Loop-Mediated Isothermal Amplification for Detection of Plant Pathogens in Wheat (Triticum aestivum)

Viral Challenges in Wheat: Comprehensive Diagnosis and Innovative Management Approaches

Wheat (Triticum aestivum L.) is a staple crop cultivated globally, providing essential nutrition to billions. However, viral diseases pose a major challenge, causing yield losses of up to 80% and significant economic damage. More than 50 distinct viruses infect wheat, with key threats including wheat streak mosaic virus (WSMV), barley yellow dwarf viruses (BYDVs), high plains wheat mosaic virus (HPWMoV), soilborne wheat mosaic virus (SBWMV), and wheat yellow mosaic virus (WYMV). These viruses are primarily transmitted by vectors such as wheat curl mites (Aceria tosichella), aphids, and soilborne fungi like Polymyxa graminis. Diagnosing wheat viral infections is challenging due to overlapping symptoms with other plant stresses and the microscopic nature of viruses. Recent advancements in molecular and serological diagnostics, including Enzyme-Linked Immunosorbent Assay (ELISA), RT-Polymerase Chain Reaction (RT-PCR), CRISPR-based detection, and biosensors, have improved virus identification and monitoring. Since chemical treatments are ineffective, integrated management strategies such as breeding virus-resistant varieties, controlling vector populations, adjusting cultural practices, and utilizing RNA interference (RNAi) are essential for mitigating disease spread. This review provides a comprehensive analysis of wheat viral diseases, focusing on cutting-edge diagnostic tools and sustainable management approaches. By addressing knowledge gaps and highlighting future research directions, it aims to support the development of virus-resistant wheat, ensuring global food security.

Conventional and cutting-edge advances in plant virus detection: emerging trends and techniques

Plant viruses pose a significant threat to global agriculture. For a long time, conventional methods including detection based on visual symptoms, host range investigations, electron microscopy, serological assays (e.g., ELISA, Western blotting), and nucleic acid-based techniques (PCR, RT-PCR) have been used for virus identification. With increased sensitivity, speed, and specificity, new technologies like loop-mediated isothermal amplification (LAMP), high-throughput sequencing (HTS), nanotechnology-based biosensors, and CRISPR diagnostics have completely changed the way plant viruses are detected. Recent advances in detection techniques integrate artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) for real-time monitoring. Innovations like hyperspectral imaging, deep learning, and cloud-based IoT platforms further support disease identification and surveillance. Nanotechnology-based lateral flow assays and CRISPR-Cas systems provide rapid, field-deployable solutions. Despite these advancements, challenges such as sequence limitations, multiplexing constraints, and environmental concerns remain. Future research should focus on refining portable on-site diagnostic kits, optimizing nanotechnology applications, and enhancing global surveillance systems. Interdisciplinary collaboration across molecular biology, bioinformatics, and engineering is essential to developing scalable, cost-effective solutions for plant virus detection, ensuring agricultural sustainability and ecosystem protection.

Rapid and simple detection of Candida albicans using closed dumbbell-mediated isothermal amplification

Introduction

Candida albicans, a human fungal pathogen, multiplies to invade body cells and causes fungal diseases in the condition of insufficient body's immune function. Early detection of C. albicans is required to guide appropriate prevention and treatment.

Methods

The purpose of this study was to establish a C. albicans assay based on newly developed closed dumbbell-mediated isothermal amplification (CDA) to achieve rapid and simple point of care diagnostic. The CDA technique was carried out by specific primers targeting at the conserved C. albicans ITS2 gene. All primers were selected and evaluated by real-time fluorescence monitoring and endpoint visual judgement indicated by hydroxy naphthol blue (HNB). Optimal primers and accelerate primers (out primers and loop primers) were designed and selected after confirmation of the fundamental CDA primers to achieve more efficient CDA reaction for C. albicans detection (CA-OL-CDA).

Results

After establishment of the assay, 9 non-Candida albicans strains, including 3 Candida species were tested to negative by adopting the established CA-OL-CDA assay, indicated high specificity. The limit of detection of Candida albicans DNA by CA-OL-CDA assay was 6.2×10-6 ng/μL of DNA (10 copies/μL), 10-fold more sensitive than real-time quantitative PCR (qPCR).

Discussion

The CA-OL-CDA assay exhibited advantages of high specificity, sensitivity, simpler and more efficient operation. In addition, the CA-OL-CDA method holds potential in on-site detection for C. albicans using color shift by adopting the reaction mixture based on HNB.

