{"type": "FeatureCollection", "features": [{"id": "10.1029/2022je007190", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:17:13Z", "type": "Journal Article", "created": "2022-01-25", "title": "InSight Pressure Data Recalibration, and Its Application to the Study of Long-Term Pressure Changes on Mars", "description": "Abstract<p>Observations of the South Polar Residual Cap suggest a possible erosion of the cap, leading to an increase of the global mass of the atmosphere. We test this assumption by making the first comparison between Viking 1 and InSight surface pressure data, which were recorded 40\uffc2\uffa0years apart. Such a comparison also allows us to determine changes in the dynamics of the seasonal ice caps between these two periods. To do so, we first had to recalibrate the InSight pressure data because of their unexpected sensitivity to the sensor temperature. Then, we had to design a procedure to compare distant pressure measurements. We propose two surface pressure interpolation methods at the local and global scale to do the comparison. The comparison of Viking and InSight seasonal surface pressure variations does not show changes larger than \uffc2\uffb18\uffc2\uffa0Pa in the CO2 cycle. Such conclusions are supported by an analysis of Mars Science Laboratory (MSL) pressure data. Further comparisons with images of the south seasonal cap taken by the Viking 2 orbiter and MARCI camera do not display significant changes in the dynamics of this cap over a 40\uffc2\uffa0year period. Only a possible larger extension of the North Cap after the global storm of MY 34 is observed, but the physical mechanisms behind this anomaly are not well determined. Finally, the first comparison of MSL and InSight pressure data suggests a pressure deficit at Gale crater during southern summer, possibly resulting from a large presence of dust suspended within the crater.</p>", "keywords": ["Atmospheric sciences", "550", "Astronomy", "Atmosphere (unit)", "FOS: Mechanical engineering", "Library science", "Oceanography", "01 natural sciences", "CO<SUB>2</SUB> ice", "pressure", "Mars Exploration Program", "Engineering", "Surface pressure", "Storm", "Martian Climate", "Space Suit Design and Ergonomics for EVA", "Martian Atmosphere", "Earth and Planetary Astrophysics (astro-ph.EP)", "Climatology", "Global and Planetary Change", "Geography", "Martian Surface", "Physics", "Geology", "Impact crater", "Condensed matter physics", "Anomaly (physics)", "World Wide Web", "Algorithm", "Satellite Observations", "Residual", "Physical Sciences", "Exploration and Study of Mars", "Astrophysics - Instrumentation and Methods for Astrophysics", "Research Article", "FOS: Physical sciences", "Mars", "Aerospace Engineering", "Pressure gradient", "Environmental science", "[SDU] Sciences of the Universe [physics]", "atmospheric mass", "Meteorology", "Orbiter", "0103 physical sciences", "Instrumentation and Methods for Astrophysics (astro-ph.IM)", "Formation and Evolution of the Solar System", "0105 earth and related environmental sciences", "Pressure system", "CO 2 ice", "Astronomy and Astrophysics", "FOS: Earth and related environmental sciences", "Astrobiology", "Computer science", "Physics and Astronomy", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Global Methane Emissions and Impacts", "Environmental Science", "cap sublimation", "Water on Mars", "Astrophysics - Earth and Planetary Astrophysics"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022JE007190"}, {"href": "https://doi.org/10.1029/2022je007190"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Planets", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2022je007190", "name": "item", "description": "10.1029/2022je007190", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2022je007190"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-25T00:00:00Z"}}, {"id": "10.1038/s41598-019-56868-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:17:20Z", "type": "Journal Article", "created": "2020-01-09", "title": "Modelling photovoltaic soiling losses through optical characterization", "description": "Abstract<p>The accumulation of soiling on photovoltaic (PV) modules affects PV systems worldwide. Soiling consists of mineral dust, soot particles, aerosols, pollen, fungi and/or other contaminants that deposit on the surface of PV modules. Soiling absorbs, scatters, and reflects a fraction of the incoming sunlight, reducing the intensity that reaches the active part of the solar cell. Here, we report on the comparison of naturally accumulated soiling on coupons of PV glass soiled at seven locations worldwide. The spectral hemispherical transmittance was measured. It was found that natural soiling disproportionately impacts the blue and ultraviolet (UV) portions of the spectrum compared to the visible and infrared (IR). Also, the general shape of the transmittance spectra was similar at all the studied sites and could adequately be described by a modified form of the \uffc3\uff85ngstr\uffc3\uffb6m turbidity equation. In addition, the distribution of particles sizes was found to follow the IEST-STD-CC 1246E cleanliness standard. The fractional coverage of the glass surface by particles could be determined directly or indirectly and, as expected, has a linear correlation with the transmittance. It thus becomes feasible to estimate the optical consequences of the soiling of PV modules from the particle size distribution and the cleanliness value.