8 research outputs found

    Advances in plant disease detection and monitoring: From traditional assays to in-field diagnostics

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    none7noHuman activities significantly contribute to worldwide spread of phytopathological adversities. Pathogen-related food losses are today responsible for a reduction in quantity and quality of yield and decrease value and financial returns. As a result, “early detection” in combination with “fast, accurate, and cheap” diagnostics have also become the new mantra in plant pathology, especially for emerging diseases or challenging pathogens that spread thanks to asymptomatic individuals with subtle initial symptoms but are then difficult to face. Furthermore, in a globalized market sensitive to epidemics, innovative tools suitable for field-use represent the new frontier with respect to diagnostic laboratories, ensuring that the instruments and techniques used are suitable for the operational contexts. In this framework, portable systems and interconnection with Internet of Things (IoT) play a pivotal role. Here we review innovative diagnostic methods based on nanotechnologies and new perspectives concerning information and communication technology (ICT) in agriculture, resulting in an improvement in agricultural and rural development and in the ability to revolutionize the concept of “preventive actions”, making the difference in fighting against phytopathogens, all over the world.openBuja I.; Sabella E.; Monteduro A.G.; Chiriaco M.S.; De Bellis L.; Luvisi A.; Maruccio G.Buja, I.; Sabella, E.; Monteduro, A. G.; Chiriaco, M. S.; De Bellis, L.; Luvisi, A.; Maruccio, G

    Postharvest Technologies of Fresh Citrus Fruit: Advances and Recent Developments for the Loss Reduction during Handling and Storage

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    Citrus spp. are spread mainly in the Mediterranean basin and represent the largest fruit source for human consumption. Postharvest losses, mainly due to diseases and metabolic disorders of fruits, can cause severe wastage, reaching 30 to 50% of the total production. Preserving quality and extending shelf life are essential objectives for postharvest technological innovation, determined by the proper handling, treatment, storage and transport of harvested produce. Moreover, the application of novel sustainable strategies is critical for the reduction of synthetic fungicide residues on fruit surfaces and the impact on the environment caused by waste disposal of fungicides. In this article, the current knowledge about the safest and more sustainable strategies, as well as advanced postharvest handling and storage technologies, will be critically reviewed

    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

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    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 π–π 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)
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