Identification and Severity Determination of Wheat Stripe Rust and Wheat Leaf Rust Based on Hyperspectral Data Acquired Using a Black-Paper-Based Measuring Method

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R²) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies.     

Improving prediction of chickpea wilt severity using machine learning coupled with model combination techniques under field conditions

Accurate estimation of disease severity in the field is a key to minimize the yield losses in agriculture. Existing disease severity assessment methods have poor accuracy under field conditions. To overcome this limitation, this study used thermal and visible imaging with machine learning (ML) and model combination (MC) techniques to estimate plant disease severity under field conditions. Field experiments were conducted during 2017–18, 2018–19 and 2021–22 to obtain RGB and thermal images of chickpea cultivars with different levels of wilt resistance grown in wilt sick plots. ML models were constructed using four different datasets created using the wilt severity and image derived indices. ML models were also combined using MC techniques to assess the best predictor of the disease severity. Results indicated that the Cubist was the best ML model, while the KNN model was the poorest predictor of chickpea wilt severity under field conditions. MC techniques improved the prediction accuracy of wilt severity over individual ML models. Combining ML models using the least absolute deviation technique gave the best predictions of wilt severity. The results obtained in the present study showed the MC techniques coupled with ML models improved the prediction accuracies of plant disease severity under field conditions.     

QTL mapping of adult-plant resistance to stripe rust in a population derived from common wheat cultivars Naxos and Shanghai 3/Catbird

Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss., is a severe foliar disease of common wheat (Triticum aestivum L.) worldwide. Use of adult-plant resistance (APR) is an efficient approach to provide long-term protection of crops from the disease. The German spring wheat cultivar Naxos showed a high level of APR to stripe rust in the field. To identify the APR genes in this cultivar, a mapping population of 166 recombinant inbred lines (RILs) was developed from a cross between Naxos and Shanghai 3/Catbird (SHA3/CBRD), a moderately susceptible line developed by CIMMYT. The RILs were evaluated for maximum disease severity (MDS) in Sichuan and Gansu in the 2009-2010 and 2010-2011 cropping seasons. Composite interval mapping (CIM) identified four QTL, QYr.caas-1BL.1RS, QYr.caas-1DS, QYr.caas-5BL.3 and QYr.caas-7BL.1, conferring stable resistance to stripe rust across all environments, each explaining 1.9-27.6, 2.1-5.8, 2.5-7.8 and 3.7-9.1?% of the phenotypic variance, respectively. QYr.caas-1DS flanked by molecular markers XUgwm353-Xgdm33b was likely a new QTL for APR to stripe rust. Because the interval between flanking markers for each QTL was less than 6.5?cM, these QTL and their closely linked markers are potentially useful for improving resistance to stripe rust in wheat breeding.     

Genetics of adult plant stripe rust resistance in CSP44, a selection from Australian wheat

Wheat line CSP44, a selection from an Australian bread wheat cultivar Condor, has shown resistance to stripe rust in India since the last twenty years. Seedlings and adult plants of CSP44 showed susceptible infection types against stripe rust race 46S119 but displayed average terminal disease severity of 2.67 on adult plants against this race as compared to 70.33 of susceptible Indian cultivar, WL711. This suggests the presence of nonhypersensitive adult plant stripe rust resistance in the line CSP44. The evaluation of F₁, F₂ and F₃ generations and F₆ SSD families from the cross of CSP44 with susceptible wheat cultivar WL711 for stripe rust severity indicated that the resistance in CSP44 is based on two genes showing additive effect. One of these two genes isYr18 and the second gene is not yet described.     

Plant competition and disease in genetically diverse wheat populations

Summary The direct and indirect effects of plant genetic diversity on epidemics and the influence of disease on plant competition were investigated using the wheat (Triticum aestivum)/stripe rust (Puccinia striiformis) system. Replacement series consisting of a susceptible and a resistant wheat genotype or two wheat genotypes susceptible to different races of stripe rust were grown in the presence and absence of the pathogen. Stripe rust severity, number of seed heads, seed yield, and seed weight were determined separately for each wheat genotype in the mixtures and the pure stands. The frequency of susceptible genotypes in a mixture explained up to 67% of the variation in disease severity. However, competitive interactions among plant genotypes sometimes appeared to alter susceptibility and obscured the relationship. In pure stands of single genotypes, disease severity explained between 52 and 58% of the variation in seed yield. In mixtures, coefficients of determination were only 10 and 31%, suggesting a strong influence of plant-plant interactions on seed yield. These results suggest that host-parasite coevolutionary models need to account for the strong effect that specific plant genotype combinations may have on disease severity and plant reproduction.Paper No. 9818 of the journal series of the Oregon Agricultural Experiment Station     

