Characterization of wheat-Thinopyrum bessarabicum genetic stock for stripe rust and Karnal bunt resistance

Utilization of modern breeding techniques for developing high yielding and uniform plant types ultimately narrowing the genetic makeup of most crops. Narrowed genetic makeup of these crops has made them vulnerable towards disease and insect epidemics. For sustainable crop production, genetic variability of these crops must be broadened against various biotic and abiotic stresses. One of the ways to widen genetic configuration of these crops is to identify novel additional sources of durable resistance. In this regard crops wild relatives are providing valuable sources of allelic diversity towards various biotic, abiotic stress tolerance and quality components. For incorporating novel variability from wild relative’s wide hybridization technique has become a promising breeding method. For this purpose, wheat-Th. bessarabicum amphiploid, addition and translocation lines have been screened in field and screen house conditions to get novel sources of yellow rust and Karnal bunt resistant. Stripe rust screening under field conditions has revealed addition lines 4JJ and 6JJ as resistant to moderately resistant while addition lines 3JJ, 5JJ, 7JJ and translocation lines Tr-3, Tr-6 as moderately resistant wheat-Thinopyrum-bessarabicum genetic stock. Karnal bunt screening depicted addition lines 5JJ and 4JJ as highly resistant genetic stock. These genetic stocks may be used to introgression novel stripe rust and Karnal bunt resistance from the tertiary gene pool into susceptible wheat backgrounds.

Combining Random Forest and XGBoost Methods in Detecting Early and Mid-Term Winter Wheat Stripe Rust Using Canopy Level Hyperspectral Measurements

Appropriate modeling methods and feature selection algorithms must be selected to improve the accuracy of early and mid-term remote sensing detection of wheat stripe rust. In the current study, we explored the effectiveness of the random forest (RF) algorithm combined with the extreme gradient boosting (XGboost) method for early and mid-term wheat stripe rust detection based on the vegetation indices extracted from canopy level hyperspectral measurements. Initially, 21 vegetation indices that were related to the early and mid-term winter wheat stripe rust were calculated on the basis of canopy level hyperspectral reflectance. Subsequently, the optimal vegetation index combination for disease detection was determined using correlation analysis (CA) combined with RF algorithms. Then, the disease severity detection model of early and mid-term winter wheat stripe rust was constructed using XGBoost method based on the optimal vegetation index combination. For the evaluation and comparison of the initial results, three commonly used classification methods, namely, RF, backpropagation neural network (BPNN), and support vector machine (SVM), were utilized. The vegetation index combinations determined by the single CA algorithm were also used to construct detection models. Compared with the detection models based on the vegetation index combination obtained using the single CA algorithm, the overall accuracy of the four detection models based on the optimal vegetation index combination based on CA combined with RF algorithms increased by 16.1% (XGBoost), 9.7% (RF), 8.1% (SVM), and 8.1% (BPNN). Among the eight models, the XGBoost detection model based on the optimal vegetation index combination using CA combined with RF algorithms, CA-RF-XGBoost, achieved the highest overall accuracy of 87.1% and the highest kappa coefficient of 0.798. Our results indicate that the RF combined with XGBoost can improve the detection accuracy of early and mid-term winter wheat stripe rust effectively at canopy scale.

A NAC Transcription Factor TuNAC69 Contributes to ANK-NLR-WRKY NLR-Mediated Stripe Rust Resistance in the Diploid Wheat Triticum urartu

Stripe rust is one of the most devastating diseases in wheat. Nucleotide-binding site (NBS) and leucine-rich repeat (LRR) domain receptors (NLRs) recognize pathogenic effectors and trigger plant immunity. We previously identified a unique NLR protein YrU1 in the diploid wheat Triticum urartu, which contains an N-terminal ANK domain and a C-terminal WRKY domain and confers disease resistance to stripe rust fungus Puccinia striiformis f. sp. Tritici (Pst). However, how YrU1 functions in disease resistance is not clear. In this study, through the RNA-seq analysis, we found that the expression of a NAC member TuNAC69 was significantly up-regulated after inoculation with Pst in the presence of YrU1. TuNAC69 was mainly localized in the nucleus and showed transcriptional activation in yeast. Knockdown TuNAC69 in diploid wheat Triticum urartu PI428309 that contains YrU1 by virus-induced gene silencing reduced the resistance to stripe rust. In addition, overexpression of TuNAC69 in Arabidopsis enhanced the resistance to powdery mildew Golovinomyces cichoracearum. In summary, our study indicates that TuNAC69 participates in the immune response mediated by NLR protein YrU1, and likely plays an important role in disease resistance to other pathogens.

