Search Results (732)

The growing environmental pollution and the imminent depletion of natural resources highlight the need for alternative building materials derived from renewable sources, including those that promote waste recycling and biodegradability. One promising alternative is biocomposites produced from filamentous fungal mycelium. In Argentina, orange and lemon peels are among the most abundant organic waste generated by the citrus industry. This study explores the development of a sustainable insulating biocomposite using Pleurotus ostreatus mycelium grown on mixtures of citrus peels, paper, and cardboard. The test specimens were prepared using varying concentrations of these components. The resulting fungal biocomposite exhibited a density approximately ten times higher than expanded polystyrene, with drying shrinkage ranging from 28% to 51%, depending on the formulation. Key properties were evaluated, including compressive strength (${\sigma }_{10}$ = 7–33 kPa), bulk density ($\rho$ = 152–181 kg/m${}^3$), and thermal conductivity ($\lambda$ = 0.29–0.36 W/mK), indicating advantageous performance for thermal insulation in construction applications. Specimens containing orange peel also demonstrated repellent activity against Triatoma infestans, main vector of transmission of Chagas’ disease, attributed to the residual limonene content retained from the citrus peels. This fungal biocomposite aligns with principles of green chemistry and circular economy, offering a biodegradable, low-impact solution with potential use in construction. The citrus waste proved to be an effective substrate for mycelial growth, producing a material with desirable mechanical and thermal properties, and added resistance to biodeterioration. Full article

Citrus Huanglongbing (HLB) is one of the most destructive diseases in the global citrus industry; its pathogen is transmitted primarily by the Asian citrus psyllid (ACP), Diaphorina citri Kuwayama, making timely monitoring and control of ACP populations essential. Real-world ACP monitoring faces several challenges, including tiny targets easily confused with the background, noise amplification and spurious detections caused by textures, stains, and specular glare on yellow-boards, unstable localization due to minute shifts of small boxes, and strict constraints on parameters, computation, and model size for long-term edge deployment. To address these challenges, we focus on the yellow-board ACP monitoring scenario and create the ACP Yellow Sticky Trap Dataset (ACP-YSTD), which standardizes background and acquisition procedures, covering common interference sources. The dataset consists of 600 images with 3837 annotated ACP, serving as a unified basis for training and evaluation. On the modeling side, we propose TGSP-YOLO11, an improved YOLO11-based detector: the detection head is reconfigured to the two scales P2 + P3 to match tiny targets and reduce redundant paths; Guided Scalar Fusion (GSF) is introduced on the high-resolution branch to perform constrained, lightweight scalar fusion that suppresses noise amplification; ShapeIoU is adopted for bounding-box regression to enhance shape characterization and alignment robustness for small objects; and Network Slimming is employed for channel-level structured pruning, markedly reducing parameters, FLOPs, and model size to satisfy edge deployment, without degrading detection performance. Experiments show that on the ACP-YSTD test set, TGSP-YOLO11 achieves precision 92.4%, recall 95.5%, and F1 93.9, with 392,591 parameters, a model size of 1.4 MB, and 6.0 GFLOPs; relative to YOLO11n, recall increases by 4.6%, F1 by 2.4, and precision by 0.2%, while the parameter count, model size, and computation decrease by 84.8%, 74.5%, and 4.8%, respectively. Compared to representative detectors (SSD, RT-DETR, YOLOv7-tiny, YOLOv8n, YOLOv9-tiny, YOLOv10n, YOLOv12n, YOLOv13n), TGSP-YOLO11 improves recall by 33.9%, 19.0%, 8.5%, 10.1%, 6.3%, 4.6%, 6.9%, and 5.7%, respectively, and F1 by 19.9, 14.9, 5.1, 6.0, 2.6, 5.6, 3.6, and 3.9, respectively. Additionally, it reduces parameter count, model size, and computation by 84.0–98.8%, 74.5–97.9%, and 3.2–94.2%, respectively. Transfer evaluation indicates that on 20 independent yellow-board images not seen during training, the model attains precision 94.3%, recall 95.8%, F1 95.0, and 159.2 FPS. Full article

