Dataset Information

Gas Biosensor Arrays Based on Single-Stranded DNA-Functionalized Single-Walled Carbon Nanotubes for the Detection of Volatile Organic Compound Biomarkers Released by Huanglongbing Disease-Infected Citrus Trees.

ABSTRACT: Volatile organic compounds (VOCs) released by plants are closely associated with plant metabolism and can serve as biomarkers for disease diagnosis. Huanglongbing (HLB), also known as citrus greening or yellow shoot disease, is a lethal threat to the multi-billion-dollar citrus industry. Early detection of HLB is vital for removal of susceptible citrus trees and containment of the disease. Gas sensors are applied to monitor the air quality or toxic gases owing to their low-cost fabrication, smooth operation, and possible miniaturization. Here, we report on the development, characterization, and application of electrical biosensor arrays based on single-walled carbon nanotubes (SWNTs) decorated with single-stranded DNA (ssDNA) for the detection of four VOCs-ethylhexanol, linalool, tetradecene, and phenylacetaldehyde-that serve as secondary biomarkers for detection of infected citrus trees during the asymptomatic stage. SWNTs were noncovalently functionalized with ssDNA using ?-? interaction between the nucleotide and sidewall of SWNTs. The resulting ssDNA-SWNT hybrid structure and device properties were investigated using Raman spectroscopy, ultraviolet (UV) spectroscopy, and electrical measurements. To monitor changes in the four VOCs, gas biosensor arrays consisting of bare SWNTs before and after being decorated with different ssDNA were employed to determine the different concentrations of the four VOCs. The data was processed using principal component analysis (PCA) and neural net fitting (NNF).

SUBMITTER: Wang H

PROVIDER: S-EPMC6865013 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Gas Biosensor Arrays Based on Single-Stranded DNA-Functionalized Single-Walled Carbon Nanotubes for the Detection of Volatile Organic Compound Biomarkers Released by Huanglongbing Disease-Infected Citrus Trees.

Wang Hui H Ramnani Pankaj P Pham Tung T Villarreal Claudia Chaves CC Yu Xuejun X Liu Gang G Mulchandani Ashok A

Sensors (Basel, Switzerland) 20191104 21

Volatile organic compounds (VOCs) released by plants are closely associated with plant metabolism and can serve as biomarkers for disease diagnosis. Huanglongbing (HLB), also known as citrus greening or yellow shoot disease, is a lethal threat to the multi-billion-dollar citrus industry. Early detection of HLB is vital for removal of susceptible citrus trees and containment of the disease. Gas sensors are applied to monitor the air quality or toxic gases owing to their low-cost fabrication, smoo ...[more]

PMID: 31689974

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Project description:Citrus production under enclosed structures can exclude the Asian citrus psyllid (ACP, Diaphorina citri) and eliminate the negative effects of citrus greening or huanglongbing (HLB) disease caused by Candidatus Liberibacter asiaticus to the grapefruit (Citrus paradisi) fresh fruit industry. Physically impeding the insect vector from accessing trees is a logical method to have disease-free groves. Our objectives were to assess the ability of enclosed screenhouses to exclude the ACP, stop HLB inoculation and dissemination, and improve fruit yield of in-ground and container-grown 6-year-old "Ray Ruby" grapefruit at super-high planting densities relative to open-air trees. We built a large structure to allow commercial-scale trials and tested two production systems (screenhouse and open-air), two planting systems (in-ground and potted), and two rootstocks ("Sour Orange" [Citrus × aurantium] and "US-897" [Citrus reticulata × Poncirus trifoliate]). The experimental design was a randomized complete block design split-split-plot with four replications. Four passively ventilated 1,080-m2 completely enclosed screenhouses were constructed using a 50-mesh monofilament high-density polyethylene screen. The main support for each enclosed, covered structure consisted of pressure-treated, wooden utility poles. Trees were planted in Sept/2013 on a density of 1,957 trees/ha. Irrigation was performed on-demand using two 7.6-LPH drip emitters per tree, and fertigation was applied three times/week using 15N-2.6P-22.4K water-soluble fertilizer at 180 kg N/ha. Psyllids were monitored using sticky cards and detected inside the screenhouses post-Hurricane Irma, which damaged the screen structures in Sept/2017, leaving openings until repairs were completed in Apr/2018. Screen aging and a tropical storm in April/2019 caused another major screen opening fixed in Oct/2019. Despite the weather-related damages to the screens, only trees cultivated in open-air tested positive for Candidatus Liberibacter asiaticus after 6 years. There was fast disease progression for all outside treatments, with 100% infection. Covered, in-ground trees exhibited the highest trunk diameter and canopy volume (P < 0.0001). Trees grown inside screenhouses exhibited higher fruit yield than outside trees, with the highest yield observed for in-ground trees on "US-897" (51,081 kg/ha) (P < 0.0001). Several open-air treatments particularly in containers did not produce any fruit. On the other hand, potted grapefruit trees cultivated inside the enclosures had the highest soluble solids content (P < 0.001). The screenhouses provided disease exclusion, increased fruit yield, and fruit quality, representing an alternative for growers interested in producing high-quality fruit for the fresh market. Production cost and economic viability still need to be evaluated for large-scale implementation.

Dataset Information

Gas Biosensor Arrays Based on Single-Stranded DNA-Functionalized Single-Walled Carbon Nanotubes for the Detection of Volatile Organic Compound Biomarkers Released by Huanglongbing Disease-Infected Citrus Trees.

Publications

Gas Biosensor Arrays Based on Single-Stranded DNA-Functionalized Single-Walled Carbon Nanotubes for the Detection of Volatile Organic Compound Biomarkers Released by Huanglongbing Disease-Infected Citrus Trees.

Similar Datasets

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