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花椒揮發(fā)油含量的近紅外光譜無(wú)損檢測(cè)
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    摘要:

    應(yīng)用近紅外漫反射光譜技術(shù),采用偏最小二乘法,針對(duì)118份完整花椒顆粒定標(biāo)樣品集,研究了掃描分辨率為4、8、16 cm-1,掃描次數(shù)為32、64、128的9種掃描參數(shù)組合情況下的揮發(fā)油含量近紅外光譜預(yù)測(cè)模型。掃描分辨率為16 cm-1、掃描次數(shù)為128時(shí),建立的預(yù)測(cè)模型最優(yōu)。在最優(yōu)參數(shù)組合情況下,定標(biāo)集樣品的內(nèi)部驗(yàn)證決定系數(shù)R2為0.907,交互驗(yàn)證誤差均方根為0.509,用20份樣品作為預(yù)測(cè)集進(jìn)行外部驗(yàn)證,外部驗(yàn)證決定系數(shù)R2為0.973,預(yù)測(cè)誤差均方根為0.272,相對(duì)分析誤差為6.28。結(jié)果表明,近紅外光譜分析技術(shù)可以快速、無(wú)損地檢測(cè)花椒顆粒中揮發(fā)油的含量。

    Abstract:

    The method of near infrared reflectance spectroscopy for predicting volatile oil content in intact Zanthoxylum bungeagum Maxim was developed. Adopting partial least squares (PLS) regression, the prediction models were built by the 118 samples in 9 kinds acquisition parameters combination with the resolution (4, 8 and 16cm-1) and the sample scans (32, 64 and 128). Results demonstrated that the model obtained at resolution of 16 cm-1and sample scans of 128 was better than the others, and the determination coefficient and RMSECV of cross validation were 0.907 and 0.509, respectively. Applying the model to the test set with 20 samples, the determination coefficient, RMSEP and RPD of test set validation were 0.973, 0.272 and 6.28, respectively. The experimental results show that NIRS can be used as a method to detect intact Zanthoxylum bungeagum Maxim volatile oil content rapidly and nondestructively. 

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王剛,祝詩(shī)平,闞建全,楊飛,郭靜,王一鳴.花椒揮發(fā)油含量的近紅外光譜無(wú)損檢測(cè)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(3):79-81.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(3):79-81.

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