Search Results (240)

Grapefruit (Citrus × paradisi Macfad.) is susceptible to Huanglongbing (HLB) disease, which prominently affects tree health and leads to a substantial loss of productivity. HLB-affected trees exhibit a nutritional imbalance expressed in either deficiencies or toxicities of the essential minerals required for plant growth, as well as changes in the production of plant metabolites. Hence, understanding foliar nutritional and metabolite fluctuations as HLB-elicited symptoms progress can assist growers in improving tree health management strategies. This study evaluated changes in foliar nutrient and phloem sap amino acid concentrations of HLB-affected grapefruit trees showing a mixed canopy of HLB-induced blotchy mottle and asymptomatic mature leaves. The trees used in our experiment were fruit-bearing seven-year-old grapefruit trees (cv ‘Rio Red’ on sour orange rootstock) grown in South Texas. Two types of foliage from HLB-affected trees were studied, (a) HLB-symptomatic and confirmed Candidatus Liberibacter asiaticus (CLas)-positive (IS) and (b) CLas-negative and HLB-asymptomatic (IA) mature leaves, which were compared to asymptomatic and CLas-free mature foliage from healthy trees (HY) in terms of their leaf nutrient and phloem sap amino acid contents. Hierarchical clustering based on leaf nutrient contents showed that 70% of IA samples clustered with HY samples, thus indicating that the levels of some nutrients were statistically similar in these two types of samples. The concentrations of the macronutrients N, Ca, Mg, and S and the micronutrients Mn and B were significantly reduced in HLB-symptomatic (IS) leaves, as compared to their IA and HY counterparts, which did not show statistically significant differences. Conversely, leaf Na concentration was approximately two-fold higher in leaves from HLB-affected trees (IA and IS) independent of symptom expression as compared to leaves from healthy trees. Significantly higher concentrations of glutamine and the S-containing amino acids taurine and cystathionine were observed in the IS leaves relative to the phloem sap of IA leaves from HLB-affected trees. In contrast, the phloem sap of IA (14%) and IS (41%) leaves from HLB-affected trees exhibited lower levels of γ-amino butyric acid (GABA) as compared to HY leaves. The results of this study highlight the changes in leaf nutrient and phloem sap amino acid profiles following CLas infection and HLB symptom development in grapefruit, and we discuss these results considering the strategies that growers can implement to correct the nutritional deficiencies and/or toxicities induced by this disease. Full article

Huanglongbing (HLB), associated with Candidatus Liberibacter asiaticus (CLas), has severely impacted global citrus production, with no economically viable control measures currently available. This study explored microwave treatment at 2450 MHz as an innovative physical method for HLB control, combining pathogen elimination efficacy with metabolomic analysis. In controlled experiments, 36 HLB-infected citrus plants were treated with 500 W or 250 W microwave irradiation and underwent 10 cycles, achieving up to 99.83% reduction CLas titer. Non-targeted metabolomic analysis identified 15 significantly altered metabolites, including upregulated beta-caryophyllene and lysophosphatidylinositols, and downregulated 5′-S-methyl-5′-thioadenosine. The results indicate that microwave treatment effectively suppressed CLas while simultaneously triggering citrus physiological metabolic changes. These findings suggest that microwave treatment could serve as a sustainable alternative to chemical controls. However, further optimization of parameters, such as wavelengths, voltages, currents, and safety protocols, will be essential for practical field implementation. Full article

