Biosensors on the Field: Early Disease Detection in Crops
DOI:
https://doi.org/10.55938/wlp.v1i2.105Keywords:
Biosensor Technologies, Nano-Biosensors, Nanomaterial-Based Bio-Sensing Devices, Nano Diagnostic Kits, Transistor-Based BiosensorAbstract
Biosensors are frequently employed in plant disease detection and cellular process understanding. This review examines their usage in agriculture with a particular emphasis on their function in identifying and managing biotic and abiotic hurdles. This article examines the possibilities of biosensor approaches based on nanoparticles for identifying and managing plant diseases in agriculture, contrasting established practices with novel sensing technologies and resolving limitations. Nano-biosensors have developed rapidly in recent years as a result of modifications and customizations known as "nano-tuning" that make advantage of nano-material properties. This leads to the creation of "Next Gen Nano-inspired Biosensors," that integrate well-known biosensors and biosensing technologies with adaptable nanomaterials or nanocomposites. Using probabilistic data to improve analysis rate, the paper unveils Preemptive Classification using Discrete Data (PC-DD). Once the detection phase is finished, data is classified utilizing a random forest technique that combines probability, difference, and series. This research investigates the use of Convolutional Neural Network (CNN)-based Feature Extraction and Feature Classification techniques for the detection of Plant Disease employing Near-infrared and Red, Green, and Blue (RGB) imaging. To extract unique labels, a Wasserstein Distance-based Feature Extraction Model and a specially designed sensor are implemented.
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