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Water-associated or water-related infectious disease outbreaks are caused by pathogens such as bacteria, viruses, and protozoa, which can be transmitted through contaminated water sources, poor sanitation practices, or insect vectors. Low- and middle-income countries bear the major burden of these infections due to inadequate hygiene and subpar laboratory facilities, making it challenging to monitor and detect infections in a timely manner. However, even developed countries are not immune to these diseases, as inadequate wastewater management and contaminated drinking water supplies can also contribute to disease outbreaks. Nucleic acid amplification tests have proven to be effective for early disease intervention and surveillance of both new and existing diseases. In recent years, paper-based diagnostic devices have made significant progress and become an essential tool in detecting and managing water-associated infectious diseases. In this review, we have highlighted the importance of paper and its variants as a diagnostic tool and discussed the properties, designs, modifications, and various paper-based device formats developed and used for detecting water-associated pathogens. [Display omitted] [ABSTRACT FROM AUTHOR]

The Main Aim of this project is to identify the Green and effected leaf with the help of raspberry pi and agricultural sensors. This study addressed a framework for detecting and preventing the transmission of plant disease using Raspberry PI. For image processing, the k means clustering algorithm was used. It has a variety of focus points for use in large harvest ranches, and it naturally distinguishes signs of illness anywhere they appear on plant leaves. The recognition of leaf disease is a key theme in pharmaceutical science since it has the benefits of tracking crops in the field in the form and thereby automatically identifies signs of disease by image processing using a clustering k-means algorithm. The word "disease" describes the form of plant damage that occurs. This paper demonstrates the most effective technique for detecting plant infections using the ideas of image processing and alerting the disease name through e-mail, SMS text, and presenting the disease name on the framework proprietor's screen monitor. Disease signs may be detected automatically, which is helpful for improving agricultural goods. The chemical application would benefit greatly from fully automated design and deployment of these technologies. Pesticides and other ingredients would be less expensive. Farm production will rise as a result of this. This system has usb camera, temperature, humidity sensor, fertilizer, GSM and Raspberry pi. All these sensors are interfaced to the raspberry pi. This system continuously monitors the all the environment conditions and display on monitor. If effected leaf detected at any place, then this system automatically sprays the fertilizer on crop. So that this system makes better and user friendly system for formers. [ABSTRACT FROM AUTHOR]

This study aims to detect and prevent greening disease in citrus trees using a deep neural network. The process of collecting data on citrus greening disease is very difficult because the vector pests are too small. In this paper, since the amount of data collected for deep learning is insufficient, we intend to use the efficient feature extraction function of the neural network based on the Transformer algorithm. We want to use the Cascade Region-based Convolutional Neural Networks (Cascade R-CNN) Swin model, which is a mixture of the transformer model and Cascade R-CNN model to detect greening disease occurring in citrus. In this paper, we try to improve model safety by establishing a linear relationship between samples using Mixup and Cutmix algorithms, which are image processing-based data augmentation techniques. In addition, by using the ImageNet dataset, transfer learning, and stochastic weight averaging (SWA) methods, more accuracy can be obtained. This study compared the Faster Region-based Convolutional Neural Networks Residual Network101 (Faster R-CNN ResNet101) model, Cascade Region-based Convolutional Neural Networks Residual Network101 (Cascade R-CNN- ResNet101) model, and Cascade R-CNN Swin Model. As a result, the Faster R-CNN ResNet101 model came out as Average Precision (AP) (Intersection over Union (IoU)=0.5): 88.2%,AP(IoU=0.75): 62.8%,Recall: 68.2%, and the Cascade R-CNN ResNet101 model was AP(IoU=0.5): 91.5%, AP (IoU=0.75): 67.2%, Recall: 73.1%. Alternatively, the Cascade R-CNN Swin Model showed AP (IoU=0.5): 94.9%, AP (IoU=0.75): 79.8% and Recall: 76.5%. Thus, the Cascade R-CNN Swin Model showed the best results for detecting citrus greening disease. [ABSTRACT FROM AUTHOR]

Given the severe impact of Citrus Huanglongbing on orchard production, accurate detection of the disease is crucial in orchard management. In the natural environments, due to factors such as varying light intensities, mutual occlusion of citrus leaves, the extremely small size of Huanglongbing leaves, and the high similarity between Huanglongbing and other citrus diseases, there remains an issue of low detection accuracy when using existing mainstream object detection models for the detection of citrus Huanglongbing. To address this issue, we propose YOLO-EAF (You Only Look Once–Efficient Asymptotic Fusion), an improved model based on YOLOv8n. Firstly, the Efficient Multi-Scale Attention Module with cross-spatial learning (EMA) is integrated into the backbone feature extraction network to enhance the feature extraction and integration capabilities of the model. Secondly, the adaptive spatial feature fusion (ASFF) module is used to enhance the feature fusion ability of different levels of the model so as to improve the generalization ability of the model. Finally, the focal and efficient intersection over union (Focal–EIOU) is utilized as the loss function, which accelerates the convergence process of the model and improves the regression precision and robustness of the model. In order to verify the performance of the YOLO-EAF method, we tested it on the self-built citrus Huanglongbing image dataset. The experimental results showed that YOLO-EAF achieved an 8.4% higher precision than YOLOv8n on the self-built dataset, reaching 82.7%. The F1-score increased by 3.33% to 77.83%, and the mAP (0.5) increased by 3.3% to 84.7%. Through experimental comparisons, the YOLO-EAF model proposed in this paper offers a new technical route for the monitoring and management of Huanglongbing in smart orange orchards. [ABSTRACT FROM AUTHOR]

Background: Murraya koenigii (L.) Spreng. has several well-established nutritional and therapeutic applications. Following our desire to investigate the global and scientific community's knowledge of medicinal plants, this study was intended to examine the evolution of knowledge related to M. Koenigii studies. The primary purpose of this paper is to clarify the status of these studies, investigate their methods, findings, and trends, and define their significance within the current research landscape. Results: To achieve these goals, bibliometric analysis was conducted, retrieving, and analyzing 934 original articles published between 1965 and 2023 based on Scopus Dataset results. Data were exported as CVS (comma-separated values) and BibTex files and analyzed using Bibliometrix and VOSviewer software. Articles from 502 sources have been identified, averaging 21.8 citations per document. The research in this plant has had exponential growth (R2 = 0.77). International co-authorship is 13.08%. India and Malaysia are the top publishing countries. Debajo, A.C. (Nigeria), Phatak,R.S. (India), and Sukari,M.A. (Malaysia) are the most productive authors. The top source is the Journal of Ethnopharmacology. "Green synthesis," "nanoparticles," "oxidative stress," "Asian citrus psyllid," "apoptosis," "antimicrobial," "anticancer," "Chromatographic profile," "bioactive compounds," and "alkaloids" are strongly related to the current trends in M. Koenigii research. Regarding the specialized topics, M. Koenigii's study concentrated on using this plant as an antioxidant agent in manufacturing and biological systems. Dynamic subjects like chromatographic profiles, essential oils, and Asian citrus psyllids were included in the motor theme. Conclusions: The current study used bibliometric techniques to evaluate research on M. Koenigii and identify trends and potential future research hot spots. [ABSTRACT FROM AUTHOR]

