Search Results (33)

Walnut (Juglans regia L.), a critical economic species, experiences substantial declines in fruit quality and yield due to Walnut Leaf Scorch (WLS). This issue is particularly severe in the Xinjiang Uygur Autonomous Region (XUAR)—one of Asia’s leading walnut-producing regions. To mitigate the disease, timely and efficient monitoring approaches for detecting infected trees and quantifying their disease severity are in urgent demand. In this study, we explored the feasibility of developing a predictive model for the precise quantification of WLS severity. First, five 4-mu (1 mu = 0.067 ha) sample plots were established to identify infected individual trees, from which the WLS Disease Index (DI) was calculated for each tree. Concurrently, hyperspectral data of individual trees were acquired via an unmanned aerial vehicle (UAV) platform. Second, DI estimation models were developed based on the Random Forest (RF) and Support Vector Machine (SVM) algorithms, with each algorithm optimized using either Grid Search (GS) or a Genetic Algorithm (GA). Finally, four integrated models (GS-RF, GA-RF, GS-SVM, and GA-SVM) were constructed and systematically compared. The results showed that the Genetic Algorithm-optimized SVM model (GA-SVM) exhibited the highest predictive accuracy and robustness, achieving a coefficient of determination (R²) of 0.6302, a Root Mean Square Error (RMSE) of 0.0629, and a Mean Absolute Error (MAE) of 0.0480. Our findings demonstrate the great potential of integrating UAV-based hyperspectral remote sensing with optimized machine learning algorithms for WLS monitoring, thus offering a novel technical approach for the macroscopic, rapid, and non-destructive surveillance of this disease. Full article

Macadamia integrifolia, a tropical and subtropical fruit tree with significant economic and nutritional value, faces serious fungal disease problems during cultivation that severely affect yield and quality. In November 2024, leaf blight symptoms of M. integrifolia were observed in Menglian, Pu’er, Yunnan, China, with a disease incidence of 23% in the field. Initial symptoms included small spots that enlarged into circular to irregular lesions with red-brown centers and brown to black margins. Finally, the leaves turned yellow and became scorched, eventually leading to massive leaf shedding. Infected leaf samples were collected, and fungal strains were isolated, purified, and inoculated via spore suspension, followed by re-isolation. The strains were conclusively identified as Pestalotiopsis colombiensis (SWFUCB2, SWFUCB1) through an integrated approach combining DNA extraction, polymerase chain reaction (PCR), sequencing, phylogenetic reconstruction, and morphological characterization. This is the first report of P. colombiensis causing M. integrifolia leaf blight disease in China, filling a gap in research on this disease. This study provided important information for epidemiological research on this disease and the development of comprehensive leaf blight disease control strategies. Full article

The intelligent transformation of crop leaf disease detection has driven the use of deep neural network algorithms to develop more accurate disease detection models. In resource-constrained environments, the deployment of crop leaf disease detection models on the cloud introduces challenges such as communication latency and privacy concerns. Edge AI devices offer lower communication latency and enhanced scalability. To achieve the efficient deployment of crop leaf disease detection models on edge AI devices, a dataset of 700 images depicting peanut leaf spot, scorch spot, and rust diseases was collected. The YOLOX-Tiny network was utilized to conduct deployment experiments with the peanut leaf disease detection model on the Jetson Nano B01. The experiments initially focused on three aspects of efficient deployment optimization: the fusion of rectified linear unit (ReLU) and convolution operations, the integration of Efficient Non-Maximum Suppression for TensorRT (EfficientNMS_TRT) to accelerate post-processing within the TensorRT model, and the conversion of model formats from number of samples, channels, height, width (NCHW) to number of samples, height, width, and channels (NHWC) in the TensorFlow Lite model. Additionally, experiments were conducted to compare the memory usage, power consumption, and inference latency between the two inference frameworks, as well as to evaluate the real-time video detection performance using DeepStream. The results demonstrate that the fusion of ReLU activation functions with convolution operations reduced the inference latency by 55.5% compared to the use of the Sigmoid linear unit (SiLU) activation alone. In the TensorRT model, the integration of the EfficientNMS_TRT module accelerated post-processing, leading to a reduction in the inference latency of 19.6% and an increase in the frames per second (FPS) of 20.4%. In the TensorFlow Lite model, conversion to the NHWC format decreased the model conversion time by 88.7% and reduced the inference latency by 32.3%. These three efficient deployment optimization methods effectively decreased the inference latency and enhanced the inference efficiency. Moreover, a comparison between the two frameworks revealed that TensorFlow Lite exhibited memory usage reductions of 15% to 20% and power consumption decreases of 15% to 25% compared to TensorRT. Additionally, TensorRT achieved inference latency reductions of 53.2% to 55.2% relative to TensorFlow Lite. Consequently, TensorRT is deemed suitable for tasks requiring strong real-time performance and low latency, whereas TensorFlow Lite is more appropriate for scenarios with constrained memory and power resources. Additionally, the integration of DeepStream and EfficientNMS_TRT was found to optimize memory and power utilization, thereby enhancing the speed of real-time video detection. A detection rate of 28.7 FPS was achieved at a resolution of 1280 × 720. These experiments validate the feasibility and advantages of deploying crop leaf disease detection models on edge AI devices. Full article

