Citrus Leaf Research Articles

A simple and effective VIGS system facilitates the control of citrus canker by silencing CsLOB1

Virus-induced gene silencing (VIGS) is a powerful technology for molecular characterization of gene functions in plants and has the potential to prevent and control plant diseases. Unfortunately, VIGS in many woody perennials such as citrus are severely hindered because they have a long juvenile period and are recalcitrant to infection compared to herbaceous plants. Here, we report the development of a simple and effective VIGS system based on citrus leaf blotch virus (CLBV), a virus endemic in most citrus-producing countries but showing no symptoms in most citrus varieties. By Agrobacterium-mediated vacuum-infiltration (AVI), pCLBV201-su245 and pCLBV201-pds391 triggered efficient gene silencing (85%) and silencing phenotypes began to appear at 30 days post infiltration/inoculation (dpi), a similar period for achieving that on herbaceous plants. Moreover, the silencing phenotypes could still be observed four years post inoculation. Further, pCLBV201-lob369 was constructed to silence the gene lateral organ boundaries1 (lob1), encoding a key factor for susceptibility to citrus canker that caused by Xanthomonas citri ssp. citri (Xcc). The resistance evaluation results showed that the lesion area, disease index, and bacterial content in the pCLBV201-lob369 treatment group were decreased by 64%, 14%, and 67%, respectively. This work provides a simple and effective VIGS system for citrus which has the potential to be used for diseases control.

Applied Deep learning approaches on canker effected leaves to enhance the detection of the disease using Image Embedding and Machine learning Techniques

Canker, a disease that causes considerable financial losses in the agricultural business, is a small deep lesion that is visible on the leaves of many plants, especially citrus/apple trees. Canker detection is critical for limiting its spread and minimizing harm. To address this issue, we describe a computer vision-based technique that detects Canker in citrus leaves using image embedding and machine learning (ML) algorithms. The major steps in our proposed model include image embedding, and machine learning model training and testing. We started with preprocessing and then used image embedding techniques like Inception V3 and VGG 16 to turn the ROIs into feature vectors that retained the relevant information associated with Canker leaf disease, using the feature vectors acquired from the embedding stage, we then train and evaluate various ML models such as support vector machines (SVM), Gradient Boosting, neural network, and K Nearest Neighbor. Our experimental results utilizing a citrus leaf picture dataset show that the proposed strategy works. With Inception V3 as the image embedder and neural network machine learning model we have obtained an accuracy of 95.6% which suggests that our approach is effective in canker identification. Our method skips traditional image processing techniques that rely on by hand features and produces results equivalent to cutting-edge methods that use deep learning models. Finally, our proposed method provides a dependable and efficient method for detecting Canker in leaves. Farmers and agricultural specialists can benefit greatly from early illness diagnosis and quick intervention to avoid disease spread as adoption of such methods can significantly reduce the losses incurred by farmers and improve the quality of agricultural produce.

Re-Fining Citrus Leaf and Fruit Spot Disease Control Options in Northern Uganda

Citrus leaf and fruit spot disease, caused by Pseudocercospora angolensis has, since 2010, come about as the most dreadful disease of citrus in Northern Uganda. Over the last few years, feedback from citrus farmers has helped in re-fining management strategies. In the first years of citrus leaf and fruit spot disease outbreak in Northern Uganda, chemical treatment was promoted as part of a control package, in addition to the destruction of heavily diseased plants and buckthorn to remove inoculum. Buck horning and destruction of diseased plants is labour-intensive and time-consuming, especially when many infected citrus trees have to be taken out, or buck horned. Research findings indicate citrus leaf and fruit spot disease fungus can be weakened with fungicide sprays to the extent that even when disease symptoms are present on leaves, it does not automatically lead to infection of fruits. This gave rise to a new control strategy where only infected plants in an orchard are pruned, and all the citrus trees in the orchard are treated with fungicides. The pruning of visibly infected plants in an orchard will lessen the inoculum load, and the fungicide sprays will stop pathogen replication. This method is not labour intensive and takes less time when equated to severe buck horning of all the trees in the orchard. However, pruning and fungicide treatment need to move together with the control of new infections that can happen via unrestricted entry during harvesting

Identification and pathogenicity of Colletotrichum species associated with twig dieback of citrus in Western Australia