Isothermal Detection Methods for Fungal Pathogens in Closed Environment Agriculture

Closed environment agriculture (CEA) is rapidly gaining traction as a sustainable option to meet global food demands while mitigating the impacts of climate change. Fungal pathogens represent a significant threat to crop productivity in CEA, where the controlled conditions can inadvertently foster their growth. Historically, the detection of pathogens has largely relied on the manual observation of signs and symptoms of disease in the crops. These approaches are challenging at large scale, time consuming, and often too late to limit crop loss. The emergence of fungicide resistance further complicates management strategies, necessitating the development of more effective diagnostic tools. Recent advancements in technology, particularly in molecular and isothermal diagnostics, offer promising tools for the early detection and management of fungal pathogens. Innovative detection methods have the potential to provide real-time results and enhance pathogen management in CEA systems. This review explores isothermal amplification and other new technologies in detection of fungal pathogens that occur in CEA.

New Approaches to Plant Pathogen Detection and Disease Diagnosis

Detecting plant pathogens and diagnosing diseases are critical components of successful pest management. These key areas have undergone significant advancements driven by breakthroughs in molecular biology and remote sensing technologies within the realm of precision agriculture. Notably, nucleic acid amplification techniques, with recent emphasis on sequencing procedures, particularly next-generation sequencing, have enabled improved DNA or RNA amplification detection protocols that now enable previously unthinkable strategies aimed at dissecting plant microbiota, including the disease-causing components. Simultaneously, the domain of remote sensing has seen the emergence of cutting-edge imaging sensor technologies and the integration of powerful computational tools, such as machine learning. These innovations enable spectral analysis of foliar symptoms and specific pathogen-induced alterations, making imaging spectroscopy and thermal imaging fundamental tools for large-scale disease surveillance and monitoring. These technologies contribute significantly to understanding the temporal and spatial dynamics of plant diseases.

A Loop-Mediated Isothermal Amplification Assay for the Rapid Detection of Didymella segeticola Causing Tea Leaf Spot

Tea leaf spot caused by Didymella segeticola is an important disease that threatens the healthy growth of tea plants (Camellia sinensis) and results in reductions in the productivity and quality of tea leaves. Early diagnosis of the disease is particularly important for managing the infection. Loop-mediated isothermal amplification (LAMP) assay is an efficient diagnostic technique with the advantages of simplicity, specificity, and sensitivity. In this study, we developed a rapid, visual, and high-sensitivity LAMP assay for D. segeticola detection based on sequence-characterized amplified regions. Two pairs of amplification primers (external primers F3 and B3 and internal primers FIP and BIP) were designed based on a specific sequence in D. segeticola (NCBI accession number: OR987684). Compared to common pathogens of other genera in tea plants and other species in the Didymella genus (Didymella coffeae-arabicae, Didymella pomorum, and Didymella sinensis), the LAMP method is specific for detecting the species D. segeticola. The assay was able to detect D. segeticola at a minimal concentration of 1 fg/μL genomic DNA at an optimal reaction temperature of 65 °C for 60 min. When healthy leaves were inoculated with D. segeticola in the laboratory, the LAMP method successfully detected D. segeticola in diseased tea leaves at 72 h post inoculation. The LAMP assays were negative when the DNA samples were extracted from healthy leaves. Leaf tissues with necrotic lesions from 18 germplasms of tea plants tested positive for the pathogen by the LAMP assay. In summary, this study established a specific, sensitive, and simple LAMP method to detect D. segeticola, which provides reliable technical support for estimating disease prevalence and facilitates sustainable management of tea leaf spot.

An improved method to study Phytophthora cinnamomi Rands zoospores interactions with host

