Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves

Ten, widely-used vegetation indices (VIs), based on mathematical combinations of narrow-band optical reflectance measurements in the visible/near infrared wavelength range were evaluated for their ability to discriminate leaves of 1 month old wheat plants infected with yellow (stripe), leaf and stem rust. Narrow band indices representing changes in non-chlorophyll pigment concentration and the ratio of non-chlorophyll to chlorophyll pigments proved more reliable in discriminating rust infected leaves from healthy plant tissue. Yellow rust produced the strongest response in all the calculated indices when compared to healthy leaves. No single index was capable of discriminating all three rust species from each other. However the sequential application of the Anthocyanin Reflectance Index to separate healthy, yellow and mixed stem rust/leaf rust classes followed by the Transformed Chlorophyll Absorption and Reflectance Index to separate leaf and stem rust classes would provide for the required species discrimination under laboratory conditions and thus could form the basis of rust species discrimination in wheat under field conditions.     

Temporal and spatial changes of chlorophyll fluorescence as a basis for early and precise detection of leaf rust and powdery mildew infections in wheat leaves

Temporal and spatial changes in parameters of fast chlorophyll fluorescence kinetics (ground fluorescence, Fo and maximal fluorescence, Fm) and red/NIR reflectance were assessed with a Pulse-Amplitude-Modulated (PAM)-Imaging system on a daily basis over a period of 2 weeks following inoculation of wheat leaves with powdery mildew and leaf rust. The early detection of these infections by means of fluorescence imaging was possible 2–3 days before visual symptoms or significant changes in normalised-differenced-vegetation index (NDVI) became apparent. The initial infection of both fungi caused an increase in Fo and decrease in photochemical efficiency (Fv/Fm, Fv/Fo). The appearance and development of fungal pustules was accompanied by reduction in Fo and Fm. This resulted mainly from lower absorption of fluorescence exciting light by the leaf mesophyll due to the shielding effect of fungal mycelium, and to lesser extent from the chlorophyll breakdown underneath pustules. Among the evaluated fluorescence parameters, Fv/Fo displayed the most pronounced response to both kinds of infection. Mildew infection influenced chlorophyll fluorescence neither in the direct vicinity of mycelium nor in the apparently healthy leaf regions. Rust infected plants, in contrast, displayed significantly reduced photochemical efficiency Fv/Fm and Fv/Fo in chlorotic tissue around pustules. The same, but less pronounced tendency was found in the apparently healthy regions of rust infected leaves in the last days of the experiment. Dark adaptation of leaves proved to be necessary for accurate detection of both pathogen infections by means of fluorescence imaging. Additional experiments are needed to estimate the potential of this technique for remote sensing under field conditions.     

Spatially discriminating Russian wheat aphid induced plant stress from other wheat stressing factors

The Russian wheat aphid (RWA) Diuraphis noxia (Mordvilko) is a major pest of winter wheat and barley in the United States. RWA induces stress to the wheat crop by damaging plant foliage, lowering the greenness of plants, and affecting productivity. The utilization of multispectral remote sensing is effective at detecting plant stress in agricultural crops. Stress to wheat plants detected in fields can be caused by several factors that can vary spatially in their presence and intensity across a field. Stress can result from factors such as nutrient deficiency, drought, diseases, and pests that can occur individually or collectively. The present study investigated the potential of using spatial pattern metrics derived from multispectral images in combination with topographic and edaphic variables to identify a set of variables to differentiate the stress induced by RWA from other stress causing factors. A discriminant function analysis was applied to 15 discriminating variables. A set of 13 variables were retained to develop a model to differentiate the three types of stress. Overall, 97 percent of patches of stress used to validate the model were correctly categorized. Stressed patches caused by RWA were 98 percent correctly classified, patches caused by drought were 94 percent correctly classified, and patches caused by agronomic conditions were 99 correctly classified. It is possible to discriminate stress induced by RWA from other stress causing factors in multispectral data when spatial attributes of the stress causing factors are incorporated in the analysis.     

