条锈病对不同抗性小麦品种的为害损失率和防治阈值研究

为研究条锈病对不同抗性水平小麦品种的为害损失,选取了对条锈病感抗程度不同、湖北省小麦生产中主推的5个品种（兰考198,高感;扶麦368,中感;华麦1168,中感;襄麦46,中抗;鄂麦DH16,高抗）为试验材料,在田间分区种植,人工接种条锈菌,喷施不同剂量氟环唑以形成不同的发病梯度,研究了5个品种在不同发病程度下的损失率,分析了品种抗性与植保贡献率的关系,并通过二次多项式回归分析,建立了不同抗性品种的防治阈值。结果表明,不同品种的受害损失率与病情发生程度均呈显著正相关;植保贡献率与品种抗性相关,品种抗病性越弱,植保贡献率越高;兰考198、扶麦368、华麦1168、襄麦46和鄂麦DH16的防治阈值分别为抽穗扬花期病指5.443、4.819、3.994、3.376和5.150。研究结果为利用品种抗病性防控小麦条锈病提供了理论依据。     

稻曲病损失率测定初报

通州、如皋两市的田间调查和室内考种结果表明,稻曲病对水稻的为害主要表现为:增加单穗病粒率,降低结实率,同时对病粒附近健粒,尤其是对靠近主轴的稻粒的千粒重有影响。通径分析结果显示,其为害损失率,主要决定于病粒率,其次是结实率。     

不同小麦品种对条锈病的抗性比较

利用抗病品种防治小麦条锈病是一项十分经济有效的措施,为了寻找既抗病又丰产的小麦品种,2007年度我们在九集镇马家洲村一组开展了不同小麦品种抗条锈病效果比较试验,取得了一定效果,现报告如下:1材料与方法1.1试验处理A:郑麦9023;B:鄂麦18;C:西农88;D:绵农6号;E:豫麦49;F:扬辐麦2号。共6个处理,3次重复,小区面积200m2,随机区组排列。1.2试验地情况试验地肥力中等,沙壤土,上茬作物为水稻。试验区域沿河、平坦,属条锈病早发区、常发区和重发区。1.3施肥情况每667m2用碳铵50kg、过磷酸钙40kg、氯化钾7.5kg作底肥,分蘖期每667m2追尿素2.5kg,…     

不同小麦品种对条锈病抗病性比较

小麦条锈病属气传病害,如果防治不力,减产至少在20%～30%以上,严重田块甚至颗粒无收.小麦条锈病是毕节市小麦生产上的主要病害之一,近年来由于多数品种种植时间长,品种抗性退化,小麦条锈病发生危害较重.为了筛选小麦条锈病抗性品种,特进行小麦条锈病品种抗性比较试验.     

小麦条锈病与麦蚜田间复合种群的观察初报

小麦一生可以遭受多种有害生物(病、虫、草害等)的危害,不同有害生物对小麦生长发育的影响可能存在着各种相互关系。对这种相互关系的探讨,既是认识麦田有害生物系统的前提,也是制定综合治理方案的理论依据。     

小麦条锈病简易预报模式

存在大面积感病品种的条件下,小麦条锈病菌是否当地越冬决定春季显病迟早。发生程度受4月中旬-6月上旬气象因素的影响,5月中至下旬降雨量是影响条锈病发生程度的主要因子,其分级相关系数r=0.9254^**。本文选取条锈病菌越冬情况、4月中旬-5月上旬降雨量、5月中-下旬降雨量、6月上旬雨温系数4个因子,按条锈病发生发展的渐进规律,制定了简易预报模式,预报效果理想。     

小麦病虫害自然损失率估计试验结果初报

近几年来由于受到品种、气候及田间栽培管理等因素影响,湖北省小麦病虫发生程度呈加重趋势,特别是小麦条锈病、赤霉病、白粉病等重大病害暴发频率高,为害损失重,对小麦安全生产构成了严重危胁.     

