Search Results (267)

Climatic changes are heavily affecting the sustainability of vegetable crops crucial for food supply worldwide, mainly in subtropical countries. One of the main threats to food security is the spread of diseases caused by plant viruses, favored by irregular rains and extreme temperatures, which reduce crop yield and quality. During a preliminary field survey carried out in two provinces of Angola in 2024, a few symptomatic plants of tomato, habanero pepper, common bean and a wild weed were sampled. These plants generally showed dwarfing, yellowing and leaf curl and were submitted to high-throughput sequencing to detect any viral agent. The evidence of mixed infections of several polyphagous viruses with RNA or DNA genomes, variously affecting the selected plants, was assessed from the sequence analysis and further confirmed for most samples by molecular tests, like (RT)-PCR or qPCR. Emerging polero-, begomo and tobamoviruses were denoted as infecting these plants. A novel, previously unknown carlavirus was also described in a wild weed. Most of those viruses are efficiently mechanically transmitted or airborne vehiculated by insect vectors. Although based on a limited number of samples, this study provides a first insight into the diversity of viruses infecting vegetable crops in Angola. It also highlights the pressing need for a broader monitoring to better understand virus distribution and epidemiology, and suggests the use of virus-free seeds to reduce the potential risk to crop production. Full article

Squash leaf curl China virus (SLCCNV) is an important geminivirus that infects cucurbit crops and is widely distributed across Asia. To elucidate its population structure and molecular evolution, 101 DNA-A and 67 DNA-B strain sequences of SLCCNV that were publicly available from 2001 to 2024 were analyzed. The strains clustered into three major geographic clades, including South Asia, the Malay Archipelago, and Mainland Southeast Asia. Recombination analysis revealed breakpoints mainly concentrated in the AC2 and BC1 regions. Signals of positive selection were indicated for AC4 and AC5 by selection pressure analysis. Significant genetic differentiation among SLCCNV populations from different geographic origins, but frequent gene flow was observed between among populations from South Asia, the Malay Archipelago, and Mainland Southeast Asia. In addition, AC5 and AV2 exhibited high variability at both the nucleotide and amino acid levels, while AC1, AC2, and AC3 were relatively conserved. Collectively, the evolutionary dynamics of SLCCNV are shaped by geographic isolation, recombination events, and differential selection pressures. This study provides important insights into the molecular evolution of SLCCNV and offers valuable guidance for region-specific surveillance, quarantine strategies, and the deployment of durable resistance against emerging viral variants. Full article

Tomato yellow leaf curl virus (TYLCV) is a major threat to tomato production, creating a need for sensitive, low-cost detection methods that can be applied to early symptomatic or low-viral-load samples. Recombinant antigen configuration may influence serological assay development, although the specific contribution of multiple-cloning-site (MCS)-derived intermediate sequences remains uncertain. In this study, a recombinant Trx-His-coat protein (CP) fusion antigen was produced using an MCS-free direct-fusion construct that retained the Trx-His tag while removing the MCS-derived intermediate sequence, followed by gradient refolding. No direct comparison with linker-containing, tag-cleaved, or tag-free antigen constructs was performed. The purified antigen was used to immunize rabbits and generate a high-titre polyclonal antibody (pAb). The resulting indirect enzyme-linked immunosorbent assay (ELISA) achieved a theoretical limit of detection of 1.8 ng/mL and an estimated pre-dilution equivalent the limit of detection (LOD) of 72 ng/mL after sample dilution. The assay showed favourable tolerance to crude tomato leaf matrices, with spike-recovery rates of 95.45–100.40%. In a preliminary evaluation using a balanced panel of 32 field-collected samples, ELISA absorbance correlated with droplet digital PCR quantification (R² = 0.9819) and plant disease index values (R² = 0.9774). Liquid chromatography–tandem mass spectrometry (LC-MS/MS) peptide mapping and AlphaFold2-based modelling were used only to provide preliminary computational context for antigen interpretation. The assay showed cross-recognition toward Tobacco curly shoot virus (TbCSV), indicating that it should not be considered strictly TYLCV species-specific. Therefore, this assay may support preliminary serological screening under the tested conditions, whereas molecular confirmation remains necessary when species-level identification is required. Full article