Determining the Influence of Water Deficiency on NPK Stress Discrimination in Maize using Spectral and Spatial Information

A necessary pre-requisite for variable rate application of plant nutrients to manage inputs in a site-specific manner is a technique to detect nutrient stresses in plants in real-time. Spectral reflectance of plant canopy may provide a non-destructive and rapid technique to detect nutrient and water stress in plants. In this study, we investigated the effect of water on nutrient stress discrimination (nitrogen, N; phosphorus, P; and potassium, K) based on the visible and near infrared reflectance of maize leaves grown under controlled greenhouse conditions. The analysis of the spectral data indicated that it was challenging to detect the nutrient deficiencies if the plant water status was unknown. However, if a priori knowledge of water stress existed, such as a well-watered situation, the ability to discriminate nutrient stress improved significantly. The analysis of whole plant behaviour (i.e., mean reflectance data from all leaves within a plant) versus leaves located at a specific location within a plant indicated that knowledge of spatial location of leaves within a plant helped to identify N and P stress and NPK as a multi-stress condition more clearly.     

Using hyperspectral remote sensing techniques to monitor nitrogen,phosphorus, sulphur and potassium in wheat (Triticum aestivum L.)

In situ, non-destructive and real time mineral nutrient stress monitoring is an important aspect of precision farming for rational use of fertilizers. Studies have demonstrated the ability of remote sensing to monitor nitrogen (N) in many crops, phosphorus (P) and potassium (K) in very few crops and none so far to monitor sulphur (S). Specially designed (1) fertility gradient experiment and (2) test crop experiments were used to check the possibility of mineral N–P–S–K stress detection using airborne hyperspectral remote sensing. Leaf and canopy hyperspectral reflectance data and nutrient status at booting stage of the wheat crop were recorded. N–P–S–K sensitive wavelengths were identified using linear correlation analysis. Eight traditional vegetation indices (VIs) and three proposed (one for P and two for S) were evaluated for plant N–P–S–K predictability. A proposed VI (P_1080_1460) predicted P content with high and significant accuracy (correlation coefficient (r) 0.42 and root means square error (RMSE) 0.180 g m^?2). Performance of the proposed S VI (S_660_1080) for S concentration and content retrieval was similar whereas prediction accuracies were higher than traditional VIs. Prediction accuracy of linear regressive models improved when biomass-based nutrient contents were considered rather than concentrations. Reflectance in the SWIR region was found to monitor N–P–S–K status in plants in combination with reflectance at either visible (VIS) or near infrared (NIR) region. Newly developed and validated spectral algorithms specific to N, P, S and K can further be used for monitoring in a wheat crop in order to undertake site-specific management.     

Spectral requirements on airborne hyperspectral remote sensing data for wheat disease detection

Remote sensing approaches are of increasing importance for agricultural applications, particularly for the support of selective agricultural measures that increase the productivity of crop stands. In contrast to multi-spectral image data, hyperspectral data has been shown to be highly suitable for the detection of crop growth anomalies, since they allow a detailed examination of stress-dependent changes in certain spectral ranges. However, the entire spectrum covered by hyperspectral data is probably not needed for discrimination between healthy and stressed plants. To define an optimal sensor-based system or a data product designed for crop stress detection, it is necessary to know which spectral wavelengths are significantly affected by stress factors and which spectral resolution is needed. In this study, a single airborne hyperspectral HyMap dataset was analyzed for its potential to detect plant stress symptoms in wheat stands induced by a pathogen infection. The Bhattacharyya distance (BD) with a forward feature search strategy was used to select relevant bands for the differentiation between healthy and fungal infected stands. Two classification algorithms, i.e. spectral angle mapper (SAM) and support vector machines (SVM) were used to classify the data covering an experimental field. Thus, the original dataset as well as datasets reduced to several band combinations as selected by the feature selection approach were classified. To analyze the influence of the spectral resolution on the detection accuracy, the original dataset was additionally stepwise spectrally resampled and a feature selection was carried out on each step. It is demonstrated that just a few phenomenon-specific spectral features are sufficient to detect wheat stands infected with powdery mildew. With original spectral resolution of HyMap, the highest classification accuracy could be obtained by using only 13 spectral bands with a Kappa coefficient of 0.59 in comparison to Kappa 0.57 using all spectral bands of the HyMap sensor. The results demonstrate that even a few hyperspectral bands as well as bands with lower spectral resolution still allow an adequate detection of fungal infections in wheat. By focusing on a few relevant bands, the detection accuracy could be enhanced and thus more reliable information could be extracted which may be helpful in agricultural practice.     

