便携式土壤全氮测定仪性能研究
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国家自然科学基金资助项目(61134011)


Performance of Portable Soil TN Detector Based on NIR Spectroscopy
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    摘要:

    为研究土壤全氮含量,自主开发了基于近红外光谱技术的便携式土壤全氮测定仪。以中国农业大学上庄实验站采集的60个土壤样本作为实验材料,分别对土壤全氮测定仪的稳定性、准确性和预测模型精度进行了测试。使用模型的测定系数(RC)、验证系数(RV)、校正均方根误差(RMSEC)、预测均方根误差(RMSEP)和相对分析误差(RPD)作为模型精度的评价指标。实验结果显示,本测定仪在波长940、1050、1100、1200、1300、1450和1550nm处的吸光度重复性误差分别为1.57%、1.80%、1.59%、0.94%、0.61%、0.64%和3.13%,平均误差1.80%;测定仪吸光度和傅里叶光谱分析仪吸光度相关系数分别达到0.971、0.948、0.928、0.873、0.920、0.901和0.913,平均值为0.922;使用测定仪平均吸光度数据,通过BP神经网络建立的土壤全氮预测模型RC、RV、RMSEC、RMSEP和RPD分别达到0.81、0.80、0.029、0.019和3.44。使用该预测模型建立的土壤全氮分布图和实际土壤全氮分布图具有高度的一致性。实验结果表明,便携式土壤全氮测定仪工作稳定,使用平均吸光度数据建立的土壤全氮预测模型具有较好的预测能力和较强的鲁棒性,可以在土壤全氮含量实时检测中应用。

    Abstract:

    In order to detect soil total nitrogen (TN) content, a portable soil TN detector was developed. The stability, accuracy and precision of the detector were tested with the sixty soil samples collected from Shangzhuang Experiment Station of China Agricultural University. The models were evaluated by the correlation coefficient of calibration (RC), the correlation coefficient of validation (RV), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and residual prediction deviation (RPD). The results showed that the repeatability error of 940nm, 1050nm, 1100nm, 1200nm, 1300nm, 1450nm and 1550nm were 1.57%, 1.80%, 1.59%, 0.94%, 0.61%, 0.64% and 3.13%, respectively. The correlation coefficients between the absorbance of soil TN detector and that of MATRIX_I Fourier spectral analyzer were 0.971, 0.948, 0.928, 0.873, 0.920, 0.901 and 0.913, respectively. The RC, RV, RMSEC, RMSEP and RPD of the model established by BP neural network was 0.81, 0.80, 0.029, 0.019 and 3.44, respectively. The experiment indicated that the portable soil TN detector performed well. 

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安晓飞,李民赞,郑立华,刘玉萌,张亚静.便携式土壤全氮测定仪性能研究[J].农业机械学报,2012,43(Z1):283-288.

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  • 在线发布日期: 2012-11-08
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