AbstractUp to 32 Colletotrichum species have been reported to be associated with pre‐ or postharvest diseases of citrus globally, while in Australia, six species have been reported to cause citrus leaf and fruit disease. Twig or shoot dieback has recently been observed as an emerging disease in citrus orchards in Western Australia. Colletotrichum species were isolated from diseased twigs showing dieback (withertip) or lesions, with or without gummosis, collected from 12 varieties of orange, mandarin and lemon. Colletotrichum gloeosporioides sensu stricto, Colletotrichum karstii and Colletotrichum novae‐zelandiae were identified using a polyphasic approach that included multigene phylogenetic analysis using sequences of internal transcribed spacer and intervening 5.8S nrDNA (ITS), glyceraldehyde‐3‐phosphate dehydrogenase (gapdh), β‐tubulin (tub2), actin (act) and histone (his3) for isolates in the boninense species complex, and Apn2–Mat1–2 intergenic spacer and partial mating type (Mat1–2) (ApMat) and glutamine synthetase (gs) for isolates in the gloeosporioides species complex, as well as morphological characteristics. C. gloeosporioides was the most prevalent species associated with twig dieback in Western Australia, while C. novae‐zelandiae was reported for the first time in Australia. Pathogenicity tests on shoot twigs from lemon and orange trees confirmed C. gloeosporioides, C. karstii and C. novae‐zelandiae as the cause of twig dieback, with C. gloeosporioides being the most aggressive species. Knowledge of the species causing twig dieback and their lifestyle will assist the development of integrated control methods.

Comparison of Citrus Leaf Water Content Estimations Based on the Continuous Wavelet Transform and Fractional Derivative Methods

Citrus tangerines are famous fruits worldwide, and monitoring the water content of citrus leaves is highly important for citrus production. However, there are still challenges in quantitatively estimating the water content of citrus leaves using hyperspectral technology, and the random noise generated during spectral acquisition and the overlapping peaks in the sensitive band of the citrus leaf water content will affect estimation accuracy. To solve these problems and further explore the roles of the continuous wavelet transform (CWT) and fractional-order derivative (FOD) in the estimation of citrus leaf water content, this study intends to use of CWT and FOD to decompose the original spectrum, and then compare the correlation between the original spectrum and leaf water content to explore whether the decomposition treatment has improved the correlation between spectrum and leaf moisture content. Then, the successive projections algorithm (SPA) was used to select feature bands and combine spectral vegetation indices. Partial least squares regression (PLSR) was used to construct water-content inversion models for citrus leaves, and the inversion accuracies of two commonly used spectral preprocessing methods were compared. The results indicate that (1) the CWT can improve the sensitivity of the spectrum to the citrus leaf water content to a certain extent, and the inversion accuracy of the CWT is approximately 5% greater than that of the FOD. (2) On the basis of the CWT and FOD methods, the inversion accuracy of the citrus leaf water content based on SPA screening increased by 9.61% and 9.29%, respectively, compared with the original spectrum. (3) Under CWT decomposition, Scale4 of the Gaus1 wavelet was screened by the SPA, and the inversion model of citrus leaf water content was constructed by combining the spectral vegetation index NDVI with the best results. The R-squared (R2) and root mean square error (RMSE) values were 0.7491 and 0.0284, respectively, which were both 0.0138 greater than those of the best inversion model for the FOD R2. In conclusion, the CWT-SPA combined with the spectral vegetation index can improve the sensitivity of the spectrum to the citrus leaf water content, eliminate a large amount of redundant data, and enhance the prediction ability and stability of the citrus leaf water content.

Diversity of 'Candidatus Liberibacter asiaticus' Strains in Texas Revealed by Prophage Sequence Analyses.