土壤逆境下植物根系分泌的有机酸及其对植物生态适应性的影响(英文)

以养分和水分胁迫为例,探讨土壤逆境下植物根系有机酸的分泌状况,以及有机酸对植物生态适应性的影响,从而为提高植物对多种逆境条件的适应能力提供理论依据。结果发现在养分和水分胁迫下,植物根系分泌的有机酸含量明显增加,这是较为普遍的主动适应性反应。有机酸能提高植物体内多种抗氧化酶的活性、渗透调节物质含量、叶绿素含量和光合作用水平,促进植物体内某些养分的吸收和运输,最终有利于植物的生长和生物量积累,减轻逆境条件对植物的毒害,提高植物的抗逆性和适应力。     

土壤干旱对不同生育期小麦叶片及种子氨基酸的影响

干旱胁挞下小麦体现人游离氨基酸含量明显增高,特别是极性氨基酸和胁迫较为敏感,拔节期土壤干旱对小麦叶片中游离氨基酸影响比开花期干旱大,复水后,随着小麦生长的恢复,叶片中游离氨其酸水平爱渐近对照,另外,拔节期和开花期土壤干旱均使小麦产量降低,胚同抗旱性品种间存在差异。     

棉长管蚜和棉蚜对受蚜虫取食胁迫棉花植株的选择行为

【目的】 研究棉长管蚜和棉蚜对其胁迫棉花的选择行为。【方法】 以无翅棉长管蚜和棉蚜成蚜为研究对象,测定棉长管蚜和棉蚜对种群密度和不同时间蚜虫胁迫的棉花行为反应。【结果】 不同种群密度棉长管蚜取食胁迫下,棉长管蚜对低密度取食胁迫的棉花与健康植株选择性上不存在差异性,而高密度则存在显著差异;棉蚜对高密度棉长管蚜取食胁迫选择性上存在显著差异。不同种群密度棉蚜取食胁迫下,棉长管蚜对被取食胁迫棉花与健康植株的选择性上不存在差异性,棉长管蚜能够适应棉蚜为害的棉花;而棉蚜对高密度棉长管蚜和棉蚜取食的棉花与健康植株选择性上存在显著差异,取食胁迫密度越高则选择差异性越大。随着棉长管蚜取食胁迫棉花时间的延长,棉长管蚜对短时间取食胁迫的棉花选择性上不存在差异性,而在取食胁迫3、5 d的棉花上存在显著差异;取食棉蚜仅在取食胁迫5 d的棉花上存在显著差异。棉蚜取食胁迫棉花不同时间后,不同受害程度棉花对后期棉长管蚜的寄主选择性不存在显著性差异。【结论】 棉花蚜虫取食偏向选择健康植株,易造成田间扩散,导致棉花受害。棉长管蚜能够适应棉蚜为害的棉花,且与棉蚜长期在田间共存。     

冬小麦条锈病生理变化及其遥感机理

对不同处理条件下的冬小麦条锈病进行 (病情指数 ) (DI)调查 ,并进行同步的光谱测定及田间取样 ,在室内测试了对病情指数有重要影响的几个参数因子 ,叶绿素含量及上叶含水量 ,并且将其与光谱反射率进行统计分析。研究结果表明 ,这些参数因子与反射率数据在 5 5 0～ 70 0和 70 0～ 1160nm范围内与DI有着相似的高相关性 ,说明条锈病害的DI变化可以通过叶绿素含量、上叶含水量参数直接的变化在光谱上得到响应 ,从而证明遥感监测DI是可行的 ,同时解释了遥感监测机理。选出与叶绿素含量、上叶含水量相关性最强的波段与DI作多元回归 ,建立的模型能很好地反演冬小麦条锈病的病情指数 ,正确率达到 75 %以上     