Phytophthora cinnamomi Rands is a highly prevalent phytopathogen worldwide, ranking among the top ten in terms of distribution. It inflicts crown rot, canker, and root rot on numerous plant species, significantly impacting the biodiversity of both flora and fauna within affected environments. With a host range spanning over 5,000 species, including important plants like Quercus suber, Quercus ilex, Castanea sativa, and commercially significant crops such as avocado (Persea americana), maize (Zea mays), and tomato (Solanum lycopersicum), Phytophthora cinnamomi poses a substantial threat to agriculture and ecosystems. The efficient dissemination of the oomycete relies on its short-lived asexually motile zoospores, which depend on water currents to infect host roots. However, managing these zoospores in the laboratory has long been challenging due to the complexity of the life cycle. Current protocols involve intricate procedures, including alternating cycles of growth, drought, and flooding. Unfortunately, these artificial conditions often result in a rapid decline in virulence, necessitating additional steps to maintain infectivity during cultivation. In our research, we sought to address this challenge by investigating zoospore survival under various conditions. Our goal was to develop a stable stock of zoospores that is both easily deployable and highly infective. Through direct freezing in liquid nitrogen, we have successfully preserved their virulence. This breakthrough eliminates the need for repeated culture transfers, simplifying the process of plant inoculation. Moreover, it enables more comprehensive studies of Phytophthora cinnamomi and its interactions with host plants.

Real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay for detection of cassava brown streak viruses

Cassava brown streak disease (CBSD) caused by Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) is the most economically important viral disease of cassava. As cassava is a vegetatively propagated crop, the development of rapid and sensitive diagnostics would aid in the identification of virus-free planting material and development of effective management strategies. In this study, a rapid, specific and sensitive real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay was developed for real-time detection of CBSV and UCBSV. The RT-RPA was able to detect as little as 2 pg/µl of purified RNA obtained from infected cassava leaves, a sensitivity equivalent to that obtained by quantitative real-time reverse transcription PCR (qRT-PCR), within 20 min at 37 °C. Further, the RT-RPA detected each target virus directly from crude leaf and stem extracts, avoiding the tedious and costly isolation of high-quality RNA. The developed RT-RPA assay provides a valuable diagnostic tool that can be adopted by cassava seed certification and virus resistance breeding programs to ensure distribution of virus-free cassava planting materials to farmers. This is the first report on the development and validation of crude sap-based RT-RPA assay for the detection of cassava brown streak viruses (UCBSV and CBSV) infection in cassava plants.

Lateral flow strip assay of a gene segment in the COVID-19 virus with combined dual readout mode and preliminary multisite hybrid chain reaction amplification

The past and present scenario of COVID-19 has revealed the necessity of simple point-of-care tests. When combined with the great advantages of amplification, lateral flow assay nucleic acid analysis represents a more sensitive molecular diagnostic technique compared to universal protein analysis. Room temperature operation, an enzyme-free nature, and in situ elongation make hybrid chain reaction amplification (HCR) a good candidate for amplified combined lateral flow assays (LFAs). Since dual modes of detection can not only satisfy different application scenarios, but also reduce the false-negative rate, in this paper, visual and fluorescent detection based on labelling with colloidal gold nanoparticles and fluorescence labelling were incorporated into a HCR integrated with a LFA. The detection assay was finished in 30 minutes. The linear relationship between the signal and the concentration of the characteristic segment in the COVID-19 ORF gene was demonstrated. The obtained detection limits of as low as 10 fM (6.02 × 103 copies per mL) and 1 fM (6.02 × 102 copies per mL), respectively, were comparable with those in the literature. The multi-site HCR amplification integrated with LFA of a 1053 bp nucleic acid chain was also preliminarily studied, and tri-site amplification was found to exhibit higher signal intensity than single-site amplification. This study provides a promising strategy for simple, sensitive, and wide-ranging detection of pathogenic bacteria.

Rapid and specific detection of wheat spindle streak mosaic virus using RT-LAMP in durum wheat crude leaf extract

To accurately determine the spread of any pathogen, including plant viruses, a quick, sensitive, cost-effective, point-of-care diagnostic assay is necessary. Wheat spindle streak mosaic virus (WSSMV) is a Bymovirus, transmitted by the plasmodiophorid Polymyxa graminis Led, which causes yellow mosaic and reduces the grain yield in wheat. Currently, detection protocols for WSSMV use ELISA or more sensitive PCR-based approaches requiring specialized laboratory and personnel. A protocol for reverse transcription loop mediated isothermal amplification (RT-LAMP) has been developed and optimized for the rapid detection of viruses using crude extracts from wheat leaves. The protocol was specific for WSSMV detection, while no reaction was observed with SBCMV or SBWMV, the non-target viruses transmitted by the same vector. The RT-LAMP assay was shown to be as sensitive as the one-step WSSMV specific RT-PCR. The RT-LAMP assay can be performed under field conditions using a portable instrument, and can help the actual spread of WSSMV, an aspect of this virus not yet well understood, to be explored.

