不同水分处理对烟草叶片高光谱及红边特征的影响

采用ASD Fieldspec HH光谱仪, 测定了不同水分处理下两个烟草品种叶片的光谱特性, 分析其红边特征参数的变化规律及其与烟叶生理指标的相关性。结果表明: 不同水分处理之间的烟草叶片光谱反射率差异明显, 但两个品种的变化规律一致。烟草伸根期和旺长期, 近红外光区的光谱反射率随土壤水分的增加而升高, 成熟期则呈相反趋势, 且光谱反射率在旺长期达到最高值。不同水分处理下烟草叶片一阶微分光谱趋势总体一致, 但红边一阶导数光谱差异显著。红边位置随土壤水分减少向长波方向移动, 发生“红移”现象。红边幅值和红边面积在伸根期和旺长期均随土壤含水量的增加而发生“红移”现象, 成熟期则发生“蓝移”现象。烟草叶片的红边位置同其生理指标的相关性要优于其他参数, 同叶绿素a含量、叶绿素b含量、类胡萝卜素含量、叶绿素总量、叶片鲜重、叶片干重、叶面积和叶片含水率均呈极显著相关关系; 红边幅值和红边面积与叶绿素a含量、叶绿素b含量、类胡萝卜素含量、叶绿素总量和叶片含水率之间均呈极显著性正相关, 红边面积同叶片干重呈极显著性负相关关系。     

微分光谱遥感及其在水稻农学参数测定上的应用研究

通过不同氮素营养水平的水稻田间试验,解析了水稻冠层微分光谱对消除背景(湿土、水面)信息的影响,证实微分光谱在消除背景信息的影响方面起到了很好的作用。用微分光谱确定出最优的波段宽度应小于10nm;将微分光谱应用于农学参数测定,存在红边位移现象,在孕穗期之前,红边随施氮量增加向长波方向移动“红移”;孕穗期之后“红移”现象基本消失,而发生“蓝移”。红边参数(红边、红边振幅、红边振幅与最小振幅的比值、红边峰值面积)与上层叶片的叶绿素含量、LAI有着密切的关系,而与叶片中的叶绿素b、类胡萝卜素之间相关性不明显。一些红边参数可作为水稻叶绿素含量、LAI测定的简捷方法。从而证实了利用微分光谱测定一些农学参数的可行性     

用于监测柑橘叶片冻害的叶绿素含量光谱反射模型研究

果树叶片的叶绿素含量（SPAD）是植株营养状况的表现,也决定其光合作用能力的强弱,并且越冬前的树体营养状态,对果树抵御极端低温和顺利越冬是一个重要的影响因素,而果树受冻时叶绿素渗出和降解也是冻害发生程度的指标。通过对不同生长期的柑橘叶片进行光谱扫描,采用逐步回归法、红边参数法和光谱指数法分析叶片光谱反射率和叶绿素含量之间的关系,构建了柑橘叶片叶绿素光谱反射模型。结果表明,柑橘叶片叶绿素含量与反射光谱之间有较强的相关性,且两种方法所得模型预测值与实测值的相对误差都小于10%,说明模型具有良好的预测结果。两种方法中,选择波段的逐步回归法比光谱指数法的精度更高,但从建模参数的物理意义和逻辑性方面考虑,推荐光谱指数法建模,该模型可为远距离遥感监测果园营养状况和冻害情况提供参考。     

小麦品质指标与冠层光谱特征的相关性的初步研究

该文通过研究冬小麦体内生化组分之间的相互关系得出，开花期叶片全氮含量与类胡萝卜素与叶绿素a的比值之间存在极显著的负相关，决定系数为0.7245，通过研究光谱指数与叶片生化组分的关系得出开花期冬小麦叶片的类胡萝卜素与叶绿素a的比值与光谱结构不敏感植被指数(SIPI)之间存在极显著的正相关，决定系数达到0.7207，且研究了冠层生化组分与籽粒品质指标间的关系，得出开花期叶片全氮与籽粒蛋白质、湿面筋、干面筋和沉降值之间存在极显著正相关。小麦不同品质指标间存在相关性，其中蛋白质品质性状间的粗蛋白含量与湿面筋含量、     