四川盆地冬繁区小麦条锈病气象等级预测模型

四川盆地冬繁区是常年受小麦条锈病危害最重的地区之一.本研究利用盆地冬繁区代表站点1999—2016年的气象资料和条锈病资料,根据发病面积比将小麦锈病发生的气象条件划分为5个等级,采用多种分析方法确定了影响小麦条锈病发生的具有明确生物学意义的气象因子,并建立了小麦条锈病气象等级预测模型.结果表明: 四川盆地小麦条锈病的发生与平均(最高、最低)气温、降水量及距平百分率、相对湿度及距平百分率、平均风速、日照时数等多种气象因子显著相关,其中,平均气温和相对湿度距平百分率起主导作用.历史回代检验中,区(县)级样本准确率64%,市级样本准确率89%.对2017年盆地冬繁区小麦锈病发生气象等级进行预报,预测结果完全正确的样本占总样本量的62.8%;误差1个等级的样本占27.9%,误差2个或2个以上等级的样本仅占9.3%,预测效果较好,能达到从气象角度对小麦锈病发生进行预报的目的.     

Stripe rust analysis of D-genome synthetic wheats (2n = 6x = 42, AABBDD) and their molecular diversity

Stripe or yellow rust caused by Puccinia striiformis f. sp. tritici is a threat to many of the existing cultivars of Pakistan. Many attempts are being made to evolve new varieties resistant to stripe rust to reduce the losses caused by this disease. For this purpose, novel genes are needed to incorporate into the existing cultivars. These genes are found in the wild progenitors of wheat that are D-genome donors to wheat. As a result of extensive research, wheat synthetic hexaploids have been developed. These synthetics have resistances against biotic as well as abiotic stresses including the yellow rust. A group of such synthetics has been identified which seems resistant to this destructive disease. This group was tested under field conditions to identify resistance against stripe rust. The same population was analysed at molecular level to explore the genetic diversity for rust resistance. Genetic diversity among 34 selected synthetic hexaploid wheats was studied by random amplified polymorphic DNA (RAPD) analysis. A set of 12 RAPD primers was applied, and the level of polymorphism was found to be 46.67%. The coefficients in the range of 71–100% were detected by genetic similarity matrix based on Nei and Li's index. These coefficients were used for constructing a dendrogram using unweighted pair group of arithmetic means. Synthetic hexaploid line 34 was found to exhibit maximum genetic distances among the 34 selected lines. The same accession also showed excellent phenotypic characters with above average grain weight. These synthetic hexaploids carrying genetic potential for stripe rust resistance and morphological traits should be useful for improvement of existing wheat cultivars.     

Role of abiotic factors on the severity of stripe rust of wheat

During last decades, stripe rust has emerged as a major disease of wheat causing considerable yield loss in northern western plain and northern hill zones of India. Considering significant impact of the disease on wheat crop, field experiments were conducted during rabi seasons of 2013 and 2015 to evaluate the effect of different abiotic factors in different varieties (HD 2967, RSP 561, Agra Local and PBW 343) on the progress and spread of the disease as well as development of a predictive model to predict the disease initiation and spread in the field. Statistical analysis of data revealed that existing of low temperature (10–12 °C), high relative humidity (90%) along with intermittent rainfall was found conducive for disease onset. Thermic variables (atmospheric, canopy and soil temperature) along with age of crop in the selected varieties showed significant positive correlation with disease severity. Step-wise regression showed high R² of 0.919, 0.885, 0.967 and 0.956 for the predicative model of stripe rust in RSP 561, HD 2967, Agra Local and PBW 343, respectively.     

Stripe rust and leaf rust resistance QTL mapping,epistatic interactions,and co-localization with stem rust resistance loci in spring wheat evaluated over three continents

Key message

In wheat, advantageous gene-rich or pleiotropic regions for stripe, leaf, and stem rust and epistatic interactions between rust resistance loci should be accounted for in plant breeding strategies.

