Quantification of Silicon in Rice Based on an Electrochemical Sensor via an Amplified Electrocatalytic Strategy - Fu, Li; Zheng, Yuhong; Zhang, Pengchong; Lai, Guosong (Micromachines (Basel), 2021)
Silicon plays a very important role in the growth of rice. The study of the relationship between rice and silicon has become a hot area in the last decade. Currently, the silica-molybdenum blue spectrophotometric method is mostly used for the determination of silicon content in rice. However, the results of this method vary greatly due to the different choices of reducing agents, measurement wavelengths and color development times. In this work, we present for the first time an electrochemical sensor for the detection of silicon content in rice. This electrochemical analysis technique not only provides an alternative detection strategy, but also, due to the rapid detection by electrochemical methods and the miniaturization of the instrument, it is suitable for field testing. Methodological construction using electrochemical techniques is a key objective. The silicon in rice was extracted by HF and becomes silica after pH adjustment. The silica was then immobilized onto the glassy carbon surface. These silica nanoparticles provided additional specific surface area for adsorption of sodium borohydride and Ag ions, which in turn formed Ag nanoparticles to fabricate an electrochemical sensor. The proposed electrochemical sensor can be used for indirect measurements of 10–400 mg/L of SiO2, and thus, the method can measure 4.67–186.8 mg/g of silicon. The electrochemical sensor can be used to be comparable with the conventional silicon-molybdenum blue spectrophotometric method. The RSD of the current value was only 3.4% for five sensors. In practical use, 200 samples of glume, leaf, leaf sheath and culm were tested. The results showed that glume had the highest silicon content and culm had the lowest silicon content. The linear correlation coefficients for glume, leaf, leaf sheath and culm were 0.9841, 0.9907, 0.9894 and 0.993, respectively.