基于光谱特征参数的温室番茄叶片叶绿素含量预测

为了快速、准确估测温室番茄叶片叶绿素含量,提升作物精细管理水平,利用光谱分析技术研究了温室番茄不同生长阶段叶绿素含量和响应光谱的相关性,在幼苗营养生长阶段叶片叶绿素含量呈增长趋势,到移植50天前后达到最大值,在此期间反射光谱的红边会向红外方向（长波）偏移,同时绿峰向蓝光（短波）方向偏移,绿峰幅值减小。从结果期开始叶绿素含量呈下降趋势,而红边、绿峰及绿峰幅值向相反方向变化。为了定量分析叶绿素含量和叶片反射光谱间的关系,从自定义的68个光谱特征参数中提取了7个能反映叶绿素含量变化的最优参量,并使用逐步回归、岭回归、主成分分量回归和偏最小二乘回归消除了最优参量的多重共线性,建立了叶绿素含量预测模型,其中岭回归模型精度最佳,均方根误差（RMSE）为0.406,决定系数(R2)为0.839。     

冬小麦冠层光谱红边特征分析

通过对不同N素营养水平冬小麦冠层光谱特性的田间试验研究,发现红边位移现象:在孕穗期前,红边随施N量增加向长波方向"红移";孕穗期后"红移"现象基本消失,继而发生"蓝移"。红边参数中红边斜率(dλred)与叶片N累积量(TN.D)、叶绿素含量(CHL.T)、叶绿素密度(CHL.D)的相关关系通过显著性检验,红边面积(∑dλ680~760)和叶片全N含量(N%)的相关关系通过显著性检验,红边位置(λred)、红边斜率、红边面积与叶面积指数有着密切关系,均通过极显著性检验,一些红边参数可作为小麦农学参数估测的简便方法。     

基于高光谱的叶片滞尘量估测模型

为探索建立叶片滞尘量高光谱估测模型,利用光谱仪和电子分析天平采集了北京市区杨树叶片高光谱数据和滞尘量数据,研究了叶片光谱特征与滞尘量间的关系,并建立了基于光谱参数的叶片滞尘量估测模型。研究结果表明:近红外波段(730~1 000 nm)光谱反射率与叶片滞尘量呈现明显的线性相关性,各波段相关系数均高于0.7,绿光区波段反射率对叶片滞尘的影响不敏感;三边参数中仅红边幅值、红边面积与叶片滞尘量达到显著相关;基于多元线性回归、主成分回归、偏最小二乘回归建立的模型均具有较强的预测能力,其中以偏最小二乘回归为模型构建方法,以749、644、514 nm波段的光谱反射率值,红边幅值,红边面积,924、1 010 nm波段组成的归一化指数,713、725 nm波段组成的差值指数,749、644 nm波段组成的归一化植被指数为自变量建立的模型估测精度最好,其建模和预测的决定系数分别达到0.734和0.731,预测均方根误差为0.311。该研究为促进高光谱技术在大气降尘监测中的应用提供参考。     

水稻成熟过程中高光谱与叶绿素、类胡萝卜素的变化规律研究

通过大田和室内试验，测定了2个品种、3个供氮水平处理的水稻冠层、主茎剑叶、完全展开倒三叶和穗在成熟过程中的不同时期的高光谱反射率及对应叶片和穗的叶绿素、类胡萝卜素含量。结果表明：不同供氮水平的水稻冠层和叶片光谱差异明显，其叶片的叶绿素、类胡萝卜素含量随供氮水平的提高而增大；冠层光谱反射率随发育期推移在可见光范围内逐渐增大，在近红外区域逐渐降低；穗光谱的红边位置象冠层、叶片光谱一样也存在“蓝移”现象；叶片叶绿素、类胡萝卜素含量和高光谱植被指数VI1(R₉₉₀/R_{553相似文献}   