Citrus diseases severely impact fruit yield and quality. To facilitate in-field, non-destructive, and rapid detection of citrus leaf physiological and pathological conditions, this study proposes a classification method for citrus leaf physiological and pathological statuses that integrates visible/near-infrared multispectral technology with deep learning. First, a handheld spectrometer was employed to acquire spectral images of five sample categories—Healthy, Huanglongbing, Yellow Vein Disease, Magnesium Deficiency and Manganese Deficiency. Mean spectral data were extracted from regions of interest within the 350–2500 nm wavelength range, and various preprocessing techniques were evaluated. The Standard Normal Variate (SNV) transformation, which demonstrated optimal performance, was selected for data preprocessing. Next, we innovatively introduced an adaptive spectral positional encoding mechanism into the Transformer framework. A lightweight, learnable network dynamically optimizes positional biases, yielding the ASTransformer (Adaptive Spectral Transformer) model, which more effectively captures complex dependencies among spectral features and identifies critical wavelength bands, thereby significantly enhancing the model’s adaptive representation of discriminative bands. Finally, the preprocessed spectra were fed into three deep learning architectures (1D-CNN, 1D-ResNet, and ASTransformer) for comparative evaluation. The results indicate that ASTransformer achieves the best classification performance: an overall accuracy of 97.7%, underscoring its excellent global classification capability; a Macro Average of 97.5%, reflecting balanced performance across categories; a Weighted Average of 97.8%, indicating superior performance in classes with larger sample sizes; an average precision of 97.5%, demonstrating high predictive accuracy; an average recall of 97.7%, showing effective detection of most affected samples; and an average F1-score of 97.6%, confirming a well-balanced trade-off between precision and recall. Furthermore, interpretability analysis via Integrated Gradients quantitatively assesses the contribution of each wavelength to the classification decisions. These findings validate the feasibility of combining a handheld spectrometer with the ASTransformer model for effective citrus leaf physiological and pathological detection, enabling efficient classification and feature visualization, and offer a valuable reference for disease detection of physiological and pathological conditions in other fruit crops. Full article

Diaphorina citri is the primary global vector of “Candidatus Liberibacter asiaticus”, the bacterium responsible for Huanglongbing. Syntaxin-1A (Syx1A), a member of the Qa-SNARE family, is essential for vesicle fusion and signal transduction, though its function in hemipteran insects remains poorly understood. This study presents the first comprehensive analysis of Syx1A expression in D. citri. Transcripts were detected across all life stages, with peak expression in the salivary glands. RNAi silencing of Syx1A reduced mRNA levels by 39.0% in nymphs and 58.0% in adults, resulting in 58.3% nmortality in nymphs within 5 days and 73.3% in adults within seven days, along with significant weight loss. Treated females showed marked declines in fecundity, ovarian degeneration, and deficient yolk deposition. RT-qPCR confirmed significant downregulation of Vg1, VgA, and VgR. These findings establish Syx1A as a regulator of growth and reproduction in citrus psyllids via modulation of yolk synthesis. RNAi targeting of Syx1A represents a promising strategy for ecologically sound pest control and may contribute to efforts in halting the transmission of the Huanglongbing pathogen CLas. Full article

The systemic delivery of oxytetracycline (OTC) by trunk injection has emerged as a viable strategy to manage huanglongbing (HLB, also known as citrus greening), a bacterial disease devastating citrus production around the world. This study examines the efficacy of delivering OTC systemically into the trunk of young, HLB-affected citrus trees using a drill-based or a drill-free system to improve tree health and productivity. Two field trials were conducted in two commercial production sites in Florida. Trees were four years old at the start of the study and composed of ‘Valencia’ or ‘OLL-8’ sweet orange (Citrus sinensis) scion grafted on X-639 (C. reticulata × Poncirus trifoliata) rootstock. Injections were performed in spring or late summer/early fall in 2022 and 2023. Using the drill-based system, 0.79 g of OTC was administered into each tree, whereas 0.15 g or 0.3 g was administered using the drill-free system. Delivering a higher dose of OTC by drill-based injection increased fruit yield and improved juice quality more than delivering lower doses by drill-free injection, though responses varied between cultivars. Injections in late summer/early fall increased the juice total soluble solids content considerably more than injections in spring. However, fall injections resulted in OTC fruit residues exceeding the maximum allowed level. Trunk injury was more extensive when OTC was applied with the drill-free system than when it was applied with the drill-based system. Full article

The Asian citrus psyllid (Diaphorina citri) is an economically important pest of citrus as it is a vector of the bacterium (Candidatus Liberibacter asiaticus, CLas) that causes huanglongbing disease (HLB). Understanding the virome of D. citri is important for uncovering factors that influence vector competence, to support biosecurity surveillance, and to identify candidate agents for biological control. Previous studies have identified several D. citri-associated viruses from various geographical populations of this pest. To further investigate virus diversity in this pest, high-throughput sequencing was used to analyse D. citri populations from the Samoan islands of Upolu and Savai’i. Eleven novel viruses from the Yadokariviridae, Botourmiaviridae, Nodaviridae, Mymonaviridae, Partitiviridae, Totiviridae, and Polymycoviridae were identified as well as some that corresponded to unclassified groups. In addition, microbiome analysis revealed the presence of several endosymbiotic microorganisms, including Wolbachia, as well as some plant pathogenic fungi, including Botrytis cinerea. However, the causative agent of HLB disease (CLas) was not detected in the RNA-Seq data. These findings highlight the complex and diverse microbiota associated with D. citri and suggest potential interactions and dynamics between microorganisms and psyllid-associated viruses. Further research is needed to understand the ecological significance of these discoveries, and whether the novel viruses play a role in regulating field populations of the psyllid. Full article

