A Novel Model for Soil Organic Matter and Total Nitrogen Detection Based on Visible/Shortwave Near-Infrared Spectroscopy

Land, Год журнала: 2025, Номер 14(2), С. 329 - 329

Опубликована: Фев. 6, 2025

Soil organic matter (SOM) and total nitrogen (TN) are critical indicators for assessing soil fertility. Although laboratory chemical analysis methods can accurately measure their contents, these techniques time-consuming labor-intensive. Spectral technology, characterized by its high sensitivity convenience, has been increasingly integrated with machine learning algorithms nutrient monitoring. However, the process of spectral data remains complex requires further optimization simplicity efficiency to improve prediction accuracy. This study proposes a novel model enhance accuracy SOM TN predictions in northeast China’s black soil. Visible/Shortwave Near-Infrared Spectroscopy (Vis/SW-NIRS) within 350–1070 nm range were collected, preprocessed, dimensionality-reduced. The scores first nine principal components after partial least squares (PLS) dimensionality reduction selected as inputs, measured contents used outputs build back-propagation neural network (BPNN) model. results show that processed combination standard normal variate (SNV) multiple scattering correction (MSC) have best modeling performance. To stability this model, three named random search (RS), grid (GS), Bayesian (BO) introduced. demonstrate Vis/SW-NIRS provides reliable PLS-RS-BPNN achieving performance (R2 = 0.980 0.972, RMSE 1.004 0.006 TN, respectively). Compared traditional models such forests (RF), one-dimensional convolutional networks (1D-CNNs), extreme gradient boosting (XGBoost), proposed improves R2 0.164–0.344 predicting 0.257–0.314 respectively. These findings confirm potential technology effective tools prediction, offering valuable insights application sensing information.

Язык: Английский

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Handheld NIR spectroscopy for real-time on-site food quality and safety monitoring

Advances in food and nutrition research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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NON-DESTRUCTIVE IDENTIFICATION OF MICROPLASTICS IN SOIL USING SPECTROSCOPY AND HYPERSPECTRAL IMAGING

TrAC Trends in Analytical Chemistry, Год журнала: 2025, Номер unknown, С. 118216 - 118216

Опубликована: Фев. 1, 2025

Язык: Английский

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Variational mode decomposition unfolded extreme learning machine for spectral quantitative analysis of complex samples

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2025, Номер unknown, С. 126354 - 126354

Опубликована: Май 1, 2025

Язык: Английский

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Detecting Low Concentrations of Microplastics in Soils Accurately Using Short-Wave Infrared Hyperspectral Imaging

Soil & Environmental Health, Год журнала: 2025, Номер unknown, С. 100157 - 100157

Опубликована: Май 1, 2025

Язык: Английский

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Comparison of Multiple NIR Instruments for the Quantitative Evaluation of Grape Seed and Other Polyphenolic Extracts with High Chemical Similarities

Foods, Год журнала: 2024, Номер 13(24), С. 4164 - 4164

Опубликована: Дек. 23, 2024

Grape seed extract (GSE), one of the world’s bestselling dietary supplements, is prone to frequent adulteration with chemically similar compounds. These frauds can go unnoticed within supply chain due use unspecific standard analytical methods for quality control. This research aims develop a near-infrared spectroscopy (NIRS) method rapid and non-destructive quantitative evaluation GSE powder in presence multiple additives. Samples were prepared by mixing pine bark (PBE) green tea (GTE) on different levels between 0.5 13% singular dual combinations. Measurements performed desktop three handheld devices performance comparison. Following spectral pretreatment, partial least squares regression (PLSR) support vector (SVR)-based models built predict concentrations various chemical parameters. Cross- external-validated could reach minimum R2p value 0.99 maximum RMSEP 0.27% prediction using benchtop data, while based data comparably good results, especially GTE, caffeic acid procyanidin content prediction. shows potential applicability NIRS coupled chemometrics as an alternate, accurate tool GSE-based supplement mixtures.

Язык: Английский

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Rapid on-site multi-indicator detection of Polygonatum cyrtonema Hua by handheld near-infrared spectroscopy with wavelength selection

Microchemical Journal, Год журнала: 2024, Номер 207, С. 111920 - 111920

Опубликована: Окт. 12, 2024

Язык: Английский

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