</p>", "keywords": ["Photovoltaic Arrays", "Cleanliness", "Particle", "PV", "02 engineering and technology", "Oceanography", "7. Clean energy", "soiling; experimental; transmittance; spectrum", "Turbidity", "Size", "Materials Science and Engineering", "\u00c5ngstr\u00f6m turbidity equation", "Transmittance", "0202 electrical engineering", " electronic engineering", " information engineering", "Photovoltaic system", "Ultraviolet", "Microscopy", "Soiling", "Energy", "Ecology", "Physics", "Q", "R", "Imaging and sensing", "Geology", "Particle size", "6. Clean water", "Photovoltaic Efficiency", "Chemistry", "Physical chemistry", "Particle (ecology)", "Physical Sciences", "Sunlight", "Medicine", "Infrared", "570", "Particle-size distribution", "PV System", "Energy science and technology", "Science", "Optical spectroscopy", "Partial Shading", "530", "Modelling", "Article", "Environmental science", "Techniques and instrumentation", "Optical physics", "Meteorology", "Artificial Intelligence", "Machine Learning Methods for Solar Radiation Forecasting", "Optical techniques", "Optoelectronics", "Aerosol", "Biology", "Renewable Energy", " Sustainability and the Environment", "Electronics", " photonics and device physics", "Building Integrated Photovoltaics", "Optics", "Photovoltaic Maximum Power Point Tracking Techniques", "FOS: Earth and related environmental sciences", "Materials science", "Photovoltaics", "Optics and photonics", "13. Climate action", "FOS: Biological sciences", "Computer Science", "Solar Thermal Energy Technologies"]}, "links": [{"href": "https://iris.uniroma1.it/bitstream/11573/1625670/2/Smestad_Modelling_2020.pdf"}, {"href": "https://www.nature.com/articles/s41598-019-56868-z.pdf"}, {"href": "https://doi.org/10.1038/s41598-019-56868-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41598-019-56868-z", "name": "item", "description": "10.1038/s41598-019-56868-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-019-56868-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-09T00:00:00Z"}}, {"id": "10.1080/14942119.2018.1419677", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:17:41Z", "type": "Journal Article", "created": "2018-01-24", "title": "Wheel rut measurements by forest machine-mounted LiDAR sensors \u2013 accuracy and potential for operational applications?", "description": "ABSTRACTSoil rutting caused by forest operations has negative economic and ecological effects and thus limits for rutting are set by forest laws and sustainability criteria. Extensive data on rut depths are necessary for post-harvest quality control and development of models that link environmental conditions to rut formation. This study explored the use of a Light Detection and Ranging (LiDAR) sensor mounted on a forest harvester and forwarder to measure rut depths in real harvesting conditions in Southern Finland. LiDAR-derived rut depths were compared to manually measured rut depths. The results showed that at 10\u201320\u00a0m spatial resolution, the LiDAR method can provide unbiased estimates of rut depth with root mean square error (RMSE) < 3.5 cm compared to the manual rut depth measurements. The results suggest that a LiDAR sensor mounted on a forest vehicle can in future provide a viable method for the large-scale collection of rut depth data as part of normal forestry operations.", "keywords": ["forest trafficability", "ta113", "550", "forest machine instrumentation", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "LIDAR sensor", "15. Life on land", "sensors", "ta4112", "rut measurement", "rut depth", "620"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/14942119.2018.1419677"}, {"href": "https://doi.org/10.1080/14942119.2018.1419677"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Forest%20Engineering", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1080/14942119.2018.1419677", "name": "item", "description": "10.1080/14942119.2018.1419677", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1080/14942119.2018.1419677"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-02T00:00:00Z"}}, {"id": "10.3929/ethz-b-000278733", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:19:53Z", "type": "Journal Article", "created": "2018-07-06", "title": "Cost\u2013benefit optimization of structural health monitoring sensor networks", "description": "<p>Structural health monitoring (SHM) allows the acquisition of information on the structural integrity of any mechanical system by processing data, measured through a set of sensors, in order to estimate relevant mechanical parameters and indicators of performance. Herein we present a method to perform the cost\uffe2\uff80\uff93benefit optimization of a sensor network by defining the density, type, and