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基于支持向量機(jī)的甘薯冷害光譜檢測方法
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河北省引進(jìn)留學(xué)人員資助項(xiàng)目(C2018340)


Spectral Detection Method for Chilling Damage of Sweet Potato Based on Support Vector Machine
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    摘要:

    針對甘薯早期冷害不易檢測,導(dǎo)致甘薯品質(zhì)下降,易感染其他病害等問題,建立了基于光譜技術(shù)的甘薯冷害無損檢測方法?;陬惪煞中詼?zhǔn)則的關(guān)鍵特征排序法選擇有效特征光譜波長,利用支持向量機(jī)算法對數(shù)據(jù)集進(jìn)行訓(xùn)練評價,檢測特征光譜波長的準(zhǔn)確性以及甘薯早期冷害發(fā)生情況。通過對5個甘薯品種共400個樣品進(jìn)行實(shí)驗(yàn),以訓(xùn)練數(shù)據(jù)與測試數(shù)據(jù)5∶5比例檢測甘薯冷害準(zhǔn)確率高達(dá)99.52%,以7∶3比例測試結(jié)果高達(dá)99.63%。實(shí)驗(yàn)結(jié)果證明特征光譜波段選擇正確,表明光譜技術(shù)可以有效識別甘薯冷害,此研究為甘薯貯存分類等后續(xù)工作提供了技術(shù)方法支持。

    Abstract:

    The storage of sweet potato is susceptible to chilling damage, which not only affects its quality but also is susceptible to other diseases, which greatly reduces the commercial and economic value of sweet potato. For the biological detection technology and traditional detection methods will cause irreversible damage to sweet potato, so a nondestructive detection method of sweet potato chilling damage based on optical fiber spectroscopy technology was established. The feature spectrum bands were selected by the key feature ranking method based on the class separability criterion. And the support vector machine algorithm was used to train and evaluate the data set to detect the accuracy of the characteristic spectrum and the occurrence of sweet potatoes before the symptoms of chilling damage were visible to the human eyes. Totally five sweet potato varieties were used for experiments. The accuracy of detecting chilling damage in sweet potatoes was as high as 99.52% with the ratio of training data and test data of 5∶5, and the incidence of the ratio of 7∶3 was as high as 9963%. The results proved the correctness of the characteristic spectrum, and the characteristic spectral bands were as follows: Jishu26 was 821.3~823.5nm; Yanshu25 was 810.5~821.9nm; Xiguahong was 8188~821.9nm; Xinong431 was 601.5~606.4nm; and Longshu9 was 759.6~761.2nm. The results showed that the spectroscopy technology can effectively detect and identify sweet potato chilling damage. This research provided technical method for subsequent work for sweet potato storage classification. 

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張曉雪,楊志輝,曹珊珊,司永勝.基于支持向量機(jī)的甘薯冷害光譜檢測方法[J].農(nóng)業(yè)機(jī)械學(xué)報,2020,51(s2):471-477. ZHANG Xiaoxue, YANG Zhihui, CAO Shanshan, SI Yongsheng. Spectral Detection Method for Chilling Damage of Sweet Potato Based on Support Vector Machine[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(s2):471-477.

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  • 收稿日期:2020-08-10
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  • 在線發(fā)布日期: 2020-12-10
  • 出版日期: 2020-12-10
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