水稻生物化学参数与高光谱遥感特征参数的相关分析

通过不同氮素营养水平的水稻田间试验，研究稻叶生物化学成份(叶绿素、类胡萝卜素、蛋白质、纤维素、淀粉含量) 与水稻冠层高光谱遥感特征参数之间的关系，结果表明，随着叶位的下移，叶片叶绿素含量与光谱特征变量之间的相关性明显减弱，绿峰反射率、红谷反射率、红边波长、蓝边面积和“三边”面积构成的植被指数等变量与上叶叶绿素含量、类胡萝卜素、纤维素、叶鞘淀粉含量之间有较好的相关性，而蛋白质含量与各种变量的相关系数均非常低。兰边面积、兰边面积和红边面积构成的植被植数与上叶叶绿素含量之间，红边面积 、绿反射峰与红反射峰构成的植被指数与叶鞘淀粉含量之间的相关系数都达到了0.01极显著检验水平，因此，可利用这些变量建立上叶叶绿素a、纤维素和叶鞘淀粉含量的估测模型。     

不同施氮水平下温室番茄叶片反射光谱特征分析

利用便携式光谱辐射仪测定了温室番茄叶片的光谱反射率,研究了不同施氮水平下特定光谱指数与叶片氮含量、光合速率及产量的关系。结果表明,温室番茄叶片的光谱反射率在可见光波段随供氮水平的升高而降低,在近红外波段随供氮水平的升高而增加。随施氮水平的提高,绿峰的蓝移和红边的红移现象明显,而红谷反射率与光合速率之间的关系可用二次方程拟合,相关系数达0.805。番茄叶片氮含量的敏感光谱波段为580~695 nm,740~900 nm,由695 nm、770 nm两个波段构建的高光谱指数(RVI、NDVI)与叶片氮含量的相关性显著。而基于原始光谱数据对番茄产量的估测也可在温室中得到很好的运用,其中光谱指数RV(I710,680)、VARI700和产量的拟合方程最优。     

谷子茎秆叶鞘叶片及其结合部位的拉伸力学性能

针对谷子机械收获作业过程中存在的秆叶易缠绕问题,该文以晋谷21、张杂10为对象,分别对谷子不同节间的茎秆、叶鞘、叶片和叶环各部位进行拉伸力学测试,并利用SAS统计软件对测试数据做分析,在此基础上分析了相关力学参数沿茎秆节间的变化规律。两个谷子品种的茎秆在上下节间处的弹性模量、抗拉力和抗拉强度均差异显著（P<0.05）。由茎秆表皮拉伸测试测得晋谷21的茎秆弹性模量为4.2～6.6 GPa,抗拉强度为67.65～130.13 MPa,抗拉力为344～1 600 N;张杂10的茎秆弹性模量为4.5～8.0 GPa,抗拉强度为73.22～136.50 MPa,抗拉力为167～567 N。两个谷子品种在不同节间位置、不同部位（叶鞘、叶片及叶环）的抗拉力和抗拉强度差异均极显著（P<0.01）。晋谷21的中上部节间叶鞘、叶片及叶环平均抗拉强度分别为13.30、10.13和4.18 MPa,平均抗拉力分别为122.16、41.23和25.80 N。张杂10的中上部节间叶鞘、叶片及叶环平均抗拉强度分别为13.30、11.77和4.24 MPa,平均抗拉力分别为104.30、59.48和22.87 N。测试结果表明,谷子茎秆、叶鞘、叶片和叶环部位中抗拉强度最弱位置在鞘叶相连接的叶环位置处。谷子机械收获时可选择在茎秆中部以上、穗部第2节间以下各节间的叶环位置处进行秆叶分离,施力大小25～30 N。研究结果可为谷子收获装置的设计与优化提供参数依据。     

