Application of Biosensor for the Identification of Various Pathogens and Pests Mitigating Against the Agricultural Production: Recent Advances

Adetunji, Charles Oluwaseun; Nwankwo, Wilson; Ukhurebor, Kingsley Eghonghon; Olayinka, Akinola Samson; Makinde, Ayodeji Samuel

doi:10.1007/978-3-030-66165-6_9

Cited by 14 publications

(10 citation statements)

References 101 publications

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“…At the moment, BioSS/NanoBioSS are used in several aspects of human endeavours such as diagnosing different diseases and monitoring and management of the quality food and environmental effluences [ 8 , 25 , 28 , 48 , 49 ]. The surface dimension ratio of most frequently used NMs in BioSS/NanoBioSS such as noble metal NPs, quantum dot (QD), carbon-based NMs, and other NMs is larger when compared to the bulk arrangement of the material and this makes their properties (chemical, electrical, and optical) different and better enhanced [ 50 ].…”

Section: Nanotech In Bioss/nanobioss Mechanismsmentioning

confidence: 99%

“…Several papers have reported on the uses of NanoTech vis-à-vis BioSS/NanoBioSS for biomedical/clinical/healthcare applications (such as identifying of viruses and pathogen microbes, detecting of cancerous cells, and breath analysis mechanism) [ 27 , 58 ], environmental applications (detection of air, soil, and water pollution) [ 59 – 61 ], and agricultural applications (climate-smart organic agriculture and identification of animals and plants pests and diseases) [ 25 , 48 , 62 – 64 ]. There have also been suggestions on modern materials science vis-à-vis NanoTech been employed in COVID-19-related researches, as this has evidently played a dynamic role in mitigating and combating the present deadly COVID-19 complications via environmental remediation [ 37 ].…”

Section: Nanotech In Bioss/nanobioss Mechanismsmentioning

confidence: 99%

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A Methodical Review on the Applications and Potentialities of Using Nanobiosensors for Disease Diagnosis

Ukhurebor

Onyancha

Aigbe

et al. 2022

BioMed Research International

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Presently, with the introduction of nanotechnology, the evolutions and applications of biosensors and/or nanobiosensors are becoming prevalent in various scientific domains such as environmental and agricultural sciences as well as biomedical, clinical, and healthcare sciences. Trends in these aspects have led to the discovery of various biosensors/nanobiosensors with their tremendous benefits to mankind. The characteristics of the various biosensors/nanobiosensors are primarily based on the nature of nanomaterials/nanoparticles employed in the sensing mechanisms. In the last few years, the identification, as well as the detection of biological markers linked with any form of diseases (communicable or noncommunicable), has been accomplished by several sensing procedures using nanotechnology vis-à-vis biosensors/nanobiosensors. Hence, this study employs a systematic approach in reviewing some contemporary developed exceedingly sensitive nanobiosensors alongside their biomedical, clinical, or/and healthcare applications as well as their potentialities, specifically for the detection of some deadly diseases drawn from some of the recent publications. Ways forward in the form of future trends that will advance creative innovations of the potentialities of nanobiosensors for biomedical, clinical, or/and healthcare applications particularly for disease diagnosis are also highlighted.

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Section: Nanotech In Bioss/nanobioss Mechanismsmentioning

confidence: 99%

Section: Nanotech In Bioss/nanobioss Mechanismsmentioning

confidence: 99%

A Methodical Review on the Applications and Potentialities of Using Nanobiosensors for Disease Diagnosis

Ukhurebor

Onyancha

Aigbe

et al. 2022

BioMed Research International

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“…Undoubtedly, there is going to be a shortage of food owing to the enormously increasing population. erefore, it is crucial to continuously develop and explore innovative agricultural techniques [3][4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Development of a Wireless Sensor Network and IoT-based Smart Irrigation System

