Design and Experiment of a Portable Near-Infrared Spectroscopy Device for Convenient Prediction of Leaf Chlorophyll Content

Sensors, Journal Year: 2023, Volume and Issue: 23(20), P. 8585 - 8585

Published: Oct. 19, 2023

This study designs a spectrum data collection device and system based on the Internet of Things technology, aiming to solve tedious process chlorophyll provide more convenient accurate method for predicting content. The has advantages integrated design, portability, ease operation, low power consumption, cost, maintenance requirements, making it suitable outdoor analysis in fields such as agriculture, environment, geology. core processor uses ESP8266-12F microcontroller collect by communicating with sensor. sensor used is AS7341 model, but its limited number spectral acquisition channels resolution may limit exploration data. To verify performance system, this experiment collected Hami melon leaf samples combined meter related measurements analysis. In experiment, twelve regression algorithms were tested, including linear regression, decision tree, support vector regression. results showed that original data, ETR had best prediction effect at wavelength 515 nm. training set, RMSEc was 0.3429, Rc2 0.9905. RMSEp 1.5670, Rp2 0.8035. addition, eight preprocessing methods denoise improvement accuracy not significant. further improve analysis, principal component isolation forest algorithm detect remove outliers After removing outliers, RFR model performed all combinations denoised using PBOR. 0.8721, 0.9429. 1.1810, 0.8683.

Language: Английский

Real-time monitoring of the column chromatography process of Ginkgo biloba using near-infrared and Raman spectroscopy combined with spectral fusion strategy

Process Biochemistry, Journal Year: 2024, Volume and Issue: 145, P. 50 - 62

Published: June 13, 2024

Language: Английский