Early detection of plant diseases is key to ensuring food production, reducing economic losses, minimizing the use of agrochemicals, and maintaining the sustainability of the agricultural sector. Citrus plants, an important source of vitamin C, fiber, and antioxidants, are among the world’s most significant fruit crops but face threats such as canker and Huanglongbing (HLB), incurable diseases that require management strategies to mitigate their impact. Manual diagnosis, although common, I s imprecise, slow, and costly; therefore, efficient alternatives are emerging to identify diseases from early stages using Artificial Intelligence techniques. This study evaluated four deep learning models, specifically convolutional neural networks. In this study, we evaluated four convolutional neural network models (DenseNet121, ResNet50, EfficientNetB0, and MobileNetV2) to detect canker and HLB in citrus leaf images. We applied preprocessing and data-augmentation techniques; transfer learning via selective fine-tuning; stratified k-fold cross-validation; regularization methods such as dropout and weight decay; and hyperparameter-optimization techniques. The models were evaluated by the loss value and by metrics derived from the confusion matrix, including accuracy, recall, and F1-score. The best-performing model was EfficientNetB0, which achieved an average accuracy of 99.88% and the lowest loss value of 0.0058 using cross-entropy as the loss function. Since EfficientNetB0 is a lightweight model, the results show that lightweight models can achieve favorable performance compared to robust models, models that can be useful for disease detection in the agricultural sector using portable devices or drones for field monitoring. The high accuracy obtained is mainly because only two diseases were considered; consequently, it is possible that these results do not hold in a database that includes a larger number of diseases. Full article

This systematic review included 31 clinical trial articles examining the effects of natural compounds on Alzheimer’s disease (AD) and mild cognitive impairment (MCI), involving 3582 participants aged 50–90. Treatment durations ranged from 8 weeks to 2 years, with an average of 12.5 months. Notably, 11 studies focused on herbal extracts highlighting their prominence in current research. These extracts showed potential cognitive and neuroprotective benefits, although results varied across compounds and study designs. Other natural compounds—including flavonoids, polyphenols, omega-3 fatty acids, Aloe vera, Spirulina, and citrus phytochemicals—may provide cognitive and neuroprotective benefits, with ginseng and Ginkgo biloba combinations also showing promise. Curcumin and Melissa officinalis had limited effects, resveratrol showed mixed outcomes with some side effects, and matcha green tea may improve cognition and sleep quality. Despite generally favorable results, the studies varied considerably in design and quality; nonetheless, herbal extracts represent a prominent category of natural interventions in AD and MCI, underscoring the need for further large-scale, high-quality clinical trials to confirm their therapeutic potential. Full article

Alternaria brown spot is an important fungal disease in citrus. The infection of young citrus organs usually coincides with strong rainfall, which causes low efficiency of fungicides and the outbreak of this disease. Here, the microbiomes of the asymptomatic peels, the spot edge, and the center of citrus fruits were compared to reveal the commensal microbes as alternative control methods for the Alternaria pathogen. As the disease severity increased from the asymptomatic peels to the spot edge and the center, the bacterial communities were more severely changed than the fungal communities. Both the bacterial diversity, represented by the Shannon diversity index, and the bacterial composition and structure significantly decreased and altered, respectively. Increased Alternaria, in relative abundance, correlated positively with bacterial genera like Massilia and Sphingomonas, while negatively correlating with bacterial genera like Delftia and Pantoea. In addition, Alternaria fASV1 positively correlated with several top ASVs of 1174_901_12 and Sphingomonas. These results suggest that the bacterial communities respond to Alternaria brown spot by Alternaria–bacteria cross-kingdom interactions; these responsive bacteria are worth testing experimentally. Full article

Citrus leprosis (CL) and citrus zonate chlorosis (ZC) were first described in Brazil in the 1930s. Both diseases, which caused non-systemic lesions primarily characterized by chlorotic and/or necrotic spots, were associated with the presence of Brevipalpus mites. While CL has since been well characterized as being caused by viruses of the genera Cilevirus (family Kitaviridae) and Dichorhavirus (family Rhabdoviridae) and transmitted by several species of Brevipalpus mites, the causal agent of ZC remained unknown. In this study, we analyzed Citrus spp. samples exhibiting typical ZC symptoms using high-throughput sequencing (HTS) to determine the etiology of ZC. We examined historical herbarium specimens collected between 1933 and 1965 alongside fresh samples collected from 2016 to 2022. Our results identified the higrevirus hibiscus green spot virus 2 (HGSV2, Higrevirus waimanalo) as the causal agent of ZC. In addition, we report for the first time the presence of a higrevirus in continental America, expand the diversity of known kitaviruses infecting citrus in Brazil, and demonstrate the transmission of an higrevirus by Brevipalpus yothersi and B. papayensis. Full article

