Effects of soil moisture content on absorbance spectra of sandy soils in sensing phosphorus concentrations using UV-VIS-NIR spectroscopy

被引:0
|
作者
Bogrekci, I. [1 ]
Lee, W. S.
机构
[1] Univ Gaziosmanpasa, Fac Agr, Dept Agr Machinery, Tasliciftlik, Tokat, Turkey
[2] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA
关键词
absorbance; moisture content; NIR; phosphates; phosphorus; PLS; reflectance; sensor; spectroscopy; UV; VIS;
D O I
暂无
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
This study was conducted to investigate the effects of soil moisture content on the absorbance spectra of sandy soils with different phosphorus (P) concentrations using ultraviolet (UV), visible (VIS), and near-infrared (NIR) absorbance spectroscopy. Sieve sizes were 125, 250, and 600 mu m for fine, medium, and coarse, respectively. The medium size of the samples was usedfor the study. Investigations were conducted at 0, 12.5, 62.5, 175, 375, 750, and 1000 mg kg(-1) P application rates. Three soil moisture contents (4%, 8%, and 12%) were investigated. P concentrations of the soil samples were analyzed and reflectance of the samples was measured between 225 and 2550 nm with a 1 nm interval. Dried soil samples reflected more light than wet soil in the 225-2550 mn range. As moisture content of the soils increased, reflectance from the soil sample decreased, which indicates that water is a strong light absorber in sandy soils. Dry soil spectra were reconstructed from the wet soil spectra by removing the moisture content effect and compared with the dry spectra of the same soil sample. Absorbance and reconstructed absorbance data were prepared as calibration and validation data sets in order to measure the Performance of the spectral signal processing used for removing the moisture content effect on absorbance spectra. A partial least squares (PLS) analysis was applied to the data to predict P concentration before and after processing the spectra. The results showed that removing the moisture effect by spectral signal processing considerably improved prediction of P in soils.
引用
收藏
页码:1175 / 1180
页数:6
相关论文
共 50 条
  • [21] Predicting Soil Salinity with Vis-NIR Spectra after Removing the Effects of Soil Moisture Using External Parameter Orthogonalization
    Liu, Ya
    Pan, Xianzhang
    Wang, Changkun
    Li, Yanli
    Shi, Rongjie
    PLOS ONE, 2015, 10 (10):
  • [22] Study on Estimation of Deserts Soil Total Phosphorus Content by Vis-NIR Spectra with Variable Selection
    Yang Ai-xia
    Ding Jian-li
    Li Yan-hong
    Deng Kai
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36 (03) : 691 - 696
  • [23] Prediction of soil organic carbon for different levels of soil moisture using Vis-NIR spectroscopy
    Nocita, Marco
    Stevens, Antoine
    Noon, Carole
    van Wesemael, Bas
    GEODERMA, 2013, 199 : 37 - 42
  • [24] Machine learning based prediction of soil total nitrogen, organic carbon and moisture content by using VIS-NIR spectroscopy
    Morellos, Antonios
    Pantazi, Xanthoula-Eirini
    Moshou, Dimitrios
    Alexandridis, Thomas
    Whetton, Rebecca
    Tziotzios, Georgios
    Wiebensohn, Jens
    Bill, Ralf
    Mouazen, Abdul M.
    BIOSYSTEMS ENGINEERING, 2016, 152 : 104 - 116
  • [25] Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction
    Zhou, Nan
    Hong, Jin
    Song, Bo
    Wu, Shichao
    Wei, Yichen
    Wang, Tao
    JOURNAL OF SPECTROSCOPY, 2024, 2024
  • [26] Estimating Soil Organic Carbon of Cropland Soil at Different Levels of Soil Moisture Using VIS-NIR Spectroscopy
    Jiang, Qinghu
    Chen, Yiyun
    Guo, Long
    Fei, Teng
    Qi, Kun
    REMOTE SENSING, 2016, 8 (09):
  • [27] Optical Properties of Bi0.1Zn0.45VO3.1 Thin Films Using UV-VIS-NIR Spectroscopy
    Punia, R.
    Kundu, R. S.
    Hooda, J.
    Parmar, Rajesh
    Kishore, N.
    PROCEEDING OF INTERNATIONAL CONFERENCE ON RECENT TRENDS IN APPLIED PHYSICS & MATERIAL SCIENCE (RAM 2013), 2013, 1536 : 539 - +
  • [28] Rapid and Low-Cost Quantification of Adulteration Content in Camellia Oil Utilizing UV-Vis-NIR Spectroscopy Combined with Feature Selection Methods
    Liu, Qiang
    Gong, Zhongliang
    Li, Dapeng
    Wen, Tao
    Guan, Jinwei
    Zheng, Wenfeng
    MOLECULES, 2023, 28 (16):
  • [29] Effects of nitrification and urease inhibitors on nitrous oxide emissions and concentrations driven by soil moisture in sandy soils
    Li, Yanyan
    Gao, Xiaopeng
    Liu, Ji
    Shen, Jianlin
    Kuang, Wennong
    Chen, Ji
    Zeng, Fanjiang
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2025, 373
  • [30] Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
    Bellino, Alessandro
    Colombo, Claudio
    Iovieno, Paola
    Alfani, Anna
    Palumbo, Giuseppe
    Baldantoni, Daniela
    IFOREST-BIOGEOSCIENCES AND FORESTRY, 2016, 9 : 101 - 108