Development and characterization of novel wheat-rye 1RS•1BL translocation lines with high resistance to Puccinia striiformis f. sp. tritici

Wheat-rye 1RS•1BL translocations from Petkus rye have contributed substantially to wheat production worldwide with their great disease resistance and yield traits. However, the resistance genes on the 1RS chromosomes have completely lost their resistance to newly emerged pathogens. Rye could widen the variation of 1RS as a naturally cross-pollinated related species of wheat. In this study, we developed three new 1RS•1BL translocation lines by crossing rye inbred line BL1, selected from Chinese landrace rye Baili, with wheat cultivar Mianyang11. These three new translocation lines exhibited high resistance to the most virulent and frequently occurring stripe rust pathotypes and showed high resistance in the field where stripe rust outbreaks have been most severe in China. One new gene for stripe rust resistance, located on 1RS of the new translocation lines, is tentatively named YrRt1054. YrRt1054 confers resistance to Puccinia striiformis f. sp. tritici pathotypes that are virulent toward Yr9 and YrCn17. This new resistance gene, YrRt1054, is available for wheat improvement programs. The present study indicated that rye cultivars may carry additional untapped variation as potential sources of resistance.

Protective role of foliar application of green-synthesized silver nanoparticles against wheat stripe rust disease caused by Puccinia striiformis

Green-synthesized nanoparticles have a tremendous antimicrobial potential to be used as an alternative to hazardous fungicides. In this study, the green synthesis of silver nanoparticles (AgNPs) was performed by using Moringa oleifera leaf extract as a reducing and stabilizing agent. The synthesized AgNPs were subjected to different characterization techniques. UV-visible spectroscopy confirmed the surface plasmon resonance band in the range of 400–450 nm, and zeta analysis revealed that the synthesized AgNPs ranged 4–30 nm in size. Scanning electron microscopy depicted tiny fused rectangular segments and the crystalline nature of the synthesized AgNPs was confirmed using X-ray diffraction. Energy dispersive X-ray (EDX) detector confirmed the presence of metallic silver ions. Fourier-transform infrared analysis revealed the presence of phenols as main reducing agents in the plant extract. Foliar application of different concentrations (25, 50, 75, and 100 ppm) of AgNPs was applied on wheat plants inoculated with Puccinia striiformis to assess the disease incidence against stripe rust disease. AgNPs at a conc. of 75 ppm were found to be more effective against wheat stripe rust disease. Furthermore, the application of AgNPs enhanced morpho-physiological attributes and reduced nonenzymatic compounds and antioxidant enzymes in wheat. The present study highlights the potential role of the green-synthesized AgNPs as a biological control of yellow rust disease.

Bacterial Coated Fertilizer Induced Resistance Against Wheat Stripe Rust

Wheat is the second largest consumed cereal by humans after Rice and its high yield and production is very critical for ever increasing global population. The wheat crop is grown all over Pakistan and threatened by several limiting factors. Stripe rust, caused by Puccinia striiformis, is the most destructive wheat pathogen and can reduce yield up to 70% in Pakistan. The present study aimed at exploring the role of Zabardast urea, a bacterial coated urea with zinc, in inducing resistance against wheat stripe rust. The study involved the collection and maintenance of stripe rust inoculum on Morroco cultivar which later used to inoculate seedlings of Akbar-2019 and Galaxy-2019 resistant and susceptible varieties with three different fertilizer levels viz. specialty fertilizer zabardast urea, plain urea with zinc and plain urea. The results demonstrated the positive role of bacterial coated urea with zinc and reduced the disease severity by 10% and 5% in susceptible and resistant cultivars, respectively, leaving resistant variety asymptomatic. The plain urea with zinc also decreased disease severity in susceptible variety Galaxy-2013 by 6% in comparison with plain urea treatment underlying the role of zinc in combating stripe rust. The study underlines the importance of specialty fertilizers in inducing resistance against stripe rust in wheat and needs further experimentation exploring the mechanisms involved in disease resistance under field conditions.

Quantitative Trait Loci Mapping of Adult Plant and Seedling Resistance to Stripe Rust (Puccinia striiformis Westend.) in a Multiparent Advanced Generation Intercross Wheat Population

Stripe rust caused by the biotrophic fungus Puccinia striiformis Westend. is one of the most important diseases of wheat worldwide, causing high yield and quality losses. Growing resistant cultivars is the most efficient way to control stripe rust, both economically and ecologically. Known resistance genes are already present in numerous cultivars worldwide. However, their effectiveness is limited to certain races within a rust population and the emergence of stripe rust races being virulent against common resistance genes forces the demand for new sources of resistance. Multiparent advanced generation intercross (MAGIC) populations have proven to be a powerful tool to carry out genetic studies on economically important traits. In this study, interval mapping was performed to map quantitative trait loci (QTL) for stripe rust resistance in the Bavarian MAGIC wheat population, comprising 394 F6 : 8 recombinant inbred lines (RILs). Phenotypic evaluation of the RILs was carried out for adult plant resistance in field trials at three locations across three years and for seedling resistance in a growth chamber. In total, 21 QTL for stripe rust resistance corresponding to 13 distinct chromosomal regions were detected, of which two may represent putatively new QTL located on wheat chromosomes 3D and 7D.