Abstract
The incorporation of artificial intelligence into agriculture presents challenges, particularly due to hardware limitations, especially in sensors. Currently, pest detection relies heavily on manual scouting by humans. Therefore, the objective of this study is to create a chemoresistive sensor that enables early identification of the characteristic volatile compound, viz., methyl jasmonate, released during pest infestations. Given the lower reactivity of esters, we have fine-tuned a composite consisting of SnO2 nanoparticles and 2D-MXene sheets to enhance adsorption and selective oxidation, resulting in heightened sensitivity. The optimized composite demonstrated a notable response even at concentrations as low as 120 ppb, successfully confirming pest infestations in tomato crops.
Published Version
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