Diaphorina citri Kuwayama is a key pest of citrus and insect vector of Huanglongbing (HLB), also known as citrus greening disease, causing significant losses in Florida and other regions. The naturally occurring effective ladybeetle predators and their impact on D. citri reduced from years of insecticide use against this pest and are not available commercially. Additionally, most species are large-sized, while most eggs and neonates of D. citri are in hard-to-reach locations such as unopened leaves, which makes access difficult for them. We evaluated a commercially available small-sized predatory ladybeetle Rhyzobius lophanthae Blaisdell against D. citri immatures. A single adult consumed an average of 24.9 eggs and 8.7 first and second instar nymphs of D. citri within 24 h. Beetles exhibited Type II functional response against nymphs with an attack rate of 0.92 h⁻¹ and a handling time of 0.08 h. Their consumption rate increased with nymphal density up to twenty per shoot. In the field test, beetles lived 10 days longer when confined with new shoots infested with D. citri immatures in a voile fabric sleeve cage in citrus trees every two days, versus seven days. In an open field release of R. lophanthae in a citrus orchard, these ladybeetles were found foraging in sentinel and neighboring trees infested with D. citri. The consumption rate of R. lophanthae on D. citri immatures and its survival in Florida orchards suggest its potential for biological control and Integrated Pest Management. Full article

Background/Objectives: Chronic diseases linked to obesity represent a major global health challenge. Although pharmaceutical treatments show efficacy, their use is often limited by side effects. Methods: This study investigated the anti-obesity effects of acid-processed Citrus reticulata Blanco peels extract (CRBE) prepared through reflux extraction with 50% ethanol, followed by acid treatment using 3 M hydrogen chloride and neutralization. Results: Following acid treatment, the composition of the extract showed a marked increase in the 5-demethylated forms of polymethoxyflavones, particularly 5-demethylnobiletin (31.86 mg/g) and 5-demethyltangeretin (34.68 mg/g), whereas the concentrations of the typical citrus polymethoxyflavones, nobiletin (14.82 mg/g) and tangeretin (10.61 mg/g), decreased. Using 3T3-L1 preadipocytes, CRBE inhibited adipogenesis concentration dependently, substantially decreasing the expression of adipogenic transcription factors and lipid metabolism-related proteins. In ob/ob mice, oral CRBE substantially suppressed body weight gain without affecting food intake, while normalizing liver function indicators and improving serum lipid profiles by reducing total cholesterol, triglycerides, and low-density lipoprotein. Conclusions: Acid-processed CRBE effectively inhibits adipocyte differentiation and exhibits anti-obesity effects in vivo, offering potential as a natural agent for obesity management with minimal side effects. Full article

The extensive application of fungicides in citrus packinghouses to mitigate economic losses has resulted in the emergence of fungicide-resistant biotypes of Penicillium spp. Furthermore, many countries have implemented strict monitoring of fungicide residues to protect consumer health and the ecosystem. Maximum residue limits (MRLs) have been established in accordance with Codex Alimentarius standards, which present challenges for exports, as exceeding MRLs may restrict market access. This study aimed to identify fungicide-resistant strains of Penicillium spp. in a Moroccan citrus packinghouse and to assess the efficacy of GRAS (Generally Recognized As Safe) salts as eco-friendly alternatives for controlling these resistant strains through in vitro and in vivo tests. A total of 31 Penicillium isolates, labeled H₁ to H₃₁, were collected; 10 were identified as P. digitatum and 21 were identified as P. italicum. Resistance to thiabendazole (61.3%) and imazalil (58.1%) was notable, with some isolates showing dual resistance. In vitro, potassium sorbate, sodium benzoate, and sodium tetraborate salts were highly effective at inhibiting the mycelial growth of resistant isolates, at a concentration of 0.3% (p < 0.0001). In vivo tests on ‘Nadorcott’ fruits demonstrated that 2% and 4% salt solutions effectively prevented the development of green and blue molds caused by Penicillium spp. and showed strong curative effects, resulting in nearly 100% inhibition of most fungal isolates. Additionally, preventive salt treatments increased the accumulation of phenolic and flavonoid compounds, while in fruits treated with sodium benzoate, chitinase and peroxidase activities were significantly enhanced. Full article