The citrus industry is of great importance in Mexico, with an estimated production value of USD 2.4 billion and the potential to generate up to 28 million employees per year. Approximately 69,000 Mexican families depend on this sector. However, it is under serious threat from the disease known as Huanglongbing (HLB). The rapid spread of this disease has caused significant economic losses, impacted the livelihoods of citrus growers, and led to substantial job losses. Currently, HLB is not under control in Mexico, and as the management strategies applied have proven to be ineffective, yields have not been recovered to pre-HLB levels, and production costs have significantly increased. Therefore, it remains the most destructive citrus disease. This review paper describes the current situation of the disease, its economic and social impact, and the measures adopted for its management in Mexico. Future perspectives highlight advances in research based on new biotechnological tools as an eco-friendly management alternative. Practical suggestions to address HLB are also mentioned in our analysis. [ABSTRACT FROM AUTHOR]

Potato is one of the most nutritious foods rich in fiber and essential vitamins and minerals. However, potato plants may suffer from diseases such as early blight, late blight, septoria leaf spot or skin diseases such as greening, silver scurf, common scab, black rot etc. These diseases may lead to huge losses in the potato yield annually. Hence, an early prediction of such diseases is required so that they can be controlled at an early stage. Several machine learning, IoT based and image processing techniques have been utilized for this purpose, and this paper aims to survey all such methods and prediction models. A total of 116 studies were analyzed, and out of them, 77 relevant studies belonging to (60%) journals, (34%) conferences and (6%) other sources have been surveyed. It has been observed that most of the selected studies (64%) have used RGB image data (proprietary or PlantVillage dataset). Also, majority of the studies (48%) have worked with imbalanced data. Late blight and early blight are the two diseases that have gained the most attention by the researchers, being included in 58% and 34% of the studies. Moreover, feature extraction/selection has been used only with image data (RGB and hyperspectral). Convolutional Neural Network is the most widely used classifier, followed by Support Vector Machines. This review will help the researchers gain an insight into the work done for disease detection in potato crop and what techniques or diseases need intervention so that yield losses can further be minimized. [ABSTRACT FROM AUTHOR]

Affected by various environmental factors, citrus will frequently suffer from diseases during the growth process, which has brought huge obstacles to the development of agriculture. This paper proposes a new method for identifying and classifying citrus diseases. Firstly, this paper designs an image enhancement method based on the MSRCR algorithm and homomorphic filtering algorithm optimized by Laplacian (HFLF-MS) to highlight the disease characteristics of citrus. Secondly, we designed a new neural network DSMENet based on the DenseNet-121 backbone structure. In DS-MENet, the regular convolution in Dense Block is replaced with depthwise separable convolution, which reduces the network parameters. The ReMish activation function is used to alleviate the neuron death problem caused by the ReLU function and improve the robustness of the model. To further enhance the attention to citrus disease information and the ability to extract feature information, a multi-channel fusion backbone enhancement method (MCF) was designed in this work to process Dense Block. We use the 10-fold cross-validation method to conduct experiments. The average classification accuracy of DS-MENet on the dataset after adding noise can reach 95.02%. This shows that the method has good performance and has certain feasibility for the classification of citrus diseases in real life. [ABSTRACT FROM AUTHOR]

Sustainable development is the theme of world economic development in the 21st century. As a key part of sustainable development, sustainable land use (SLU) encompasses economic development and environmentally friendly and social progress. In recent decades, China has formulated many environmental regulatory policies to achieve sustainable development and "carbon peaking and carbon neutrality (double-carbon)" goals, among which the carbon emission trading scheme (CETS) is the most representative and provides valuable research. In this paper, we aimed to reflect the spatio-temporal evolution of SLU in China under the influence of environmental regulatory policies through an indicator measurement strategy based on the DID estimation method. The study conclusions are as follows: (1) The CETS can effectively improve SLU from the perspectives of economic development and environmentally friendly progress, and the impact has primarily been in the pilot areas. And, its effectiveness is closely linked to local locational factors. (2) With respect to the dimension of economic development, the CETS has not changed the provincial distribution patterns of SLU; rather, it continues to remain "high to low, east to west". However, regarding the environmentally friendly progress dimension, the CETS has significantly changed the provincial distribution patterns of SLU, which are characterized by spatial agglomeration with urban agglomerations such as the Pearl River Delta (PRD) and the Yangtze River Delta (YRD) as the core. (3) The screening results of the SLU indicators based on economic development showed that the CETS primarily improved the innovation capacities of pilot regions, and the impacts on economic levels were relatively small. Similarly, the screening results of the SLU indicators based on environmentally friendly progress showed that the CETS had primarily acted on reducing pollution emission intensity and strengthening greening construction, revealing only short-term effects on improving energy use efficiency. Based on the above, this paper explored the meaning and role of the CETS in more detail, with a view to providing insight into the implementation and formulation of environmental regulation policies. [ABSTRACT FROM AUTHOR]

Pesticide application is an essential means of controlling plant diseases and pests in citrus orchards. In recent years, fixed spraying systems have gradually been used as alternatives to traditional sprayers and manual sprayers in some hilly citrus orchards. In this paper, influences of fixed system spraying parameters, such as droplet size and spraying height, on spraying quality were elucidated and analyzed. The performances of two nozzle types, pressure-swirl nozzles and fixed spray plate sprinklers, were assessed and compared by effective droplet coverage ratio (DCR), droplet distribution uniformity coefficient of variation (CV), and droplet penetration ratio (DPR). The results showed that appropriately increasing droplet size and spraying height could improve the DCR and distribution uniformity of pressure-swirl nozzles. The DCR and distribution uniformity of fixed spray plate sprinklers had a positive correlation with droplet size, while spraying height had no significant effect on these variables. Additionally, with the increase in droplet size, DPR initially increased and then gradually decreased. The optimized results showed that the optimal parameters for pressure-swirl nozzles were a droplet size of 240 μm and spraying height of 100 cm, while for fixed spray plate sprinklers, the results were a droplet size of 240 μm and spraying height of 50 cm. Comparison results showed that the spraying quality of fixed spray plate sprinklers was better overall, with values of DCR, CV, and DPR being 37.15%, 24.20%, and 71.67%, respectively, while the corresponding values for pressure-swirl nozzles were 39.65%, 35.41%, and 56.02%. Based on the above results and the occurrence rule of citrus pests and disease, the optimal spraying parameters of fixed spraying systems were selected to control the Asian citrus psyllid Diaphorina citri. Furthermore, the effect of fixed spraying systems on controlling Diaphorina citri reached the maximum at 3 days after spraying, which was 97.83%, and the effect declined at 14 days after spraying, which was 85.47%. This study provides valuable scientific references for guiding the application of fixed spraying systems in hilly citrus orchards. [ABSTRACT FROM AUTHOR]

Background: As one of the most widely planted fruit trees in southern China, citrus occupies an important position in the agriculture field and forestry economy in China. There are many kinds of citrus diseases. If citrus infected with diseases cannot be controlled in time, it easily seriously affects citrus production and causes large economic losses. Timely monitoring of disease characteristics in the citrus growth process is important for implementing timely control measures. Citrus images are easily disturbed by environmental factors such as dust, low light, clouds or leaf shadows. This makes it easy for some disease spot features in citrus pictures to be obscured. Occluded lesions cannot be effectively extracted and recognized. Second, similar characteristics of different diseases also make it difficult to distinguish the different types of diseases. However, the existing machine vision technology for identifying citrus diseases still has some difficulties in dealing with the above problems. Results: This paper proposes a new citrus disease identification framework. First, a citrus image enhancement algorithm based on the MSR-AMSR algorithm is proposed, which can enhance the image and highlight the disease characteristic information. The AMSR algorithm can also greatly alleviate the interference of clouds and low light on image lesions, making the image features clearer. Second, an MF-RANet network is proposed to recognize citrus disease images. MF-RANet is composed of a main feature frame and a detail feature frame. The main feature frame uses the cross stacking structure of ResNet50 and RAM to extract the main features in the citrus image dataset. RAM is used to extract the attention weight in the feature layer, which enables RAM to give higher weight to disease features. The detailed feature frame path uses AugFPN to extract features from multiple scales and fuse the main feature frame path. AugFPN enables the network to retain more detailed features, so it can effectively distinguish similar features in different diseases. In addition, we use the ELU activation function not only to solve the problem of gradient explosion and gradient disappearance but also to effectively use the negative input of the network. Finally, we use the label smoothing regularization method to prevent overfitting the network in the classification process. Finally, the experimental results show that the highest detection accuracy of the network for Huanglong disease, Corynespora blight of citrus, fat spot macular disease, citrus scab, citrus canker and healthy citrus is 96.77%, 96.22%, 95.96%, 95.93%, 94.04% and 97.55%, respectively. Conclusions: The citrus disease algorithm based on AMSR and MF-RANet can effectively perform the disease detection function. It has a high recognition rate for different kinds of citrus diseases. With the addition of AMSR preprocessing, RAM, AugFPN, ELU activation function and other structures, the MF-RANet network performance improves. [ABSTRACT FROM AUTHOR]

