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基于光譜技術(shù)的褐殼血斑蛋鑒別方法研究
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“十二五”國家科技支撐計劃資助項目(2011BAD20B12)、高等學(xué)?;究蒲袠I(yè)務(wù)費專項資金資助項目(2012FZA6006)和杭州市農(nóng)業(yè)科研攻關(guān)專項資助項目(20120232B55)


Detection of Blood Spots in Brown Eggs Based on Spectroscopic Techniques
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    摘要:

    血斑蛋是一種帶有血絲的異常蛋,。通過自制的雞蛋內(nèi)部品質(zhì)光譜檢測系統(tǒng),采集40個正常蛋和60個人工注射血樣的血斑蛋的可見/近紅外光譜,,研究比較了3種不同的血斑蛋判別方法:傳統(tǒng)的血值判別法,、偏最小二乘判別法(DPLS)以及融合光譜信息與蛋殼顏色信息的最小二乘支持向量機(LS-SVM)判別法,結(jié)果表明基于顏色信息融合的最小二乘支持向量機的判別結(jié)果明顯優(yōu)于傳統(tǒng)的血值判別法,,正常蛋的判別正確率為90%,,血斑蛋的判別正確率為91.7%,證明了此方法可用于褐色蛋的血斑檢測,。

    Abstract:

    The abnormal egg, blood-egg, has the internal optically active anomalies blood spots. A detection system based on Vis/NIR spectroscopy was designed for eggs’ internal quality inspection. Then, spectra data of 40 brown normal eggs and 60 artificial abnormal eggs obtained by injecting a small amount of blood ingredient were collected. Three analytical methods: the traditional discrimination method using blood value, discriminant partial least squares analysis (DPLS) and least squares support vector machine (LS-SVM) combined with spectral information and eggshell color information were compared for discrimination analysis. The final results showed that the discrimination rate based on LS-SVM method was 90.0% for normal eggs and that was 91.7% for blood-spot eggs, better than the results using traditional discrimination analysis methods. The results suggested that LS-SVM was an effective analytical tool in detecting blood-spot eggs with brown eggshell.

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徐惠榮,徐文豪,陳華瑞,姚 洋,張安紅.基于光譜技術(shù)的褐殼血斑蛋鑒別方法研究[J].農(nóng)業(yè)機械學(xué)報,2014,45(2):194-198. Xu Huirong, Xu Wenhao, Chen Huarui, Yao Yang, Zhang Anhong. Detection of Blood Spots in Brown Eggs Based on Spectroscopic Techniques[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(2):194-198.

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  • 收稿日期:2012-12-19
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  • 在線發(fā)布日期: 2014-02-10
  • 出版日期: 2014-02-10
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