稻曲病危害单季稻损失率测定

稻曲病Ustilaginoidea virens(Cooke)TakahashiJ是恩施州一季中稻的主要穗期病害,常年发生面积5·33万hm2左右。病菌以子囊孢子和分生孢子侵染花器及幼颖;水稻抽穗扬花期适逢降雨,感病严重。病穗上的孢子座成熟后呈墨绿色,龟裂后飞溅,严重影响稻谷品质和产量。为测定该病对产量     

小麦条锈病病叶的RAPD分析初探

小麦条锈病菌(Puccinia striiformis f.sp.tritici)生理小种划分的依据是对品种苗期的致病性,其致病性必须通过寄主植物方能表现出来,病叶就是寄主—病原物相互作用的结合体。有关条锈病菌的人工培养尚无报道。秆锈病菌和叶锈病菌的人工培养研究表明,专性寄生锈菌在人工培养过程中的变异很大,其在遗传、进化和分类研究中的应用前景尚难以作出肯定的评价。如果以相应病叶作为小种分析的材料,将有助于尚不能人工培养的     

小麦品种对小麦条锈病抗病性试验评价

2006～2007年对13个小麦品种在自然发病情况下进行抗条锈病试验,结果表明,对小麦条锈病表现为抗病的品种有淮麦17、96.23粉质、云杂3号、繁19、宜麦1号,其中96-23粉质、宜麦1号的产量较高,繁19、淮麦17的产量居中;对小麦条锈病表现为耐病的品种有川麦107、楚麦3号,且产量较高.绵阳19、白粒5号对小麦条锈病高度摩病.     

Models for predicting potential yield loss of wheat caused by stripe rust in the U.S. Pacific Northwest

Climatic variation in the U.S. Pacific Northwest (PNW) affects epidemics of wheat stripe rust caused by Puccinia striiformis f. sp. tritici. Previous models only estimated disease severity at the flowering stage, which may not predict the actual yield loss. To identify weather factors correlated to stripe rust epidemics and develop models for predicting potential yield loss, correlation and regression analyses were conducted using weather parameters and historical yield loss data from 1993 to 2007 for winter wheat and 1995 to 2007 for spring wheat. Among 1,376 weather variables, 54 were correlated to yield loss of winter wheat and 18 to yield loss of spring wheat. Among the seasons, winter temperature variables were more highly correlated to wheat yield loss than the other seasons. The sum of daily temperatures and accumulated negative degree days of February were more highly correlated to winter wheat yield loss than the other monthly winter variables. In addition, the number of winter rainfall days was found correlated with yield loss. Six yield loss models were selected for each of winter and spring wheats based on their better correlation coefficients, time of weather data availability during the crop season, and better performance in validation tests. Compared with previous models, the new system of using a series of the selected models has advantages that should make it more suitable for forecasting and managing stripe rust in the major wheat growing areas in the U.S. PNW, where the weather conditions have become more favorable to stripe rust.     

水稻条纹叶枯病产量损失与防治指标研究初报

通过对条纹叶枯病不同病情与产量损失关系的研究,初步探明了水稻条纹叶枯病对产量的影响,病株率(x)与产量损失率(y)之间的关系为正相关,回归方程为y=1.06 0.84x(R=0.9278)。据此提出水稻条纹叶枯病的防治指标为病株率3%。     

Simulation modelling of yield losses caused by wheat stem rust

Stem rust, or black rust, of wheat, caused by Puccinia graminis f. sp. tritici, has recently re-emerged in several parts of the world, with epidemics occurring in eastern Africa, as well as northern and southern Europe. Damage mechanisms from disease dynamically affect the physiology of the crop as it grows and develops, and as the epidemic progresses, leading to yield losses in the stem rust-diseased wheat stand. Process-based agrophysiological models that include disease-induced damage mechanisms can help to better understand the physiological processes leading to yield losses, and to inform strategic decisions such as breeding strategies. Such models have not been developed for wheat stem rust so far. Two damage mechanisms for stem rust, light stealing and assimilate diversion, were incorporated in the agrophysiological simulation model WHEATPEST. The model, tested from experimental field data retrieved from the literature, provides a satisfactory representation of the system, although consistently underestimates relative yield losses by about 6.9%, resulting in relative yield losses between 17% and 56%. Analyses highlight the importance of the diversion of assimilates toward the pathogen in the magnitude of yield loss. Considering only the reduction of green leaf area would underestimate damage from stem rust by at least threefold. The analysis also shows the importance of the dynamic interplay between disease and crop growth, especially the dynamics of leaf area, on yield loss. Directions to consider additional damage mechanisms are proposed, and perspectives for future research, especially in relation to plant breeding strategies under climate change, are offered.     

