Stepwise model parametrisation using satellite imagery and hemispherical photography: tuning AquaCrop sensitive parameters for improved winter wheat yield predictions in semi-arid regions

Crop models are complex with many parameters, which has limited their application. Here we present an approach which both removes the model complexity through reducing the parameter dimensionality through sensitivity analysis, and presents a subsequent efficient approach to model parameterisation using swarm optimisation. We do this for two key model outputs, crop canopy and yield, and for two types of observational data, hemispheric photographs and Landsat7 imagery. Importantly we compare the usefulness of these two sources of data in terms of accurate yield prediction. The results showed that the dominant model parameters that predict canopy cover were generally consistent across the fields, with the exception of those related water stress. Although mid-season canopy cover extracted from Landsat7 was underestimated, good agreement was found between the simulated and observed canopy cover for both sources of data. Subsequently, less accurate yield predictions were achieved with the Landsat7 compared to the hemispherical photography-based parametrizations. Despite the small differences in the canopy predictions, the implications for yield prediction were substantial with the parametrization based on hemispherical photography providing far more accurate estimates of yield. There are, however, additional resource implications associated with hemispherical photography. We evaluate these trade-offs, providing model parametrization sets and demonstrating the potential of satellite imagery to assist AquaCrop, particularly on large scales where ground measurements are challenging.This work is part of the SAFA (Sustainable Agriculture For Africa) project which is funded by OCP, Morocco

Electromagnetic modelling of Leaf Water Potential under Ultra-Wide Band Microwaves Sensing

Noninvasive sensor of plant that measure leaf concentration water is purposed. It is based on a microstrip structure where the loaded layer is represented by a mathematical model. The leaf is represented with the cellulose Cole-Debye model, that includes freshwater molecules which are simulated with different size to characterize the turgescence and plasmolysis behavior. The concept is validated and compared to Cole-Debye model for different situation of stress leaf, represented by an equivalent dielectric cell over the sensor

Electromagnetic modelling of Leaf Water Potential under Ultra-Wide Band Microwaves Sensing

Noninvasive sensor of plant that measure leaf concentration water is purposed. It is based on a microstrip structure where the loaded layer is represented by a mathematical model. The leaf is represented with the cellulose Cole-Debye model, that includes fresh water molecules which are simulated with different size to characterize the turgescence and plasmolysis behavior. The concept is validated and compared to Cole-Debye model for different situation of stress leaf, represented by an equivalent dielectric cell over the sensor

High Sensitivity SSR Based Sensor Used for Permittivity Measurement

The proposed compact sensor is based on a Split Square Resonator (SRR) to improve the detection. The dimensions of the SRR have been chosen to provide a mutual coupling with a high sensitivity. The material under test (MUT) is placed in the near-field region of the sensor. This design exhibits a high sensitivity close to 58% as the relative permittivity of MUT’s changes from 1 to 10. The proposed sensor can measure the permeability and losses

Electromagnetic modelling of Leaf Water Potential under Ultra-Wide Band Microwaves Sensing

Noninvasive microwave sensor of plant that measure leaf concentration water is purposed. It is based on a microstrip structure where the loaded layer is represented by a mathematical model. The leaf is represented with the cellulose Cole-Debye model, that includes freshwater molecules which are simulated with different size to characterize the turgescence and plasmolysis behavior. The concept is validated and compared to Cole-Debye model for different situation of stress leaf, represented by an equivalent dielectric cell over the sensor

The quality monitoring of paracetamol medicament using a noninvasive microwave sensor

International audienceEnvironmental conditions, including temperature, humidity, and light, can impact the quality of drugs. Microwave-based approaches offer a fast and cost-effective way to detect quality variations, providing an alternative to traditional techniques in the pharmaceutical and cosmetic industries. This article proposes the use of a microwave sensor for monitoring the quality of pharmaceutical drugs at distinct temperature levels. A small planar sensor based on three hexagonal split ring resonators (TH-SRR) is fabricated. The design is manufactured on an FR-4 dielectric substrate. The sensor is tested on a 1000 mg paracetamol tablet, at temperatures ranging from 40 to 80 ∘ C. The Variation in the permittivity that characterizes product degradation is translated into a shift in the frequency of the scattering matrix elements. To validate the microwave approach, drug quality is examined with the laser-induced breakdown spectroscopy (LIBS) technique, an optical emission laser used for both qualitative and quantitative investigations of elements contained in a sample. The existing elements are classified using the National Institute of Standards and Technology (NIST) database and categorized according to their spectral line wavelengths. The experiments show the presence of optimal wavelength values for carbon (C), hydrogen (H), nitrogen (N), and oxygen (O) at 247.92 nm, 656.49 nm, 244.23 nm, and 777.48 nm, respectively. The microwave experimental results show a shift frequency of approximately 1 MHz on average when the tablet is heated at 80 ∘ C for 15 min. Meanwhile, the LIBS measurement shows a remarkable shift in terms of intensity of approximately 8884 and 812 for carbon and hydrogen, respectively. Understanding how paracetamol dries under high temperatures and improving the process settings of the microwave sensor are investigated and assessed in this work. © 2023, Springer Nature Limited

Medium-Resolution Mapping of Evapotranspiration at the Catchment Scale Based on Thermal Infrared MODIS Data and ERA-Interim Reanalysis over North Africa

International audienceAccurate quantification of evapotranspiration (ET) at the watershed scale remains an important research challenge for managing water resources in arid and semiarid areas. In this study, daily latent heat flux (LE) maps at the kilometer scale were derived from the two-source energy budget (TSEB) model fed by the MODIS leaf area index (LAI), land surface temperature (LST) products, and meteorological data from ERA-Interim reanalysis from 2001 to 2015 on the Tensift catchment (center of Morocco). As a preliminary step, both ERA-Interim and predicted LE at the time of the satellite overpass are evaluated in comparison to a large database of in situ meteorological measurements and eddy covariance (EC) observations, respectively. ERA-Interim compared reasonably well to in situ measurements, but a positive bias on air temperature was highlighted because meteorological stations used for the evaluation were mainly installed on irrigated fields while the grid point of ERA-Interim is representative of larger areas including bare (and hot) soil. Likewise, the predicted LE was in good agreement with the EC measurements gathered on the main crops of the region during 15 agricultural seasons with a correlation coefficient r = 0.70 and a reasonable bias of 30 W/m2. After extrapolating the instantaneous LE estimates to ET daily values, monthly ET was then assessed in comparison to monthly irrigation water amounts provided by the local agricultural office added to CRU precipitation dataset with a reasonable agreement; the relative error was more than 89% but the correlation coefficient r reached 0.80. Seasonal and interannual evapotranspiration was analyzed in relation to local climate and land use. Lastly, the potential use for improving the early prediction of grain yield, as well as detecting newly irrigated areas for arboriculture, is also discussed. The proposed method provides a relatively simple way for obtaining spatially distributed daily estimates of ET at the watershed scale, especially for not ungauged catchments