Development of a Fluorescence Resonance Energy Transfer (FRET)-Based DNA Biosensor for Detection of Synthetic Oligonucleotide of Ganoderma boninense

Bakhori, Noremylia Mohd; Yusof, Nor Azah; Abdullah, Abdul Halim; Hussein, Mohd Zobir

doi:10.3390/bios3040419

Cited by 43 publications

(11 citation statements)

References 10 publications

(9 reference statements)

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“…[163] Applying synthesized biocompatible nanosized CdSe quantum dots (QDs) with the DNA probe, Bakhori et al exploited the fluorescence resonance energy transfer (FRET) technology to detect the synthetic oligonucleotide of DNA for Ganoderma boninense, an oil palm pathogen. [164] The FRET approach with QDs could determine the hybridization process, demonstrating a high sensitivity and a low detection limit of 3.55 × 10 -9 m. Due to a high surface-to-volume ratio, gold nanoparticles (Au-NPs) have been employed for pathogen detection with low detection limits and high specificity. As shown in Figure 6f, Zhao et al reported a dual amplified electrochemical sandwich enzyme-linked immunoassay (ELISA) to tag the Au-NPs with the Horseradish peroxidase (HRP) antibodies to detect Pantoea stewartii sbusp.…”

Section: Soil Insect/pest Sensorsmentioning

confidence: 99%

“…exploited the fluorescence resonance energy transfer (FRET) technology to detect the synthetic oligonucleotide of DNA for Ganoderma boninense , an oil palm pathogen. [ 164 ] The FRET approach with QDs could determine the hybridization process, demonstrating a high sensitivity and a low detection limit of 3.55 × 10 –9 m . Due to a high surface‐to‐volume ratio, gold nanoparticles (Au‐NPs) have been employed for pathogen detection with low detection limits and high specificity.…”

Section: Advances Of Typical Soil Sensorsmentioning

confidence: 99%

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Soil Sensors and Plant Wearables for Smart and Precision Agriculture

et al. 2021

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a compelling need to utilize advanced technologies in the agriculture sector to increase agricultural productivity and reduce food losses to guarantee food security. [2] In this regard, "smart agriculture" or "precision agriculture" has been attracting increasing attention due to its capability for using less to grow more compared to traditional agricultural practices. In addition, it improves the quality of the work environment and social aspects of farming, ranching, and other relevant professions. [4] Smart agriculture comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management to optimize production by accounting for variabilities and uncertainties within sustainable agricultural systems. [3][4][5] Among the set of technologies, advanced sensing systems that monitor soil health and conditions and crop developments are of paramount importance because they collect and evaluate critical data for decision making and management, especially when crop growth conditions vary considerably over space and time. Spatial variation may result from soil properties, diseases, weeds, pests, and previous land management. In particular, some soil properties (e.g., moisture, pH, nutrients) and plant diseases may form long-term spatial patterns. Temporal variability arises from weather patterns and management practices. In summary, the soil properties relevant to crop growth include a range of soil conditions including soil gas, moisture, temperature, nutrients, pH, and pollutants in the soil (Figure 1). [6,7] Monitoring the soil conditions will provide key information not only to improve resource utilization to maximize farming outputs and minimize environmental side effects but also to build site-specific databases of relationships between soil conditions and plant growth for intelligent and sustainable agriculture systems. Traditionally, soil properties are measured by soil sampling and offsite laboratory analysis or by on-site measurement to provide an extensive knowledge of soil information. [8] Seasonally varying crop growth conditions, such as water stress, lack of nutrients, diseases, weeds, and insects, are evaluated by visual inspection and laboratory analysis of plant tissues. The relatively periodically coarse sampling/measurement rate of these conventional strategies may not be sufficient to reveal variation at the appropriate spatial and temporal resolution. Novel technologies for collecting soil information with sufficient spatiotemporal resolutions are in demand to build efficient smart or precision agriculture systems. With the Soil sensors and plant wearables play a critical role in smart and precision agriculture via monitoring real-time physical and chemical signals in the soil, such as temperature, moisture, pH, and pollutants and providing key information to optimize crop growth circumstances, fight against biotic and abiotic stresses, and enhance crop yields. Herein, the recent advances of the important soil sensors in agricultural applications, in...