Abstract

Leaf rust (Puccinia triticina Eriks.) and stripe rust (Puccinia striiformis f. tritici Eriks) contribute to major production losses in many regions worldwide. The objectives of this research were to identify and study epistatic interactions of quantitative trait loci (QTL) for stripe and leaf rust resistance in a doubled haploid (DH) population derived from the cross of Canadian wheat cultivars, AC Cadillac and Carberry. The relationship of leaf and stripe rust resistance QTL that co-located with stem rust resistance QTL previously mapped in this population was also investigated. The Carberry/AC Cadillac population was genotyped with DArT^® and simple sequence repeat markers. The parents and population were phenotyped for stripe rust severity and infection response in field rust nurseries in Kenya (Njoro), Canada (Swift Current), and New Zealand (Lincoln); and for leaf rust severity and infection response in field nurseries in Canada (Swift Current) and New Zealand (Lincoln). AC Cadillac was a source of stripe rust resistance QTL on chromosomes 2A, 2B, 3A, 3B, 5B, and 7B; and Carberry was a source of resistance on chromosomes 2B, 4B, and 7A. AC Cadillac contributed QTL for resistance to leaf rust on chromosome 2A and Carberry contributed QTL on chromosomes 2B and 4B. Stripe rust resistance QTL co-localized with previously reported stem rust resistance QTL on 2B, 3B, and 7B, while leaf rust resistance QTL co-localized with 4B stem rust resistance QTL. Several epistatic interactions were identified both for stripe and leaf rust resistance QTL. We have identified useful combinations of genetic loci with main and epistatic effects. Multiple disease resistance regions identified on chromosomes 2A, 2B, 3B, 4B, 5B, and 7B are prime candidates for further investigation and validation of their broad resistance.     

Genetics of durable resistance to leaf rust and stripe rust of an Indian wheat cultivar HD2009

The Indian bread wheat cultivar HD2009 has maintained its partial resistance to leaf rust and stripe rust in India since its release in 1976. To examine the nature, number and mode of inheritance of its genes for partial leaf rust and stripe rust resistance, this cultivar was crossed with cultivar WL711, which is susceptible to leaf rust and stripe rust. The F1, F2, F3 and F5 generations from this cross were assessed separately for adult plant disease severity under artificial epidemic of race 77-5 of leaf rust and race 46S119 of stripe rust. Segregation for rust reaction in the F2, F3 and F5 generations indicated that resistance to each of these rust diseases is based on 2 genes, each with additive effects. Although the leaf rust resistance of HD2009 is similar in expression to that conferred by the gene Lr34, but unlike the wheats carrying this gene, cultivar HD2009 did not show leaf tip necrosis, a morphological marker believed to be tightly linked to the leaf rust resistance gene Lr34. Thus, the non-hypersensitive resistance of HD2009 was ascribed to genes other than Lr34.     

Atmospheric teleconnection patterns associated with wheat stripe rust disease in North China

 Previous work has shown that long-term (>40 years) time series of wheat stripe rust disease from North China contain a signal related to the Southern Oscillation Index (SOI). However, no cause-and-effect relationships or direct links between SOI and disease have been established. Because mid-latitude teleconnection patterns form important links between global atmospheric variations and regional weather anomalies, such as the Southern Oscillation, studies of such patterns could result in a better physical and biological interpretation for the SOI-disease association observed previously. We used cross-spectral analyses to determine if and on which time scales severity of stripe rust in five regions of North China between 1952 and 1990 was associated with fluctuations in four Northern Hemisphere teleconnection patterns. These included the Pacific/North American, the Western Atlantic, the Western Pacific, and the Eurasian patterns. The analysis showed consistent and significant (P≤0.10) coherence relationships between the Western Atlantic (WA) pattern and stripe rust severity at a periodicity of 3.00 years. The phase relationships showed that, at the 3.00-year periodicity, the WA series and the disease series were out of phase by about half a period in all five regions. This phase difference indicated that peaks in the WA series, which are associated with below-normal winter temperatures over much of China, coincided with troughs in the disease series (i.e. low disease severity), presumably because of the negative effect of low winter temperatures on survival of the stripe rust pathogen. The analysis further showed that the WA series and the SOI series were highly significantly (P≤0.01) coherent at a periodicity of 4.33 years, which could explain the association between SOI and stripe rust severity reported previously. Received: 12 February 1997 / Accepted: 18 May 1998     

QTL mapping of stripe,leaf and stem rust resistance genes in a Kariega × Avocet S doubled haploid wheat population

Adult plant resistance to stripe (yellow) rust in the wheat cultivar Kariega has previously been ascribed to a major quantitative trait locus (QTL) on each of chromosomes 2B and 7D, along with a number of minor QTL. We have extended both the size of the cv. Kariega × cv. Avocet S mapping population, and the marker coverage within it, by assembling a set of Diversity Array Technology (DArT) markers. This has allowed for the analysis of the genetic basis of the adult plant and seedling resistances to stripe, leaf and stem rust present in the two mapping population parents. The stripe rust reactions of the segregating material were assessed in both field (three scoring dates) and greenhouse experiments. The chromosome 2B QTL became more important than the Lr34/Yr18 complex on chromosome 7D as the plants aged. As the infection progressed, the two QTL explained an increasing proportion of the variance for percentage leaf area infected. The cv. Kariega allele at the minor chromosome 4A QTL had a consistent effect on the severity of stripe rust infection and the overall plant reaction at the earlier scoring dates, but lost importance as the disease progressed. Several rust resistances were detected using an improved greenhouse-based test.     

