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雞糞工廠化堆肥過程中有機(jī)質(zhì)含量預(yù)測模型
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王曉燕,,博士生,,主要從事生物質(zhì)資源開發(fā)與利用相關(guān) 技術(shù)研究,Email: [email protected]

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“十一五” 國家科技支撐計劃資助項目(2006BAD07A13〖CD*2〗2、2006BAD10B05)


Prediction Model for Organic Matter Content in Chicken Manure  during Plantfield Composting
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    摘要:

    以148份肉雞糞和菊花渣工廠化高溫堆肥過程樣品為研究對象,,分別探討了基于基本理化指 標(biāo)和近紅外光譜預(yù)測雞糞堆肥過程中有機(jī)質(zhì)含量的可行性。根據(jù)樣品中干物質(zhì)含量,、pH值和 電導(dǎo)率3種理化指標(biāo)與有機(jī)質(zhì)含量的相關(guān)關(guān)系建立了基于理化指標(biāo)預(yù)測有機(jī)質(zhì)含量的一元和 二元線性回歸模型,。結(jié)果表明,利用干物質(zhì)含量預(yù)測有機(jī)質(zhì)含量簡便,、易行且最具實際應(yīng)用 價值(R2=081, P<0001),。采用多元線性回歸、主成分回歸和偏最小二乘回 歸3種定量分析方法分別建立了雞糞堆肥過程有機(jī)質(zhì)含量的近紅外預(yù)測模型,。其中,,主成分 回歸和偏最小二乘定量分析方法所得預(yù)測模型的驗證決定系數(shù)(r2)均為095,驗 證相對分析誤差(RPD)均大于40,,所建模型的預(yù)測精度較高,,可用于實際檢測工作。

    Abstract:

    The objective of this study was to explore the feasibility to estimate organic m atter (OM) content in chicken manure during aerobic composting. Two types of reg ression methods were used with physicochemical properties and nearinfrared spe ctroscopy (NIRS). Single and two variable linear regressions between the values of dry matter (DM), pH value, electrical conductivity (EC) and OM content were develop ed. Results showed that it was significant in practice to estimate the OM conten t using DM value with a higher coefficient of determination (R2=081, P <0001). In addition, multiple linear regression (MLR), principle component r egression (PCR) and partial least square regression (PLS) were used to develop NIRS models for OM. It was observed that the both models of PCR and PLS were rob u st with the coefficient of determination in validation set r2=095, respe ctively. And both the ratios of standard deviation of validation set to root mea n square error of prediction (RPD) are greater than 40.

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王曉燕,黃光群,韓魯佳.雞糞工廠化堆肥過程中有機(jī)質(zhì)含量預(yù)測模型[J].農(nóng)業(yè)機(jī)械學(xué)報,2010,41(1). Wang Xiaoyan, Huang Guangqun, Han Lujia. Prediction Model for Organic Matter Content in Chicken Manure  during Plantfield Composting[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(1).

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