Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.

Soil pH is an important parameter that affects plant nutrient uptake and biological activity and has received extensive attention and research. In this paper, we propose a neural network algorithm using Ghostnet combined with Convolutional Block Attention Module (CABM) to realize the near-infrared (...

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Main Authors: Jianguo Zhu, Wenjin Wang, Peng Tian
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0325426
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author Jianguo Zhu
Wenjin Wang
Peng Tian
author_facet Jianguo Zhu
Wenjin Wang
Peng Tian
author_sort Jianguo Zhu
collection DOAJ
description Soil pH is an important parameter that affects plant nutrient uptake and biological activity and has received extensive attention and research. In this paper, we propose a neural network algorithm using Ghostnet combined with Convolutional Block Attention Module (CABM) to realize the near-infrared (NIR) PH spectral measurement of soil. The method firstly utilizes Monte Carlo Cross Validation (MCCV) method to reject the anomalous samples in the data, and then uses GhostNet combined with CBAM algorithm to train and predict the PH values of the four Lucas soil spectral data measured by the two different methods, and compares the prediction results with those of PLSR and VGGNet-16 methods. The results showed that the [Formula: see text] of the GhostNet-CBAM method could reach up to 0.9447, and the RMSE reached as low as 0.3267, and the scatter density plots of the predicted and true values further confirmed that the method could quickly and accurately obtain the soil pH parameters.
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institution DOAJ
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language English
publishDate 2025-01-01
publisher Public Library of Science (PLoS)
record_format Article
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spelling doaj-art-96b5a62e41ca4d929a0e4c21ae4f04b82025-08-20T03:21:51ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01206e032542610.1371/journal.pone.0325426Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.Jianguo ZhuWenjin WangPeng TianSoil pH is an important parameter that affects plant nutrient uptake and biological activity and has received extensive attention and research. In this paper, we propose a neural network algorithm using Ghostnet combined with Convolutional Block Attention Module (CABM) to realize the near-infrared (NIR) PH spectral measurement of soil. The method firstly utilizes Monte Carlo Cross Validation (MCCV) method to reject the anomalous samples in the data, and then uses GhostNet combined with CBAM algorithm to train and predict the PH values of the four Lucas soil spectral data measured by the two different methods, and compares the prediction results with those of PLSR and VGGNet-16 methods. The results showed that the [Formula: see text] of the GhostNet-CBAM method could reach up to 0.9447, and the RMSE reached as low as 0.3267, and the scatter density plots of the predicted and true values further confirmed that the method could quickly and accurately obtain the soil pH parameters.https://doi.org/10.1371/journal.pone.0325426
spellingShingle Jianguo Zhu
Wenjin Wang
Peng Tian
Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
PLoS ONE
title Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
title_full Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
title_fullStr Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
title_full_unstemmed Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
title_short Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM.
title_sort spectroscopic measurement of near infrared soil ph parameters based on ghostnet cbam
url https://doi.org/10.1371/journal.pone.0325426
work_keys_str_mv AT jianguozhu spectroscopicmeasurementofnearinfraredsoilphparametersbasedonghostnetcbam
AT wenjinwang spectroscopicmeasurementofnearinfraredsoilphparametersbasedonghostnetcbam
AT pengtian spectroscopicmeasurementofnearinfraredsoilphparametersbasedonghostnetcbam