Huanglongbing (HLB), caused by Candidatus Liberibacter asiaticus (CLas), is the most devastating disease threatening global citrus production. Although no commercial citrus varieties exhibit complete HLB resistance, genotype-specific tolerance variations remain underexplored. This study conducted a comparative transcriptomic profiling of six commercially citrus cultivars in South China, four susceptible cultivars (C. reticulata cv. Tankan, Gongkan, Shatangju, and C. sinensis Osbeck cv. Newhall), and two tolerant cultivars (C. limon cv. Eureka; C. maxima cv Guanxi Yu) to dissect molecular mechanisms underlying HLB responses. Comparative transcriptomic analyses revealed extensive transcriptional reprogramming, with tolerant cultivars exhibiting fewer differentially expressed genes (DEGs) and targeted defense activation compared to susceptible genotypes. The key findings highlighted the genotype-specific regulation of starch metabolism, where β-amylase 3 (BAM3) was uniquely upregulated in tolerant varieties, potentially mitigating starch accumulation. Immune signaling diverged significantly: tolerant cultivars activated pattern-triggered immunity (PTI) via receptor-like kinases (FLS2) and suppressed ROS-associated RBOH genes, while susceptible genotypes showed the hyperactivation of ethylene signaling and oxidative stress pathways. Cell wall remodeling in susceptible cultivars involved upregulated xyloglucan endotransglucosylases (XTH), contrasting with pectin methylesterase induction in tolerant Eureka lemon for structural reinforcement. Phytohormonal dynamics revealed SA-mediated defense and NPR3/4 suppression in Eureka lemon, whereas susceptible cultivars prioritized ethylene/JA pathways. These findings delineate genotype-specific strategies in citrus–CLas interactions, identifying BAM3, FLS2, and cell wall modifiers as critical targets for breeding HLB-resistant cultivars through molecular-assisted selection. This study provides a foundational framework for understanding host–pathogen dynamics and advancing citrus immunity engineering. Full article

Citrus Huanglongbing (HLB) is one of the most devastating diseases in the global citrus industry, but its early detection under complex field conditions remains a major challenge. Existing methods often suffer from insufficient dataset diversity and poor generalization, and struggle to accurately detect subtle early-stage lesions and multiple HLB symptoms in natural backgrounds. To address these issues, we propose an enhanced YOLO11-based framework, DCH-YOLO11. We constructed a multi-symptom HLB leaf dataset (MS-HLBD) containing 9219 annotated images across five classes: Healthy (1862), HLB blotchy mottling (2040), HLB Zinc deficiency (1988), HLB yellowing (1768), and Canker (1561), collected under diverse field conditions. To improve detection performance, the DCH-YOLO11 framework incorporates three novel modules: the C3k2 Dynamic Feature Fusion (C3k2_DFF) module, which enhances early and subtle lesion detection through dynamic feature fusion; the C2PSA Context Anchor Attention (C2PSA_CAA) module, which leverages context anchor attention to strengthen feature extraction in complex vein regions; and the High-efficiency Dynamic Feature Pyramid Network (HDFPN) module, which optimizes multi-scale feature interaction to boost detection accuracy across different object sizes. On the MS-HLBD dataset, DCH-YOLO11 achieved a precision of 91.6%, recall of 87.1%, F1-score of 89.3, and mAP50 of 93.1%, surpassing Faster R-CNN, SSD, RT-DETR, YOLOv7-tiny, YOLOv8n, YOLOv9-tiny, YOLOv10n, YOLO11n, and YOLOv12n by 13.6%, 8.8%, 5.3%, 3.2%, 2.0%, 1.6%, 2.6%, 1.8%, and 1.6% in mAP50, respectively. On a publicly available citrus HLB dataset, DCH-YOLO11 achieved a precision of 82.7%, recall of 81.8%, F1-score of 82.2, and mAP50 of 89.4%, with mAP50 improvements of 8.9%, 4.0%, 3.8%, 3.2%, 4.7%, 3.2%, and 3.4% over RT-DETR, YOLOv7-tiny, YOLOv8n, YOLOv9-tiny, YOLOv10n, YOLO11n, and YOLOv12n, respectively. These results demonstrate that DCH-YOLO11 achieves both state-of-the-art accuracy and excellent generalization, highlighting its strong potential for robust and practical citrus HLB detection in real-world applications. Full article