Fungal diseases that may occur before or after harvest are the main challenges of the postharvest citrus industry. Some fungal diseases are slight and only drastically reduce the marketability of the product, while some postharvest fungal diseases of citrus grow rapidly and also infect their adjacent fruits. Infected fruits can neither be stored for a long time nor be exported. For this reason, early detection of fungal infections is very essential. In this paper, all optical methods used to identify citrus fungal diseases, including imaging-based methods and spectroscopic-based methods, are investigated. The application of these methods in detecting citrus fungal diseases is also reviewed. [ABSTRACT FROM AUTHOR]

Predatory mites are effective natural enemies of small arthropods, including pest mites and insects, which provide biological control of several crop pests worldwide. The family Phytoseiidae (Acari: Mesostigmata) is a diverse group of predators found in cultivated crops and other habitats containing natural vegetation. Although some phytoseiid species are commercialized and widely used in biological control programs, the determination of natural populations and identification of the species is a vital first step in understanding their interactions with the crop, environment, and pests. The citrus crop is a diverse agroecosystem colonized by a variety of pests including mites and warrants an understanding of the complex of predators. We collected predatory mites from multiple citrus groves in Florida, to find and identify species for biological control in citrus crops. The examination of the specimens involved the use of Olympus CX-41 microscope, and drawings were prepared with the help of the attached camera Lucida. Any needed corrections were made using tracing paper, rapidograph pen, and Adobe Photoshop version CS6. Neoseiulus hexaporus sp. nov. is described and illustrated as a new species based on its distinct morphology compared with previously described species in paspalivorus group. We also provide a complementary redescription of Neoseiulus mumai (Denmark), including an important diagnostic character of leg chaetotaxy which had led to the description of a new species, Neoseiulus kikuyu Ma, Fan & Zhang. We also provide new illustrations of N. mumai to facilitate its diagnosis. [ABSTRACT FROM AUTHOR]

The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama is an economically important pest of citrus because it vectors the causal pathogens of huanglongbing (HLB) or citrus greening disease. Biological control is an important component of citrus pest management but requires consistent strengthening of its impact on pest complex. The brown lacewing Sympherobius barberi Banks is a known predator of several insect pests from Asia, Europe, and America. However, there is not much information about its effectiveness against D. citri. We evaluated S. barberi against the D. citri and frozen eggs of the Mediterranean flour moth Ephestia kuehniella , the latter is a common diet used for rearing predators in laboratories. Adult S. barberi successfully fed on D. citri eggs and nymphs under both light and dark conditions. Diaphorina citri was also suitable for the development and reproduction of S. barberi except for slightly prolonged larval development compared with E. kuehniella diet. The egg hatch from the total number of eggs laid on D. citri and E. kuehniella diets averaged 65% and 52%, respectively. Females laid 64% eggs on dimpled white paper compared to 36% combined on plain paper and leaves of citrus, orange jasmine, eggplant and cantaloupe. Sympherobius barberi released at densities of 2–6 adults against eggs and nymphs of D. citri on infested orange jasmine plants in the cages provided a reduction of 43–81% in the number of provided eggs or nymphs. In the field tests on D. citri infested citrus trees, reduction averaged 35% in five cohorts in which developing colonies of 28–32 nymphs were provided to one S. barberi per cage. Findings suggest the significant potential of S. barberi as a predator of D. citri and to contribute to reducing huanglongbing. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the traditional Trichogramma pill dispenser is inaccurate due to the change of wind speed during operation, and the traditional algorithm cannot meet the accuracy and applicability of the Unmanned Aerial Vehicle (UAV) path identification and the delivery process, this paper proposes path recognition of UAV based on an improved super-greening algorithm and design of adaptive Trichogramma pill dispenser. The improved super-greening algorithm and the maximum inter-class variance method are used to automatically obtain the green feature binary image, and the morphological processing is used to improve the image quality; the crop location point extraction algorithm based on edge detection is used to extract the feature points, and the feature points are used to fit the navigation line. The wind pressure sensor is used to obtain the voltage signal, and the measured voltage is output after being processed by the airborne 5G board, and the motor speed is controlled according to the adaptive PID control algorithm. The simulation results show that the improved super-greening algorithm more truly reflects the green content in the image, which makes the image extraction more accurate; the crop positioning point extraction algorithm of edge detection is 3.4 and 3.7 smaller than the vertical projection algorithm in average error and positioning error respectively; compared with the vertical projection method, the edge detection method reduces the time consumption by 150 ms and increases the accuracy by 8%; adaptive PID control algorithm compared with the traditional PID control algorithm, the rise time, adjustment time and overshoot are 1.5%, 4.8% and 11.5% smaller respectively. The research results can provide research ideas for the application of UAV precise delivery of Trichogramma bee pills technology in agriculture. [ABSTRACT FROM AUTHOR]

Citrus psyllid is the main vector of Huanglongbing, and as such, it is responsible for huge economic losses across the citrus industry. The small size of this pest, difficulties in data acquisition, and the lack of target detection algorithms suitable for complex occlusion environments inhibit detection of the pest. The present paper describes the construction of a standard sample database of citrus psyllid in multi-focal lengths and out-of-focus states in the natural environment. By integrating the attention mechanism and optimizing the key module of BottleneckCSP, YOLOv5s-BC, we have created an accurate detection algorithm for small targets. Based on YOLOv5s, our algorithm incorporates an SE-Net channel attention module into the Backbone network and improves the detection of small targets by guiding the algorithm to the channel characteristics of small-target information. At the same time, the BottleneckCSP module in the neck network is improved, and extraction of multiple features of recognition targets is improved by the addition of a normalization layer and SiLU activation function. Experimental results based on a standard sample database show the recognition accuracy (intersection over union (IoU) = 0.5) of the YOLOv5s-BC algorithm for citrus psyllid to be 93.43%, 2.41% higher than that of traditional YOLOv5s. The accuracy and recall rates are also increased by 1.31% and 4.22%, respectively. These results confirm that the YOLOv5s-BC algorithm has good generalization ability in the natural context of citrus orchards, and it offers a new approach for the control of citrus psyllid. [ABSTRACT FROM AUTHOR]

