On using artificial intelligence and the internet of things for crop disease detection: A contemporary survey

H Orchi, M Sadik, M Khaldoun - Agriculture, 2022 - mdpi.com
The agricultural sector remains a key contributor to the Moroccan economy, representing
about 15% of gross domestic product (GDP). Disease attacks are constant threats to …

[HTML][HTML] From laboratory to proximal sensing spectroscopy for soil organic carbon estimation—A review

T Angelopoulou, A Balafoutis, G Zalidis, D Bochtis - Sustainability, 2020 - mdpi.com
Rapid and cost-effective soil properties estimations are considered imperative for the
monitoring and recording of agricultural soil condition for the implementation of site-specific …

SHAP values accurately explain the difference in modeling accuracy of convolution neural network between soil full-spectrum and feature-spectrum

L Zhong, X Guo, M Ding, Y Ye, Y Jiang, Q Zhu… - … and Electronics in …, 2024 - Elsevier
Acquiring soil nutrient content quickly and accurately through remote sensing is the key to
advance precision agriculture. The development of deep learning has provided new …

Estimation of leaf nitrogen content in rice using vegetation indices and feature variable optimization with information fusion of multiple-sensor images from UAV

S Xu, X Xu, C Blacker, R Gaulton, Q Zhu, M Yang… - Remote Sensing, 2023 - mdpi.com
LNC (leaf nitrogen content) in crops is significant for diagnosing the crop growth status and
guiding fertilization decisions. Currently, UAV (unmanned aerial vehicles) remote sensing …

Prediction of various soil properties for a national spatial dataset of Scottish soils based on four different chemometric approaches: A comparison of near infrared and …

RK Haghi, E Pérez-Fernández, AHJ Robertson - Geoderma, 2021 - Elsevier
Infrared spectroscopic techniques, in combination with chemometric approaches, have been
widely used to estimate different physical and chemical properties in soil samples. This …

[HTML][HTML] Spectral fusion modeling for soil organic carbon by a parallel input-convolutional neural network

Y Hong, S Chen, B Hu, N Wang, J Xue, Z Zhuo, Y Yang… - Geoderma, 2023 - Elsevier
Abstract Visible-to-near-infrared (vis–NIR) and mid-infrared (MIR) spectroscopy have been
widely utilized for the quantitative estimation of soil organic carbon (SOC). The fusion of vis …

Soil exchangeable cations estimation using Vis-NIR spectroscopy in different depths: Effects of multiple calibration models and spiking

D Zhao, M Arshad, J Wang, J Triantafilis - Computers and Electronics in …, 2021 - Elsevier
Due to high rate of nutrient removal by cotton plants, the productive cotton-growing soils of
Australia are becoming depleted of exchangeable (exch.) cations. For long-term …

Early detection of tomato spotted wilt virus infection in tobacco using the hyperspectral imaging technique and machine learning algorithms

Q Gu, L Sheng, T Zhang, Y Lu, Z Zhang… - … and Electronics in …, 2019 - Elsevier
The hyperspectral imaging technique was used for the non-destructive detection of tomato
spotted wilt virus (TSWV) infection in tobacco at an early stage. Spectra ranging from 400 to …

[HTML][HTML] Early detection of bacterial wilt in tomato with portable hyperspectral spectrometer

Y Cen, Y Huang, S Hu, L Zhang, J Zhang - Remote Sensing, 2022 - mdpi.com
As a kind of soil-borne epidemic disease, bacterial wilt (BW) is one of the most serious
diseases in tomatoes in southern China, which may significantly reduce food quality and the …

Evaluation of Vis-NIR preprocessing combined with PLS regression for estimation soil organic carbon, cation exchange capacity and clay from eastern Croatia

B Miloš, A Bensa, B Japundžić-Palenkić - Geoderma regional, 2022 - Elsevier
This study aimed to evaluate (i) the potential of visible-near-infrared (Vis-NIR) preprocessing
techniques combined with a partial least square (PLS) regression to estimate soil organic …