving complex proteins, ATP synthase subunits, ferredoxin NADPH oxidoreductase and some Calvin cycle enzymes). Physiological and biochemical parameters (such as shoot apex dissection, chlorophyll, proline and sugar content determination) sustained proteomics findings allowing the present research to contribute to the current knowledge on these long-term responses, which may be crucial to stress adaptation under field conditions.     

Near-infrared reflectance spectroscopy as a fast and non-destructive tool to predict foliar organic constituents of several woody species

Near-infrared reflectance spectroscopy (NIRS) was used to estimate N, neutral detergent fibre (NDF), acid detergent fibre (ADF), lignin and cellulose contents in leaves of a heterogeneous group of 17 woody species from the Central Western region of the Iberian Peninsula. The sample set consisted of 182 samples of leaves of deciduous and evergreen species, showing a wide range of concentrations determined by reference methods: 6.60–35.2 g kg⁻¹ (N), 15.5–66.0% (NDF), 10.2–57.3% (ADF), 3.45–27.4% (lignin) and 5.79–31.3% (cellulose). Reflectance spectra, obtained for samples of dried and ground leaves, were recorded as log1/R (R=reflectance) from 1,100 to 2,500 nm. NIRS calibrations were developed using multiple linear (MLR) and partial least-squares (PLSR) regressions, and tested by external validation. Spectral data were transformed to the first and second derivative (1D, 2D). The PLSR method and derivative transformations provided the best statistics and showed lower standard errors of calibration (SEC) and higher coefficients of multiple determination (R ²). In the external validation the standard errors of prediction (SEP) were 0.76 g kg⁻¹ (N), 2.11% (NDF), 1.47% (ADF), 0.85% (lignin) and 0.86% (cellulose). The results obtained show that NIRS is very effective for the estimation of these organic constituents in leaf tissue of woody species. This technique can be used in ecological or ecophysiological studies as an alternative to the more time-consuming standard methods.