Climate change has facilitated the introduction, establishment, and movement of invasive species in northern regions, enabling the colonization of previously unsuitable areas. While the responses of insects to these changes have been increasingly studied, our understanding of how such alterations impact trophic interactions still requires further research to make reliable predictions about the spread of diseases in a warming world. Phytoplasmas, a group of obligate parasitic unculturable Mollicutes, primarily rely on leafhoppers (Hemiptera: Cicadellidae) for transmission, spread, and survival. Phytoplasmas are associated with over 600 diseases affecting more than 1,000 plant species, including berries, grapevines, and other small fruits. In North America, diseases such as grapevine yellows, blueberry stunt, and strawberry green petal diseases have been linked to phytoplasma strains transmitted by known leafhopper species. However, the number of phytoplasma diseases has significantly increased in North America over the past decade, suggesting the presence of unidentified vectors or an abundance of leafhopper vectors. This short review provides an overview of the current knowledge on leafhoppers as vectors of phytoplasmas to berries, focusing on the last decade's research in Canada. This paper also explores the potential implications of climate change on this pathosystem, including the anticipated range expansion of leafhopper species, changes in phytoplasma acquisition and transmission, and the risk of new leafhopper-transmitted plant-pathogen introductions through the arrival of new leafhopper species. [ABSTRACT FROM AUTHOR]

Since greening (aka HLB), the most economically devastating disease of citrus worldwide was detected in Florida in 2005, citrus acreage and fruit production has reduced by more than 70%. Transmitted by the insect vector Asian citrus psyllid, the disease results in exacerbated preharvest drop, smaller fruit, and a rapid decline of trees leading to a significant reduction of yield. Currently, there is no cure for the disease. A strategy to cope with the disease relies on identifying tolerant or more productive varieties, and understanding factors that make them more productive. Under these circumstances, a combination of rootstock and scion that results in better fruit yield is highly desirable. In this paper we investigated phenological attributes of the main sweet orange varieties planted in Florida, Hamlin and Valencia, grafted on Swingle and US-942 rootstocks, two of the most used rootstocks by Florida citrus growers. Our goal was to better understand the phenology associated with the consistently higher yields of trees grafted on US-942. We assessed fruiting characteristics and abscission dynamics of fruit and leaves. We found that trees on US-942 rootstock, especially from Valencia scion, significantly set more terminals than cluster fruit; terminal fruit is larger and experiences less drop resulting in better yields. In general, rootstock did not have a significant influence on the fruit-bearing characteristics in Hamlin. Similarly, we found that fruit detachment force was not significantly influenced by rootstock. Our results show that in an HLB endemic situation, fruiting characteristics should be considered when selecting rootstocks and rootstock–scion combinations, so genetics resulting in larger, single fruits per fruiting branch should be favored. [ABSTRACT FROM AUTHOR]

In this paper, a delayed differential model of citrus Huanglongbing infection is analyzed, in which the latencies of the citrus tree and Asian citrus psyllid are considered as two time delay factors. We compute the equilibrium points and the basic reproductive numbers with and without time delays, i.e. R 0 and R ̃ 0 , and then show that R ̃ 0 completely determines the local stability of the disease-free equilibrium. Moreover, the conditions for the existence of transcritical bifurcation are derived from Sotomayor's Theorem. The stability of the endemic equilibrium and the existence of Hopf bifurcation are investigated in four cases: (1) τ 1 = τ 2 = 0 , (2) τ 1 > 0 , τ 2 = 0 , (3) τ 1 = 0 , τ 2 > 0 and (4) τ 1 > 0 , τ 2 > 0. Optimal control theory is then applied to the model to study two time-dependent treatment efforts and minimize the infection in citrus and psyllids, while keeping the implementation cost at a minimum. Numerical simulations of the overall systems are implemented in MatLab for demonstration of the theoretical results. [ABSTRACT FROM AUTHOR]

Huanglongbing (HLB) is a disease of citrus that caused by phloem-restricted bacteria of the Candidatus Liberibacter group. In this paper, we present a HLB transmission model to investigate the effects of temperature-dependent latent periods and seasonality on the spread of HLB. We first establish disease free dynamics in terms of a threshold value R 0 p , and then introduce the basic reproduction number R 0 and show the threshold dynamics of HLB with respect to R p and R 0. Numerical simulations are further provided to illustrate our analytic results. [ABSTRACT FROM AUTHOR]

This paper studies a new model for Huanglongbing with seasonal fluctuations. Switching coefficients and switching control schemes are considered in this model. The main purpose of this paper is to study the effects of switching control schemes on dynamics of the model. Firstly, we theoretically investigate the basic reproductive number and its computation formulae for general impulsive switching model with periodic environment. Secondly, the basic reproductive number and global dynamics of the impulsive switching model for Huanglongbing are analyzed. Finally, numerical results indicate that spring and autumn are the optimum seasons for killing psyllids, and winter is the optimum season for removing infected trees. [ABSTRACT FROM AUTHOR]

Huanglongbing (otherwise known as HLB or greening) is currently the most devastating citrus disease worldwide. HLB is primarily associated with the phloem-inhabiting bacterium 'Candidatus Liberibacter asiaticus' (CLas). Currently, there are no citrus species resistant to CLas. Genetic transformation is one of the most effective approaches used to induce resistance against plant diseases. Antimicrobial peptides (AMPs) have shown potential breakthroughs to improve resistance to bacterial diseases in plants. In this paper, we confirm the Agrobacterium-mediated transformation of Pera sweet orange expressing the AMP sarcotoxin IA (stx IA) gene isolated from the flesh fly Sarcophaga peregrina and its reaction to CLas, involving plant performance and fruit quality assessments. Four independent transgenic lines, STX-5, STX-11, STX-12, and STX-13, and a non-transgenic control, were graft-inoculated with CLas. Based on our findings, none of the transgenic plants were immune to CLas. However, the STX-5 and STX-11 lines showed reduced susceptibility to HLB with mild disease symptoms and low incidence of plants with the presence of CLas. Fruit and juice quality were not affected by the genetic transformation. Further, no residues of the sarcotoxin IA protein were found in the juice of the STX-11 and STX-12 fruits, though detected in the juice of the STX-5 and STX-13 lines, as revealed by the immunoblotting test. However, juices from all transgenic lines showed low traces of sarcotoxin IA peptide in its composition. The accumulation of this peptide did not cause any deleterious effects on plants or in fruit/juice. Our findings reinforce the challenges of identifying novel approaches to managing HLB. [ABSTRACT FROM AUTHOR]

Huanglongbing (HLB), primarily transmitted by the citrus psyllid, is the most devastating citrus disease worldwide. Planting disease-free citrus seedlings is one of the significant intervention strategies for HLB. In this paper, a compartment model is used to investigate the importation and local transmission of the disease. Due to the continuous input of the diseased citrus seedlings from outside, the traditional theoretical analysis methods are insufficient to describe and predict its dynamical behaviors based on the analysis determined by the basic reproductive ratio ℛ 0 . The criteria for the existence and local stability of disease-free and endemic equilibria are deduced. Then a complete theoretical, bifurcation, and sensitivity analyses are carried out on the simplified system. Based on our study, we have the following interesting findings: (a) the importation of diseased citrus seedlings in orchards plays a vital role in the transmission of HLB, and planting disease-free citrus seedlings will effectively inhibit the spread of the disease; (b) the importation of diseased citrus seedlings can affect the stability of the equilibrium of the full system; (c) the simplified system may exhibit some complex dynamic phenomena, such as saddle-node bifurcation, forward bifurcation, backward bifurcation, and bistability; (d) global sensitivity analysis shows that the mortality and biting rate of citrus psyllids have a greater impact on ℛ 0 than other parameters. These observations provide theoretical guidance for policymakers to determine the long-term viability of implemented HLB intervention strategies. [ABSTRACT FROM AUTHOR]