Genetic Analysis and Molecular Tagging a Novel Yellow Rust Resistance Gene Derived from Synthetic Hexaploid Wheat Germplasm M08

Yellow rust of wheat （caused by Puccinia striiformis Westend. f. sp. tritici Eriks.） has been periodically epidemic and severely damaged wheat production in China. The development of resistant cultivars could be an effective way to reduce yield losses of wheat caused by yellow rust. Rust reaction tests and genetic analysis indicated that M08, the synthetic hexaploid wheat derived from hybridization between Triticum durum （2n = 6X = 28; genome AABB） and Aegilops tauschii （2n = 2X = 14; genome DD）, showed resistance to current prevailing yellow rust races at seedling stage, which was controlled by a single dominant gene, designated as YrAm. Bulked segregant analysis was used to identify microsatellite markers linked to gene YrAm in an F2 population derived from cross M08 （resistant） × Jinan 17 （susceptible）. Three microsatellite marker loci Xgwm77, Xgwm285, and Xgwml31 located on chromosome 3B were mapped to the YrAm locus. Xgwml31 was the closest marker locus and showed a linkage distance of 7.8 cM to the resistance locus. Thus, it is assumed that YrAm for resistance to yellow rust may be derived from Triticum durum and is located on the long arm of chromosome 3B.     

水稻光温敏不育系对SRBSDV的抗性与内源激素的关系分析

利用人工接种SRBSDV(Southern rice black-streaked dwarf virus)和采用高效液相色谱技术(High Performance Liquid Chromatography,HPLC)测定内源激素的研究方法,对SRBSDV胁迫下高抗SRBSDV水稻光温敏不育系1S和高感SRBSDV水稻光温敏不育系10S两个不同抗性不育系水稻幼苗植株内源激素赤霉素(GA3)、生长素(IAA)、水杨酸(SA)和脱落酸(ABA)的动态变化进行了研究.结果表明:1)人工接种SRBSDV后,促进生长类的激素GA3、IAA在10S处理植株中含量平均值显著低于其对照植株,在第5和第6天感病症状开始出现时达到最低值;在1S处理植株中IAA含量平均值显著低于其对照植株,GA3含量平均值也低于对照植株,但未达到5％显著水平.2)抗御信号分子SA在处理植株中含量平均值显著高于对照植株,在感病症状开始出现时,其含量都达到最高值,但10S在最高值后开始较快下降,而1S的SA含量则保持显著高于对照植株的水平.3)与衰老、死亡有关的内源激素ABA在处理植株中含量高于对照植株,10S的ABA含量显著高于1S,与其对照植株差异显著;1S与其对照差异不显著.4)SRBSDV胁迫改变了植株体内IAA/ABA和GA3/ABA的平衡.结论:SRBSDV胁迫改变了不育系内源激素含量,但这种变化究竟是由病毒侵染直接造成的,还是病毒诱导了细胞损伤或影响了水稻光温敏不育系同化作用后所造成的,还有待深入研究.     

Characteristics of oxidative stress of plants with C3 and C4 photosynthesis during salinization

Reaction to oxidative stress caused by the addition of 300 mM NaCl to the nutrient solution is investigated in wheat plants with C3 photosynthesis and in red-colored amaranth plants with C4 photosynthesis. Amaranth plants, unlike wheat, are able to detoxify the superoxide radical with the participation of the enzyme superoxide dismutase and low-molecular-weight antioxidant amarathine, to effectively oppose the accumulation of active oxygen species, and to reduce the intensity of lipid peroxidation processes. A compensatory relation between amaranthine content and superoxide dismutase activity is found in amaranth leaves under salt stress. It is shown that amaranth plants are more resistant to the development of oxidative stress in leaves than wheat plants.     