Tomato leaf disease detection in natural environments is challenged by subtle early-stage symptoms, complex backgrounds, leaf occlusion, and scale variation, which can lead to missed detections, false detections, and unstable leaf localization. Meanwhile, practical agricultural applications impose higher requirements on model lightweightness and edge-deployment capability. To address these issues, this study proposes DFR-YOLOv12n, a lightweight tomato leaf disease detection model based on YOLOv12n that integrates detail-preserving downsampling, feature enhancement, and regression optimization. First, a multi-source dataset collected in natural environments was constructed and curated, covering eight categories: bacterial spot, early blight, late blight, leaf mold, mosaic virus disease, septoria leaf spot, yellow leaf curl virus disease, and healthy leaves. Second, SPDConv was introduced into key downsampling layers to preserve fine-grained disease-related visual cues. The A2C2f_DEConv module was incorporated into the P3 feature fusion branch to enhance leaf texture and disease-related appearance features under complex backgrounds. In addition, MPDIoU was adopted to optimize bounding box regression and improve whole-leaf localization under occlusion and background interference. The optimal model configuration was determined through insertion-position, module comparison, and ablation experiments. Compared with the baseline model, DFR-YOLOv12n increased Precision, Recall, and mAP@0.5 from 86.8%, 76.9%, and 86.5% to 88.1%, 81.7%, and 88.6%, respectively. Meanwhile, FLOPs decreased from 5.83 G to 5.27 G, the parameter count decreased from 2.51 M to 2.25 M, and the model size decreased from 5.22 MB to 4.71 MB. Furthermore, the model was successfully deployed and validated on the Jetson Nano platform, demonstrating its potential for edge applications. The results indicate that DFR-YOLOv12n achieves a favorable balance among detection accuracy, model complexity, and deployment feasibility, providing a reference for intelligent tomato leaf disease detection in natural environments. Full article

Global agriculture is seriously threatened by plant diseases, which result in large losses in both productivity and quality. Timely and accurate disease detection is essential for effective crop management and food security. This work presents an improved MobileNetV2 architecture with Modified Lite Attention (MLA) Model for detecting plant leaf disease. Our methodology incorporates pre-processing, feature extraction through attention model, convolution layers, and classifying into diseased or healthy categories. Further, multiclassification of diseases is performed on a dataset comprising 4432 samples including whitefly, leaf spot, leaf curl, yellowish and healthy leaves. The proposed attention model is compared with existing attention models like CBAM (Convolutional Block Attention Model), SE (Squeeze and Excitation), ECA (Efficient Channel Attention) and SDMnet (Spatially Dilated Multi-Scale Network) to validate our hybrid MLA feature extraction technique. Customizing the categorization with fully connected layers and utilisation of a pre-trained MobileNetV2 model allow the system to achieve excellent results. Findings show encouraging accuracy, surpassing 97% compared to existing techniques for multiclass dataset classification. The integration of MobileNetV2 with custom dense layers enables robust detection even with limited datasets, making it ideal for use in mobile or low-resource agricultural environments. Further, the proposed method is tested on the PlantVillage dataset consisting of 10,836 samples using K-Fold cross-validation for K = 5 and K = 4 to obtain an average accuracy of 98.4% and 98.69%, respectively. Full article

High-throughput sequencing is becoming the method of choice for plant diagnostics. It allows the detection of known and novel viruses and viroids, even in co-infection, without preliminary knowledge of the target. However, this method has its own limitations when compared to real-time PCR or ELISA. Laboratories that implement this type of technologies in-house must ensure that the performance criteria meet the requirements associated with their diagnostic activity. In this study, we present a workflow for in-house plant viruses and viroid detection, based on total RNA extraction, ribodepletion, Illumina sequencing and bioinformatics analyses. Performance criteria such as analytical sensitivity, analytical specificity, selectivity, repeatability, reproducibility and robustness were evaluated on the tomato brown rugose fruit virus (RNA genome), the tomato leaf curl New Delhi virus (DNA genome), and the pepper chat fruit viroid (RNA genome). The performance levels obtained meet the requirements for virus and viroid detection in symptomatic plant samples. Full article

