Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Salinity Stresses, Nitrogen, Phosphorus, and Potassium Deficiencies in Rice

Sanchez, Lee; Ermolenkov, Alexei; Biswas, Sudip; Septiningsih, Endang M.; Kurouski, Dmitry

doi:10.3389/fpls.2020.573321

Cited by 30 publications

(34 citation statements)

References 34 publications

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“…Because these changes are pathogen-specific, RS has species-level sensitivity. Similar metabolic changes are observed upon abiotic stresses (Altangerel et al, 2017;Gupta et al, 2020;Sanchez, Ermolenkov, Biswas, et al, 2020). Detection and identification of these changes in rice enabled highly accurate identification of nitrogen (N), phosphorus (P), and potassium (K) deficiencies with 85% accuracy as early as 2 days after stress introduction (Sanchez, Ermolenkov, Biswas, et al, 2020).…”

Section: Introductionmentioning

confidence: 80%

Raman spectroscopy‐based diagnostics of water deficit and salinity stresses in two accessions of peanut

Morey

Farber

McCutchen³

et al. 2021

Plant Direct

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Water deficit and salinity are two major abiotic stresses that have tremendous effect on crop yield worldwide. Timely identification of these stresses can help limit associated yield loss. Confirmatory detection and identification of water deficit stress can also enable proper irrigation management. Traditionally, unmanned aerial vehicle (UAV)‐based imaging and satellite‐based imaging, together with visual field observation, are used for diagnostics of such stresses. However, these approaches can only detect salinity and water deficit stress at the symptomatic stage. Raman spectroscopy (RS) is a noninvasive and nondestructive technique that can identify and detect plant biotic and abiotic stress. In this study, we investigated accuracy of Raman‐based diagnostics of water deficit and salinity stresses on two greenhouse‐grown peanut accessions: tolerant and susceptible to water deficit. Plants were grown for 76 days prior to application of the water deficit and salinity stresses. Water deficit treatments received no irrigation for 5 days, and salinity treatments received 1.0 L of 240‐mM salt water per day for the duration of 5‐day sampling. Every day after the stress was imposed, plant leaves were collected and immediately analyzed by a hand‐held Raman spectrometer. RS and chemometrics could identify control and stressed (either water deficit or salinity) susceptible plants with 95% and 80% accuracy just 1 day after treatment. Water deficit and salinity stressed plants could be differentiated from each other with 87% and 86% accuracy, respectively. In the tolerant accessions at the same timepoint, the identification accuracies were 66%, 65%, 67%, and 69% for control, combined stresses, water deficit, and salinity stresses, respectively. The high selectivity and specificity for presymptomatic identification of abiotic stresses in the susceptible line provide evidence for the potential of Raman‐based surveillance in commercial‐scale agriculture and digital farming.

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Section: Introductionmentioning

confidence: 80%

Raman spectroscopy‐based diagnostics of water deficit and salinity stresses in two accessions of peanut

Morey

Farber

McCutchen³

et al. 2021

Plant Direct

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“…Liberibacter disease in tomatoes (Sanchez et al, 2020b) Tomato, leaf -747 cm −1 (pectin); 1,000, 1,115, 1,155, 1,184, 1,218, and 1,525 cm −1 (carotenoids)…”

Section: Resultsmentioning

confidence: 99%

“…Raman spectroscopy allows for non-invasive and non-destructive detection and identification of biotic (Egging et al, 2018;Farber and Kurouski, 2018;Sanchez et al, 2019aSanchez et al, , 2019c and abiotic (Altangerel et al, 2017;Sanchez et al, 2020b) stresses. RS can be used for accurate and rapid plant phenotyping and the assessment of the nutritional content of grains (Krimmer et al, 2019;Farber et al, 2020c).…”

Section: Introductionmentioning

confidence: 99%

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

Payne

Kurouski

2021

Front. Plant Sci.

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Digital farming is a novel agricultural philosophy that aims to maximize a crop yield with the minimal environmental impact. Digital farming requires the development of technologies that can work directly in the field providing information about a plant health. Raman spectroscopy (RS) is an emerging analytical technique that can be used for non-invasive, non-destructive, and confirmatory diagnostics of diseases, as well as the nutrient deficiencies in plants. RS is also capable of probing nutritional content of grains, as well as highly accurate identification plant species and their varieties. This allows for Raman-based phenotyping and digital selection of plants. These pieces of evidence suggest that RS can be used for chemical-free surveillance of plant health directly in the field. High selectivity and specificity of this technique show that RS may transform the agriculture in the US. This review critically discusses the most recent research articles that demonstrate the use of RS in diagnostics of abiotic and abiotic stresses in plants, as well as the identification of plant species and their nutritional analysis.

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“…Previously reported experimental results demonstrated absence of photodegradation of plant material at these experimental conditions. We also observed neither visual signs of laser-induced photodegradation of rice leaves during spectral acquisition nor any noticeable structural changes in plants in the control group of plants (Sanchez et al, 2020b). Stalk scans were acquired while gently pressing the device onto a flat side of the stalk to maximize the contact between the device and stalk.…”

Section: Raman Spectroscopymentioning

confidence: 92%

Raman-Based Diagnostics of Stalk Rot Disease of Maize Caused by Colletotrichum graminicola

et al. 2021

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Stalk rot caused by Colletotrichum graminicola is a disease of worldwide importance. Stalk rot is difficult to detect at the early stages of infection because the fungus colonizes the tissues inside the maize stem. Current diagnostic methods are time-consuming, laborious, and destructive to the stem tissue. We utilized Raman spectroscopy to follow the development of stalk rot in three different maize genotypes grown either in the field or the greenhouse. We then used the acquired spectra to calibrate statistical models to differentiate amongst the different disease timepoints and the genotypes themselves. This non-invasive spectroscopic method enabled high-accuracy identification of stalk rot based on both stalk and leaf spectra. We additionally found that leaf spectra were favorable for identifying maize by genotype. Finally, we identified Raman bands that showed correlation with the sizes of stalk rot-associated lesions in the stems. We demonstrated that Raman spectroscopy is a viable tool for detection of stalk rot disease, as well as potent for the differentiation of maize genotypes.

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Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Salinity Stresses, Nitrogen, Phosphorus, and Potassium Deficiencies in Rice

Cited by 30 publications

References 34 publications

Raman spectroscopy‐based diagnostics of water deficit and salinity stresses in two accessions of peanut

Raman spectroscopy‐based diagnostics of water deficit and salinity stresses in two accessions of peanut

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

Raman-Based Diagnostics of Stalk Rot Disease of Maize Caused by Colletotrichum graminicola

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