{"title":"Pedotransfer functions development for modeling FC and PWP using Vis-NIR spectra combined with PLSR and regression models","authors":"Xizhen Zhu , Piaoyun Gu , Gang Wu","doi":"10.1016/j.vibspec.2024.103731","DOIUrl":null,"url":null,"abstract":"<div><p>The utilization of the soil pedotransfer functions (PTFs) developed based on the basic soil propertied is an alternative, fast, cost-effective and applicable approach for the prediction of field capacity (FC) and permanent wilting point (PWP). In addition, the Visible–Near-Infrared (Vis-NIR) spectra in soil science has gained prominence due to its practicality and relevance. In this paper, we used the data of the soil PWP and FC of 135 soil samples, easily measurable soil properties and Vis-NIR spectroscopy. The multiple linear regression (MLR) model was utilized to formulate PTFs model and Vis-NIR spectroscopy combined with MLR and partial least-squares (PLSR) was used to develop Spectrotransfer Function (STF). Results showed that among the easily measurable soil properties, particle-size diameter (dg) with Beta of −0.72 and −0.63 the most influential parameters for predicting FC and PWP, respectively, followed by the clay content. Developed PTFs for both FC and PWP with a R<sup>2</sup> of 0.71 and 0.68, respectively, had a better performance than other previous developed PTFs. Results also revealed that the PLSR with a higher R<sup>2</sup> (0.81) and lower RMSE (4 %) significantly performed better in comparison to STF for both FC and PWP prediction.</p></div>","PeriodicalId":23656,"journal":{"name":"Vibrational Spectroscopy","volume":"135 ","pages":"Article 103731"},"PeriodicalIF":2.7000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vibrational Spectroscopy","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0924203124000845","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The utilization of the soil pedotransfer functions (PTFs) developed based on the basic soil propertied is an alternative, fast, cost-effective and applicable approach for the prediction of field capacity (FC) and permanent wilting point (PWP). In addition, the Visible–Near-Infrared (Vis-NIR) spectra in soil science has gained prominence due to its practicality and relevance. In this paper, we used the data of the soil PWP and FC of 135 soil samples, easily measurable soil properties and Vis-NIR spectroscopy. The multiple linear regression (MLR) model was utilized to formulate PTFs model and Vis-NIR spectroscopy combined with MLR and partial least-squares (PLSR) was used to develop Spectrotransfer Function (STF). Results showed that among the easily measurable soil properties, particle-size diameter (dg) with Beta of −0.72 and −0.63 the most influential parameters for predicting FC and PWP, respectively, followed by the clay content. Developed PTFs for both FC and PWP with a R2 of 0.71 and 0.68, respectively, had a better performance than other previous developed PTFs. Results also revealed that the PLSR with a higher R2 (0.81) and lower RMSE (4 %) significantly performed better in comparison to STF for both FC and PWP prediction.
期刊介绍:
Vibrational Spectroscopy provides a vehicle for the publication of original research that focuses on vibrational spectroscopy. This covers infrared, near-infrared and Raman spectroscopies and publishes papers dealing with developments in applications, theory, techniques and instrumentation.
The topics covered by the journal include:
Sampling techniques,
Vibrational spectroscopy coupled with separation techniques,
Instrumentation (Fourier transform, conventional and laser based),
Data manipulation,
Spectra-structure correlation and group frequencies.
The application areas covered include:
Analytical chemistry,
Bio-organic and bio-inorganic chemistry,
Organic chemistry,
Inorganic chemistry,
Catalysis,
Environmental science,
Industrial chemistry,
Materials science,
Physical chemistry,
Polymer science,
Process control,
Specialized problem solving.