Research on non-destructive identification technology of rice varieties based on HSI and GBDT

IF 3.1 3区 物理与天体物理 Q2 INSTRUMENTS & INSTRUMENTATION Infrared Physics & Technology Pub Date : 2024-08-16 DOI:10.1016/j.infrared.2024.105511
Shujia Li , Laijun Sun , Yujie Tian , Xiaoli Lu , Zhongyu Fu , Guijun Lv , Lingyu Zhang , Yuantong Xu , Wenkai Che
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Abstract

Accurate identification of rice varieties is of great significance for rice planting, field management and storage, and is also a key link in the process of agricultural breeding. In this study, a gradient boosting decision tree (GBDT) model was established based on hyperspectral imaging (HSI) to realize high-speed and non-destructive variety identification of six rice varieties. In this study, the near-infrared hyperspectral images of 600 rice samples of 6 varieties were taken as the research object, and the characteristic spectra of sensitive regions of the sample spectral images were processed by multiplicative scatter correction (MSC), and after the characteristic wavelengths were determined by the importance scores, the GBDT model to realize the identification of rice sample varieties, and the grid search algorithm was used to optimize the four internal parameters of GBDT. The results showed that the established GBDT model for the accuracy of rice variety identification of vitro test set samples reached 95%, indicating that HSI can be used to quickly and non-destructively identify rice varieties, and provide a new idea for batch online non-destructive testing of rice seeds.

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基于 HSI 和 GBDT 的水稻品种无损鉴定技术研究
准确识别水稻品种对水稻种植、田间管理和储藏具有重要意义,也是农业育种过程中的关键环节。本研究建立了基于高光谱成像(HSI)的梯度提升决策树(GBDT)模型,实现了对 6 个水稻品种的高速、无损的品种鉴定。本研究以6个品种600个水稻样品的近红外高光谱图像为研究对象,对样品光谱图像敏感区域的特征光谱进行乘法散射校正(MSC)处理,通过重要性评分确定特征波长后,建立GBDT模型实现水稻样品的品种鉴定,并采用网格搜索算法对GBDT的4个内部参数进行优化。结果表明,建立的 GBDT 模型对体外测试集样品的水稻品种鉴定准确率达到 95%,表明可以利用 HSI 快速、无损地鉴定水稻品种,为水稻种子批量在线无损检测提供了新思路。
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来源期刊
CiteScore
5.70
自引率
12.10%
发文量
400
审稿时长
67 days
期刊介绍: The Journal covers the entire field of infrared physics and technology: theory, experiment, application, devices and instrumentation. Infrared'' is defined as covering the near, mid and far infrared (terahertz) regions from 0.75um (750nm) to 1mm (300GHz.) Submissions in the 300GHz to 100GHz region may be accepted at the editors discretion if their content is relevant to shorter wavelengths. Submissions must be primarily concerned with and directly relevant to this spectral region. Its core topics can be summarized as the generation, propagation and detection, of infrared radiation; the associated optics, materials and devices; and its use in all fields of science, industry, engineering and medicine. Infrared techniques occur in many different fields, notably spectroscopy and interferometry; material characterization and processing; atmospheric physics, astronomy and space research. Scientific aspects include lasers, quantum optics, quantum electronics, image processing and semiconductor physics. Some important applications are medical diagnostics and treatment, industrial inspection and environmental monitoring.
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