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Section: Soil Insect/pest Sensorsmentioning

confidence: 99%

Section: Advances Of Typical Soil Sensorsmentioning

confidence: 99%

Soil Sensors and Plant Wearables for Smart and Precision Agriculture

et al. 2021

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“…The quantum dots unit utilizes Förster Resonance Energy Transfer (FRET) modeling in its detection operation [ 27 ]. By using a similar technology, Bakhori et al [ 28 ] detected synthetic oligonucleotide of Ganoderma boninense. However, this work employed adjusted quantum dots with carboxylic groups that are then conjugated using a DNA probe.…”

Section: Related Literaturementioning

confidence: 99%

“…However, this work employed adjusted quantum dots with carboxylic groups that are then conjugated using a DNA probe. This gave rise to an improved sensitivity of the system, yielding 3.55 × 10 −9 M as the detection limit [ 28 ].…”

Section: Related Literaturementioning

confidence: 99%

Smart and Climate-Smart Agricultural Trends as Core Aspects of Smart Village Functions

Adesipo

Fadeyi

Kuča

et al. 2020

Sensors

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Attention has shifted to the development of villages in Europe and other parts of the world with the goal of combating rural–urban migration, and moving toward self-sufficiency in rural areas. This situation has birthed the smart village idea. Smart village initiatives such as those of the European Union is motivating global efforts aimed at improving the live and livelihood of rural dwellers. These initiatives are focused on improving agricultural productivity, among other things, since most of the food we eat are grown in rural areas around the world. Nevertheless, a major challenge faced by proponents of the smart village concept is how to provide a framework for the development of the term, so that this development is tailored towards sustainability. The current work examines the level of progress of climate smart agriculture, and tries to borrow from its ideals, to develop a framework for smart village development. Given the advances in technology, agricultural development that encompasses reduction of farming losses, optimization of agricultural processes for increased yield, as well as prevention, monitoring, and early detection of plant and animal diseases, has now embraced varieties of smart sensor technologies. The implication is that the studies and results generated around the concept of climate smart agriculture can be adopted in planning of villages, and transforming them into smart villages. Hence, we argue that for effective development of the smart village framework, smart agricultural techniques must be prioritized, viz-a-viz other developmental practicalities.

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“…By exploiting the photoluminescence of GO and quenching ability of gold nanoparticles (AuNPs) for organic fluorophores, a series of FRET-based biosensors of GO arrays were realized towards aptasensing [ 105 ] and immunosensing [ 106 ] of proteins, and for the detection of sequence-specific DNA hybridization [ 107 , 114 ]. Correspondingly, probe biomolecules including aptamers [ 105 ], antibodies [ 106 ], ssDNAs and molecular beacons (MBs) [ 115 , 116 ] have been utilized in these selective FRET assays of proteins and nucleic acids (e.g., DNA bases and sequences).…”

Section: Graphenementioning

confidence: 99%

Plasma-Enabled Carbon Nanostructures for Early Diagnosis of Neurodegenerative Diseases

2014

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Carbon nanostructures (CNs) are amongst the most promising biorecognition nanomaterials due to their unprecedented optical, electrical and structural properties. As such, CNs may be harnessed to tackle the detrimental public health and socio-economic adversities associated with neurodegenerative diseases (NDs). In particular, CNs may be tailored for a specific determination of biomarkers indicative of NDs. However, the realization of such a biosensor represents a significant technological challenge in the uniform fabrication of CNs with outstanding qualities in order to facilitate a highly-sensitive detection of biomarkers suspended in complex biological environments. Notably, the versatility of plasma-based techniques for the synthesis and surface modification of CNs may be embraced to optimize the biorecognition performance and capabilities. This review surveys the recent advances in CN-based biosensors, and highlights the benefits of plasma-processing techniques to enable, enhance, and tailor the performance and optimize the fabrication of CNs, towards the construction of biosensors with unparalleled performance for the early diagnosis of NDs, via a plethora of energy-efficient, environmentally-benign, and inexpensive approaches.

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Development of a Fluorescence Resonance Energy Transfer (FRET)-Based DNA Biosensor for Detection of Synthetic Oligonucleotide of Ganoderma boninense

Cited by 43 publications

References 10 publications

Soil Sensors and Plant Wearables for Smart and Precision Agriculture

Soil Sensors and Plant Wearables for Smart and Precision Agriculture

Smart and Climate-Smart Agricultural Trends as Core Aspects of Smart Village Functions

Plasma-Enabled Carbon Nanostructures for Early Diagnosis of Neurodegenerative Diseases

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