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首页> 外文期刊>Journal of near infrared spectroscopy >Determination of the viability of retinispora (Hinoki cypress) seeds using shortwave infrared hyperspectral imaging spectroscopy
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Determination of the viability of retinispora (Hinoki cypress) seeds using shortwave infrared hyperspectral imaging spectroscopy

机译:用短波红外高光谱成像光谱法测定Retinispora(Hinoki Cypress)种子的活力

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The combination of hyperspectral imaging with multivariate data analysis methods has recently been applied to develop a nondestructive technique, required to determine the seed viability of artificially aged vegetable and cereal seeds. In this study, we investigated the potential of shortwave infrared hyperspectral imaging to determine the viability of naturally aged seeds and thereafter develop a model for online seed sorting system. The hyperspectral images of 400 Hinoki cypress tree seeds were acquired, and germination tests were conducted for viability confirmation, which indicated 31.5% of the viable seeds. Partial least square discriminant analysis models with 179 variables in the wavelength region of 1000-1800 nm were developed with a maximum model accuracy of 98.4% and 93.8% in both the calibration and validation sets, respectively. The partial least square discriminant analysis beta coefficient revealed the key wavelengths to differentiate viable from nonviable seeds, determined based on the differences in the chemical compositions of the seeds, including their lipid and fatty acid contents, which may control the germination ability of the seeds. The most effective wavelengths were selected using two model-based variable selection methods (i.e., the variable importance of projection (15 variables) and the successive projections algorithm (8 variables)) to develop the model. The successive projections algorithm wavelength selection method was considered to develop a viability model, and its application to the raw data resulted in a prediction accuracy of 94.7% in the calibration set and 92.2% in the validation set. Our results demonstrate the potential of shortwave infrared hyperspectral imaging spectroscopy as a powerful nondestructive method to determine the viability of Hinoki cypress seeds. This method could be applied to develop an online seed sorting system for seed companies and nurseries.
机译:最近应用了具有多变量数据分析方法的高光谱成像的组合来开发非破坏性技术,以确定人工老化植物和谷物种子的种子活力所必需。在这项研究中,我们研究了短波红外高光谱成像的潜力,以确定天然老化种子的可行性,此后为在线种子分选系统产生模型。获得400次曲调赛柏树种子的高光谱图像,进行萌发试验,用于生存率确认,指出了31.5%的活种子。在1000-1800nm波长区域中的局部最小二乘判别分析模型具有1000-1800nm的波长区域,分别在校准和验证集中的最大模型精度为98.4%和93.8%。局部最小二乘判别分析β系数揭示了与非可行性种子分化的关键波长,基于种子化学组成的差异,包括它们的脂质和脂肪酸含量,这可以控制种子的萌发能力。使用基于模型的可变选择方法(即,投影(15变量)的可变重要性以及连续投影算法(8变量))来选择最有效的波长以开发模型。考虑连续投影算法波长选择方法开发活力模型,其在原始数据中的应用导致校准集中的预测精度为94.7%,验证集中的92.2%。我们的结果表明,短波红外高光谱成像光谱的潜力作为一种强大的非破坏性方法,以确定Hinoki柏树种子的活力。该方法可以应用于开发用于种子公司和苗圃的在线种子分选系统。

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