Xylella fastidiosa (Xf) is a quarantine pathogen heavily affecting economically important crops worldwide. Different sequence types (STs) belonging to Xf subspecies are present in various areas of Spain, including the Balearic Islands, and cause the almond leaf scorch disease (ALSD) in Prunus spp. The increased demand for rapid tests for early detection of the pathogen should enforce strict containment measures. Molecular detection through isothermal amplification reactions enables simplified instrumentation and the use of raw nucleic acid extracts. Colorimetric loop-mediated isothermal amplification (cLAMP) was applied to rapidly detect Xf in naturally infected almonds on Mallorca Island (Spain), using a quick crude sap extraction without DNA purification. Following tissue homogenization, an alkaline treatment for target DNA extraction was conducted before the cLAMP test. The cLAMP assay was able to detect up to 100 CFU/mL of the Xf bacterial suspension diluted in healthy almond sap. The same crude extracts used in the cLAMP test were also tested by qPCR. An overall positive agreement of about 47% was observed between the results of the two techniques, while a decrease in cLAMP sensitivity was evident as the bacterial titer declined in infected plants over Cq > 26–27. This study shows the potential of the cLAMP application as a rapid and low-cost point-of-care diagnostic method for the timely monitoring of Xf directly in the field. Full article

Xylella fastidiosa is an aerobic, Gram-negative bacterium that is responsible for many plant diseases. The bacterium is the causal agent of Pierce’s disease in grapes and is also responsible for citrus variegated chlorosis, peach phony disease, olive quick decline syndrome and leaf scorches of various species. The production of biofilm is intrinsically linked with persistence and transmission in X. fastidiosa. Biofilm formation is regulated by members of the Diffusible Signal Factor (DSF) quorum sensing signalling family which are comprised of a series of long chain cis-unsaturated fatty acids. This article describes the evaluation of a library of N-acyl sulfonamide bioisosteric analogues of BDSF, XfDSF1 and XfDSF2 for their ability to control biofilm production in X. fastidiosa. The compounds were screened against both the wild-type strain Temecula and an rpfF* mutant which can perceive but not produce XfDSF. Planktonic cell abundance was measured via OD600 while standard crystal violet assays were used to determine biofilm biomass. Several compounds were found to be effective biofilm inhibitors depending on the nature of the sulfonamide substituent. The findings reported here may provide future opportunities for biocontrol of this important plant pathogen. Full article

Olive tree orchards are suffering from wildfires in many Mediterranean countries. Following a wildfire event, identifying damaged olive trees is crucial for developing effective management and restoration strategies, while rapid damage assessment can support potential compensation for producers. Moreover, the implementation of real-time health monitoring in olive groves allows producers to carry out targeted interventions, reducing production losses and preserving crop health. This research examines the use of deep learning methodologies in true-color images from Unmanned Aerial Vehicles (UAV) to detect damaged trees, including withering and desiccation of branches and leaf scorching. More specifically, the object detection and image classification computer vision techniques area applied and compared. In the object detection approach, the algorithm aims to localize and identify burned/dry and unburned/healthy olive trees, while in the image classification approach, the classifier categorizes an image showing a tree as burned/dry or unburned/healthy. Training data included true color UAV images of olive trees damaged by fire obtained by multiple cameras and multiple flight heights, resulting in various resolutions. For object detection, the Residual Neural Network was used as a backbone in an object detection approach with a Single-Shot Detector. In the image classification application, two approaches were evaluated. In the first approach, a new shallow network was developed, while in the second approach, transfer learning from pre-trained networks was applied. According to the results, the object detection approach managed to identify healthy trees with an average accuracy of 74%, while for trees with drying, the average accuracy was 69%. However, the optimal network identified olive trees (healthy or unhealthy) that the user did not detect during data collection. In the image classification approach, the application of convolutional neural networks achieved significantly better results with an F1-score above 0.94, either in the new network training approach or by applying transfer learning. In conclusion, the use of computer vision techniques in UAV images identified damaged olive trees, while the image classification approach performed significantly better than object detection. Full article