Sugar Belle^® mandarin is considered tolerant to Huanglongbing (HLB); however, recent reports have raised concerns about its fruit quality, noting issues such as reduced fruit size, thin peel, poor coloration, decreased firmness, and suboptimal juice quality. Two-year field experiments were conducted to improve external and internal fruit characteristics through foliar application of potassium (K) in five-year-old Sugar Belle mandarin grown in Florida sandy soil. The experiment consisted of foliar K supply (17 kg/ha) via Potassium Nitrate (PN, 4.7 kg/ha N), Dipotassium Phosphate (DKP, 12.7 kg/ha P₂O₅), PN with boron (PNB, 0.84 kg/ha B) at different application times (May, July, September), including one-time Gibberellic acid spray (GA@10 mg/L) and control treatments. PN application during July (PN_J) or two applications of PN with B during May and July (PNB_MJ) resulted in a larger fruit size (>65 mm). Results showed that PN application before fall (May or July) resulted in a significantly thicker peel (2.3 mm), 1.15 fold more than the control and GA treatment. Fruit puncture resistance force was significantly higher (33.1 N) with GA treatment (p = 0.07), followed by PNB_MJ (32.6 N). Meanwhile, K spray positively influenced juice qualities and peel color, regardless of application time or source. However, GA treatment significantly reduced juice quality and peel color. These findings highlighted the benefits of foliar K supply as PN to improve fruit qualities in HLB-affected citrus grown in sandy soil. Full article

Huanglongbing (HLB), caused mainly by Candidatus Liberibacter asiaticus (CLas), is a devastating disease threatening citrus production worldwide, leading to leaf mottling, fruit deformation, and significant yield losses. This study generated a comprehensive co-expression network analysis using RNA-seq data from 17 public datasets. Weighted gene co-expression network analysis (WGCNA) was applied to identify gene modules associated with citrus species, tissue types, and days post-infection (DPIs). These modules revealed significant enrichment in biological pathways related to stress responses, metabolic reprograming, ribosomal protein synthesis, chloroplast and plastid function, cellular architecture, and intracellular transport. The results offer a molecular framework for understanding HLB pathogenesis and host response. By elucidating module-specific functions and their correlation with species- and tissue-specific responses, this study provides a robust foundation for identifying key genetic targets. These insights facilitate breeding programs focused on developing HLB-tolerant citrus cultivars, contributing to the long-term sustainability and resilience of global citrus production. Full article

Huanglongbing (HLB), a globally devastating citrus disease, demands sophisticated mathematical modeling to decipher its complex transmission dynamics and inform optimized disease management protocols. This investigation develops an innovative compartmental framework that simultaneously incorporates two critical factors in HLB epidemiology: saturated removal rates of infected citrus trees and behavioral bias in vector movement patterns. Our study delves into the dynamics of non-spatial systems by analyzing the basic reproduction numbers, equilibria, bifurcation phenomena, and the stability of these equilibria. Additionally, we explore the impact of spatial factors on system stability. Results indicate that when the basic reproduction number $R_0<1$, the system may exhibit bistable behavior, while $R_0>1$ leads to a unique stable equilibrium. Notably, vector bias significantly enhances the likelihood of forward bifurcation, and the delay in the removal of diseased trees increases the risk of backward bifurcation. However, reaction–diffusion processes do not alter the stability of the system’s equilibria, and the spatial system lacks complex dynamic properties. This research offers valuable insights into the mechanisms driving HLB transmission and provides a foundation for developing effective control strategies. Full article