The relationship of soil and leaf nutrients to rice leaf oranging

A symptom called leaf‐oranging, indicating a deficiency of many nutrients, occurs in paddy rice (Oryzasativa L.) when production expands into some upland soils. Rice (Gui Chou cv.) was grown in culture pots in a flooded, weathered, upland soil (Nacogdoches) and compared to rice growth in a flooded soil currently used for paddy rice production (Dacosta) in Texas to understand the soil and plant factors involved in leaf‐oranging. Fertilizer rates of 0, 10, and 100 mg N/kg as (NH₄)₂SO₄ were applied to each soil along with phosphorus (P) and potassium (K) fertilizer. The orange Leaf Index (OLI), a measure of leaf‐oranging, was determined weekly and increased to 60–70% for plants grown in the upland soil but its progression was delayed by higher N treatments. No leaf‐oranging was observed in the paddy soil. The soil evoking leaf‐oranging was low in silicon (Si) and high in iron (Fe). In addition, analysis of leaves from these plants showed 19–25% higher leaf ammonium‐nitrogen (NH₄‐N), 9–137% higher manganese (Mn) levels and lower total N:NH₄ concentration compared to normal rice leaves four weeks after transplanting. This inferred that leaf‐oranging probably was associated with some degree of NH₄‐N toxicity and antagonism with K. Leaf‐oranging was also associated with low calcium (Ca) assimilation or Ca uptake inhibition because of the heavy Fe‐oxide coating of the roots of the affected rice plants. In this experiment, leaf‐oranging was not associated with toxic levels of Fe or Mn.     

叶温测量仪的研制及其在叶片参数测量中的应用

为探索植物自身水分状态,研究叶气温差与叶片厚度变化,自行研制了叶温测量仪,同时利用YI-201020植物叶片参数测量仪,对辣椒和花生不同生长阶段的叶片温度和叶片厚度进行监测,结合环境温度,并对各个生长阶段的叶气温差和叶片厚度作相关性分析,结果表明:传感器线性度为1%,回程误差0.02V,灵敏度为0.04V/℃,分辨力为0.3℃,仪器在测量范围0～90℃下最大示值误差为0.27℃,得到仪器的扩展不确定度为0.41℃;叶气温差和叶片厚度在各个时期都呈显著的正相关,其中成长期显著性最为明显。研究结果对植物物理学研究有参考价值。     

Nitrogen nutrition,leaf resistance,and leaf photosynthetic rate of the rice plant

The evidence that indicates a close association between nitrogen nutrition and the Photosynthetic rate of single rice leaves (Table 1) shows that the photosynthetic rate is related to the nitrogen content on a dry weight basis or on a leaf area basis, Photosynthesis of single leaves can be analyzed in terms of a series of diffusion resistances, i.e., stomatal, mesophyll, and carboxylation (1, 3, 6). Nitrogen nutrition may affect either one of these or more than two at the same time. Nitrogen nutrition affects mainly the mesophyll resistance, and the stomatal resistance to a lesser extent, in cotton, beans, and maize (10) while it affects both the stomatal and mesophyll resistance in sugar beet (8).     

A comparison of the chemical composition of the corn leaf and the grain sorghum leaf

Abstract

Leaf samples were taken from corn and grain sorghum being grown in adjacent fields with the same soil type and with the same cultural practices insofar as possible. The samples were analyzed for N, P, K, Ca, Mg, Fe, Zn and Mn. Results show that the nutrient composition of the leaves of corn and grain sorghum were consistently different for most nutrients. The differences were sufficiently great and consistent to strongly suggest that critical nutrient levels need to be established for grain sorghum instead of using diagnostic criteria established for corn.     

