Calibration of Soil Water Content Data from EnviroSCAN System Using Artificial Neural Network
Hussein M. Al-Ghobari, Mohamed S. A. El Marazky, Abdulwahed M. Aboukarima, Mamdouh Minyawi
Journal of Experimental Agriculture International · pp. 1–11 · Published 14 May 2016
10.9734/AJEA/2016/26237Abstract
Irrigation is one of the essential issues in agriculture in developing countries. Usually, in the developing countries, traditional farmers are likely to use more water than the required for crop production, thus wasting water. Hence, soil water sensors are typically needed in such situations to alert the farmer when the field needs irrigation and when it does not. One of these sensors is the EnviroScan system. It has the potential to monitor and estimate the soil water content continuously at various soil depths. Calibration is important to obtain accurate results. In this study, the volumetric soil water content and scaled frequencies from the EnviroScan system were recorded in a 60- cm soil profile. An artificial neural network (ANN) was used to calibrate the soil water content compared with a regression analysis using field data at different soil depths in sandy clay loam soil. Several ANN architectures were employed in order to determine the optimum architecture. The coefficients of determination (R2) of a regression calibration equation of scaled frequency against the gravimetric soil water content were 0.9225, 0.9623, and 0.9593 for 0–20 cm, 20–30 cm, and 30–60 cm soil depths. The R2 between gravimetric soil water content and the estimated by ANN model was 0.9928 for a 0–20 cm soil depth, 0.9809 for a 20–30 cm soil depth, and 0.9878 for a 30–60 cm soil depth. Using the data set for the entire 60-cm soil profile for calibration by ANN model, the R2 value was 0.9715.
References (20)
- 1 Multilayer feedforward networks are universal approximators [DOI]
- 2 Multilayer feedforward networks are universal approximators [DOI]
- 3 On the approximate realization of continuous mappings by neural networks [DOI]
- 4 Optimization of enzymatic clarification of sapodilla juice using response surface methodology [DOI]
- 5 Soil Profile Water Content Determination: Sensor Accuracy, Axial Response, Calibration, Temperature Dependence, and Precision [DOI]
- 6 Artificial neural networks for diagnosis and survival prediction in colon cancer [DOI]
- 7 Optimization of oven toasting for improving crispness and other quality attributes of ready to eat potato-soy snack using response surface methodology [DOI]
- 8 Evaluation of capacitance probes for optimal irrigation of citrus through soil moisture monitoring in an entisol profile [DOI]
- 9 Field Calibration of a Capacitance Water Content Probe in Fine Sand Soils [DOI]
- 10 Soil moisture estimation using an artificial neural network: a feasibility study [DOI]
- 11 Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester [DOI]
- 12 Evaluation of Soil Moisture Sensors under Intelligent Irrigation Systems for Economical Crops in Arid Regions [DOI]
- 13 Application Of Neural Networks In Financial Data Mining [DOI]
- 14 Predicting the Dielectric Constant–Water Content Relationship Using Artificial Neural Networks [DOI]
- 15 A new approach for neutron moisture meter calibration: artificial neural network [DOI]
- 16 Prediction of Extrudate Properties Using Artificial Neural Networks [DOI]
- 17 A Low Cost Portable Temperature-Moisture Sensing Unit With Artificial Neural Network Based Signal Conditioning For Smart Irrigation Applications [DOI]
- 18 Neutron Moisture Meter Calibration in Six Soils of Uzbekistan Affected by Carbonate Accumulation [DOI]
- 19 Using neural networks for calibration of time-domain reflectometry measurements [DOI]
- 20 On-line measurement of some selected soil properties for controlled input crop management systems
Cited by 5
P. C. S. Moncks, É. Corrêa, L. Guidoni · Bioresource Technology · 2022
Daniel Kibirige, E. Dobos · Water · 2021
Tamás Deák, Réka Diána Bertóti, Endre Dobos · Geosciences and Engineering · 2022
Showing 3 of 5 known citations — external sources report more than can currently be individually listed.
Related research
- A Clinical Decision Support System to Identify and Stage Breast Cancer Tumor — shares topic coverage
- Neural Network and Regression Based Model for Cows’ Milk Yield Prediction in Different Climatic Gradients — shares topic coverage
- Modeling of Two-Phase Gas Deviation Factor for Gas-Condensate Reservoir using Artificial Neural Network — shares topic coverage
- Comparative Performance of Multiple Linear Regression and Artificial Neural Network Based Models in Estimation of Evaporation — shares topic coverage
- Prediction of Oilfield Scale formation Using Artificial Neural Network (ANN) — shares topic coverage
Article metrics
Real usage data collected on this platform.
33
Page views
0
PDF downloads
9
Outbound clicks
5
Citations
Views over time
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
Traffic sources
Referring site, by host.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.