Hyperspectral measurements of severity of stripe rust on individual wheat leaves

The objective of this study was to assess the effect of severity of stripe rust (Puccinia striiformis) on the hyperspectral reflectance of wheat. A total of 110 leaf samples with a range of disease severity were collected at the heading stage (Stage ?, 29 April) and grain filling stage (Stage II, 21 May). The spectra of the adaxial and abaxial surfaces of the leaf samples were taken using an ASD Leaf Clip, and the spectral characteristics were analysed. The photochemical reflectance index (PRI) was used to build two linear regression functions from the two growth stages using 70 leaves, and the remaining 40 leaves were used to validate their effectiveness. The results indicated that P. striiformis caused changes in foliar water and chlorophyll, and those changes made it feasible to assess disease severity using in situ hyperspectral measurements. In general, the reflectance values from the adaxial surfaces of the leaf samples were smaller than the abaxial surfaces. In comparison to Stage ?, the spectral contrast of four different disease severities was greater at Stage II. By comparing the regression functions, the coefficient of determination using the set of leaves for validation for Stage ? (R ²?=?0.74) was smaller than that for Stage II (R ²?=?0.83). However, the coefficient of determination for validation for Stage ? (R ²?=?0.91) was slightly larger than that of Stage II (R ²?=?0.90). The results suggest that the ASD Leaf Clip is an ideal tool to collect in situ hyperspectral measurements of wheat leaves showing symptoms of stripe rust, and Stage II is more appropriate to assess severity compared to Stage ?.     

小麦条锈病流行小种对小麦新品系产量的影响

研究了小麦条锈病流行小种条中30、31、32对不同小麦品种(系)的影响.结果表明:目前小麦条锈病流行小种因品种(系)不同可平均减产1 206kg/hm2,减幅15.1%,最大减产3076.50kg/hm2,减幅45.9%;千粒重平均下降5.52g,降幅14%,最大下降14.0g,降幅40%;穗粒数的差异较小,平均下降0.01粒,降幅0.13%.相关分析表明,条锈病的反应型和严重度是影响小麦产量和千粒重的主要因素,相关系数均达极显著水平;普遍率也具有一定的影响,但未达到显著水平.根据减产程度将材料分为三种类型,即按接种与药剂防治的差异分为极显著、显著和不显著.我们认为:小麦条锈病对产量影响较大,生产中应注意利用接种与药剂防治差异不显著的抗锈材料;在缺乏抗锈材料的地区,如果材料不抗条锈病,但产量等其他性状突出,则可以考虑采用药剂防治.     

陇东小麦条锈菌越夏菌量测定及在秋季病情测报中的应用

依据陇东越夏菌量的流行结构,采用菌量指示田及生物捕捉测定侵染源菌量,用人工接菌和自然发病的方法测定越夏海拔下限,以确定菌原有效传播范围。此结果用于陇东条锈病秋季病情测报,其病情预报与实际流行程度相符。     

小麦抗病遗传多样性对条锈病的调控效应

选用小麦抗条锈病近等基因系的5个品种,进行不同混播处理,研究了混播群体中存在各不同抗病基因时对小麦条锈病的控制效果。试验结果表明,两个单基因品种混播多不能显著降低条锈病的发生,而3个以上单基因品种混播多可显著降低条锈病的发生,而且4~5个品种混播的REM值也说明多个品种的混播可减少条锈病的发生。但是,防效并非完全与混播基因数目有关,而与基因的类型也有关。不同抗病基因对条锈菌生理小种的选择存在差异,小麦群体中所含的丰富抗病基因可减缓优势小种的出现。千粒重数据显示,品种混播的千粒重高于单个品种。     

Genetic analysis and molecular mapping of wheat genes conferring resistance to the wheat stripe rust and barley stripe rust pathogens

