Fu Li, Zheng Yuhong, Zhang Pengchong, Lai Guosong
Key Laboratory of Novel Materials for Sensor of Zhejiang Province, College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.
Institute of Botany, Jiangsu Province & Chinese Academy of Sciences (Nanjing Botanical Garden Mem. Sun Yat-Sen), Nanjing 210014, China.
Micromachines (Basel). 2021 Aug 30;12(9):1048. doi: 10.3390/mi12091048.
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 SiO, 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.
硅在水稻生长中起着非常重要的作用。过去十年间，水稻与硅之间关系的研究已成为一个热门领域。目前，硅钼蓝分光光度法大多用于测定水稻中的硅含量。然而，由于还原剂、测量波长和显色时间的选择不同，该方法的结果差异很大。在本研究中，我们首次提出了一种用于检测水稻中硅含量的电化学传感器。这种电化学分析技术不仅提供了一种替代检测策略，而且由于电化学方法检测速度快且仪器小型化，适用于现场检测。采用电化学技术构建方法是一个关键目标。水稻中的硅经氢氟酸提取后，调节pH值后变为二氧化硅。然后将二氧化硅固定在玻碳表面。这些二氧化硅纳米颗粒为硼氢化钠和银离子的吸附提供了额外的比表面积，进而形成银纳米颗粒以制备电化学传感器。所提出的电化学传感器可用于间接测量10 - 400 mg/L的SiO，因此该方法可测量4.67 - 186.8 mg/g的硅。该电化学传感器可用于与传统的硅钼蓝分光光度法进行比较。五个传感器的电流值相对标准偏差仅为3.4%。在实际应用中，对颖壳、叶片、叶鞘和茎杆的200个样品进行了测试。结果表明，颖壳的硅含量最高，茎杆的硅含量最低。颖壳、叶片、叶鞘和茎杆的线性相关系数分别为0.9841、0.9907、0.9894和0.993。