Challenges to Cannabis sativa Production from Pathogens and Microbes-The Role of Molecular Diagnostics and Bioinformatics

The increased cultivation of Cannabis sativa L. in North America, represented by high Δ9-tetrahydrocannabinol-containing (high-THC) cannabis genotypes and low-THC-containing hemp genotypes, has been impacted by an increasing number of plant pathogens. These include fungi which destroy roots, stems, and leaves, in some cases causing a build-up of populations and mycotoxins in the inflorescences that can negatively impact quality. Viroids and viruses have also increased in prevalence and severity and can reduce plant growth and product quality. Rapid diagnosis of the occurrence and spread of these pathogens is critical. Techniques in the area of molecular diagnostics have been applied to study these pathogens in both cannabis and hemp. These include polymerase chain reaction (PCR)-based technologies, including RT-PCR, multiplex RT-PCR, RT-qPCR, and ddPCR, as well as whole-genome sequencing (NGS) and bioinformatics. In this study, examples of how these technologies have enhanced the rapidity and sensitivity of pathogen diagnosis on cannabis and hemp will be illustrated. These molecular tools have also enabled studies on the diversity and origins of specific pathogens, specifically viruses and viroids, and these will be illustrated. Comparative studies on the genomics and metabolomics of healthy and diseased plants are urgently needed to provide insight into their impact on the quality and composition of cannabis and hemp-derived products. Management of these pathogens will require monitoring of their spread and survival using the appropriate technologies to allow accurate detection, followed by appropriate implementation of disease control measures.

Strategy of functional nucleic acids-mediated isothermal amplification for detection of foodborne microbial contaminants: A review

Foodborne microbial contamination (FMC) is the leading cause of food poisoning and foodborne illness. The foodborne microbial detection methods based on isothermal amplification have high sensitivity and short detection time, and functional nucleic acids (FNAs) could extend the detectable object of isothermal amplification to mycotoxins. Therefore, the strategy of FNAs-mediated isothermal amplification has been emergingly applied in biosensors for foodborne microbial contaminants detection, making biosensors more sensitive with lower cost and less dependent on nanomaterials for signal output. Here, the mechanism of six isothermal amplification technologies and their application in detecting FMC is firstly introduced. Then the strategy of FNAs-mediated isothermal amplification is systematically discussed from perspectives of FNAs' versatility including recognition elements (Aptamer, DNAzyme), programming tools (DNA tweezer, DNA walker and CRISPR-Cas) and signal units (G-quadruplex, FNAs-based nanomaterials). Finally, challenges and prospects are presented in terms of addressing the issue of nonspecific amplification reaction, developing better FNAs-based sensing elements and eliminating food matrix effects.

An enhanced activity and thermostability of chimeric Bst DNA polymerase for isothermal amplification applications

Loop-mediated isothermal amplification (LAMP) is a widely used method for clinical diagnosis, customs quarantine, and disease prevention. However, the low catalytic activity of Bst DNA polymerase has made it challenging to develop rapid and reliable point-of-care testing. Herein, we developed a series of Bst DNA polymerase mutants with enhanced activity by predicting and analyzing the activity sites. Among these mutants, single mutants K431D and K431E showed a 1.93- and 2.03-fold increase in catalytic efficiency, respectively. We also created a chimeric protein by fusing the DNA-binding domain of DNA ligase from Pyrococcus abyssi (DBD), namely DBD-K431E, which enabled real-time LAMP at high temperatures up to 73 ℃ and remained active after heating at 70 ℃ for 8 h. The chimeric DBD-K431E remained active in the presence of 50 U/mL heparin, 10% ethanol, and up to 100 mM NaCl, and showed higher activity in 110 mM (NH4)2SO4, 110 mM KCl, and 12 mM MgSO4. Notably, it generated a fluorescence signal during the detection of Salmonella typhimurium at 2 × 102 ag/μL of genomic DNA and 1.24 CFU/mL of bacterial colony, outperforming the wild type and the commercial counterpart Bst 2.0. Our results suggest that the DBD-K431E variant could be a promising tool for general molecular biology research and clinical diagnostics. KEY POINTS: • Residue K431 is probably a key site of Bst DNA polymerase activity • The chimeric DBD-K431E is more inhibitor tolerant and thermostable than Bst-LF • The DBD-K431E variant can detect Salmonella typhimurium at 102 ag/μL or 100 CFU/mL.