Prophages/phages are important components of the genome of 'Candidatus Liberibacter asiaticus' (CLas), an unculturable alphaproteobacterium associated with citrus huanglongbing (HLB) disease. Phage variations have significant contributions to CLas strain diversity research, which provide critical information for HLB management. In this study, prophage variations among selected CLas strains from southern Texas were studied. The CLas strains were collected from three different CLas inhabitant environments: citrus leaf, citrus root, and Asian citrus psyllid (ACP), the vector of CLas. Regardless of the different habitats and time span, more than 80% of CLas strains consistently had both Type 1 and Type 2 prophages, the same prophage type profile as in CLas strains from Florida but different to those reported in California and China. Further studies were performed on prophage type diversity. Analyses on Type 1-specific PCR amplicon sequences (encoding an endolysin protein) revealed the presence of two groups: Type 1-A, clustered around prophage SC1 originating from Florida, and Type 1-B, clustered with prophage P-SGCA5-1 originating in California. Type 1-B strains were mostly from ACP of nearby citrus orchards. On the other hand, analyses on Type 2-specific PCR amplicon sequences (encoding a putative hypothetical protein) showed a single group clustering around prophage SC2 originated from Florida, although a different Type 2 prophage has been reported in California. The presence of two distinct Type 1 prophage groups suggested the possibility of two different CLas introductions in southern Texas. The results from this study provide an initial baseline of information on genomic and population diversity of CLas in Texas.

Volatile chemical profiling and distinction of Citrus essential oils by GC analyses with correlation matrix; evaluation of its in vitro radical scavenging and microbicidal efficacy

Leaf volatile oil compositions of five Citrus species viz., Citrus aurantifolia, Citrus limon, Citrus maxima, Citrus medica and Citrus medica * Citrus limon were examined in this study by Gas Chromatography-Flame Ionisation Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC–MS) analysis and percentage volatile compositions were compared. Thirty-eight compounds were identified that account for 90 to 99 % of essential oil composition from Citrus species, respectively. GC–MS profiling of essential oils revealed that Citrus leaf oils were predominantly characterized by limonene (15.76±0.01% to 29.36±0.46%) as one of the major constituents. Monoterpenoids (77.38±0.19% to 98.05±0.05%) are the prominent class of constituents present in the volatile oils of four Citrus plants under study whereas in one species (C. maxima), sesquiterpene hydrocarbons (38.97±0.21%) were the dominant category. The data from GC analyses were subjected to correlation study to analyse the correlation between the volatile constituents among the selected Citrus species. These essential oils were initially evaluated for their antioxidant capacity and the leaf oils exhibited promising radical scavenging property with an average IC50 value of 29.15±0.01 μg/mL. This study was further designed to evaluate antimicrobial efficacy of five Citrus leaf essential oils against various pathogenic bacterial and fungal strains. Four examined essential oils gave a comparative antibacterial activity with a minimum inhibitory concentration (MIC) value against tested bacterial strains ranging from 3.62±0.02mg/mLto60.0±0.32mg/mL.Citrus leaf oils were found to be more sensitive to Escherichia coli with MIC values ranged between 3.62±0.03 to 10.15±0.02 mg/mL. These essential oils also exhibited strong inhibitory potential against tested fungal strains, Aspergillus niger and Candida albicans, with MIC ranging from 3.22±0.02 to 28.17±0.04 mg/mL. Out of the five essential oils screened in this study, four of them have shown significant antimicrobial and antioxidant activities which can be attributed to synergistic potential of major monoterpenoid constituents present in these oils viz., geranial, neral, citronellal, nerol, geraniol, geranyl formate rather than the sesquiterpene dominated essential oil. Based on the findings obtained and conclusions derived, it is evident that the selected Citrus leaf essential oils are promising natural agents to fight free radical damage and antibiotic-resistant microbes.

Correlation of citrus leaf miner, Phyllocnistis citrella with leaf physio-morphological and biochemical factors in acid lime leaves

Correlation of citrus leaf miner, Phyllocnistis citrella with leaf physio-morphological and biochemical factors in acid lime leaves

Population dynamics and management of citrus leaf miner, Phyllocnistis citrella (Stainton) in nursery

Population dynamics and management of citrus leaf miner, Phyllocnistis citrella (Stainton) in nursery

Population dynamics of citrus leaf miner and bark eating caterpillars on sweet orange (Citrus sinensis) using ICT-based pest surveillance

Population dynamics of citrus leaf miner and bark eating caterpillars on sweet orange (Citrus sinensis) using ICT-based pest surveillance

Denoising Diffusion Probabilistic Models and Transfer Learning for citrus disease diagnosis.