HLB is a severe and devastating disease affecting citrus plants, for which no cure is currently available. The pathogen CLas is an unculturable, phloem-limited α-proteobacterium associated with HLB. Phages, known for their ability to directly lyse pathogenic bacteria, have been widely recognized as effective control agents in both medical and agricultural fields. In this study, we identified 191 prophages across 48 Liberibacter genomes using comparative genomics and phylogenetic methods. These prophages were classified into 17 distinct types, with 13 novel types, named NF1 to NF13. Diversity analysis revealed that the number of prophages per genome ranged from one to eight, with an average of four. Annotation showed that the genome sizes of NF1–NF13 ranged from 10,160 bp to 72,736 bp, with an average size of 27,616 bp, containing between 7 and 66 genes (average: 27 genes). Further functional enrichment of the sequences within 5 kb upstream and downstream of the integration site identified six main aspects, involving four core biological processes: genome structure modification, gene expression regulation, stress response activation, and metabolic pathway modulation. It is speculated that the insertion of the prophage significantly impacts the host. Six virulence factors, including carB, clpC, flhA, algW, rffG, and IlpA, were identified in the prophages. Interestingly, prophages containing carB or clpC are predominantly found in CLas, which may contribute to the global colonization of CLas. Notably, among the 35 identified Type 4 prophages, 19 were found to be active. Type 4 is the only active prophage type, making it a promising candidate for developing phage therapy against CLas. This study is significant for a deeper understanding of the diversity of Liberibacter and the interactions between prophages and their hosts. Full article

Huanglongbing (HLB), also known as citrus greening, is a devastating disease affecting the citrus industry worldwide. This study aimed to investigate the transcriptional responses of two Rutaceae species, Ponkan Mandarin (susceptible) and Punctate Wampee (resistant), to HLB infection. Comparative transcriptome analysis was conducted to identify differentially expressed genes (DEGs) and pathways involved in defense mechanisms. The transcriptome data showed that in the susceptible Ponkan Mandarin, there were 1519 upregulated genes and 700 downregulated genes, while in the resistant Punctate Wampee variety, there were 1611 upregulated genes and 1727 downregulated genes. Upon infection, 297 genes were upregulated in both varieties, while 211 genes were downregulated in both. These genes included transcription factors from different families such as WRKY, ERF, and MYB. Ponkan Mandarin primarily relies on pathways like lignin synthesis and cell wall modification to defend against HLB, whereas Punctate Wampee mainly resists HLB by regulating cellular homeostasis and metabolism. Weighted Gene Co-expression Network Analysis (WGCNA) identified ten potential key resistance genes in the resistant Punctate Wampee variety, including genes involved in lignin biosynthesis and genes related to cellular signaling pathways. These findings not only enhance our understanding of the distinct defense mechanisms employed by citrus species against HLB infection but also offer novel perspectives for developing effective prevention and management strategies against this disease. Full article

This study develops a high-dimensional impulsive differential equation model to analyze Huanglongbing (HLB) transmission dynamics, incorporating seasonal fluctuations in vector psyllid populations and multi-pronged control measures: (1) periodic removal of infected/dead citrus trees to eliminate pathogen reservoirs and (2) non-uniform pesticide applications timed to disrupt psyllid life cycles. The model analytically derives the basic reproduction number ($R_0$) and proves the existence of a unique disease-free periodic solution. Theoretical analysis reveals a threshold-dependent stability: when $R_0<1$, the disease-free solution is globally asymptotically stable, ensuring pathogen extinction; when $R_0>1$, the system becomes uniformly persistent, indicating endemic HLB. Numerical simulations validate these findings and demonstrate that integrated interventions, combining psyllid population control and removal of infected plants, can significantly suppress HLB spread. The results provide a mathematical framework for optimizing intervention timing and intensity, offering actionable strategies for citrus growers. Full article

In agriculture, machine learning (ML) and deep learning (DL) have increased significantly in the last few years. The use of ML and DL for image classification in plant disease has generated significant interest due to their cost, automatization, scalability, and early detection. However, high-quality image datasets are required to train robust classifier models for plant disease detection. In this work, we have created an image dataset of 649 orange leaves divided into two groups: control (n = 379) and huanglongbing (HLB) disease (n = 270). The images were acquired with several smartphone cameras of high resolution and processed to remove the background. The dataset enriches the information on characteristics and symptoms of citrus leaves with HLB and healthy leaves. This enhancement makes the dataset potentially valuable for disease identification through leaf segmentation and abnormality detection, particularly when applying ML and DL models. Full article