Bemisia tabaci is a globally destructive agricultural pest and an efficient vector of begomoviruses, which cause recurrent epidemics across South Asia, including cotton leaf curl disease in Pakistan. Increasing evidence shows that bacterial endosymbionts play a central role in shaping whitefly biology, population dynamics, and vector competence. However, the distribution of these symbionts remains poorly resolved in Pakistan, a region where begomoviruses are persistent and widespread. This study investigated the cryptic species diversity, secondary endosymbiont composition and their infection frequency in B. tabaci populations collected from major agricultural regions of Pakistan. A total of 274 adult whiteflies belonging to Asia II-1 (n = 199), MEAM-1 (n = 67), Asia I (n = 7), and Asia II-8 (n = 1) were screened using a symbiont-specific PCR assay for six endosymbionts. The primary endosymbiont Candidatus Portiera aleyrodidarum was detected in all individuals, whereas five secondary endosymbionts (Arsenophonus, Cardinium, Hamiltonella, Wolbachia and Rickettsia) were identified with distinct cryptic species- and region-specific patterns. Notably, Arsenophonus was the most prevalent endosymbiont, occurring in 68% of Asia II-1, 100% of Asia I, and 21% of MEAM-1 individuals, with the highest regional prevalence in Punjab (80%) and Khyber Pakhtunkhwa (77%). Logistic regression analyses confirmed significantly higher infection probabilities in indigenous Asia II-1 populations. Network analysis revealed structured co-occurrence patterns, including strong negative associations between Arsenophonus and Hamiltonella. Phylogenetic analyses revealed close relatedness of Pakistani Arsenophonus strains to those reported from neighboring regions, indicating regional community rather than unique local diversification. The dominance of Arsenophonus in Pakistani whitefly populations is of particular significance, given its role in protecting begomoviruses within the insect vector and its implication in facilitating virus persistence and transmission. This study, for the first time in Pakistan, provides a comprehensive assessment of endosymbiont–cryptic species associations in Pakistani B. tabaci populations and highlights the dominant prevalence of Arsenophonus as a potential key player in local virus vector dynamics. Full article

Tomato yellow leaf curl virus (TYLCV) is a major plant pathogen that spreads worldwide through persistent circulative transmission by Bemisia tabaci. During transmission, TYLCV crosses several physiological barriers in the insect vector, evading immune defenses and altering host metabolic pathways to facilitate viral accumulation. Polyamines, essential for maintaining nucleic acid stability and promoting cellular processes, are known to play a critical role in viral accumulation. However, their role in TYLCV accumulation within B. tabaci is not well understood. Here, we demonstrate that TYLCV infection leads to significant alterations in polyamine levels in B. tabaci, with polyamine availability positively affecting viral DNA accumulation. Polyamine availability leads to higher viral loads and suppresses the expression of immune and MAPK signaling genes. These findings provide new insights into virus–vector and metabolic interactions underlying viral persistence in insect vectors. Full article

Tomato yellow leaf curl virus (TYLCV) is one of the most destructive viral diseases causing severe yield losses in tomato production worldwide. This study investigated the effects of TYLCV infection on plant growth, photosynthetic physiological responses, and yield formation in greenhouse-grown tomatoes and evaluated the applicability of physiological trait-based yield prediction models. Two large-fruited tomato cultivars widely cultivated in Korean protected horticulture systems, ‘Daphnis’ and ‘Pink Star’, were inoculated with TYLCV under greenhouse conditions, and their growth, physiological responses, and yield characteristics were compared under high- and low-temperature growing seasons. TYLCV infection significantly reduced leaf length, leaf width, and leaf area index (LAI), and decreased both flowering truss number and fruit-setting truss number, resulting in reduced total yield. Physiological analyses showed that infected plants exhibited decreases in the OJIP fluorescence rise curve and Fv/Fm values, indicating a reduced photochemical efficiency in photosystem II. In addition, A–Ci response curve analysis revealed a reduction in net photosynthetic rate, suggesting limited carbon assimilation capacity. Total yield showed significant positive correlations with maximum net photosynthetic rate (Amax), Fv/Fm, and Ci300. GGE and GT biplot analyses further indicated that yield was closely associated with photosynthetic performance and canopy development traits. A multiple regression model based on physiological traits and virus infection status explained a significant proportion of the variation in tomato yield (R² = 0.367), indicating that TYLCV infection acts as a key limiting factor for yield reduction. These findings demonstrate that TYLCV infection restricts tomato productivity through reduced photosynthetic efficiency and altered canopy structure. Moreover, physiological trait-based yield prediction approaches may provide a useful framework for evaluating productivity under viral infection conditions and for developing data-driven crop management strategies in greenhouse tomato production systems. Full article