Superresolution is a concept to increase the resolution. The main objective of this paper is the study of iterative curvature based method for super-resolving low resolution of a leaf diseased images. The domain specific prior is incorporated into superresolution by the means of iterative curvature SR based estimation of missing high frequency details from infected leaf images. The model is composed of two step pixel filling approach. Through this proposed work, fine edges of SR images are preserved without applying complex mathematical algorithms based on wavelet, fast curvelet, etc. In this paper, we have validated proposed scheme over 9 infected leaf images of various crops like soybean, cotton, rose, citrus family etc. shows better result in visual as well as subjective quality as that of complex multi frame SR algorithms like reconstruction and registration along with less computational time. This concept is most useful for agricultural expert for helping our farmers for exact leaf disease detection and accurate remedial actions. The experimental result shows the best visible SR result of an infected leaf along with MSE and PSNR i.e. Statistical results. It also shows the comparison of proposed method with the existing techniques successfully. [ABSTRACT FROM AUTHOR]

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Cumulatively, these studies highlight some critical considerations to be made when performing diagnoses of plant diseases such as: a) Are there genetic variants of a causal agent that may be missed by standard molecular disease assays due to genetic variability of the causal agent? C) Can symptoms of a biotic disease be confused for other biotic or abiotic diseases? I savastanoi i causing the olive knot disease with epiphytic and endophytic bacteria " by Dokosozi and Bozkurt is an interesting contribution from Turkey that describes a promising biological control against the olive knot bacterium I Pseudomonas savastanoi i pv. [Extracted from the article]

Overconfidence is a universal and prevalent cognitive bias affecting decision making in operation management. In this paper, overconfidence is defined as a cognitive bias in which decision makers overestimate the accuracy of demand forecasting or (and) the demand itself. We call these two behaviors overprecision and overestimation, respectively. In order to explore how overconfidence affects decision making of the green product manufacturer, we build the demand function based on the manufacturer's overconfidence and establish a newsboy-based model. Then the influence of overconfidence on product greenness, output, and profit is mainly discussed. We have several new sights as follows. First, overconfidence makes the manufacturer produce greener products than the rational manufacturer, and overestimation results in a higher greenness deviation than overprecision. Second, the influence of overconfidence on the output of green products is quite different from that of nongreen products. Specifically speaking, overestimation makes the manufacturer produce more products than the rational manufacturer, so do the overprecision manufacturer and the dual-overconfident manufacturer under the low-profit condition. But in high-profit condition, when greening investment factor is low and (or) consumers are sensitive enough to greenness, the overprecision manufacturer produces more than the rational manufacturer; when the level of overestimation exceeds a threshold, output of the dual-overconfident is greater than that of the rational manufacturer. Third, overconfidence makes the real profit of the manufacturer less than optimal profit of the rational manufacturer. There is a positive cross-effect of overprecision and overestimation in real profit of the dual-overconfident manufacturer. That is, to some extent, one kind of overconfidence can offset the decline in profit caused by the other kind of overconfidence. [ABSTRACT FROM AUTHOR]

Citrus greening, also called Huanglongbing (HLB), has affected citrus production globally. In Florida, the disease has decimated citrus production area and overall fruit yields. Emerging results show that some nutrients applied in a balanced and constant nutrition (BCN) program alleviate tree stress by improving root health, canopy size and tissue nutrient concentration. In this paper, we discuss the current strategies for managing citrus in Florida, and roles of macro- and micronutrients in citrus and other crops. Further, we discuss the role of macro- and micronutrients in potentially restoring root health and tree performance. We wrap up by discussing future research opportunities on the health and nutrition of HLB-affected citrus trees. [ABSTRACT FROM AUTHOR]

This paper documents pest management practices adopted by citrus farmers in two of the citrus-growing regions in Morocco. The survey data propose possible recommendations to ensure sustainable pest management strategies. By variety, the surface area occupied by the Navel and Maroc-late represented 25% and 23%, respectively. 54% of the citrus farmers used certified sour orange rootstocks. 79% of farmers adopted soil plowing using a plow called Cover-Crop. Drip irrigation was widely practiced in the two regions studied. Citrus growers perceived mealybug, medfly, and mites as the most common insects, and Phytophthora rot and dry root rot as the most devastating fungal diseases infecting citrus production. 54% of the respondents used a pre-established treatment schedule. A total of 21 active ingredients of insecticides belonging to 15 different chemical groups were inventoried during the survey. Organophosphates were the most widely used insecticides (28%), followed by pyrethroids (17.9%), and neonicotinoids (16%). For disease control, copper compounds were used by all respondents. The manual–mechanical weed control method was widely practiced. 29% of respondents admitted to having little knowledge about the impact of climate change, 43% reported about a shift in dates of production practices, and 35% experienced pest outbreaks in their orchards. Due to the unregulated management practices, our findings emphasize the necessity of extension services to citrus farmers on the adoption of integrated citrus production. This system will help achieve sustainable citrus production, protect the environment, and optimize citrus yield. [ABSTRACT FROM AUTHOR]

The largest citrus-producing region in Brazil, concentrated in the states of São Paulo and Minas Gerais, is also the largest citrus-producing region in the world. Data from 2016 indicate that for every five glasses of orange juice consumed in the world, three are produced in Brazil. Thus, citriculture stands out in Brazilian agribusiness. Along with the growth of this agricultural sector is the emergence of diseases that affect citrus trees. In this paper, two mathematical models are presented to describe the dynamics and chemical control of citrus diseases. These models involve the theory of optimal control, considering the spatial spread of disease vectors. The first model consists of a system of ordinary differential equations with transport rates. The second model involves the Greedy Randomized Adaptive Search Procedure in control theory, considering the spread of the vectors from a partial differential equation model involving diffusion. The models are approached in a scenario for Huanglongbing disease, also called greening, which is considered to be the most devastating citrus disease in the world because of its characteristics and the damage it causes, and because there is still no cure. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chemical control is the most used and effective method to control Diaphorina citri, the vector of the phloem‐limited bacteria associated with citrus huanglongbing (HLB) disease. The objectives of this study were to determine the effectiveness of flupyradifurone applied via dripping irrigation systems on D. citri. Bioassays were conducted using leaves harvested on various dates post treatment, and insecticide residue in leaf tissue was quantified. RESULTS: The drip application of flupyradifurone on citrus trees provided high‐level and long‐term control against D. citri adult, and the median lethal concentration (LC50) for ingestion of flupyradifurone in D. citri was 22.22 mg kg–1 (fresh leaf). Flupyradifurone residue was detected in leaf tissue within 3 days after treatment. The measured level of flupyradifurone peaked on day 40 day after application, and then showed a steady decline in subsequent days for all three applied dosages. The amounts of flupyradifurone in upper, middle, and lower leaves were similar, and trends in the change in concentration of flupyradifurone were consistent. CONCLUSIONS: The results demonstrate that flupyradifurone can be a valuable new tool for D. citri management programs, and drip‐applied flupyradifurone provides an extended period of control efficacy. This paper could provide a reference to reduce the dependence on foliar‐applied insecticides, with associated benefits for non‐target exposure to workers and pollinators. © 2021 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

In the agricultural industry, there is still a need for improved systematic integration of knowledge related to citrus pests and diseases. Creating a knowledge base focused on citrus pests and diseases and developing a knowledge map would enable the formation of a system providing accurate and convenient prevention and control methods for citrus growers. However, the majority of existing data on citrus pests and diseases is unstructured, making identifying named entities from large volumes of unstructured text data particularly important for creating a knowledge map. In this paper, we propose a training model based on Bidirectional Encoder Representation from Transformers (BERT), combined with Bidirectional Long and Short Term Memory Networks (BiLSTM) and Conditional Random Field (CRF), to extract specific entity categories from unstructured data. When tested on a created dataset, the model achieved an accuracy rate of 0.9423 and an f1 value of 0.8048. The results demonstrate that the proposed method can be applied to extract specific entity categories from text data related to citrus pests and diseases, laying a solid foundation for the subsequent construction of a knowledge map. This paper introduces a method for named entity recognition in the field of citrus pests and diseases, which could serve as a reference for constructing knowledge maps in other fields and improving the utilization of domain knowledge. [ABSTRACT FROM AUTHOR]

