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PLS算法在高光譜估測加工番茄白粉病色素含量中的應(yīng)用
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國家自然科學基金資助項目(30800733)和“十一五”國家科技支撐計劃資助項目(2007DAH121301)


PLS Algorithm Application in Hyperspectral Estimation of Pigment Contents in Processing Tomato Leaves under Powdery Mildew
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    摘要:

    采用傳統(tǒng)光譜特征參數(shù)和新建光譜特征參數(shù)對色素含量進行多光譜特征參數(shù)的偏最小二乘法(PLS)估算,以此來估測加工番茄白粉病病葉色素含量,,并進行精度檢驗,。結(jié)果表明:色素含量原始光譜與反對數(shù)光譜的敏感波長分別為350~718nm,、719~839nm和350~718nm,、728~857nm,。從傳統(tǒng)光譜特征參數(shù)和新建光譜特征參數(shù)中選取9個光譜特征參數(shù)PSNDa,、GNDVI,、PSSRa,、PSSRb,、GM、TPMPa,、 TPMPb,、 TPMPc和TPMPd,分別構(gòu)成PGP ,、PGT,、 TTT 3組對色素含量進行估測,TTT組為色素含量光譜組合最佳估測模型,。

    Abstract:

    Both traditional and new spectral characteristic parameters were used to estimate the pigment content of leaves by employing PLS algorithm. Therefore the pigment content of leaves under powdery mildew in processing tomato could be estimated and tested. The result showed that the sensitive bands of original and opposing spectrum were 350~718nm, 719~839nm and 350~718nm, 728~857nm, respectively. Then three groups named PGP, PGT and TTT were composed, including the optimal 9 spectral characteristic parameters from either traditional or new parameters(PSNDa, GNDVI, PSSRa, PSSRb, GM, TPMPa, TPMPb, TPMPc and TPMPd). After estimating the pigment content, the best estimation model was TTT.

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尹小君,李滿春,趙思峰,王登偉. PLS算法在高光譜估測加工番茄白粉病色素含量中的應(yīng)用[J].農(nóng)業(yè)機械學報,2012,43(2):175-180. Yin Xiaojun, Li Manchun, Zhao Sifeng, Wang Dengwei. PLS Algorithm Application in Hyperspectral Estimation of Pigment Contents in Processing Tomato Leaves under Powdery Mildew[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(2):175-180.

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  • 在線發(fā)布日期: 2012-02-17
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