Resistance of wild wheat to stripe rust: Predictive method by ecology and allozyme genotypes

From 114 accessions of wild emmer wheat from 11 sites in Israel, known for their allozymic variation (Nevo & al. 1982), individual genotypes were tested for resistance to one isolate of stripe rust both in the seedling stage in a growth chamber and in the adult plant stage in the field. The results indicate that resistance to stripe rust in seedlings and adults are significantly correlated (r_s = 0.40, p < 0.001). Genetic polymorphisms of resistance to stripe rust vary geographically and are predictable by climatic, as well as allozymic markers. Three variable combinations of rainfall, evaporation, and temperature explain significantly 0.40–0.53 of the spatial variance in disease resistance to stripe rust, suggesting the operation of natural selection. Several allozyme genotypes are significantly associated with disease resistance. We conclude that natural populations of wild emmer wheat in Israel contain large amounts of disease resistance genes. These populations could be effectively screened and then utilized by the phytopathologist for identifying resistant genotypes and producing new resistant cultivars.Patterns of Resistance of Wild Wheat to Pathogens in Israel II.     

Quantitative trait loci for slow-rusting resistance in wheat to leaf rust and stripe rust identified with multi-environment analysis

Rust diseases are a major cause of yield loss in wheat worldwide, and are often controlled through the incorporation of resistance genes using conventional phenotypic selection methods. Slow-rusting resistance genes are expressed quantitatively and are typically small in genetic effect thereby requiring multiple genes to provide adequate protection against pathogens. These effects are valuable and are generally considered to confer durable resistance. Therefore an understanding of the chromosomal locations of such genes and their biological effects are important in order to ensure they are suitably deployed in elite germplasm. Attila is an important wheat grown throughout the world and is used as a slow-rusting donor in international spring wheat breeding programs. This study identified chromosomal regions associated with leaf rust and stripe rust resistances in a cross between Attila and a susceptible parent, Avocet-S, evaluated over 3 years in the field. Genotypic variation for both rusts was large and repeatable with line-mean heritabilities of 94% for leaf rust resistance and 87% for stripe rust. Three loci, including Lr46/Yr29 on chromosome 1BL, were shown to provide resistance to leaf rust whereas six loci with small effects conferred stripe rust resistance, with a seventh locus having an effect only by epistasis. Disease scoring over three different years enabled inferences to be made relating to stripe rust pathogen strains that predominated in different years.     

黄淮麦区小麦品种(系)中Yr26基因的SSR检测

选用与Yr26紧密连锁的SSR标记Xgwm11和Xgwm18结合田间抗性鉴定,对239份黄淮麦区小麦品种(系)进行检测,以明确Yr26基因在黄淮麦区小麦品种资源中的分布.结果表明:共有35份品种(系)含有与Yr26紧密连锁的SSR标记Xgwm18或Xgwm11的特征带,占检测样本的14.6%.在这35份材料中,31份田间抗性鉴定表现免疫至中抗,4份表现中感.分子标记检测与田间抗病性检测吻合度较好,该标记可以用于Yr26基因的分子标记辅助选择.综合分子标记和田间鉴定,31份小麦(系)含有Yr26基因,占102份抗病材料的30.39%.     

Mapping of quantitative adult plant field resistance to leaf rust and stripe rust in two European winter wheat populations reveals co-location of three QTL conferring resistance to both rust pathogens

Key message

We detected several, most likely novel QTL for adult plant resistance to rusts. Notably three QTL improved resistance to leaf rust and stripe rust simultaneously indicating broad spectrum resistance QTL.