Tomato is widely produced in Burkina Faso for its culinary, nutritional, and economic value. Tens of thousands of farmers are involved in its production throughout the country. However, they face significant biotic constraints that limit yields and income. In particular, tomato yellow leaf curl virus (TYLCV), a begomovirus transmitted by whiteflies (Bemisia tabaci), severely affects tomato production. This study evaluated the response of 13 tomato genotypes to tomato yellow leaf curl disease (TYLCD), including eight lines with different Ty resistance gene combinations; three local improved varieties, and two commercial varieties in western and central Burkina Faso. All genotypes developed TYLCD symptoms with considerable variability in genotypic responses. Four genotypes carrying a single gene, namely CLN4279O (Ty2), CLN4270I (Ty1/Ty3), CLN4270F (Ty1/Ty3), and CLN4018G (Ty2), exhibited the best field tolerance, with lower disease incidence and severity across sites. In contrast, genotype CLN4078A carrying two resistance genes (Ty1/Ty3 + Ty2), and the checks PETOMECH and ROMA VF were highly susceptible. Hierarchical clustering grouped the genotypes into four classes based on tolerance level and yield. These findings highlight the variability in resistance expression under field conditions and suggest possible interactions between host genotype, environmental factors, and virus populations. Broader multi-site evaluations, supported by molecular diagnostics to identify endemic TYLCV strains, are needed to refine the selection process. Full article

Plant viral diseases threaten the tomato agricultural industry. A smart decentralized diagnostic network was realized across the main Sicilian tomato-producing provinces for real-time detection/monitoring of Begomovirus solanumdelhiense (tomato leaf curl New Delhi virus—ToLCNDV), transmitted by Bemisia tabaci, Tobamovirus fructirugosum (tomato brown rugose fruit virus—ToBRFV), Orthotospovirus tomatomaculae (tomato spotted wilt virus—TSWV) and Amalgavirus lycopersici (southern tomato virus—STV). The network deployed smart portable thermocyclers and ready-to-use molecular diagnostic kits (real-time RT-LAMP, RT-qPCR). Data were remotely analyzed and in situ application of the developed kits was evaluated. Results revealed widespread STV infection (>70%) across all provinces, a variable ToBRFV presence with higher incidence in Ragusa (65%) and Siracusa (55.6%) provinces, ToLCNDV mainly concentrated in Siracusa (61.4%) and Trapani (60.2%) provinces, and localized TSWV outbreaks. ToLCNDV detection in Bemisia tabaci MED specimens confirmed the vector’s role in field transmission (up to 100% incidence). Performance comparison between laboratory and point-of-care conditions showed comparable accuracy, specificity, robustness, and rapid, cost-effective virus detection/monitoring. This diagnostic network enhances early diagnosis and timely phytosanitary interventions in tomato crops. The system supports integrated management strategies by reducing diagnostic delays and improving outbreak containment, control measures application and agroecosystem stability. Full article

TCP transcription factors constitute a key regulatory family in plants, playing crucial roles in plant growth and development. Although this gene family has been extensively studied across diverse plant species, research in Gypsophila paniculata remains limited. Through genome-wide identification and analysis, this study identified 17 GpTCP in G. paniculata. Our analysis revealed that all GpTCP proteins contain a conserved TCP domain, with subcellular localization predictions indicating nuclear localization. Promoter analysis identified multiple cis-regulatory elements associated with plant organ development and growth regulation. Chromosomal synteny studies showed that gene expansion within the G. paniculata TCP gene family occurred after subfamily differentiation. Over-expression of GpTCP10 in Arabidopsis thaliana caused root development inhibition, leaf curling, smaller flowers, and yellowing of flowers. Further studies showed that in two normally growing G. paniculata varieties with different flower sizes, GpTCP10 was specifically expressed in leaf and floral tissues, with significantly higher expression levels in the smaller-flowered G. paniculata. These findings reveal the evolutionary characteristics of the TCP family in G. paniculata, and highlight the role of GpTCP10 in regulating organ growth and development in transgenic Arabidopsis thaliana and floral organ size in G. paniculata. Full article

