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Chitarra, L. G.; Bulk, R.W. van den

doi:10.1023/a:1024275610233

Cited by 41 publications

(12 citation statements)

References 55 publications

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“…Direct methods for detection and identification of plant pathogens include flow cytometry, gas and liquid chromatography coupled with mass-spectrometry (GC- and LC-MS), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, fluorescence in situ hybridization (FISH), and polymerase chain reaction (PCR). , These exhibit high pathogen specificity; however, they have their own limitations. Specifically, PCR is highly sensitive to contamination from environmental DNA, can be inhibited by small quantities of organic solvents and requires initial design of primers based on known DNA sequences.…”

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confidence: 99%

“…Additionally, these techniques typically cannot detect all pathogens . Flow cytometry requires analyzed material be in suspension and often generates excessive amount of data, making sample analysis complicated. , GC- and LC-MS are costly, destructive, and have limited portability. , Lack of noninvasive, nondestructive, confirmatory technology to detect plant infection is what sparked and challenged us to investigate the capacity of Raman spectroscopy to solve this problem.…”

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confidence: 99%

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Detection and Identification of Fungal Infections in Intact Wheat and Sorghum Grain Using a Hand-Held Raman Spectrometer

2018

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Global population growth drives increasing food demand, which is anticipated to increase by at least 20% over the next 15 years. Rapid detection and identification of plant pathogens allows for up to a 50% increase in the total agricultural yield worldwide. Current molecular methods for pathogen diagnostics, such as polymerase chain reaction (PCR), are costly, time-consuming, and destructive. These limitations recently catalyzed a push toward developing minimally invasive and substrate general techniques that can be used in the field for confirmatory detection and identification of plant pathogens. Raman spectroscopy (RS) is a noninvasive, nondestructive, and label-free technique that can be used to determine chemical structure of analyzed specimens. In this study, we demonstrate that by using a hand-held Raman spectrometer, we can identify whether wheat or sorghum grains are healthy or not and identify present plant pathogens. We show that RS enables diagnosis of simple diseases, such as ergot, that are caused by one pathogen, as well as complex diseases, such as black tip or mold, which are induced by several different pathogens. The combination of chemometric analysis and RS allows for distinguishing between healthy and infected grains with high accuracy. We also show that RS can be used to determine states of disease development on grain. These results demonstrate that Raman-based approach for disease detection on plants is sample agnostic.

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confidence: 99%

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Detection and Identification of Fungal Infections in Intact Wheat and Sorghum Grain Using a Hand-Held Raman Spectrometer

2018

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“…In the last decades, several molecular techniques have been developed for the detection of plant stress. The most commonly used are polymerase chain reaction (PCR and real-time PCR) and enzyme-linked immunosorbent assay (ELISA); other techniques, mainly applied for disease detection, include immunoflourescence imaging (Gautam et al, 2020), flow cytometry (Chitarra and Bulk, 2003), fluorescence in situ hybridization (FISH; Farber et al, 2019), and DNA microarrays.…”

Section: Molecular Methodsmentioning

confidence: 99%

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Galieni¹,

D’Ascenzo

Stagnari

et al. 2021

Front. Plant Sci.

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Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

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“…There are many traditional techniques that have been developed to detect AFB 1 in multifarious samples, including gas chromatography (GC) [9], high-performance liquid chromatography (HPLC) [10], enzyme-linked immunosorbent assay (ELISA) [11,12], and LC coupled with tandem mass spectrometry (LC-MS/MS) [13]. However, these methods usually need precise equipment, professional technical personnel, and generally require hours or days to obtain data.…”

Section: Introductionmentioning

confidence: 99%

Detection of Aflatoxin B1 Based on a Porous Anodized Aluminum Membrane Combined with Surface-Enhanced Raman Scattering Spectroscopy

Feng

et al. 2020

Nanomaterials

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An Aflatoxin B1 (AFB1) biosensor was fabricated via an Ag nanoparticles assembly on the surface of a porous anodized aluminum (PAA) membrane. First, the Raman reporter 4-Aminothiophenol (4-ATP) and DNA (partially complementary to AFB1 aptamer) were attached to the surface of Ag nanoparticles (AgNPs) by chemical bonding to form a 4-ATP-AgNPs-DNA complex. Similarly, the surface of a PAA membrane was functionalized with an AFB1 aptamer. Then, the PAA surface was functionalized with 4-ATP-AgNPs-DNA through base complementary pairing to form AgNPs-PAA sensor with a strong Raman signal. When AFB1 was added, AgNPs would be detached from the PAA surface because of the specific binding between AFB1 and the aptamer, resulting in a reduction in Raman signals. The detection limit of the proposed biosensor is 0.009 ng/mL in actual walnut and the linear range is 0.01–10 ng/mL. The sensor has good selectivity and repeatability; it can be applied to the rapid qualitative and quantitative detection of AFB1.

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Cited by 41 publications

References 55 publications

Detection and Identification of Fungal Infections in Intact Wheat and Sorghum Grain Using a Hand-Held Raman Spectrometer

Detection and Identification of Fungal Infections in Intact Wheat and Sorghum Grain Using a Hand-Held Raman Spectrometer

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Detection of Aflatoxin B1 Based on a Porous Anodized Aluminum Membrane Combined with Surface-Enhanced Raman Scattering Spectroscopy

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