基于典型叶片模板自动匹配的虫损叶面积测量

为了定量化评估农作物的虫害程度,提出了一种基于典型叶片模板自动匹配的叶片虫损面积测量新方法。先将叶片图像二值化并提取其外轮廓;再对提取的轮廓进行多边形近似,以多边形的顶点为端点将叶片外轮廓划分成若干子轮廓;然后采用形状上下文对完整叶片与虫损叶片之间的子轮廓进行自动配准,找出其间的相互映射关系;最后根据映射关系对虫损叶片进行重建,计算出虫损面积。对10类不同叶片的测量分析表明：该方法平均每叶片耗时0.962 s,最大相对误差为8.22%,平均相对误差为4.78%。其中,形状复杂度高的叶片平均相对误差为7.48%,复杂度中等的叶片为5.99%,复杂度低的叶片为1.84%。结果表明,该方法能准确而快速地测量虫损叶面积。     

Non-destructive estimation of sunflower leaf area and leaf area index under different water regime managements

Leaf area (LA) is a valuable parameter in many agronomic and plant physiological studies. Its measurement is time consuming and involves leaf destruction. Therefore, there is a tendency in using simple, fast, non-destructive, and electronic devices methods to estimate LA. The aim of this study was to estimate LA across different water regime treatments using a combination of leaf mass and leaf dimensions of sunflower (Helianthus annuus L.). For this purpose, different leaf sizes were collected from plants during the growing season on different time intervals. Experiment was conducted during 2012 summer time in Sari Agriculture Sciences and Natural Resources University, Iran. On field leaf dimension measurements were carried out, and leaves sketches were put on paper, scanned and then areas were measured using AutoCAD software. Multivariate linear and non-linear regression models were constructed between LA and other leaf components measured. All constructed models provided highly significant correlations (r = 0.90–0.99) between LA and different leaf components. The exponential model [LA = 0.619 [(L × W)^0.5]^2.019] provided the best estimation of sunflower LA (R² = 0.993). In conclusion, the simple and quick models developed in this study could predict the sunflower LA and leaf area index (LAI) with high precision.     

Ultraviolet leaf reflectance of common urban trees and the prediction of reflectance from leaf surface characteristics

The spectral reflectance and transmittance over the wavelength range of 250–700 nm were evaluated for leaves of 20 deciduous tree species and leaf sheaths of five isogenic wax variants of Sorghum bicolor differing in visible reflectance due to cuticular waxes. Using the sorghum sheath reflectance and cuticle surface characteristics as a model, it was concluded that tree leaf reflectance above 0.06 was likely due to the presence of variously-shaped fine epicuticular wax structures on the leaf surface. Increasing the density of sub-micron wax structures corresponded to an enhanced ultraviolet (UV) reflectance over the PAR reflectance of a given leaf surface—either S. bicolor sheath or tree leaf. Amorphous globular epicuticular wax structures did not appear to scatter UV as well as wax filaments or vertical plates in varying patterns even when the dimensions of the structures were similar. Further work is needed to clarify this relationship and the influence of cellular pigments on subsurface contributions to the reflectance.     

21000-2300nm波段的小麦冠层光谱特性与叶面积指数和叶片氮含量间的关系及其受叶片水分含量的影响

The effects of leaf water status in a wheat canopy on the accuracy of estimating leaf area index （LAI） and N were determined in this study using extracted spectral characteristics in the 2 000-2 300 nm region of the short wave infrared （SWI） band. A newly defined spectral index, relative adsorptive index in the 2 000-2 300 nm region （RAI2000-2300）, which can be calculated by RAI2000-2300 = （R2224 - R2054） （R2224 ＋ R2054）-1 with R being the reflectance at 2 224 or 2 054 nm, was utilized. This spectral index, RAI2000-2300, was significantly correlated （P 〈 0.01） with green LAI and leaf N concentration and proved to be potentially valuable for monitoring plant green LAI and leaf N at the field canopy scale. Moreover, plant LAI could be monitored more easily and more successfully than plant leaf N. The study also showed that leaf water had a strong masking effect on the 2 000-2 300 nm spectral characteristics and both the coefficient between RAI2000-2300 and green LAI and that between RAI2000-2300 and leaf N content decreased as leaf water content increased.