盐胁迫对5种抗旱型小麦苗期生理特性的影响

[目的]探讨盐胁迫对不同抗旱型小麦品种苗期叶片抗氧化酶活性和相关生理指标的影响,为耐盐抗旱型小麦品种筛选和抗盐机制研究提供科学依据.[方法]选取5种抗旱型小麦品种(晋麦47、长4642、长6350、长6154和长6878),通过水培试验模拟不同盐胁迫处理(T1:Hoagland营养液+100 mmol/L NaCl;T2:1/2浓度Hoagland营养液+200 mmol/L NaCl;CK:1/2浓度Hoagland营养液)对小麦幼苗期的伤害效应,分别在胁迫第3 d和第7 d测定植株超氧化物歧化酶(SOD)和过氧化物酶(POD)活性及叶片丙二醛(MDA)和脯氨酸含量,分析不同抗旱型小麦对盐胁迫的响应差异.[结果]不同抗旱型小麦品种对不同盐胁迫浓度及胁迫时间的响应存在差异,其中晋麦47的叶片SOD活性在低盐浓度(T1处理)胁迫下被激活,随着盐浓度升高及胁迫时间延长,SOD活性又逐渐降低,叶片POD活性和MDA含量相对处于较低水平.方差分析结果表明,取样时间对小麦叶片SOD活性的影响极显著(P<0.01,下同),叶片POD活性在不同盐胁迫处理、不同品种、采样时间及盐胁迫处理和品种互作间均存在极显著差异;叶片MDA含量在不同盐胁迫处理、不同品种和采样时间间存在极显著差异;脯氨酸含量在不同盐胁迫处理、采样时间间存在极显著差异.相关性分析结果表明,叶片MDA含量与SOD活性无明显相关性,而与POD活性及叶片和根系脯氨酸含量均呈极显著正相关.[结论]叶片POD活性和MDA含量可作为小麦的耐盐性筛选指标.5个抗旱型小麦品种中,晋麦47在苗期具有相对较强的耐盐性,适合在盐碱地推广种植.     

云烟121健康与感黑胫病烟株根系及根际土壤丛枝菌根真菌差异研究

【目的】明确云烟121健康与患黑胫病烟株根系及根际土壤丛枝菌根真菌（Arbuscular mycorrhizal fungi,AMF）侵染特征的差异,为后续AMF在缓解烟株土传病害方面的应用打下理论基础。【方法】以云烟121健康和患黑胫病烟株根系及根际土壤为试验材料,采用显微形态观察法对2种烟株根系AMF侵染水平及根际...     

水分胁迫与植物氮代谢的关系 水分胁迫时氮素对小麦叶片氮代谢的影响

本研究结果表明,提高氮素营养水平可减缓缺水植物的氮代谢紊乱,增强其抗旱性。即在水分胁迫时,氮素营养水平较高的小麦叶片具有较高的硝酸还原酶活性和较低的蛋白酶、肽酶及核糖核酸酶活性,从而使蛋白质和RNA保持较高的水平,且游离氨基酸大量积累的土壤水分临界值也有所降低。并进一步证明,氮素对氮代谢的良好影响是因为改善了植物体内的水分状况。此外,对氮素增强植物抗旱性的机理和旱区增施氮肥的意义也进行了讨论。     

