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Development of a Low-Cost Narrow Band Multispectral Imaging System Coupled with Chemometric Analysis for Rapid Detection of Rice False Smut in Rice Seed

机译:低成本窄带多光谱成像系统结合化学计量学分析可快速检测水稻种子中的黑穗病

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摘要

Spectral imaging is a promising technique for detecting the quality of rice seeds. However, the high cost of the system has limited it to more practical applications. The study was aimed to develop a low-cost narrow band multispectral imaging system for detecting rice false smut (RFS) in rice seeds. Two different cultivars of rice seeds were artificially inoculated with RFS. Results have demonstrated that spectral features at 460, 520, 660, 740, 850, and 940 nm were well linked to the RFS. It achieved an overall accuracy of 98.7% with a false negative rate of 3.2% for , and 91.4% with 6.7% for respectively, using the least squares-support vector machine. Moreover, the robustness of the model was validated through transferring the model of to with the overall accuracy of 90.3% and false negative rate of 7.8%. These results demonstrate the feasibility of the developed system for RFS identification with a low detecting cost.
机译:光谱成像是检测水稻种子质量的有前途的技术。但是,该系统的高成本将其限制在更实际的应用中。该研究旨在开发一种低成本的窄带多光谱成像系统,用于检测水稻种子中的水稻假黑穗病(RFS)。用RFS人工接种了两个不同的水稻种子品种。结果表明,在460、520、660、740、850和940 nm处的光谱特征与RFS紧密相关。使用最小二乘支持向量机,它的整体准确率达到98.7%,假阴性率分别为3.2%和91.4%,错误率为6.7%。此外,通过将模型转换为,验证了模型的鲁棒性,总体准确性为90.3%,假阴性率为7.8%。这些结果证明了开发的系统以低检测成本进行RFS识别的可行性。

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