Application of loop-mediated isothermal amplification combined with lateral flow assay visualization of Plasmodium falciparum kelch 13 C580Y mutation for artemisinin resistance detection in clinical samples

Resistance to the antimalarial drug artemisinin (ART) has emerged in Greater Mekong Subregion. The molecular marker predominantly used to identify ART resistance is the C580Y mutation in Pfkelch13 of Plasmodium falciparum. Rapid and accurate detection of ART resistance in the field is necessary to guide malaria containment and elimination interventions. Our study evaluates the PfC580Y by using the loop-mediated isothermal amplification and single nucleotide polymorphism analysis visualization using a lateral flow assay (LAMP-SNP-LFA) method for detecting ART resistance in clinical samples collected from Thailand between 2014 and 2019. The optimized incubation condition for the reaction was determined as 45 min at 56 °C, followed by visual detection of positive amplicons using LFA. The assay demonstrated high analytical sensitivity and specificity, with a limit of detection of 16.8 copies of C580Y plasmid/µL of and 100% accuracy for C580Y mutation detection. The PfC580Y LAMP-SNP-LFA method is faster and simpler than conventional polymerase chain reaction/DNA sequencing and has the potential to support antimalarial management policies, malaria control, and global elimination efforts.

Development of Loop-Mediated Isothermal Amplification Method for Rapid and Sensitive Identification of Hermetia illucens (Diptera: Stratiomyidae)

The black soldier fly (BSF) is well known for its ability to biologically convert organic waste into insect biomass, including protein and oil, which can be utilised as animal feed. Since raw BSF products, such as BSF powder, are difficult to differentiate from other biological raw materials, therefore new analytical approaches are required. In this study, we have developed a new and fast method based on loop-mediated isothermal AMPlification (LAMP) reaction that can diagnose black soldier fly larvae and BSF byproducts with high accuracy, specificity and sensitivity. Species-specific primers for BSF were designed based on targeting the mitochondrial cytochrome C oxidase I (COI) gene. The assay was able to detect as low as 820 fg/L of BSF DNA in 60 min at 65 °C, which was a hundredfold higher than the detection limit of classical polymerase chain reaction and did not show cross-reactivity. In conclusion, the LAMP assay demonstrated excellent sensitivity and specificity to detect BSF and BSF byproducts, with a sampling-to-result identification time of 60 min.

Paper-based colorimetric loop-mediated isothermal amplification (LAMP) assay for the identification of latent Colletotrichum in harvested fruit

Paper-based analytical devices (PADs) have gained enormous attention because of their low-cost, simple fabrication, and portability. Here, we propose a paper-based device for performing reverse transcription loop-mediated isothermal amplification (RT-LAMP) with real-time simultaneous detection of C. gloeosporioides latent infections in tomatoes. RT-LAMP-based PAD platform comprises a paper substrate on which the DNA amplification reaction occurs. Among different types of tested papers, cellulose membrane (grade 4) enabled effective visualization of the amplification result. The assay was found highly selective for the latent stage of C. gloeosporioides with lower limit of detection (LOD) of 0.5 pg of total extracted RNA. The developed assay generated the results within 40 min and hence can be efficiently employed for identifying C. gloeosporioides in resource-limited settings.

Detecting the Minimum Limit on Wheat Stripe Rust in the Latent Period Using Proximal Remote Sensing Coupled with Duplex Real-Time PCR and Machine Learning

Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was used to collect the canopy hyperspectral data, and the Pst content was obtained via a duplex real-time polymerase chain reaction (PCR) during the latent period, respectively. The disease index (DI) and molecular disease index (MDI) were calculated. The regression tree algorithm was used to determine the MDL of the Pst based on hyperspectral feature parameters. The logistic, IBK, and random committee algorithms were used to construct the classification model based on the MDL. The results showed that when the MDL was 0.7, IBK had the best recognition accuracy. The optimal model, which used the spectral feature R_2nd.dv ((the second derivative of the original hyperspectral value)) and the modeling ratio 2:1, had an accuracy of 91.67% on the testing set and 90.67% on the 10-fold cross-validation. Thus, during the latent period, the MDL of Pst was determined using hyperspectral technology as 0.7.