Xylella fastidiosa (Xf), a gram-negative bacterium, is a notorious, world-wide plant pathogen with an extended latent period that presents a challenge for early disease detection and control interventions. We used thermal imaging of tissue-cultured, experimentally Xf-infected blueberry plants to identify visually pre-symptomatic leaves and compared the minimum force required to dislodge symptomatic leaves from infected plants to leaves on uninfected (control) blueberry plants. For two different blueberry cultivars and one pathogenic isolate of X. fastidiosa, we found no statistical difference between the mean downward force for leaf dislodgement, regardless of symptom category, on Xf-infected blueberry plants. That force was about 50% to 30% of the mean force to remove leaves from uninfected blueberry plants depending on the cultivar. These results indicate that visually pre-symptomatic leaves may be just as readily lost under field conditions as visually symptomatic leaves, both of which are important for early disease detection. Second, some thermally symptomatic and visually symptomatic leaves appeared to self-prune (abscise) and this may be an unrecognized early symptom of Xf-caused disease in blueberries. Last, it is possible that the self-pruning of visually asymptomatic leaves may occur in other agriculturally and culturally important plants infected by X. fastidiosa, but this remains an unrecognized early disease symptom. Full article

Olive Quick Decline Syndrome (OQDS) associated with Xylella fastidiosa subsp. pauca is one of the most destructive diseases of olive trees in the Salento Peninsula (Southern Italy), particularly on the cultivars Cellina di Nardò and Ogliarola Salentina. This study proposes the NuovOlivo protocol as a management strategy to permit coexistence between X. fastidiosa subsp. pauca and olive drupes and extra-virgin oil production. Thirty-two private olive orchards affected by OQDS and cultivated following the standard agronomic techniques in use in the area were surveyed during the 2019–2023 olive-growing seasons. Tested cultivars included Cellina di Nardò, Ogliarola Salentina, Coratina, Ascolana Tenera, Nociara, Leccino, and Bella di Cerignola. At the beginning of the protocol application, the susceptible plants showed OQDS symptom severity of 40–80% and did not produce olives or oil, while the resistant(?)/tolerant cultivars exhibited a 2–8% leaf scorch and a drupe production less than 1–2 kg/plant. After the removal of dry branches in January–February, plants were sprayed two times per year (preferably in March and October) with NuovOlivo^®, a mixture of aqueous botanical extracts esterified in the presence of sodium hydroxide with vegetable oils and activated at the time of use with sodium bicarbonate. In all the orchards, a slow-release fertilizer was distributed, and weeds were controlled by mowing or chopping. Upon eventual appearance, the dry twigs were removed. Treated olive trees produced new vegetation, rebuilt their foliage, reduced OQDS symptoms, and turned out cluster inflorescence and drupes. The drupes yield was 6.67–51.36 kg per plant, with an average of 13.19% in extra-virgin olive oil (free acidity 0.01–0.2%). Plants used as controls showed OQDS symptoms and were unproductive, and newly formed shoots were desiccated. The proposed protocol promotes, supports, and restores new vegetation, flowers, fruits, and oil production of the treated olive plants affected by OQDS without losing susceptible olive plants. The Apulian landscape and economy, based on olive presence and production, could be also safeguarded. Full article

