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基于正交變換與SPXY樣本劃分的冬小麥葉綠素診斷
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國家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2016YFD0300600-2016YFD0300606、2016YFD0300610)、國家自然科學(xué)基金項(xiàng)目(31501219)和中央高?;究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(2017TC029)


Prediction of Winter Wheat Chlorophyll Content Based on Gram-Schmidt and SPXY Algorithm
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    摘要:

    冬小麥葉綠素含量的準(zhǔn)確預(yù)測,可為冬小麥田間精細(xì)化管理提供依據(jù)。采集冬小麥冠層400~900nm范圍反射光譜,經(jīng)一階微分預(yù)處理后,為了抑制由于連續(xù)波長自變量多重共線性對葉綠素含量診斷模型的干擾,利用Gram-Schmidt正交變換算法初步提取葉綠素敏感波長特征參數(shù)為848、620、677nm。在定量模型的建立過程中,對比了傳統(tǒng)隨機(jī)樣本集劃分與以空間中樣本間距離遠(yuǎn)近為指導(dǎo)的SPXY樣本集劃分方法,并討論了大田冠層反射光譜對葉綠素濃度診斷的最優(yōu)精度,研究結(jié)果表明,以620nm和677nm兩個(gè)敏感波長結(jié)合SPXY樣本劃分方法建立的多元線性回歸模型預(yù)測精度較高,且葉綠素質(zhì)量濃度為0.3mg/L分辨間隔時(shí),建模決定系數(shù)和驗(yàn)證決定系數(shù)分別達(dá)0.730和0.739,可為無損檢測冬小麥拔節(jié)期葉綠素含量提供技術(shù)支持。

    Abstract:

    Accurate prediction of wheat chlorophyll content is important for guiding precision management in the field. The canopy spectrum of winter wheat canopy was measured by ASD Field Spec Handheld 2, and the first-order differential processing method was conducted on the band of 400~900nm in the paper. In order to select the sensitive bands for the chlorophyll content detection of winter wheat, the Gram-Schmidt transformation algorithm was used in the research. The insignificant variables and the redundant information were identified and removed from the independent variables set. As a result, the orthogonal transformation data of first-order differential at 848nm, 620nm and 677nm were extracted. A representative set of wheat chlorophyll content of modeling samples was selected by using sample set partitioning based on joint x-y distance algorithm (SPXY). The results showed that multiple linear regression (MLR) prediction model based on Gram-Schmidt and SPXY algorithm is better than the random sampling method. The chlorophyll content of winter wheat were clustered respectively at intervals of 0.2mg/L, 0.3mg/L and 0.5mg/L. The modeling results showed that the optimal resolution was at 0.3mg/L, the determination coefficient R2c and the R2v of the calibration model which was built based on 620nm and 677nm sensitive bands were respectively 0.730 and 0.739. The study could help to evaluate the nutritional status of winter wheat and precision fertilization.

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毛博慧,孫紅,劉豪杰,張俊逸,李民贊,楊立偉.基于正交變換與SPXY樣本劃分的冬小麥葉綠素診斷[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2017,48(s1):160-165. MAO Bohui, SUN Hong, LIU Haojie, ZHANG Junyi, LI Minzan, YANG Liwei. Prediction of Winter Wheat Chlorophyll Content Based on Gram-Schmidt and SPXY Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(s1):160-165.

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  • 收稿日期:2017-07-10
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  • 在線發(fā)布日期: 2017-12-10
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