Highly sensitive fluorescence detection of tobacco mosaic virus RNA based on polysaccharide and ARGET ATRP double signal amplification

Plant diseases caused by tobacco mosaic viruses (TMV) reduce the yield and quality of crops and cause significant losses. Early detection and prevention of TMV has important value of research and reality. Herein, a fluorescent biosensor was constructed for highly sensitive detection of TMV RNA (tRNA) based on the principle of base complementary pairing, polysaccharides and atom transfer radical polymerization by electron transfer activated regeneration catalysts (ARGET ATRP) as double signal amplification strategy. The 5'-end sulfhydrylated hairpin capture probe (hDNA) was first immobilized on amino magnetic beads (MBs) by a cross-linking agent, which specifically recognizes tRNA. Then, chitosan binds to BIBB, providing numerous active sites for fluorescent monomer polymerization, which successfully significantly amplifying the fluorescent signal. Under optimal experimental conditions, the proposed fluorescent biosensor for the detection of tRNA has a wide detection range from 0.1 pM to 10 nM (R² = 0.998) with a limit of detection (LOD) as low as 1.14 fM. In addition, the fluorescent biosensor showed satisfactory applicability for the qualitative and quantitative analysis of tRNA in real samples, thereby demonstrating the potential in the field of viral RNA detection.

Current and emerging trends in techniques for plant pathogen detection

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.

Detection of Cytb Point Mutation (G143A) that Confers High-Level Resistance to Pyraclostrobin in Glomerella cingulata Using LAMP Method

Glomerella leaf spot (GLS) caused by Glomerella cingulata is a newly emerging disease that results in severe defoliation and fruit spots in apples. In China, the compound of pyraclostrobin and tebuconazole was registered to control GLS in 2018 and has achieved excellent control efficiency. In this study, we showed that the high-level resistant isolates of G. cingulata to pyraclostrobin, caused by the point mutation at codon 143 (GGT→GCT, G143A) in the cytochrome b gene, has appeared in apple orchards in Shandong Province in 2020, and the resistance frequency was 4.8%. Based on the genotype of the resistant isolates, we developed a loop-mediated isothermal amplification (LAMP) assay for detection of the pyraclostrobin resistance. The LAMP assay was demonstrated to have good specificity, sensitivity, and repeatability, and it exhibited high accuracy in detecting pyraclostrobin resistance in the field. This study reported the resistance status of GLS to pyraclostrobin in Shandong Province and developed a molecular tool for the detection of pyraclostrobin resistance, which is of practical significance for the scientific control of GLS.

Peanut leaf disease identification with deep learning algorithms

Peanut is an essential food and oilseed crop. One of the most critical factors contributing to the low yield and destruction of peanut plant growth is leaf disease attack, which will directly reduce the yield and quality of peanut plants. The existing works have shortcomings such as strong subjectivity and insufficient generalization ability. So, we proposed a new deep learning model for peanut leaf disease identification. The proposed model is a combination of an improved X-ception, a parts-activated feature fusion module, and two attention-augmented branches. We obtained an accuracy of 99.69%, which was 9.67%-23.34% higher than those of Inception-V4, ResNet 34, and MobileNet-V3. Besides, supplementary experiments were performed to confirm the generality of the proposed model. The proposed model was applied to cucumber, apple, rice, corn, and wheat leaf disease identification, and yielded an average accuracy of 99.61%. The experimental results demonstrate that the proposed model can identify different crop leaf diseases, proving its feasibility and generalization. The proposed model has a positive significance for exploring other crop diseases' detection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01370-8.

Fast and Sensitive Detection of Soil-Borne Cereal Mosaic Virus in Leaf Crude Extract of Durum Wheat

Soil-borne cereal mosaic virus (SBCMV) is a furovirus with rigid rod-shaped particles containing an ssRNA genome, transmitted by Polymyxa graminis Led., a plasmodiophorid that can persist in soil for up to 20 years. SBCMV was reported on common and durum wheat and it can cause yield losses of up to 70%. Detection protocols currently available are costly and time-consuming (real-time PCR) or have limited sensitivity (ELISA). To facilitate an efficient investigation of the real dispersal of SBCMV, it is necessary to develop a new detection tool with the following characteristics: no extraction steps, very fast results, and high sensitivity to allow pooling of a large number of samples. In the present work, we have developed a reverse transcription loop-mediated isothermal amplification (RT-LAMP) protocol with such characteristics, and we have compared it with real-time PCR. Our results show that the sensitivity of LAMP and real-time PCR on cDNA and RT-LAMP on crude extracts are comparable, with the obvious advantage that RT-LAMP produces results in minutes rather than hours. This paves the way for extensive field surveys, leading to a better knowledge of the impact of this virus on wheat health and yield.