Thaumatin-like proteins (TLPs), a subfamily of pathogenesis-related (PR) proteins, play a vital role in plant defense against pathogens. In this study, 23 CsTLP genes were identified in the Citrus sinensis genome. These genes encode proteins ranging from 203 to 512 amino acids, with molecular weights between 21.88 and 53.75 kDa, classifying them as small molecular weight proteins. The CsTLP genes are unevenly distributed across eight chromosomes, with chromosome 3 containing the highest number (6 genes). Subcellular localization predictions indicate that most CsTLPs are located in the extracellular space. Phylogenetic analysis with Arabidopsis thaliana TLPs classified the CsTLPs into 10 clades, with clade 5 being the largest. Three segmentally duplicated gene pairs were identified, suggesting a mechanism for the expansion of this gene family. Expression profiling revealed tissue-specific patterns, with the highest expression levels observed in roots and leaves. Under biotic stress, qRT-PCR analysis of 12 selected CsTLPs demonstrated pathogen-specific responses: CsTLP9 and CsTLP22 were strongly upregulated during Huanglongbing (HLB, bacterial) infection, by 21.70-fold and 9.47-fold, respectively. Multiple genes, including CsTLP5/13/18/21/23, exhibited over 10-fold upregulation following Citrus Anthracnose (CA, fungal) infection; however, most genes showed only weak responses to Citrus tristeza virus (CTV, viral). These findings underscore the regulatory significance of CsTLPs in pathogen responses and provide an important theoretical foundation for enhancing molecular disease-resistance breeding in Citrus sinensis. Full article

Huanglongbing (HLB), associated with the bacterial pathogen Candidatus Liberibacter asiaticus (CLas), is one of the most destructive diseases affecting citrus. Although some citrus cultivars are tolerant of the disease, no commercially resistant varieties exist to date. Resistance, however, has been identified in the sexually compatible distant relative, the Australian desert lime (C. glauca) and its F₁ hybrids. In an effort to develop commercial varieties with resistance to HLB, we produced interspecific hybrid populations between an HLB-resistant C. glauca × C. maxima F₁ hybrid and two mandarins (C. reticulata). The progenies were evaluated under natural CLas infection conditions in Florida for infection status, disease symptom severity, and growth to determine whether resistance or tolerance was manifested. After four years of evaluations, using two cluster analyses (K-means and hierarchical cluster), three groups were identified: (1) progeny that was uninfected, had very low infection levels or recovered from infection, and also had low defoliation and above average growth, (2) progeny that was infected and showed high defoliation and below average growth, and (3) progeny that was infected with generally high titters, low defoliation and above average growth. Overall, these results indicate the interspecific hybrid progeny in the field segregated into apparent resistant, susceptible and tolerant trees. Full article

Genetic truncation or mutation of the gene encoding band 4.1, ezrin, radixin, and moesin (FERM) domain protein containing 4A (FRMD4A) is associated with brain developmental diseases, including microcephaly with global developmental delay. It has also been identified as a risk factor for Alzheimer’s disease. By analogy with other FERM domain-containing proteins, FRMD4A is believed to regulate cell morphogenesis and/or cell polarization in central nervous system (CNS) cells; however, it remains unclear whether and how dysfunction of FRMD4A and/or its closely homologous protein FRMD4B causes abnormal morphogenesis in neuronal cells. Here, we describe for the first time the roles of FRMD4A and FRMD4B in process elongation in neuronal cells. Knockdown of Frmd4a or Frmd4b using specific RNA-targeting clustered regularly interspaced short palindromic repeat (CRISPR) and Cas13-fitted gRNAs led to decreased process elongation in primary cortical neurons. Similar decreases in neuronal marker expression were observed in the N1E-115 cell line, a model of neuronal differentiation. Furthermore, hesperetin, an aglycone of the citrus flavonoid hesperidin known to promote neuroprotective signaling, recovered the decreased process elongation induced by the knockdown of Frmd4a or Frm4b. Hesperetin also stimulated phosphorylation of mitogen-activated protein kinases/extracellular signal-regulated kinases (MAPKs/ERKs), which could help promote neuronal processes. These results suggest that FRMD4A and FRMD4B regulate process elongation through a possible signaling pathway linked to the sustained phosphorylation of MAPKs/ERKs. Crucially, this study reveals that, at the molecular and cellular levels, hesperetin can restore normal phenotypes when FRMD4A protein or FRMD4B protein is impaired. Full article

