Emerging Smart Biosensors for the Specific and Ultrasensitive Detection of Plant Abiotic Stresses

The functionalities of microRNAs (miRNAs) and their target genes toward stress in plants have been revealed to humans due to the extensive work conducted in the last decade. A tissue-specific change in the regulation of miRNAs occurs as a result of plant stress. In this study, an optical biosensor has been used to measure the concentration of various miRNAs that involve plant stress response in tomatoes after applying drought, salinity, and temperature stresses to the plant. To carry out the experiments, plants were cultivated in a greenhouse environment. To apply drought conditions in plants, they were stressed by withholding water at various levels of field capacity. Saline irrigation water was used to apply salinity. Cold and heat stresses were applied to study the effects of temperature. The concentration of several plant miRNAs, including miRNA-167, miRNA-172, miRNA-393, and miRNA-396, in plant samples was measured after applying the stresses to the plants. After creating a database in which the plant miRNA concentrations were the inputs while the plant stress level was the model output, the artificial neural network was utilized to learn the patterns between the inputs and output. The results indicated that an artificial neural network with an architecture of 4-8-4 could predict the severity of the plant stress with the MSE and R2 values of 0.070 and 0.94, respectively. This shows that combining optical biosensors and machine learning techniques could detect the stress level in stress conditions with acceptable specificity and sensitivity.