The Early, Rapid, and Non-Destructive Detection of Citrus Huanglongbing (HLB) Based on Microscopic Confocal Raman

Wang, Kangkang; Liao, Youqiang; Meng, Yaoyong; Jiao, Xianzhi; Huang, Wei; Liu, Timon Chengyi

doi:10.1007/s12161-019-01598-1

Cited by 19 publications

(12 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cluster plot of the three-dimensional principal component space (D). Reproduced with permission from ref , copyright SPRINGER NATURE, 2019.…”

Section: Applications Of Rs and Sers In Plant Diseasementioning

confidence: 99%

“…In the experiment, Wang et al picked and collected from an experimental plot. They used a confocal Raman spectrometer with a laser wavelength of 785 nm to measure the RS spectra of healthy, asymptomatic, and symptomatic intact leaves 46 (Figure 2A, inset). The test area was the mesophyll cells of the leaf midrib part presented under the microscope, which was the most stable part during the measurement.…”

Section: Applications Of Rs and Sers In Plant Diseasementioning

confidence: 99%

See 1 more Smart Citation

Advanced Application of Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy in Plant Disease Diagnostics: A Review

Weng

Wang

et al. 2021

J. Agric. Food Chem.

View full text Add to dashboard Cite

Plant diseases result in 20–40% of agricultural loss every year worldwide. Timely detection of plant diseases can effectively prevent the development and spread of diseases and ensure the agricultural yield. High-throughput and rapid methods are in great demand. This review investigates the advanced application of Raman spectroscopy (RS) and surface-enhanced Raman spectroscopy (SERS) in the detection of plant diseases. The determination of bacterial diseases and stress-induced diseases, fungal diseases, viral diseases, pests in beans, and mycotoxins related to plant diseases using RS and SERS are discussed in detail. Then, biomarkers for RS and SERS detection are analyzed with regard to plant disease diagnosis. Finally, the advantages and challenges are further illustrated. Additionally, potential alternatives are proposed for the challenges. The review is expected to provide a reference and guidance for the use of RS and SERS in plant disease diagnostics.

show abstract

“…Cluster plot of the three-dimensional principal component space (D). Reproduced with permission from ref , copyright SPRINGER NATURE, 2019.…”

Section: Applications Of Rs and Sers In Plant Diseasementioning

confidence: 99%

Section: Applications Of Rs and Sers In Plant Diseasementioning

confidence: 99%

Advanced Application of Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy in Plant Disease Diagnostics: A Review

Weng

Wang

et al. 2021

J. Agric. Food Chem.

View full text Add to dashboard Cite

show abstract

“…Currently, HLB disease detection methods are time consuming and involve multiple stages of sample preparation. Efforts have been done to have an early diagnostic of the disease with no sucess 16 – 21 . Due to these reasons, our group has been focusing attention on HLB disease and a new potential diagnostic method.…”

Section: Resultsmentioning

confidence: 99%

“…In addition, the technique has limitations in differentiating viable and dead bacterial cells from each other, leading to an inaccurate quantification 13 – 15 . Efforts have been made in order to have a successful disease diagnostic through other analytical platforms, such as nuclear magnetic resonance (NMR) spectroscopy 16 , 17 , infrared spectroscopy (IV) 18 , capillary electrophoresis with diode array detection (CE-DAD) 19 , differential mobility spectrometry (DMS) 20 , and confocal Raman microscopy 21 . Despite this, these techniques sometimes require a time-consuming sample preparation methodologies and generate complex data that need a time-demanding statistical data treatment (spectroscopic methods) or final adjustments for spatial resolution (microscopic methods) 22 – 25 .…”

Section: Introductionmentioning

confidence: 99%

Mass spectrometry imaging as a potential technique for diagnostic of Huanglongbing disease using fast and simple sample preparation

Pontes

Vendramini

Fernandes

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Huanglongbing (HLB) is a disease of worldwide incidence that affects orange trees, among other commercial varieties, implicating in great losses to the citrus industry. The disease is transmitted through Diaphorina citri vector, which inoculates Candidatus Liberibacter spp. in the plant sap. HLB disease lead to blotchy mottle and fruit deformation, among other characteristic symptoms, which induce fruit drop and affect negatively the juice quality. Nowadays, the disease is controlled by eradication of sick, symptomatic plants, coupled with psyllid control. Polymerase chain reaction (PCR) is the technique most used to diagnose the disease; however, this methodology involves high cost and extensive sample preparation. Mass spectrometry imaging (MSI) technique is a fast and easily handled sample analysis that, in the case of Huanglongbing allows the detection of increased concentration of metabolites associated to the disease, including quinic acid, phenylalanine, nobiletin and sucrose. The metabolites abieta-8,11,13-trien-18-oic acid, suggested by global natural product social molecular networking (GNPS) analysis, and 4-acetyl-1-methylcyclohexene showed a higher distribution in symptomatic leaves and have been directly associated to HLB disease. Desorption electrospray ionization coupled to mass spectrometry imaging (DESI-MSI) allows the rapid and efficient detection of biomarkers in sweet oranges infected with Candidatus Liberibacter asiaticus and can be developed into a real-time, fast-diagnostic technique.

show abstract

“…Several plant diseases with diverse etiology have been already studied using RS with the intention of performing an early plant disease diagnostic: Candidatus Liberibacter asiaticus and Xanthomonas axonopodis pv. citri bacterial pathogens in orange [Citrus x sinensis (L.) Osbeck] [14][15][16], pepper mild mottle virus (PMMoV) and Obuda pepper virus (ObPV) in chili crops (Capsicum annuum L.) [17]; Tomato yellow leaf curl Sardinia virus (TYLCSV) and tomato spotted wilt virus (TSWV) in tomato cultivars (S. lycopersicum) [18], the fungus Aspergillus flavus, A. niger, Fusarium spp., and, Diplodia spp., affecting maize grain (Zea mays L.) [19], the abutilon mosaic virus (AbMV) affecting abutilon (Abutilum hybridum Voss) cultivars [20] and the diagnosis of rose rosette disease (Rosa spp.) caused by the rose rosette virus (RRV) which is transmitted by eriophyid mites [21], among others.…”

Section: Introductionmentioning

confidence: 99%

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition

Vallejo-Pérez

Sosa-Herrera

Navarro‐Contreras

et al. 2021

Plants

View full text Add to dashboard Cite

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.

show abstract

The Early, Rapid, and Non-Destructive Detection of Citrus Huanglongbing (HLB) Based on Microscopic Confocal Raman

Cited by 19 publications

References 31 publications

Advanced Application of Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy in Plant Disease Diagnostics: A Review

Advanced Application of Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy in Plant Disease Diagnostics: A Review

Mass spectrometry imaging as a potential technique for diagnostic of Huanglongbing disease using fast and simple sample preparation

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition

Contact Info

Product

Resources

About