Ndunagu

Ukhurebor

Akaaza

et al. 2022

Applied and Environmental Soil Science

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This study proposes a smart irrigation system (SIS) using the drip method, which was designed and implemented using wireless sensor networks and an open-source Internet of Things (IoT) cloud computing platform (“Thingspeak.com”) for data collection, storing, data analytics, and visualization. The methodology incorporates the integration of hardware and software components to make irrigation decisions based on web resources like the weather forecast from “weather.com” and sensor values from soil samples. The data collected are then analyzed at the edge server and updated every 15 minutes. Based on the threshold value, the system starts pumping water or stops the irrigation process depending on the irrigation schedule. A web application was developed to display the result so that we could monitor and control the system using an android application edge or a web browser. Based on the data recorded and measured, the data are in comma-separated values (CSV) format and contain 143731 entries with 10 columns. The sample size used contains 5722 rows and 6 columns from the result of our machine learning algorithms using Microsoft Excel and Jupyter Notebook to process and evaluate the performance of the drip SIS, considering the soil moisture, soil temperature, sunlight, rain, and pump. The results confirm the threshold metrics classification evaluation, and some of the metrics computed from our confusion matrix are shown in the classification summary results, showing the accuracy to be 89%, the misclassification rate (error rate) is equal to 10%, the sensitivity is equal to 79%, the specificity is equal to 93%, and the precision of the model is 81%. The evaluation, when compared to K-nearest neighbours using K = 6 and K = 1, shows the prediction accuracy to be 97% and 98%. The results indicate the system is highly efficient and reliable in performing irrigation and managing water resources and can be adopted in rural areas to boost agricultural productivity.

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“…Biosensors are used for agricultural and environmental monitoring applications to detect various pathogens and other environmental contaminants [ 37 , 38 ]. Due to their relatively high detection rate and short response time, the frequency of the use of biosensors is increasing [ 39 , 40 ].…”

Section: Introductionmentioning

confidence: 99%

“…Due to their relatively high detection rate and short response time, the frequency of the use of biosensors is increasing [ 39 , 40 ]. However, the main challenges that is faced by current biosensors lie in their sensor performance, sampling, scaling up, and detection in open areas [ 37 , 38 ]. Roy et al [ 41 ] fabricated an array of whole-cell biosensors to detect the aromatic pollutants such as benzene, phenols, and toluene, which are carcinogenic compounds that are found in polluted water sources.…”

Section: Introductionmentioning

confidence: 99%

Multi-Layer Biosensor for Pre-Symptomatic Detection of Puccinia strifformis, the Causal Agent of Yellow Rust

et al. 2022

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The yellow rust of wheat (caused by Puccinia striiformis f. sp. tritici) is a devastating fungal infection that is responsible for significant wheat yield losses. The main challenge with the detection of this disease is that it can only be visually detected on the leaf surface between 7 and 10 days after infection, and by this point, counter measures such as the use of fungicides are generally less effective. The hypothesis of this study is to develop and use a compact electrochemical-based biosensor for the early detection of P. striiformis, thus enabling fast countermeasures to be taken. The biosensor that was developed consists of three layers. The first layer mimics the wheat leaf surface morphology. The second layer consists of a sucrose/agar mixture that acts as a substrate and contains a wheat-derived terpene volatile organic compound that stimulates the germination and growth of the spores of the yellow rust pathogen P. s. f. sp. tritici. The third layer consists of a nonenzymatic glucose sensor that produces a signal once invertase is produced by P. striiformis, which comes into contact with the second layer, thereby converting sucrose to glucose. The results show the proof that this innovative biosensor can enable the detection of yellow rust spores in 72 h.

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Application of Biosensor for the Identification of Various Pathogens and Pests Mitigating Against the Agricultural Production: Recent Advances

Cited by 14 publications

References 101 publications

A Methodical Review on the Applications and Potentialities of Using Nanobiosensors for Disease Diagnosis

A Methodical Review on the Applications and Potentialities of Using Nanobiosensors for Disease Diagnosis

Development of a Wireless Sensor Network and IoT-based Smart Irrigation System

Multi-Layer Biosensor for Pre-Symptomatic Detection of Puccinia strifformis, the Causal Agent of Yellow Rust

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