Identification of Wheat Canopy Structure Using Hyperspectral Data

Some winter wheat varieties were selected in this experiment. The results were as follows： 1） Leaf orientation value （LOV） and leaf area index （LAI） of wheat had different contributions to canopy spectral reflectance （CSR）. For example, LOV affected greatly canopy spectra more than LAI did in jointing stage, but LAI had a greater effect on CSR than LOV did after the ground was near to be covered completely. 2） Twenty treatments including different varieties and densities were arranged in this experiment, and the result of cluster analysis showed that all these treatments can be parted into four clusters according to LAI and LOV： varieties with erect leaves and low LAI （denoted as A）, varieties with erect leaves and high LAI （denoted as B）, varieties with horizontal leaves and low LAI （denoted as C）, varieties with horizontal leaves and high LAI （denoted as D）. Their CSR had difference in 400-700 nm and 700-1 150 nm at jointing stage, especially in different plant types. 3） There was obvious distribution difference among different clusters in scatter plot （X=△R890, Y=R890）, △R890 was the reflectance increment from jointing to booting stage. It was seen from the Y-axis direction that R890 of horizontal varieties were higher than the erect ones, and seen from the X-axis direction that the greater △R890 was, the lower LAI one within the same plant type varieties, which indicted that the combination of plant-type and the population magnitude can be initially identified by this method.     

Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

The aim of this study was to evaluate the accuracy of the spectro-optical, photochemical reflectance index (PRI) for quantifying the disease index (DI) of yellow rust (Biotroph Puccinia striiformis) in wheat (Triticum aestivum L.), and its applicability in the detection of the disease using hyperspectral imagery. Over two successive seasons, canopy reflectance spectra and disease index (DI) were measured five times during the growth of wheat plants (3 varieties) infected with varying amounts of yellow rust. Airborne hyperspectral images of the field site were also acquired in the second season. The PRI exhibited a significant, negative, linear, relationship with DI in the first season (r ² = 0.91, n = 64), which was insensitive to both variety and stage of crop development from Zadoks stage 3–9. Application of the PRI regression equation to measured spectral data in the second season yielded a coefficient of determination of r ² = 0.97 (n = 80). Application of the same PRI regression equation to airborne hyperspectral imagery in the second season also yielded a coefficient of determination of DI of r ² = 0.91 (n = 120). The results show clearly the potential of PRI for quantifying yellow rust levels in winter wheat, and as the basis for developing a proximal, or airborne/spaceborne imaging sensor of yellow rust in fields of winter wheat.     

溶磷细菌Enterobacteria sp EnHy-401对盐渍土壤中小麦生长的影响

盆栽试验结果表明,溶磷菌Enterobacteria sp.EnHy-401能较好地在盐渍土壤中定植,并对小麦的生长和矿质营养的吸收有促进作用。与对照相比,生长在经接菌处理盐渍土中的小麦,其地上部分和根系的干重增加了28.1%和14.6%,植株中对磷、钙、钾和镁的吸收率分别提高了34.4%、36.3%、31.5%、6.3%。该菌株所表现出来的对盐渍土壤中磷素有效性的提高、对小麦吸收K＋、Ca2＋、Mg2＋、P等矿质营养的促进作用以及小麦生长与矿质营养元素吸收之间高度的相关性表明,溶磷菌株Enterobacteria sp.EnHy-401对盐胁迫下小麦生长的促进效应主要是通过改善盐渍土中部分矿质营养的供应,增强植株对P、Ca,Mg、K等营养元素的选择性吸收而实现,该效应受到土壤盐分和营养基质的影响。     

小麦蓝矮病植原体延伸因子(EF-Tu) tuf基因序列的同源性分析

 【目的】利用分子生物学方法分析小麦蓝矮病植原体延伸因子tuf基因，从亚组水平上确定小麦蓝矮病植原体的分类地位。【方法】电镜观察自然发病的小麦蓝矮病病叶；用引物fTufu/rTufu对小麦蓝矮病植原体延伸因子tuf基因进行PCR扩增；核苷酸序列测定及分析。【结果】经电镜超微结构观察，在韧皮部观察到大量典型植原体。通过PCR扩增得到约850 bp的特异片段。感受态转化后，进行测序，结果表明小麦蓝矮病植原体tuf基因片段长842 bp，编码280个氨基酸。分析比较15种植原体延伸因子tuf基因的同源性，结果表明小麦蓝矮病植原体与三叶草绿变（KVF）亲缘关系最近，核苷酸同源性为99.9％，氨基酸同源性为100％。【结论】从亚组水平上确定了小麦蓝矮病植原体的分类地位，为研究小麦蓝矮病植原体的来源及致病分子机理提供理论依据。