Plant Disease diagnosis based on deep learning mechanisms has been extensively studied and applied. However, the complex and dynamic agricultural growth environment results in significant variations in the distribution of state samples, and the lack of sufficient real disease databases weakens the information carried by the samples, posing challenges for accurately training models. This paper aims to test the feasibility and effectiveness of Denoising Diffusion Probabilistic Models (DDPM), Swin Transformer model, and Transfer Learning in diagnosing citrus diseases with a small sample. Two training methods are proposed: The Method 1 employs the DDPM to generate synthetic images for data augmentation. The Swin Transformer model is then used for pre-training on the synthetic dataset produced by DDPM, followed by fine-tuning on the original citrus leaf images for disease classification through transfer learning. The Method 2 utilizes the pre-trained Swin Transformer model on the ImageNet dataset and fine-tunes it on the augmented dataset composed of the original and DDPM synthetic images. The test results indicate that Method 1 achieved a validation accuracy of 96.3%, while Method 2 achieved a validation accuracy of 99.8%. Both methods effectively addressed the issue of model overfitting when dealing with a small dataset. Additionally, when compared with VGG16, EfficientNet, ShuffleNet, MobileNetV2, and DenseNet121 in citrus disease classification, the experimental results demonstrate the superiority of the proposed methods over existing approaches to a certain extent.

The Effect of Using some Integrated Pest Management Factors on the Life Aspects of the Citrus Leaf Miner Phyllocnistis citrella Stainton (Lepidoptera: Gracillariidae) in the Laboratory

The study aimed to evaluate the efficiency of some integrated management factors in controlling the citrus leaf miner insect in the laboratory and to choose the best of them for field use to reduce the damage of this pest. The factors which used in this study involved two chemical pesticides Movento and Oxymatrine, as well as the use of growth regulators Match and biological fungi Beauveria bassiana (B.b..) and Metarhizium anisopliae (M.a..) and the interaction among them to get the most effective way to control the pest. The results of the study showed Movento is the most studied factor affecting the citrus miner insect in terms of the death rate on the larvae, as it recorded 96.52%, while the growth regulator Match recorded the lowest death rate of 49.20%. As for pupae, the chemical pesticide Movento also excelled by recording the highest death rate, reaching 62.59%, while the growth regulator Match recorded the lowest death rate for pupae stage, which amounted to 23.96%. It is clear from the results that the pupae are more resistant to factors that been used in this study compared with larvae. Results also proved that adults of insect were more effective with factors that used in this study compared with larvae and pupae stage. Movento pesticide showed mortality percentage reached to 100% for adults compared with growth regulator Match, which scored 73.62%, while it did not differ from the pesticide Oxymatrine, which gave 99.14%. The results of interactions among the factors on the larvae of the citrus leaf miner showed that the treatments Movento, Oxymatrine and Match, Movento+B.b.., total interaction had the highest mortality rate for the larvae stage which recorded 100% followed by the treatments Oxymatrine and the Movento + M.a. which recorded 95.56% each. While B.b. and M.a. treatments and the interaction between them, recorded the lowest mortality rate, reaching 9.25, 23.80, and 23.33%, respectively, as for pupae stage. The total interaction treatment only gave the highest mortality rate for pupae of the citrus leaf miner insect, as it recorded 100% and followed by the treatments Movento + B.b. and Movento + Match, which recorded 95.56% for each, while the treatments B.b. and M.a. was recorded the lowest death rate, which amounted to 6.68, 18.73, and 16.66%, respectively.

Potential functions of the shared bacterial taxa in the citrus leaf midribs determine the symptoms of Huanglongbing.

Citrus is a globally important fruit tree whose microbiome plays a vital role in its growth, adaptability, and resistance to stress. With the high throughput sequencing of 16S rRNA genes, this study focused on analyzing the bacterial community, especially in the leaf midribs, of healthy and Huanglongbing (HLB)-infected plants. We firstly identified the shared bacterial taxa in the midribs of both healthy and HLB-infected plants, and then analyzed their functions. Results showed that the shared bacterial taxa in midribs belonged to 62 genera, with approximately 1/3 of which modified in the infected samples. Furthermore, 366 metabolic pathways, 5851 proteins, and 1833 enzymes in the shared taxa were predicted. Among these, three metabolic pathways and one protein showed significant importance in HLB infection. With the random forest method, six genera were identified to be significantly important for HLB infection. Notably, four of these genera were also among the significantly different shared taxa. Further functional characterization of these four genera revealed that Pseudomonas and Erwinia likely contributed to plant defense against HLB, while Streptomyces might have implications for plant defense against HLB or the pathogenicity of Candidatus Liberibacter asiaticus (CLas). Overall, our study highlights that the functions of the shared taxa in leaf midribs are distinguished between healthy and HLB-infected plants, and these microbiome-based findings can contribute to the management and protection of citrus crops against CLas.