In order to promote the healthy and sustainable development of citrus industry in Guangxi and reduce the harm of Diaphorina citri and citrus Huanglongbing on citrus industry, the paper summarizes the occurrence of D. citri in Guangxi, and put forward comprehensive control technique, so as to provide the reference for guiding prevention and control of major pests in citrus industry. [ABSTRACT FROM AUTHOR]

[Objectives] The paper was to explore a faster and more accurate detection method for citrus psyllid to prevent and control yellowshoot disease and inhibit its transmission. [Methods] We used an improved YOLOX based edge detection method for psyllid, added Convolutional Block Attention Module (CBAM) to the backbone network, and further extracted important features in the channel and space dimensions. The Cross Entropy Loss in the object loss was changed to Focal Loss to further reduce the missed detection rate. [Results] The algorithm described in the study fitted in with the detection platform of psyllid. The data set of psyllid was taken in Lianjiang Orange Garden, Zhanjiang City, Guangdong Province, deeply adapted to the actual needs of agricultural and rural development. Based on YOLOX model, the backbone network and loss function were improved to achieve a more excellent detection method of citrus psyllid. The AP value of 85.66% was obtained on the data set of citrus psyllid, which was 2.70% higher than that of the original model, and the detection accuracies were 8.61%, 4.32% and 3. 62% higher than that of YOLOv3, YOLOv4-Tiny and YOLOv5-s, respectively, which had been greatly improved. [Conclusions] The improved YOLOX model can better identify citrus psyllid, and the accuracy rate has been improved, laying a foundation for the subsequent real-time detection platform. [ABSTRACT FROM AUTHOR]

Citrus is one of the most commonly farmed and popular fruit crops globally. Citrus fruits are high in vitamins, minerals, and dietary fibre, which are essential for overall health. Oranges are the most widely traded citrus fruit, accounting for more than half of global citrus production. Tangerines, lemons, and mandarins are the next most commonly farmed varieties. Citrus production and export have steadily expanded over the previous three decades, though slower than competing items like mangoes, avocados, and melons. The production of citrus fruit is heavily hampered due to diseases in its growth stages. Again, the diseases not only appear in leaves but also in fruits. So, the quality of fruits is degraded due to the appearance of flaws. The citrus fruits are graded in two ways: first based on their skin tone and second on their size. So, there is a requirement to assess citrus diseases to avoid the degradation of production. Further, there is a need to grade citrus fruit to make easy packaging concerning its quality; so that the proper values of Citrus fruits be generated. This article studied and analysed different methodologies reported for citrus disease prediction and grading of citrus fruit in the postharvest stage based on machine vision between 2010 and 2021. This paper outlines the current achievements, limitations, and suggestions for future research on citrus diseases and their fruit grading. [ABSTRACT FROM AUTHOR]

Diaphorina citri Kuwayama is a serious insect pest of citrus worldwide due to the capacity to transmit causal agent of the huanglongbing. Mineral oils are recommended in the integrated pest management programs to prevent resistance development. The primary objective of this study was to determine emergence inhibition and antifeedant effect of three mineral oils with similar n-paraffin carbon number against D. citri. The results of topical contact toxicity showed that Antong was the most toxic with 50% lethal concentration value of 189 ng/insect. Each mineral oil at the concentrations of 0.1, 0.2 and 0.5% (v/v) significantly inhibited the emergence of adults from treated fifth-instar nymphs, and 0.5% (v/v) of the oils had a long residue activity that they inhibited over 56% adult emergence up to 10 days. We found significant repellency of D. citri from citrus tree resets that were treated with mineral oils compared with control. 0.5% (v/v) of the mineral oils significantly inhibited feeding of D. citri adults with reduction of 39–68% honeydew, and the nymphs that fed on citrus leaves treated with different concentrations raised heads and upper abdomens to form a half-erect posture. Our studies indicated that mineral oils could effectively reduce or suppress the spread of HLB by repellency and less feeding, as well as emergence inhibition to reduce D. citri populations. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Psyllidae), is a prominent pest of citrus because it transmits Candidatus Liberibacter asiaticus associated with huanglongbing. Phototactic behavior ubiquitously exists in insects and plays essential roles in host‐searching and mate‐searching in ACP. However, its mechanism has remained unclear to date. In this paper, molecular assays were performed to understand the relation between opsins and the phototactic behavior of ACP. RESULTS: We cloned five opsin genes and analyzed their expression patterns. The main three opsin genes (Dc‐UV, Dc‐BW and Dc‐LW) displayed high expression levels in daytime, and the expression levels of the other two opsin genes (Dc‐UV‐like and Dc‐arthropsin) increased during nighttime. In constant darkness, the expression patterns and levels of opsin genes of ACP were altered. Under starvation, the expression levels of the main three opsins were reduced (53.89–84.10%). In contrast, the expression levels in females increased (27.55–60.58%). Feeding of double‐stranded RNA (Dc‐UV, Dc‐LW or Dc‐BW) have reduced the phototactic efficiency of ACP to ultraviolet light (44.79%), green light (54.81%) and blue light (43.00%), respectively. CONCLUSION: The results suggest that the expression levels and patterns of opsins of ACP were influenced by photoperiod and the physiological status of ACP. Our research indicates that opsins play crucial roles in phototactic behavior in ACP. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Meizhou is the main citrus fruit producing area in China, and its pomelo planting area and output value rank second in China. In this paper, the present situation of prevention and control of citrus HLB (Huanglongbing) in this city in recent years is introduced, some successful experiences are mentioned, some shortcomings are also analyzed, and combined with the problems existing in the current process of prevention and control of citrus HLB, this paper puts forward some measures, such as timely removal of the diseased individuals, control of planthoppers, establishment of the HLB demonstration site of comprehensive prevention and control and large aseptic seedling breeding base, active introduction of HLB pathogen inspection and quarantine equipment, strengthening supervision and inspection, comprehensive control and other measures, in order to provide scientific basis for the prevention and control of the disease in Meizhou. [ABSTRACT FROM AUTHOR]

More and more organizations are heading to maximize the efficiency of their resources and enhancing their energy and waste management policies and practices. The extant literature argues that enterprise resource planning (ERP) systems, or what is known as sustainable ERP systems, can aid organization in their "greening" efforts. This paper builds upon the existing body of knowledge on sustainable ERP and supply chain greening domains and presents a qualitative case study conducted at an organization that is active within the agriculture sector. The case organization was assessed on its expectancy towards implementing a new ERP system and the paper explores how this system can potentially support the company's initiatives within sustainability and innovation. This research shows that (sustainable) ERP systems are expected to improve time-management and efficiency and are not necessarily viewed as a solution that can aid organizations to become more sustainable. [ABSTRACT FROM AUTHOR]