Abstract

The rusts of wheat (Puccinia spp.) are destructive fungal wheat diseases. The deployment of resistant cultivars plays a central role in integrated rust disease management. Durability of resistance would be preferred, but is difficult to analyse. The Austrian winter wheat cultivar Capo was released in the 1989 and grown on a large acreage during more than two decades and maintained a good level of quantitative leaf rust and stripe rust resistance. Two bi-parental mapping populations: Capo × Arina and Capo × Furore were tested in multiple environments for severity of leaf rust and stripe rust at the adult plant stage in replicated field experiments. Quantitative trait loci associated with leaf rust and stripe rust severity were mapped using DArT and SSR markers. Five QTL were detected in multiple environments associated with resistance to leaf rust designated as QLr.ifa-2AL, QLr.ifa-2BL, QLr.ifa-2BS, QLr.ifa-3BS, and QLr.ifa-5BL, and five for resistance to stripe rust QYr.ifa-2AL, QYr.ifa-2BL, QYr.ifa-3AS, QYr.ifa-3BS, and QYr.ifa-5A. For all QTL apart from two (QYr.ifa-3AS, QLr.ifa-5BL) Capo contributed the resistance improving allele. The leaf rust and stripe rust resistance QTL on 2AL, 2BL and 3BS mapped to the same chromosome positions, indicating either closely linked genes or pleiotropic gene action. These three multiple disease resistance QTL (QLr.ifa-2AL/QYr.ifa-2AL, QLr.ifa.2BL/QYr.ifa-2BL, QLr.ifa-3BS/QYr.ifa.3BS) potentially contribute novel resistance sources for stripe rust and leaf rust. The long-lasting resistance of Capo apparently rests upon a combination of several genes. The described germplasm, QTL and markers are applicable for simultaneous resistance improvement against leaf rust and stripe rust.     

中国小麦条锈菌转主寄主小檗的鉴定

用萌发的小麦条锈菌冬孢子接种采自陕西省境内的陕西小檗、少齿小檗和长穗小檗,3种小檗均产生了性孢子器和锈孢子器。用人工接种小麦条锈菌冬孢子在陕西小檗上产生的锈孢子器接种小麦铭贤169产生了典型的条锈菌夏孢子堆症状。特异性PCR和DNA序列分析表明,人工接种产生于小檗上的锈孢子、接种锈孢子于小麦上产生的夏孢子堆与小麦条锈菌DNA的ITS区序列完全一致。更为重要的是,用采自田间受锈菌侵染的小檗叶片产生的锈孢子接种小麦铭贤169,经培养在小麦铭贤169叶片上产生了典型的条锈病症状。从而证实,在自然条件下,在中国,小檗不仅可作为小麦条锈菌的转主寄主,而且小麦条锈菌可在小檗上完成其有性繁殖过程。这一发现对进一步揭示我国小麦条锈菌高度的群体遗传多样性与毒性变异机理、完善小麦条锈病的防治策略具有十分重要的理论和实际意义。     

小麦持久抗条锈品种斯汤佩利的遗传机制研究

对持久抗条锈小麦品种斯汤佩利进行了抗条锈特点研究和抗性遗传分析.斯汤佩利反应型0～1型,普遍率、严重度和病情指数3个抗性组分及其平均日变化率都很低,与三类对照品种之间有极显著差异.与中抗-中感为特征的、抗性由多基因或由主效基因与多基因共同控制的一般持久抗病品种相比,属于典型特例.其抗条锈性由2对显性基因互补控制,干尖性状由1对显性基因控制,二者之间不连锁,因此,干尖不能作为斯汤佩利抗锈性的辅助选择标记.     

西科麦2028抗条锈性的遗传分析

西科麦2028是地理远缘小麦材料的杂交后代,具有突出的抗条锈病性能。为了解西科麦2028对小麦条锈病的抗性遗传规律,以西科麦2028和铭贤169的杂交群体为研究对象,采用我国目前小麦条锈菌流行小种CYR31、CYR32、CYR33、Su11-4对供试群体进行成株期接种,分析杂交后代的抗病性及分布情况。结果表明:西科麦2028对CYR31的抗病性由3对显性基因控制;对CYR32由2对显性和1对隐性基因控制;对CYR33由1对显性基因控制;对Su11-4由1对显性和1对隐性基因控制。     

小麦条锈菌分子生态学研究进展

小麦条锈病是危害最严重的小麦流行性病害之一,小麦条锈菌的生态学研究对制定合理的防治策略和抗锈育种具有重要意义.近十几年来,DNA分子标记技术被应用于小麦条锈菌的群体遗传学研究,推动了小麦条锈菌分子生态学研究的快速发展,为揭示小麦条锈菌的群体生态特性开辟了一个新的途径.本文系统介绍小麦条锈菌分子生态学研究的主要进展,并就我国当前研究的局限性和发展趋势进行了分析.