This study presents a robust and extensible hybrid classification framework for accurately detecting diseases in citrus leaves by integrating transfer learning-based deep learning models with classical machine learning techniques. Features were extracted using advanced pretrained architectures—DenseNet201, ResNet50, MobileNetV2, and EfficientNet-B0—and refined via the minimum redundancy maximum relevance (mRMR) method to reduce redundancy while maximizing discriminative power. These features were classified using support vector machines (SVMs), ensemble bagged trees, k-nearest neighbors (kNNs), and neural networks under stratified 10-fold cross-validation. On the lemon dataset, the best configuration (DenseNet201 + SVM) achieved 94.1 ± 4.9% accuracy, 93.2 ± 5.7% F1 score, and a balanced accuracy of 93.4 ± 6.0%, demonstrating strong and stable performance. To assess external generalization, the same pipeline was applied to mango and pomegranate leaves, achieving 100.0 ± 0.0% and 98.7 ± 1.5% accuracy, respectively—confirming the model’s robustness across citrus and non-citrus domains. Beyond accuracy, lightweight models such as EfficientNet-B0 and MobileNetV2 provided significantly higher throughput and lower latency, underscoring their suitability for real-time agricultural applications. These findings highlight the importance of combining deep representations with efficient classical classifiers for precision agriculture, offering both high diagnostic accuracy and practical deployability in field conditions. Full article

Detecting citrus Huanglongbing (HLB) in orchard environments is particularly challenging due to multi-scale targets and occlusions due to clustering, which manifest as complex and variable backgrounds, targets ranging from distant single leaves to nearby full canopies, and frequent instances where symptomatic leaves are hidden behind others, all significantly hindering accurate detection. To overcome these challenges, this study introduces a novel citrus object detection model, Multi-Scale Huanglongbing DETR (MSHLB-DETR), developed on the basis of an improved Real-Time DEtection TRansformer (RT-DETR). The model significantly enhances detection accuracy and efficiency for HLB under complex orchard conditions. To address the issue of small target feature loss in leaf detection, a new efficient transformer module called Smart Disease Recognition for Citrus Huanglongbing with Multi-scale (SDRM) is introduced. SDRM includes a space-to-depth (SPD) module and inverted residual mobile block (IRMB), which facilitate deep interaction between local and global features and significantly improve the computational efficiency of the transformer. Additionally, the transformer encoder incorporates a Context-Guided Block (CGBlock) for contextual feature learning. To evaluate the proposed model under complex background conditions, a dataset of 4367 images was collected from diverse orchard scenes, preprocessed, and divided into training, validation, and testing subsets. The experimental results demonstrate that the proposed MSHLB-DETR achieved the best detection performance on the test set, with an ${\mathrm{mAP}}_{50}$ of 96.0%, surpassing other state-of-the-art models of similar scale. Compared to the original RT-DETR, the proposed model increased ${\mathrm{mAP}}_{50}$ by 15.8%, reduced Params by 7.5%, and decreased GFLOPs by 5.2%. This study reveals the critical importance of developing efficient multi-scale detection techniques for the accurate identification of citrus Huanglongbing in complex real-time monitoring scenarios. The proposed algorithm is expected to provide valuable references and new insights for the precise and timely detection of citrus Huanglongbing. Full article

This retrospective review traces personal encounters along the complex path of plant yellowing diseases—graft-transmissible disorders historically attributed to elusive viruses, but later linked to phloem-invading, wall-less bacteria known as Mollicutes. These include two plant-infecting genera: the cultivable Spiroplasma and the non-cultivable ‘Candidatus Phytoplasma’. A third group—the walled, psyllid-transmitted Candidatus Liberibacter—was later implicated in closely similar syndromes. This shift in understanding marked a major turning point in plant pathology, offering new insights into yellowing diseases characterized by stunting, decline, and poor or deformed growth. The review focuses on key syndromes: citrus little leaf disease (LLD), or citrus stubborn disease (CSD), caused by Spiroplasma citri; and several Mollicute -related disorders, including safflower phyllody, Bermuda grass yellowing, and papaya dieback (PDD) (Nivun Haamir), the latter linked to ‘Candidatus Phytoplasma australiense’. Despite differing causes and vectors, citrus LLD-CSD and PPD share an erratic, unpredictable pattern of natural outbreaks—sometimes a decade apart—hindering grower engagement and sustained control efforts. While scientific understanding has deepened, practical management remains limited. The recent global spread of Huanglongbing (HLB), caused by Candidatus Liberibacter species, underscores the urgent need for improved strategies to manage this resilient group of phloem-limited bacterial pathogens. Full article