土壤学报2024，Vol.61Issue(3)：687-698,12.DOI:10.11766/trxb202210040548
可见-近红外与中红外光谱预测土壤养分的比较研究
Comparative Study on Prediction of Soil Nutrients by Visible-Near Infrared and Mid-infrared Spectroscopy
摘要
Abstract
[Objective]Predicting soil nutrients by visible-near infrared(vis-NIR)and mid-infrared(MIR)spectroscopy has the advantages of being fast,cost-effective and environmental friendly.Soil spectra contain abundant information of soil properties,and can be combined with machine learning methods to effectively and accurately predict soil nutrients,which can provide support and guidance for timely fertilization management.The objective of this study was to compare the predictive ability of vis-NIR(350-2 500 nm)and MIR spectroscopy(4 000-650 cm-1)for predicting both the total and available contents of soil nitrogen(N),phosphorus(P)and potassium(K),in order to construct an optimal model for estimation of different nutrient contents.[Method]In this study,500 samples were collected from the surface layers(0-20 cm)of the dryland in Guizhou Province for determination of soil N,P and K contents and spectral analysis.The vis-NIR spectra were measured by Cary 5000 and the MIR spectra by Thermo Scientifit Nicolet iS50.Soil spectra were pre-processed by Savitzky-Golay(SG)smoothing for denoising and standard normal variate(SNV)transformation for baseline correction.Partial least squares regression(PLSR)and support vector machine(SVM)were used to predict the contents of total nitrogen(TN),total phosphorus(TP),total potassium(TK),alkali-hydrolyzable nitrogen(AN),available phosphorus(AP)and available potassium(AK).[Result]The results showed that:(1)Whether using the vis-NIR spectroscopy or the MIR spectroscopy,the prediction accuracy of PLSR model was better than that of SVM model.(2)The accuracy of MIR spectroscopy for prediction of TN,TK and AN was significantly higher than that of vis-NIR spectroscopy.Vis-NIR and MIR spectroscopy could reliably predict TN and TK(ratio of performance to interquartile distance(RPIQ)>2.10),while MIR spectroscopy could predict AN with moderate accuracy(RPIQ=1.87).However,both types of spectra had poor ability to predict TP,AP and AK(RPIQ<1.34).(3)When the variable in the projection(VIP)score was>1.5,there were more important bands selected by PLSR models in the MIR region than the vis-NIR region.The important bands selected for estimation of TN were mainly concentrated near 1 910 and 2 207 nm in the vis-NIR region,and centered around 1 120,1 000,960,910,770,and 668 cm-1 in the MIR region.The important bands of TK were mainly distributed around 540,2 176,2 225,and 2 268 nm in the vis-NIR region,and around 1 040,960,910,776,720,and 668 cm-1 in the MIR region.[Conclusion]Therefore,MIR spectroscopy combined with PLSR model proved to be promising for accurate prediction of soil nutrients,especially for the estimation of TN and TK,and can provide technical support for guiding timely fertilization.关键词
可见-近红外光谱/中红外光谱/土壤养分/偏最小二乘回归/支持向量机Key words
Visible-near infrared spectroscopy/Mid-infrared spectroscopy/Soil nutrients/Partial least squares regression/Support vector machine分类
农业科技引用本文复制引用
李学兰,李德成,郑光辉,曾荣,蔡凯,高维常,潘文杰,姜超英,曾陨涛..可见-近红外与中红外光谱预测土壤养分的比较研究[J].土壤学报,2024,61(3):687-698,12.基金项目
国家自然科学基金项目(42107322)、中国烟草总公司贵州省公司科技项目(201910)、江苏省高校自然科学基金面上项目(20KJB210009)共同资助Supported by the National Natural Science Foundation of China(No.42107322),the Science and Technology Project of China National Tobacco Corporation Guizhou Provincial Company(No.201910),and the Natural Science Foundation of Colleges and Universities of Jiangsu Province,China(No.20KJB210009) （42107322）