The detection of Xylella fastidiosa in Portugal occurred through prospection in 2019 in Vila Nova de Gaia, Porto, in plants of Lavandula dentata L. Currently, in Portugal, there are 18 Xylella fastidiosa Demarcated Zones (DZs). The main objective of this study is to gain a comprehensive understanding of this problem within the defined Demarcated Zones in the North Region of Portugal from 2019 to June 2023. This work comprised two phases: the prospection phase (inspecting plants, sampling, and submission of samples to the laboratory) and the research phase (collecting and organizing data and statistical treatment). Our findings provide essential insights, suggesting that the Northern Region of Portugal is highly conducive to Xylella fastidiosa. Portugal has Xf-preferred hosts such as the olive tree, orange tree, Laurus nobilis, Rosa spp., Nerium oleander L., Pelargonium sp., Hedera helix L., and Lavandula dentata L. Portugal’s favorable environmental factors such as temperature and humidity can have an important role in influencing the interaction between bacteria and hosts. Nevertheless, it is crucial to consider variations in the behavior of insect vectors, as these variations can limit the prevalence of the disease. Activities like the transport of infected planting materials from the first Demarcated Zone of the Area Metropolitana do Porto could be associated with the introduction and spread of Xylella fastidiosa, potentially triggering new disease outbreaks in the country. Our findings confirm the alarming spread of Xylella fastidiosa across Portugal. Factors such as the presence of insect vectors, abundance of host plants, and climate suitability play pivotal roles in Xylella fastidiosa dispersal. We recommend that countries identified with relatively high risk, like Portugal, undertake thorough individual risk analyses. The implementation of preventive measures and, if necessary, the enhancement of surveillance systems for early detection of Xylella fastidiosa in plants and insect vectors are crucial steps. Full article

Increasing the ultraviolet radiation (UV) level, particularly UV-B due to damage to the stratospheric ozone layer by human activities, has huge negative effects on plant and animal metabolism. As a widely grown cool-season forage grass and turfgrass in the world, perennial ryegrass (Lolium perenne) is UV-B-sensitive. To study the effects of miR164, a highly conserved microRNA in plants, on perennial ryegrass under UV stress, both OsmiR164a overexpression (OE164) and target mimicry (MIM164) transgenic perennial ryegrass plants were generated using agrobacterium-mediated transformation, and UV-B treatment (~600 μw cm⁻²) of 7 days was imposed. Morphological and physiological analysis showed that the miR164 gene affected perennial ryegrass UV tolerance negatively, demonstrated by the more scorching leaves, higher leaf electrolyte leakage, and lower relative water content in OE164 than the WT and MIM164 plants after UV stress. The increased UV sensitivity could be partially due to the reduction in antioxidative capacity and the accumulation of anthocyanins. This study indicated the potential of targeting miR164 and/or its targeted genes for the genetic manipulation of UV responses in forage grasses/turfgrasses; further research to reveal the molecular mechanism underlying how miR164 affects plant UV responses is needed. Full article

Lighting conditions are an important controller of plant growth and development, and they affect secondary metabolite synthesis. In this research, we explored the effect of additional UV irradiation of various ranges in addition to the main one at PPFD 160 µmol m⁻² s⁻¹ on the accumulation of some secondary metabolites of stevia (Stevia rebaudiana Bertoni). The fresh weight of leaves was slightly higher under additional UV-A and UV-B irradiation compared with the control variant, and the leaf surface area was significantly larger, respectively, by 23.3 and 20.7% than in the control variant, while the rate of photosynthesis did not decrease. Plants under additional UV-B and UV-C irradiation were under the greatest light stress, as evidenced by a decrease in antioxidant capacity by an average of 30% compared to the control and UV-A. The total flavonoid content was significantly higher (by 74%) under UV-B irradiation. The highest concentration of steviol glycoside was observed during budding and flowering under UV-B and UV-C irradiation (by 13.2 and 11.3%, respectively). Analysis of hyperspectral images, chlorophyll fluorescence, and vegetation indices showed light stress increasing under UV-C irradiation, which caused an increase in the relative chlorophyll content, scorches, leaf morphology changes, a CO₂ absorption rate decrease, and plant growth inhibition. UV-B irradiation can be used as an optimal type of irradiation based on a set of indicators. Full article