The Asian citrus psyllid (ACP) is an important pest because it transmits a bacterium putatively responsible for huanglongbing, a devastating citrus disease. Research on ACP chemical ecology is of interest with respect to identifying attractants and repellents for managing the psyllid. We report on an assay for investigating ACP attraction to the foliar odor of one of its host plants, orange jasmine ( Murraya exotica L.). Flush shoots from this plant were placed into 25 dram vials covered with a paper wrapper, a lid with a small entrance hole was snapped onto each vial, the vials were placed into a small cage, adult ACP were released into the cage, and the location of the adults was determined 24 h later. A positive response required an adult to find and enter a vial. When single males or females were released, they were attracted into vials with flush 64 % of the time. At release rates of 25, 50 or 100 adults with 30 repetitions for each rate, relatively large mean percentages of adults (ca. 83 %) positively responded to flush shoots. ACP can escape from the assay vial and will do so if flush is not present. Working with ACP in empty vials, fluoropolymer resin applied to the inside of vials reduced escapes but did not eliminate them. An entrapment funnel for reducing escapes was tested, but it reduced ACP response rates. A good method of preventing escapes remains to be developed. When two vials of flush were placed in the assay cage and one was treated with a candidate repellent, only 8 % of adults settled in the vial with the repellent. [ABSTRACT FROM AUTHOR]

The unprecedented worldwide spread of the Citrus greening disorder, called Huanglongbing (HLB), has urged researchers for rapid interventions. HLB poses a considerable threat to global citriculture owing to its devastating impact on citrus species. This disease is caused by Candidatus Liberibacter species (CLs), primarily transferred through psyllid insects, such as Trioza erytreae and Diaphorina citri. It results in phloem malfunction, root decline, and altered plant source-sink relationships, leading to a deficient plant with minimal yield before it dies. Thus, many various techniques have been employed to eliminate HLB and control vector populations through the application of insecticides and antimicrobials. The latter have evidenced short-term efficiency. While nucleic acid-based analyses and symptom-based identification of the disease have been used for detection, they suffer from limitations such as false negatives, complex sample preparation, and high costs. To address these challenges, secreted protein-based biomarkers offer a promising solution for accurate, rapid, and cost-effective disease detection. This paper presents an overview of HLB symptoms in citrus plants, including leaf and fruit symptoms, as well as whole tree symptoms. The differentiation between HLB symptoms and those of nutrient deficiencies is discussed, emphasizing the importance of precise identification for effective disease management. The elusive nature of CLs and the challenges in culturing them in axenic cultures have hindered the understanding of their pathogenic mechanisms. However, genome sequencing has provided insights into CLs strains' metabolic traits and potential virulence factors. Efforts to identify potential host target genes for resistance are discussed, and a high-throughput antimicrobial testing method using Citrus hairy roots is introduced as a promising tool for rapid assessment of potential treatments. This review summarizes current challenges and novel therapies for HLB disease. It highlights the urgency of developing accurate and efficient detection methods and identifying the complex relations between CLs and their host plants. Transgenic citrus in conjunction with secreted protein-based biomarkers and innovative testing methodologies could revolutionize HLB management strategies toward achieving a sustainable citrus cultivation. It offers more reliable and practical solutions to combat this devastating disease and safeguard the global citriculture industry. • Huanglongbing (HLB) poses a considerable threat to global citriculture. • HLB caused by Candidatus Liberibacter species and transferred by psyllid insects. • Pesticides, antimicrobial, transgenic plants, thermotherapy, etc. Can control HLB. • Combination of different techniques could revolutionize HLB management. [ABSTRACT FROM AUTHOR]

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Psyllidae), is a major pest of citrus due to its role as the vector of the bacterium that causes huanglongbing. In commercial citrus, ACP control currently relies on the application of insecticides, which may not be sustainable long-term, nor practical in urban areas. The sterile insect technique (SIT) is an alternative strategy in which large numbers of pests are reared, sterilized using radiation, and then released into the field to compete with wild individuals for matings, suppressing population growth. As a fundamental step toward the development of SIT for ACP, this study sought to identify the optimum radiation dose required to sterilize ACP without affecting their survival and mating capacity. Virgin adult ACP of both sexes were subjected to doses of X-ray irradiation ranging from 40 to 480 Gy, then paired with a nonirradiated mate and allowed to produce offspring. Fecundity was estimated as the number of eggs laid, and fertility as the proportion of those eggs that hatched. Females were more radio-sensitive than males, exhibiting a major drop in fecundity at even the lowest dose and 100% sterility at 80 Gy. In contrast, a fivefold higher dose (400 Gy) did not achieve complete sterility in males, with around 5% offspring survival. However, F1 progeny of males exposed to 320 Gy or higher were subsequently found to be 100% sterile. This confirmation of inherited sterility suggests that balancing the sterilizing effects of radiation against its mortality-inducing effects may warrant further evaluation. [ABSTRACT FROM AUTHOR]

Background: With the rapid development of single-cell sequencing technology, histological studies are no longer limited to conventional homogenized tissues. Laser microdissection enables the accurate isolation of specific tissues or cells, and when combined with next-generation sequencing, it can reveal important biological processes at the cellular level. However, traditional laser microdissection techniques have often been complicated and time-consuming, and the quality of the RNA extracted from the collected samples has been inconsistent, limiting follow-up studies. Therefore, an improved, simple, and efficient laser microdissection method is urgently needed. Results: We omitted the sample fixation and cryoprotectant addition steps. Instead, fresh samples were embedded in Optimal Cutting Temperature medium within 1.5 ml centrifuge tube caps, rapidly frozen with liquid nitrogen, and immediately subjected to cryosectioning. A series of section thicknesses of citrus rind were tested for RNA extraction, which showed that 18 μm thickness yielded the highest quality RNA. By shortening the dehydration time to one minute per ethanol gradient and omitting the tissue clearing step, the resulting efficient dehydration and preserved morphology ensured high-quality RNA extraction. We also propose a set of laser microdissection parameters by adjusting the laser power to optimal values, reducing the aperture size, and lowering the pulse frequency. Both the epidermal and subepidermal cells from the citrus rind were collected, and RNA extraction was completed within nine hours. Using this efficient method, the transcriptome sequencing of the isolated tissues generated high-quality data with average Q30 values and mapping rates exceeding 91%. Moreover, the transcriptome analysis revealed significant differences between the cell layers, further confirming the effectiveness of our isolation approach. Conclusions: We developed a simple and rapid laser microdissection method and demonstrated its effectiveness through a study based on citrus rind, from which we generated high-quality transcriptomic data. This fast and efficient method of cell isolation, combined with transcriptome sequencing not only contributes to precise histological studies at the cellular level in citrus but also provides a promising approach for cell-specific transcriptome analysis in a broader range of other plant tissues. [ABSTRACT FROM AUTHOR]

Brown spot of citrus caused by Alternaria citri is one of the emerging threats to the successful production of citrus crops. The present study, conducted with a substantial sample size of 50 leaf samples for statistical reliability, aimed to determine the change in mineral content in citrus leaves after brown spot disease attack. Leaf samples from a diverse range of susceptible citrus varieties (Valentia late, Washington navel, and Kinnow) and resistant varieties (Citron, Eruka lemon, and Mayer lemon) were analyzed. Significant variations (p ≤ 0.05) in mineral contents were observed across reaction groups (inoculated and un-inoculated), types (resistant and susceptible), and varieties of citrus in response to infection of Alternaria citri. The analysis of variance showed significant changes in mineral levels of citrus leaves, including nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), zinc (Zn), sodium (Na), iron (Fe), and copper (Cu). The results indicate that the concentration of N and P differed by 6.63% and 1.44%, respectively, in resistant plants, while susceptible plants showed a difference of 6.07% and 1.19%. Moreover, resistant plants showed a higher concentrations of K, Ca, Mg, Zn, Na, Fe, and Cu at 8.40, 2.1, 1.83, 2.21, 1.58, 2.89, and 0.36 ppm respectively, compared to susceptible plants which showed concentrations of 5.99, 1.93, 1.47, 1.09, 1.24, 1.81, and 0.31 ppm respectively. Amounts of mineral contents were reduced in both resistant as well as susceptible plants of citrus after inoculation. Amount of N (8.56), P (1.87) % while K (10.74), Ca (2.71), Mg (2.62), Zn (2.20), Na (2.08), Fe (3.57) and Cu (0.20) ppm were recorded in un-inoculated group of citrus plants that reduced to 3.15 and 0.76% and 3.66, 1.40, 0.63,0.42, 0.74, 1.13 and 0.13 ppm in inoculated group respectively. It was accomplished that susceptible varieties contained lower ionic contents than resistant varieties. The higher concentrations of ionic contents in resistant citrus varieties build up the biochemical and physiological processes of the citrus plant, which help to restrict spread of pathogens. Further research could explore the interplay between mineral nutrition and disease resistance in citrus, potentially leading to the development of new disease-resistant varieties. [ABSTRACT FROM AUTHOR]