Comparative Study of the Co-Occurring Alternaria and Colletotrichum Species in the Production of Citrus Leaf Spot.

Both of the two citrus diseases, Alternaria brown spot (ABS) and Anthracnose, caused by Alternaria and Colletotrichum spp., respectively, can produce leaf lesions which are hard to differentiate. These two diseases have been confused as causal agents of brown spot for over a decade in China. In this study, citrus leaves with or without brown spot were collected from Zhaoqing, Guangdong and Wanzhou, Chongqing, and were further used for the taxonomic and functional comparisons between the co-occurring Alternaria and Colletotrichum species. In the amplicon sequencing, the average relative abundance and the composition of Alternaria, but not Colletotrichum, increased (from 0.1 to 9.9, p = 0.059; and to 0.7, p < 0.05) and significantly altered (p < 0.01) with the brown spot in Zhaoqing and Wanzhou, respectively. Two representative isolates Alternaria sp. F12A and Colletotrichum sp. F12C, from the same brown spot, were proved with different virulence and host response activation to citrus leaves. F12A caused typical symptoms of brown spot with the average spot length expanded to 5 and 6.1 cm, and also altered the citrus global gene expression 48 and 72 h after inoculation. In addition, F12A enriched the expression of genes that were most frequently involved in plant defense. In comparison, F12C caused leaf spot limited to the wounded site, and its milder activation of host response recovered 72 h after inoculation. Our study indicates that the incidence of brown spot in China is caused by Alternaria species, and the ABS should be a fungal disease of major concern on citrus.

Early diagnosis and mechanistic understanding of citrus Huanglongbing via sun-induced chlorophyll fluorescence

Citrus Huanglongbing (HLB) is a serious disease that is devastating the citrus industry worldwide. The infection of HLB causes a significant impact on the photosynthesis and growth of citrus but the early diagnosis of HLB is challenging. This study aims to propose an effective method for early HLB diagnosis and mechanistic understanding via sun-induced chlorophyll fluorescence (SIF) during the whole growth period of citrus. SIF signals and net photosynthetic rate (A) of healthy, asymptomatic HLB (aHLB) and symptomatic HLB (sHLB) citrus leaf samples were acquired throughout the whole citrus growth period. Seasonal variations of the peak SIF yield at 687 nm (SIFY687) and 741 nm (SIFY741) and A were investigated. Leaf chlorophyll a content (Ca), chlorophyll b content (Cb), and carotenoids content (Cxc) were also measured by spectrophotometry in the laboratory. It was found that the A of the aHLB was close to that of sHLB, which was significantly different from the healthy leaves at the physiological fruit dropping (PFD) period. The ratio of chlorophyll content (Chl) to Cxc (Chl/Cxc) was evidently different between aHLB and healthy leaves at the late PFD and early fruit expanding (FE) stage, which could be a potential biomarker to identify HLB in the incubation period. The classification result showed PFD was the optimal stage for HLB diagnosis and the index based on SIFY741 was recommended (overall accuracy > 90 %). Moreover, HLB had a great influence on the relationship between A and SIF at the PFD stage, and the coefficients of determination (R2) of the univariate linear regression model between A and SIFY687 and SIFY741 decreased from 0.81 and 0.72 to 0.21 and 0.17, respectively. These results demonstrate the HLB effect on the relationship between A and SIF, and that the SIF could be a proxy to citrus photosynthesis and further used to diagnose early HLB in situ.

Degradation dynamics, residues, processing factors, and dietary risk assessment of bisultap in citrus by LC-MS/MS.