Background: Automated monitoring of crop health and the precise detection of abiotic stress, such as herbicide damage, are demanding challenges for modern agriculture. Abiotic stresses are a demanding challenge for modern agriculture, responsible for up to 82% of yield losses in major food crops. To address this, researchers are increasingly leveraging artificial intelligence (AI) to automate the detection and management of these stressors. Methods: In particular, this paper presents an instance segmentation framework to precisely detect interveinal chlorosis and leaf curling on potato leaves, two common symptoms of herbicide damage and soft wind. Within the context of precision agriculture and the need to address the inherent ambiguity in manual leaf assessment, this study employs a partial label learning approach to refine the dataset. This method utilizes an EfficientNet-b1 model to classify ambiguous samples, generating high-confidence pseudo-labels for instances that are difficult to categorize visually. The core of the proposed framework is a Mask2Former model, which is first fine-tuned on general potato leaf dataset to enhance its segmentation capabilities and then transferred on the refined, pseudo-labeled dataset. Results & Conclusions: This two-stage approach yields a highly accurate segmentation tool, achieving 89% mAP₅₀ and a pseudo-label classification accuracy of 95%, designed for integration into smart agriculture systems like ground level robotics or unmanned aerial vehicles for real-time, automated crop monitoring. Full article

Tomato leaf curl New Delhi virus (ToLCNDV) is a bipartite begomovirus (family Geminiviridae) originally isolated from tomatoes and later evolved to cross-infect cucurbit crops, causing severe economic damage in Asia and Europe. In this study, we sequenced and characterized complete genomes of two ToLCNDV isolates collected from Hebei (ToLCNDV-HB) and Jiangsu (ToLCNDV-JS) provinces of China infecting melon. We constructed infectious clones for ToLCNDV-HB and ToLCNDV-JS, which could systemically infect Nicotiana benthamiana, tomato, and four species of cucurbitaceous plants. Notably, ToLCNDV-HB induced more severe symptoms and accumulated higher viral DNA and protein accumulation than ToLCNDV-JS in N. benthamiana, melon, and bottle gourd. Sequence analysis showed that sequence variations are present only in AV2, AC1, and AC4. However, only the AV2 ORF from ToLCNDV-HB was more efficient than that from that ToLCNDV-JS in enhancing potato X virus’s pathogenicity and suppressing post-transcriptional gene silencing (PTGS). An AV2-swapping experiment between ToLCNDV-HB and ToLCNDV-JS confirmed its vital role in determining the differential pathogenicity. Further evidence shows that virions from both clones are mechanically transmissible. This is the first report comparing the differential pathogenicity of two Chinese ToLCNDV isolates in cucurbits. The AV2 protein, a key pathogenicity determinant, represents a potential target for breeding ToLCNDV-resistant cucurbit varieties. Full article

Viral diseases pose a serious threat to pumpkin cultivation, which is an important cucurbitaceous vegetable crop. Recently, multi-virus mixed infections in plants have been continuously detected and reported. However, studies on mixed virus infections in pumpkins are limited. Through metavirome and polymerase chain reaction (PCR) analysis, we found that pumpkins exhibiting severe viral symptoms were co-infected with squash leaf curl China virus and tomato leaf curl New Delhi virus. Transcriptome analysis revealed that 2927 genes were upregulated, and 2273 were downregulated in virus-infected pumpkin plants, compared to the gene expression in healthy pumpkin plants. Cluster analysis showed that the expression of genes related to RNA silencing and the salicylic acid resistance pathway was higher in virus-infected pumpkin plants than in healthy pumpkin plants. Furthermore, quantitative real-time PCR confirmed that the expression pattern of genes related to RNA silencing and the salicylic acid resistance pathway aligned with the transcriptome sequencing results. Our findings provide a reference for investigating the mechanism of mixed infections by these two viruses to aid in the prevention and control of viral diseases in pumpkins. Full article