The impact of Xylella fastidiosa (Xf) subsp. pauca on the environment and economy of Southern Italy has been devastating. To restore the landscape and support the local economy, introducing new crops is crucial for restoring destroyed olive groves, and the almond tree (Prunus dulcis Mill. D. A. Webb) could be a promising candidate. This work focused on the resistance of the cultivar “Filippo Ceo” to Xf and evaluated its physiological and molecular responses to individual stresses (drought or pathogen stress) and combined stress factors under field conditions over three seasons. Filippo Ceo showed a low pathogen concentration (≈10³ CFU mL⁻¹) and a lack of almond leaf scorch symptoms. Physiologically, an excellent plant water status was observed (RWC 82–89%) regardless of the stress conditions, which was associated with an increased proline content compared to that of the control plants, particularly in response to Xf stress (≈8-fold). The plant’s response did not lead to a gene modulation that was specific to different stress factors but seemed more indistinct: upregulation of the LEA and DHN gene transcripts by Xf was observed, while the PR transcript was upregulated by drought stress. In addition, the genes encoding the transcription factors (TFs) were differentially induced by stress conditions. Filippo Ceo could be an excellent cultivar for coexistence with Xf subps. pauca, confirming its resistance to both water stress and the pathogen, although this similar health status was achieved differently due to transcriptional reprogramming that results in the modulation of genes directly or indirectly involved in defence strategies. Full article

Xylella fastidiosa, a gram-negative bacterium vectored to plants via feeding of infected insects, causes a number of notorious plant diseases throughout the world, such as Pierce’s disease (grapes), olive quick decline syndrome, and coffee leaf scorch. Detection of Xf in infected plants can be challenging because the early foliar disease symptoms are subtle and may be attributed to multiple minor physiological stresses and/or borderline nutrient deficiencies. Furthermore, Xf may reside within an infected plant for one or more growing seasons before traditional visible diagnostic disease symptoms emerge. Any method that can identify infection during the latent period or pre-diagnostic disease progress state could substantially improve the outcome of disease control interventions. Because Xf locally and gradually impairs water movement through infected plant stems and leaves over time, infected plants may not be able to effectively dissipate heat through transpiration-assisted cooling, and this heat signature may be an important pre-diagnostic disease trait. Here, we report on the association between thermal imaging, the early stages of Xf infection, and disease development in blueberry plants, and discuss the benefits and limitations of using thermal imaging to detect bacterial leaf scorch of blueberries. Full article

Camptotheca acuminata Witches’-broom disease (CaWB) is the most destructive disease affecting C. acuminata in China. Previous studies on CaWB have failed to clarify the incidence pattern in C. acuminata after infection with phytoplasma. The time interval between phytoplasma infection of C. acuminata and the onset of Witches’-broom symptoms in C. acuminata was very long. C. acuminata inoculated with CaWB showed leaf margin scorching symptoms at 4 weeks in inoculated leaves. At 16 weeks after infection (WAI), old leaves were shed, while new leaves showed a mild leaf margin scorch; at 28 WAI, typical symptoms appeared. Transcriptomic and metabolomic analyses of the three sampling periods revealed 194 differentially expressed genes, mainly enriched in MAPK signaling, plant–pathogen interaction, phenylpropanoid biosynthesis, starch and phenylpropanoid biosynthesis, and phenylpropanoid biosynthesis pathways. The expression of calcium-dependent protein kinase (CDPK), β Ketoacyl-CoA Synthase1/10 (KCS1/10), and WRKY22/29 genes in the plant–pathogen interaction pathway significantly increased, indicating that they may be key genes in the CaWB phytoplasma-mediated maintenance of ROS homeostasis. Moreover, isochlorogenic acid B, atractylenolide II, and 3-methoxybenzoic acid were found, which might serve as signaling or functional substances in the defense response. Our results provide novel insights into the pathogenesis of CaWB and the defense response of C. acuminata under the influence of phytoplasma. Additionally, we identified potential candidate genes related to the defense response of C. acuminata, laying the foundation for further research. Full article

Xylella fastidiosa (Xf) is classified as a quarantine pest due to its consequences on economically significant crops. Its main form of transmission in Europe is through the insect Philaenus spumarius. Due to climate change, the populations of insect vectors have become more extensive, resulting in the dissemination of the bacteria over longer periods, but the destruction of these insects raises issues due to their role in nature. Upon infection, Xf causes the occlusion of xylem vessels via bacterial aggregates and tylosis production by the plant as a response to infection. Although symptomatic manifestations of Xf are often linked to water stress, a variety of plant species have been found to carry the pathogen without symptoms, making it all too easy to evade detection when relying on visual inspections. Beyond water stress, other conditions (individual plant resistance/tolerance, bacterial concentrations, transpiration rates, and interactions between subspecies) may be implicated in symptom development. A thorough understanding of how this disease develops, especially its capacity to spread from the initial focus and establish a systemic infection, is imperative. This review focuses on the Xf infection process, the development of symptoms, its spread within Portugal, and the actions that have been taken to counter it. Full article