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基于ISE的土壤硝態(tài)氮原位檢測模型比較
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浙江省重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2020C02017)、云南省院士工作站項(xiàng)目(LJGZZ-2018001)和中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(2021TC031)


Comprison of Detection Models for Soil Nitrate Concentration Based on ISE
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    摘要:

    針對離子選擇電極預(yù)測土壤硝態(tài)氮濃度易受土壤懸液組分影響的問題,,以提高離子選擇電極預(yù)測土壤硝態(tài)氮濃度精準(zhǔn)度為目標(biāo),探討了Nernst,、SAM、BP-ANN 3種模型的濃度預(yù)測性能,。開展標(biāo)準(zhǔn)溶液檢測實(shí)驗(yàn),,預(yù)判3個模型的預(yù)測性能,結(jié)合田間玉米監(jiān)測實(shí)驗(yàn)和盆栽粉冠番茄監(jiān)測實(shí)驗(yàn)驗(yàn)證樣本實(shí)驗(yàn)結(jié)果,。實(shí)驗(yàn)結(jié)果表明,,3個模型的預(yù)測結(jié)果與樣本真值均具有較好的一致性。其中,,SAM模型的濃度預(yù)測結(jié)果最為精確,其決定系數(shù)均不小于0.9,,且MAE,、MRE、RMSE分別為2.03~5.08mg/L,、0.64%~8.79%,、2.21~5.49mg/L。SAM濃度預(yù)測模型具有精度較高,、抗干擾性好的特點(diǎn),,對基于ISE的土壤硝態(tài)氮原位檢測具有一定的參考價(jià)值。

    Abstract:

    There are a variety of ions in soil suspension, so when using ion selective electrode to detect soil nitrate-nitrogen, it is particularly vulnerable to the interference of other ions, which will greatly affect the accuracy of detection. In order to improve the accuracy of monitoring soil nitrate concentration by ion selective electrode, it is necessary to establish a model to predict the concentration. The prediction performances of Nernst, SAM and BP-ANN models for soil nitrate concentration detection were discussed. The standard solution test was carried out to predict the prediction performance of the three models. Combined with the field corn monitoring experiment and potted pink crown tomato monitoring experiment to verify the sample experimental results, the soil nitrate concentration was taken as the output of the three models, and the effect of optical method on the determination of soil nitrate concentration was compared. The experimental results showed that the prediction results of the three models were in good agreement with the true values of the samples. Among them, the SAM model was the most accurate, and its correlation coefficients were not less than 0.9. The variation ranges of MAE, MRE and RMSE were 2.03~5.08mg/L, 0.64%~8.79% and 2.21~5.49mg/L, respectively. SAM concentration prediction model had the characteristics of high precision and good anti-interference. It can run on a relatively simple platform and had a wider range of application. In addition, when combined with the fluid control system, it can ensure the detection accuracy and improve the detection efficiency. It had a certain reference value for in-situ detection of soil nitrate nitrogen based on ISE.

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路 逍,潘林沛,李雁華,陳 銘,劉 剛,張 淼.基于ISE的土壤硝態(tài)氮原位檢測模型比較[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2021,52(S0):297-303. LU Xiao, PAN Linpei, LI Yanhua, CHEN Ming, LIU Gang, ZHANG Miao. Comprison of Detection Models for Soil Nitrate Concentration Based on ISE[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(S0):297-303.

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  • 收稿日期:2021-07-06
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  • 在線發(fā)布日期: 2021-11-10
  • 出版日期: 2021-12-10
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