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电化学指纹图谱对 spp.及其杂种后代的生物识别。

Biometric Identification of spp. and Their Hybrid Progenies by Electrochemical Fingerprints.

机构信息

Jiangsu Engineering Research Center for Taxodium Rich, Germplasm Innovation and Propagation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing Botanical Garden, Memorial Sun Yat-Sen, Nanjing 210014, China.

College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.

出版信息

Biosensors (Basel). 2021 Oct 18;11(10):403. doi: 10.3390/bios11100403.

Abstract

The use of electrochemical fingerprints for plant identification is an emerging application in biosensors. In this work, , , , and 18 of their hybrid progenies were collected for this purpose. This is the first attempt to use electrochemical fingerprinting for the identification of plant hybrid progeny. Electrochemical fingerprinting in the leaves of spp. was recorded under two conditions. The results showed that the electrochemical fingerprints of each species and progeny possessed very suitable reproducibility. These electrochemical fingerprints represent the electrochemical behavior of electrochemically active substances in leaf tissues under specific conditions. Since these species and progenies are very closely related to each other, it is challenging to identify them directly using a particular electrochemical fingerprinting. Therefore, electrochemical fingerprints measured under different conditions were used to perform pattern recognition. We can identify different species and progenies by locating the features in different pattern maps. We also performed a phylogenetic study with data from electrochemical fingerprinting. The results proved that the electrochemical classification results and the relationship between them are closely related.

摘要

电化学指纹图谱在植物鉴定中的应用是生物传感器领域的一个新兴应用。为此,本研究收集了 3 个种和 18 个杂种后代的样本。这是首次尝试将电化学指纹图谱用于鉴定植物杂种后代。在两种条件下记录了 种的叶片电化学指纹图谱。结果表明,每个物种和杂种后代的电化学指纹图谱具有非常合适的重现性。这些电化学指纹图谱代表了叶组织中电化学活性物质在特定条件下的电化学行为。由于这些物种和杂种后代彼此非常密切相关,因此直接使用特定的电化学指纹图谱进行鉴定具有一定的挑战性。因此,使用不同条件下测量的电化学指纹图谱进行模式识别。我们可以通过定位不同模式图中的特征来识别不同的物种和杂种后代。我们还对电化学指纹图谱的数据进行了系统发育研究。结果证明,电化学分类结果及其相互关系密切相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/8534068/4a3c40068504/biosensors-11-00403-g001.jpg

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