Detecting abiotic stresses in rice plants using a smart optical biosensor based on gold nanoparticles

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Asefpour Vakilian Keyvan

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Iranian Journal of Biosystems Engineering Year:2024 | Volume:55 | Issue:1 Page(s): 51-69

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Information Journal Paper

Title

Detecting abiotic stresses in rice plants using a smart optical biosensor based on gold nanoparticles

Author(s)

Asefpour Vakilian Keyvan | Issue Writer Certificate

Keywords

Genetic Algorithm

Machine learning

microRNA concentration

Support vector machine

Abstract

The specific detection of the type and severity of plant abiotic stresses to take timely measures helps prevent yield reduction. This study introduces a new method to detect the type and severity of stress in rice plants under salinity, drought, and heat conditions by investigating microRNAs. The concentration of eight microRNAs in the tissue of plants subjected to salinity, drought, and heat conditions was measured with the help of an optical biosensor based on gold nanoparticles. The biosensor worked based on probe-target hybridization, in which the mixture of probe/citrate-capped gold nanoparticles (compound 1) and microRNA/polyethyleneimine-capped nanoparticles (compound 2) resulted in the aggregation of nanoparticles and changes in their spectroscopic properties. In the following, Machine learning methods were used to predict the type and severity of stress using such concentrations. The results showed that the Support vector machine optimized by the Genetic Algorithm was able to detect the severity of salinity, drought, and heat stress applied to rice plants with appropriate performance and with coefficients of determination of 0.94, 0.91, and 0.86, respectively. Then, the results of feature selection based on the cooperative game theory showed that among the microRNAs studied, miRNA-156, miRNA-393, and miRNA-159 had the largest contribution in predicting drought, salinity, and heat stresses in the rice plants, respectively. The findings of the research show that the examination of plant microRNAs with the help of optical biosensors can lead to reliable features for determining plant growth conditions and plant stresses in the early stage.

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