Citrus leaf miners are a common pest harming citrus production and quality during citrus planting. During the citrus plant's growth phase, bisultap formulation was frequently used to boost yield and produce fruit of high quality. However, research on citrus's dietary risk assessment for bisultap residues, dissipation and residues is lacking. Liquid chromatography-tandem mass spectrometry was used to develop an accurate and sensitive analytical method for derivatizing bisultap into nereistoxin in whole fruit, pulp and peel. At various levels of addition, the mean recovery of bisultap ranged from 84.64% to 111.09% with a reasonable relative RSD (< 20%). The half-lives in Guangxi and Guizhou were 3.96 and 6.03 days, respectively. After 14-21 days of bisultap application, total residues (bisultap and its metabolite nereistoxin) in the whole fruit were from < 0.02 to 0.228 mg kg-1 in the four experiment sites. Total residue (bisultap and nereistoxin, expressed by bisultap) in whole fruit was approximately 1.05-7.23 times that of pulp. The washing process with tap water removed 85.71% to 98.78% of the bisultap residue in the whole fruit. Bisultap's risk assessment value in citrus was in the range 0.16-1.28%. In the whole citrus fruit, bisultap degrades rapidly. Bisultap residues primarily accumulate on citrus peels, and so washing and peeling citrus may effectively remove bisultap residues. For various age groups, the chronic dietary risk of bisultap was acceptable. © 2023 Society of Chemical Industry.

CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile

CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile

Arthropod Biodiversity of Citrus Ecosystem with Special Reference to Citrus Leaf Miner

The citrus leaf miner (CLM), scientifically known as Phyllocnistis citrella Stainton and belonging to the Gracillaridae family, is a significant nuisance for citrus nurseries and the tender leaves of young citrus plants. Damage caused by the larvae is conspicuous especially on the young foliage during initial phase of development and the management of the pest is highly critical. The present studies were carried out at ICAR-Central Citrus Research Institute, Nagpur during 2013 to 2015 to document the species composition of bioagents (parasitoids and predators), their incidence levels and species richness/ diversity in citrus ecosystems with reference to citrus leaf miner. During the study, we documented individuals from two classes, four orders and six families of insects. Class Insecta was dominant followed by Arachnida. Among the six families, Eulophidae and Coccinellidae were the most dominant bioagent groups for parasitoid and predator, respectively. Relative abundance of the bioagents of P. citrella revealed that C. phyllocnistoides was the predominant one and constituted 30% of total bioagents collected followed by Cirrospilus sp. (including C. quadristriatus, C. ingenuus) (25%), E. brevicornis (15%) and S. striatipes (9%). Coccinellids constituted about 3%; whereas, chrysopid predator, M. desjardinsi and spider species constituted 13% and 7%, respectively of the total bioagent collection. Understanding of the bioagent complex in citrus ecosystem will help us to identify the promising ones for biological control as well as guide us the bioagent active frame to avoid pesticide sprays to sustain them naturally in the ecosystem.

First report of citrus leaf blotch virus (CLBV) infection among lemon trees in Korea

First report of citrus leaf blotch virus (CLBV) infection among lemon trees in Korea

A Field Deployable Real-Time Loop-Mediated Isothermal Amplification Targeting Five Copy nrdB Gene for the Detection of 'Candidatus Liberibacter asiaticus' in Citrus.

Huanglongbing (HLB) is one of the most destructive diseases in citrus, which imperils the sustainability of citriculture worldwide. The presumed causal agent of HLB, 'Candidatus Liberibacter asiaticus' (CLas) is a non-culturable phloem-limited α-proteobacterium transmitted by Asian citrus psyllids (ACP, Diaphorina citri Kuwayama). A widely adopted method for HLB diagnosis is based on quantitative real-time polymerase chain reaction (qPCR). Although HLB diagnostic qPCR provides high sensitivity and good reproducibility, it is limited by time-consuming DNA preparation from plant tissue or ACP and the requirement of proper lab instruments including a thermal cycler to conduct qPCR. In an attempt to develop a quick assay that can be deployed in the field for CLas detection, we developed a real-time loop-mediated isothermal amplification (rt-LAMP) assay by targeting the CLas five copy nrdB gene. The rt-LAMP assay using various plant sample types and psyllids successfully detected the nrdB target as low as ~2.6 Log10 copies. Although the rt-LAMP assay was less sensitive than laboratory-based qPCR (detection limit ~10 copies), the data obtained with citrus leaf and bark and ACP showed that the rt-LAMP assay has &gt;96% CLas detection rate, compared to that of laboratory-based qPCR. However, the CLas detection rate in fibrous roots was significantly decreased compared to qPCR due to low CLas titer in some root DNA sample. We also demonstrated that the rt-LAMP assay can be used with a crude leaf DNA extract which is fully deployable in the field for quick and reliable HLB screening.