Application for Identifying the Origin and Predicting the Physiologically Active Ingredient Contents of Gastrodia elata Blume Using Visible–Near-Infrared Spectroscopy Combined with Machine Learning

Foods, Journal Year: 2023, Volume and Issue: 12(22), P. 4061 - 4061

Published: Nov. 8, 2023

Gastrodia elata (G. elata) Blume is widely used as a health product with significant economic, medicinal, and ecological values. Due to variations in the geographical origin, soil pH, content of organic matter, levels physiologically active ingredient contents G. from different origins may vary. Therefore, rapid methods for predicting origin these ingredients are important market. This paper proposes visible-near-infrared (Vis-NIR) spectroscopy technology combined machine learning. A variety learning models were benchmarked against one-dimensional convolutional neural network (1D-CNN) terms accuracy. In identification models, 1D-CNN demonstrated excellent performance, F1 score being 1.0000, correctly identifying 11 origins. quantitative outperformed other three algorithms. For prediction set eight ingredients, namely, GA, HA, PE, PB, PC, PA, GA + total, RMSEP values 0.2881, 0.0871, 0.3387, 0.2485, 0.0761, 0.7027, 0.3664, 1.2965, respectively. The Rp2 0.9278, 0.9321, 0.9433, 0.9094, 0.9454, 0.9282, 0.9173, 0.9323, study that showed highly accurate non-linear descriptive capability. proposed combinations Vis-NIR have potential quality evaluation elata.

Language: Английский

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A detailed mapping of soil organic matter content in arable land based on the multitemporal soil line coefficients and neural network filtering of big remote sensing data

Geoderma, Journal Year: 2024, Volume and Issue: 447, P. 116941 - 116941

Published: June 12, 2024

Language: Английский

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Vis/NIR Spectroscopy and Chemometrics for Non-Destructive Estimation of Chlorophyll Content in Different Plant Leaves

Sensors, Journal Year: 2025, Volume and Issue: 25(6), P. 1673 - 1673

Published: March 8, 2025

Vegetation biochemical and biophysical variables, especially chlorophyll content, are pivotal indicators for assessing drought’s impact on plants. Chlorophyll, crucial photosynthesis, ultimately influences crop productivity. This study evaluates the mean squared Euclidean distance (MSD) method, traditionally applied in soil analysis, estimating content five diverse leaf types across various months using visible/near-infrared (vis/NIR) spectral reflectance. The MSD method serves as a tool selecting representative calibration dataset. By integrating with partial least squares regression (PLSR) Cubist model, we aim to accurately predict focusing key bands within ranges of 500–640 nm 740–1100 nm. In validation dataset, PLSR achieved high determination coefficient (R2) 0.70 low bias error (MBE) 0.04 mg g−1. model performed even better, demonstrating an R2 0.77 exceptionally MBE 0.01 These results indicate that dataset leaves, vis/NIR spectrometry combined is promising alternative traditional methods quantifying over months. technique non-destructive, rapid, consistent, making it invaluable drought impacts plant health

Language: Английский

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Updating of the Archival Large-Scale Soil Map Based on the Multitemporal Spectral Characteristics of the Bare Soil Surface Landsat Scenes

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(18), P. 4491 - 4491

Published: Sept. 12, 2023

For most of the arable land in Russia (132–137 million ha), dominant and accurate soil information is stored form map archives on paper without coordinate reference. The last traditional map(s) (TSM, TSMs) were created over 30 years ago. Traditional and/or archival (ASM, ASMs) are outdated terms storage formats, dates, methods production. technology constructing a multitemporal line (MSL) makes it possible to update ASMs TSMs based processing big remote-sensing data (RSD). To construct an MSL, spectral characteristics bare surface (BSS) used. BSS RSD distinguished within framework conceptual apparatus neighborhood line. filtering deep machine learning. In course work, vector georeferenced version ASM updated coefficient “C” MSL. maps verified field surveys (76 pits). called interpretation (SIC “C”). SIC has more detailed legend compared (7 sections/chapters instead 5), greater accuracy (smaller errors first second kind), potential suitability for calculating organic matter/carbon (SOM/SOC) reserves (soil types/areals statistically significant divided according thickness organomineral horizon content SOM plowed layer). When updating, systematic underestimation numbers contours areas soils with manifestations negative/degradation processes (slitization erosion) TSM was established. process all three shortcomings ASMs/TSMs (archaic storage, creation) eliminated. digital (thematic raster), modern, methods. time, actualization carried out MSL (coefficient

Language: Английский

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The modified external parameter orthogonalization with removed PC2 to remove effectively the moisture effect on the spectra

Geoderma, Journal Year: 2024, Volume and Issue: 450, P. 117051 - 117051

Published: Sept. 30, 2024

Language: Английский

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