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基于在線近紅外光譜的堆肥全過程關(guān)鍵參數(shù)快速檢測(cè)
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國(guó)家奶牛產(chǎn)業(yè)技術(shù)體系項(xiàng)目(CARS36)和教育部創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃項(xiàng)目(IRT-17R105)


Rapidly Detection of Key Parameters in Whole Composting Process Based on Online Near Infrared Spectroscopy
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    摘要:

    為探究在線近紅外光譜儀對(duì)堆肥全過程含水率、pH值、電導(dǎo)率、有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)、總碳質(zhì)量分?jǐn)?shù)、總氮質(zhì)量分?jǐn)?shù)和碳氮比等關(guān)鍵參數(shù)進(jìn)行實(shí)時(shí)分析的可行性,以采集的60個(gè)堆肥全過程樣品為研究對(duì)象,利用在線近紅外光譜儀、結(jié)合偏最小二乘法,建立了有機(jī)肥堆肥過程中含水率、pH值、電導(dǎo)率、有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)、總碳質(zhì)量分?jǐn)?shù)、總氮質(zhì)量分?jǐn)?shù)和碳氮比的近紅外定量分析模型。研究結(jié)果顯示:在線近紅外光譜儀可實(shí)現(xiàn)堆肥全過程上述關(guān)鍵參數(shù)的速測(cè)(RSD<10%),其中,含水率和總氮質(zhì)量分?jǐn)?shù)的R2C和RPD分別為0.94和3.62、0.92和3.14,模型效果優(yōu)秀;pH值、總碳質(zhì)量分?jǐn)?shù)和碳氮比的R2C和RPD分別為0.90和1.89、0.83和2.12、0.82和2.15,模型效果良好;電導(dǎo)率和有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)的R2C和RPD分別為0.79和1.85、0.80和1.93,模型效果一般,模型精度有待提高。各參數(shù)近紅外預(yù)測(cè)值與實(shí)際測(cè)量值之間的偏差很小,并且近紅外預(yù)測(cè)值與實(shí)際測(cè)量值隨堆肥時(shí)間的變化趨勢(shì)具有較好的一致性。

    Abstract:

    Livestock and poultry manure may result in significant environmental challenges. Meanwhile, it is an advantageous raw material for the production of organic fertilizer due to the rich nutrients such as organic matter, nitrogen, phosphorus and potassium. Aerobic composting is an effective way to solve the livestock manure pollution problem and realize utilization of this valuable resource. However, composting is an extremely complex process of physical and chemical changes. Online detection tools of the key parameters are important for both composting process control and organic fertilizer quality assurance. Aiming to investigate the feasibility of online near infrared (NIR) spectrometer to conduct realtime analysis of moisture content (MC), pH value, electrical conductivity (EC), organic matter (OM), total carbon (TC), total nitrogen (TN) and carbon to nitrogen (C/N ratio) ratio in the whole composting process and evaluate its ability to accurately predict these changes. Totally 60 samples in the whole composting process were collected. The NIR quantitative analysis models of MC, pH value, EC, OM, TC, TN and C/N ratio were established by using the online NIR spectrometer combined with partial least square method. The research results showed that the online NIR spectrometer can realize the rapid detection of key parameters in the whole composting process (RSD<10%), with excellent predictions for MC and TN with R2C and RPD value of 0.94 and 3.62, 0.92 and 3.14, respectively, good predictions for pH value, TC and C/N ratio with R2C and RPD value of 0.90 and 1.89, 0.83 and 2.12, 0.82 and 215, respectively, approximate predictions for EC and OM with R2C and RPD value of 0.79 and 1.85, 0.80 and 1.93, respectively; the deviation between the NIRpredicted and measured values of each parameter was small, the NIR predictions were in good agreement with measured values as the composting process progressed. The above research results laid the foundation for realizing the process analysis of organic fertilizer production based on the online NIR spectroscopy. 

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楊增玲,黃圓萍,沈廣輝,梅佳琪,韓魯佳.基于在線近紅外光譜的堆肥全過程關(guān)鍵參數(shù)快速檢測(cè)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2019,50(5):356-361,384. YANG Zengling, HUANG Yuanping, SHEN Guanghui, MEI Jiaqi, HAN Lujia. Rapidly Detection of Key Parameters in Whole Composting Process Based on Online Near Infrared Spectroscopy[J]. Transactions of the Chinese Society for Agricultural Machinery,2019,50(5):356-361,384.

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  • 收稿日期:2018-11-15
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  • 在線發(fā)布日期: 2019-05-10
  • 出版日期: 2019-05-10
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