ABSTRACT Stripe rust is one of the most important diseases of wheat and barley worldwide. On wheat it is caused by Puccinia striiformis f. sp. tritici and on barley by P. striiformis f. sp. hordei Most wheat genotypes are resistant to P. striiformis f. sp. hordei and most barley genotypes are resistant to P. striiformis f. sp. tritici. To determine the genetics of resistance in wheat to P. striiformis f. sp. hordei, crosses were made between wheat genotypes Lemhi (resistant to P. striiformis f. sp. hordei) and PI 478214 (susceptible to P. striiformis f. sp. hordei). The greenhouse seedling test of 150 F(2) progeny from the Lemhi x PI 478214 cross, inoculated with race PSH-14 of P. striiformis f. sp. hordei, indicated that Lemhi has a dominant resistance gene. The single dominant gene was confirmed by testing seedlings of the F(1), BC(1) to the two parents, and 150 F(3) lines from the F(2) plants with the same race. The tests of the F(1), BC(1), and F(3) progeny with race PSH-48 of P. striiformis f. sp. hordei and PST-21 of P. striiformis f. sp. tritici also showed a dominant gene for resistance to these races. Cosegregation analyses of the F(3) data from the tests with the two races of P. striiformis f. sp. hordei and one race of P. striiformis f. sp. tritici suggested that the same gene conferred the resistance to both races of P. striiformis f. sp. hordei, and this gene was different but closely linked to Yr21, a previously reported gene in Lemhi conferring resistance to race PST-21 of P. striiformis f. sp. tritici. A linkage group consisting of 11 resistance gene analog polymorphism (RGAP) markers was established for the genes. The gene was confirmed to be on chromosome 1B by amplification of a set of nullitetrasomic Chinese Spring lines with an RGAP marker linked in repulsion with the resistance allele. The genetic information obtained from this study is useful in understanding interactions between inappropriate hosts and pathogens. The gene identified in Lemhi for resistance to P. striiformis f. sp. hordei should provide resistance to barley stripe rust when introgressed into barley cultivars.     

杀菌剂Fulicur与Caramba防治小麦条锈病的研究

Fulicur与Caramba对小麦条锈病具有优异的保护和治疗作用 ,用药量省 ,持效期长。温室试验结果表明 ,使用Fulicur 1.15mL/L、Caramba 1.75mL/L对小麦叶片具有很好的保护作用 ,对已发病的小麦叶片能够铲除叶片内的病菌 ,达到治愈的目的。田间试验结果表明 ,孕穗期一次用药可保证整个生育期不被侵染 ,发病后用药 ,防效可达 95%以上 ,效果略高于三唑酮的常规用量     

Primary disease gradients of wheat stripe rust in large field plots

ABSTRACT Field data on disease gradients are essential for understanding the spread of plant diseases. In particular, dispersal far from an inoculum source can drive the behavior of an expanding focal epidemic. In this study, primary disease gradients of wheat stripe rust, caused by the aerially dispersed fungal pathogen Puccinia striiformis, were measured in Madras and Hermiston, OR, in the spring of 2002 and 2003. Plots were 6.1 m wide by 128 to 171 m long, and inoculated with urediniospores in an area of 1.52 by 1.52 m. Gradients were measured as far as 79.2 m downwind and 12.2 m upwind of the focus. Four gradient models-the power law, the modified power law, the exponential model, and the Lambert's general model-were fit to the data. Five of eight gradients were better fit by the power law, modified power law, and Lambert model than by the exponential, revealing the non-exponentially bound nature of the gradient tails. The other three data sets, which comprised fewer data points, were fit equally well by all the models. By truncating the largest data sets (maximum distances 79.2, 48.8, and 30.5 m) to within 30.5, 18.3, and 6.1 m of the focus, it was shown how the relative suitability of dispersal models can be obscured when data are available only at a short distance from the focus. The truncated data sets were also used to examine the danger associated with extrapolating gradients to distances beyond available data. The power law and modified power law predicted dispersal at large distances well relative to the Lambert and exponential models, which consistently and sometimes severely underestimated dispersal at large distances.