Bacterial canker disease caused by Clavibacter michiganensis is a substantial threat to the cultivation of tomatoes, leading to considerable economic losses and global food insecurity. Infection is characterized by white raised lesions on leaves, stem, and fruits with yellow to tan patches between veins, and marginal necrosis. Several agrochemical substances have been reported in previous studies to manage this disease but these were not ecofriendly. Thus present study was designed to control the bacterial canker disease in tomato using green fabricated silver nanoparticles (AgNps). Nanosilver particles (AgNPs) were synthesized utilizing Moringa oleifera leaf extract as a reducing and stabilizing agent. Synthesized AgNPs were characterized using UV–visible spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray (EDX), and Fourier transform infrared spectrometry (FTIR). FTIR showed presence of bioactive compounds in green fabricated AgNPs and UV-visible spectroscopy confirmed the surface plasmon resonance (SPR) band in the range of 350 nm to 355 nm. SEM showed the rectangular segments fused together, and XRD confirmed the crystalline nature of the synthesized AgNPs. The presence of metallic silver ions was confirmed by an EDX detector. Different concentrations (10, 20, 30, and 40 ppm) of the green fabricated AgNPs were exogenously applied on tomato before applying an inoculum of Clavibacter michigensis to record the bacterial canker disease incidence at different day intervals. The optimal concentration of AgNPs was found to be 30 µg/mg that exhibited the most favorable impact on morphological (shoot length, root length, plant fresh and dry weights, root fresh and dry weights) and physiological parameters (chlorophyll contents, membrane stability index, and relative water content) as well as biochemical parameters (proline, total soluble sugar and catalase activity). These findings indicated a noteworthy reduction in biotic stress through the increase of both enzymatic and non-enzymatic activities by the green fabricated AgNPs. This study marks a first biocompatible approach in assessing the potential of green fabricated AgNPs in enhancing the well-being of tomato plants that affected with bacterial canker and establishing an effective management strategy against Clavibacter michiganensis. This is the first study suggests that low concentration of green fabricated nanosilvers (AgNPs) from leaf extract of Moringa oleifera against Clavibacter michiganensis is a promisingly efficient and eco-friendly alternative approach for management of bacterial canker disease in tomato crop. [ABSTRACT FROM AUTHOR]

Entomopathogenic nematodes (EPNs) are an important component of integrated pest management (IPM) strategies; understanding their compatibility with other biocontrol options is of crucial importance in promoting their use. In this study, the toxicity of azadirachtin, sulfoxaflor, spindle oil (Mineral oil), and thyme oil was tested on the survival and pathogenicity of Steinernema carpocapsae (Weiser, 1955) (Rhabditida: Steinernematidae), Steinernema bicornutum sp. n. (Rhabditida: Steinernematidae), Heterorhabditis bacteriophora (Poinar, 1976) (Rhabditida: Heterorhabditidae), and Heterorhabditis indica (Poinar, Karunakar & David, 1992) under controlled conditions (25 ± 1 °C, 60 ± 10% RH). The toxicity of aforementioned agrochemicals to EPNs was evaluated in 12-well plates and the infective juveniles (IJs) of each EPN species (6000 IJs/50 µL ddh2O) were exposed to the recommended field concentrations of agrochemicals. In the pathogenicity tests, the agrochemical and IJs solutions (3000 IJs/ml agrochemical) were applied to potato tubers in plastic containers which contained 20 adults of Planococcus citri (Risso, 1813) (Hemiptera: Pseudococcidae). The survival of IJs and P. citri (Adults) was evaluated daily for three consecutive days after treatment. The results revealed that all tested EPN species were quite compatible with tested agrochemicals and showed survival of over 95% after 72 h of exposure to tested agrochemicals. EPNs and spindle oil combination induced the highest mortality of adult P. citri, and all EPN species caused mortalities over 90% at 72 h after treatment, except for S. bicornotum-spindle oil combination. Additive effects were observed in all combinations of EPNs with agrochemicals except for thyme oil. It appears, therefore, that EPNs applied in combination with azadirachtin, sulfoxaflor, and spindle oil have a great potential for successful control of P. citri. However, further studies are still required to determine the antagonistic or otherwise synergistic effects of tested chemicals on EPNs in controlling P. citri under field conditions. [ABSTRACT FROM AUTHOR]

We describe a series of operational questions posed during the state-wide response in California to the arrival of the invasive citrus disease Huanglongbing. The response is coordinated by an elected committee from the citrus industry and operates in collaboration with the California Department of Food and Agriculture, which gives it regulatory authority to enforce the removal of infected trees. The paper reviews how surveillance for disease and resource allocation between detection and delimitation have been addressed, based on epidemiological principles. In addition, we describe how epidemiological analyses have been used to support rule-making to enact costly but beneficial regulations and we highlight two recurring themes in the programme support work: (i) data are often insufficient for quantitative analyses of questions and (ii) modellers and decision-makers alike may be forced to accept the need to make decisions on the basis of simple or incomplete analyses that are subject to considerable uncertainty. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Asian citrus psyllid, Diaphorina citri Kuwayama, is the primary vector of the phloem‐inhabiting bacterium Candidatus Liberibacter asiaticus putatively responsible for citrus greening (huanglongbing), a devastating citrus disease. Infestations of D. citri frequently develop on Citrus and other genera within the Rutaceae subfamily Aurantioideae including Murraya and Bergera. The genotype Poncirus trifoliata is also a member of the Aurantioideae and readily hybridizes with Citrus spp., but colonization by D. citri is reduced on this genotype. RESULTS: Working with young potted seedlings grown in a greenhouse, we found that the development of D. citri immatures on four P. trifoliata cultivars, especially 'Kryder 55‐5', was slower compared with the development of immatures on the susceptible Citrus macrophylla. In choice assays, adult psyllids exhibited antixenotic behavior towards accessions of P. trifoliata and laid fewer eggs on this genotype compared with C. macrophylla. CONCLUSIONS: Based on reduced oviposition and delays in development, P. trifoliata exhibits a combination of antixenosis and antibiosis host‐plant resistance to D. citri. A companion plant assay showed that the presence of C. macrophylla stimulated higher oviposition rates on P. trifoliata, but nymph development remained retarded on P. trifoliata. Here, we show that the antixenosis associated with trifoliate accessions can be overcome to some extent by the presence of a preferred susceptible host plant; but in combination with antibiosis P. trifoliata remains an inferior host plant. © 2018 Society of Chemical Industry Asian citrus psyllids are the primary vectors of the bacterium responsible for citrus greening disease in Florida and worldwide. This paper discusses the effects of different types of host‐plant resistance exhibited by Poncirus trifoliata (trifoliate citrus) on oviposition and nymphal development of citrus psyllids. [ABSTRACT FROM AUTHOR]