红外与毫米波学报2023，Vol.42Issue(6)：816-824,9.DOI:10.11972/j.issn.1001-9014.2023.06.015
土壤中红外光谱库支持下的局部建模集优化
Novel local calibration optimization from soil mid-infrared spectral library
摘要
Abstract
Soil mid-infrared(MIR)can provide a rapid,non-polluting,and cost-efficient method for estimating soil properties,such as soil organic carbon(SOC).Although there is a wide interest in using the soil spectral library(SSL)for soil analysis at various scales,the SSL with a general calibration often produces poor predictions at local scales.Therefore,developing methods to'localize'the spectroscopic modelling is a reliable way to improve the use of SSL.In this study,we proposed a new approach that aims to rapidly build the optimal local model from the SSL by calculat-ing the spectral similarity and developing the local calibration,in order to further improve the prediction accuracy.The distance matrix was constructed by three distance algorithms,namely Euclidean distance,Mahalanobis distance,and Cosine distance,which were compared and used to measure the similarity between the local samples and the SSL.The capacity curve,which was taken from the distance matrix,was used with a method called"continuum-removal"to find the feature points.Partial least-squares regression was used to build the spectroscopic models for SOC estimation.We found that for all three distance algorithms combined with the continuum-removal,the local calibration derived from the first feature point gave us a good idea of how accurate the prediction would be.The Mahalanobis distance can effective-ly develop the optimal local calibration from the MIR SSL,which not only achieved the best accuracy(R2 = 0.764,RMSE = 1.021%)but also used the least number of samples from SSL(14%SSL).On local scales,the approach we proposed can significantly improve both the analytical cost and the accuracy of the soil MIR technique.关键词
土壤碳/相似度/距离矩阵/连续统去除/偏最小二乘回归Key words
soil carbon/similarity/distance matrix/continuum-removal/PLSR分类
信息技术与安全科学引用本文复制引用
沈佳丽,陈颂超,洪永胜,李硕..土壤中红外光谱库支持下的局部建模集优化[J].红外与毫米波学报,2023,42(6):816-824,9.基金项目
国家自然科学基金(41601370)、农业农村部光谱检测重点实验室开放基金课题(2022ZJUGP003)和中央高校基本科研业务费专项资金(CCNU22JC022) Supported by the Young Scientists Fund of the National Natural Science Foundation of China(41601370) （41601370）
the Key Laboratory of Spectroscopy Sensing,Ministry of Agriculture and Rural Affairs,P.R.China(2022ZJUGP003) （2022ZJUGP003）
the Fundamental Research Funds for the Central Universities(CCNU22JC022) （CCNU22JC022）