positioning of the sensors to be deployed. The effectiveness (benefit) of an SHM system may be quantified by means of information theory, namely through the expected Shannon information gain provided by the measured data, which allows the inherent uncertainties of the experimental process (i.e., those associated with the prediction error and the parameters to be estimated) to be accounted for. In order to evaluate the computationally expensive Monte Carlo estimator of the objective function, a framework comprising surrogate models (polynomial chaos expansion), model order reduction methods (principal component analysis), and stochastic optimization methods is introduced. Two optimization strategies are proposed: the maximization of the information provided by the measured data, given the technological, identifiability, and budgetary constraints; and the maximization of the information\uffe2\uff80\uff93cost ratio. The application of the framework to a large-scale structural problem, the Pirelli tower in Milan, is presented, and the two comprehensive optimization methods are compared.</p>", "keywords": ["Stochastic Processes", "structural health monitoring", "structural health monitoring; Bayesian inference; cost\u2013benefit analysis; stochastic optimization; information theory; Bayesian experimental design; surrogate modeling; model order reduction", "Chemical technology", "Cost-Benefit Analysis", "Bayesian inference", "Bayesian experimental design", "Uncertainty", "Bayes Theorem", "TP1-1185", "02 engineering and technology", "stochastic optimization", "Bayesian experimental design; Bayesian inference; Benefit analysis; Cost; Information theory; Model order reduction; Stochastic optimization; Structural health monitoring; Surrogate modeling; Algorithms; Monte Carlo Method; Nonlinear Dynamics; Stochastic Processes; Uncertainty; Bayes Theorem; Cost-Benefit Analysis; Analytical Chemistry; Atomic and Molecular Physics", " and Optics; Biochemistry; Instrumentation; Electrical and Electronic Engineering", "Article", "surrogate modeling", "0201 civil engineering", "Nonlinear Dynamics", "model order reduction", "cost\u2013benefit analysis", "Monte Carlo Method", "Algorithms", "information theory"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/18/7/2174/pdf"}, {"href": "https://re.public.polimi.it/bitstream/11311/1085132/1/Sensors_2018b.pdf"}, {"href": "https://doi.org/10.3929/ethz-b-000278733"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sensors", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3929/ethz-b-000278733", "name": "item", "description": "10.3929/ethz-b-000278733", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3929/ethz-b-000278733"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-06T00:00:00Z"}}, {"id": "2311.04674", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:01Z", "type": "Journal Article", "created": "2024-04-09", "title": "Direct electrochemical reduction of graphene oxide thin film for aptamer-based selective and highly sensitive detection of matrix metalloproteinase 2", "description": "Simple and low-cost biosensing solutions are suitable for point-of-care applications aiming to overcome the gap between scientific concepts and technological production. To compete with sensitivity and selectivity of golden standards, such as liquid chromatography, the functionalization of biosensors is continuously optimized to enhance the signal and improve their performance, often leading to complex chemical assay development. In this research, the efforts are made on optimizing the methodology for electrochemical reduction of graphene oxide to produce thin film-modified gold electrodes. Under the employed specific conditions, 20 cycles of cyclic voltammetry (CV) are shown to be optimal for superior electrical activation of graphene oxide into electrochemically reduced graphene oxide (ERGO). This platform is further used to develop a matrix metalloproteinase 2 (MMP-2) biosensor, where specific anti-MMP2 aptamers are utilized as a biorecognition element. MMP-2 is a protein which is typically overexpressed in tumor tissues, with important roles in tumor invasion, metastasis as well as in tumor angiogenesis. Based on impedimetric measurements, we were able to detect as low as 3.32 pg/mL of MMP-2 in PBS with a dynamic range of 10 pg/mL - 10 ng/mL. Besides high specificity, ERGO-based aptasensor showed a potential of reuse due to demonstrated successful signal restoration after experimental detection of MMP-2.", "keywords": ["Physics - Instrumentation and Detectors", "FOS: Physical sciences", "Biomolecules (q-bio.BM)", "Physics - Applied Physics", "Electrochemical Techniques", "Biosensing Techniques", "02 engineering and technology", "Applied Physics (physics.app-ph)", "Instrumentation and Detectors (physics.ins-det)", "Aptamers", " Nucleotide", "01 natural sciences", "0104 chemical sciences", "03 medical and health sciences", "0302 clinical medicine", "Quantitative Biology - Biomolecules", "Limit of Detection", "FOS: Biological sciences", "Matrix Metalloproteinase 2", "Humans", "Graphite", "Gold", "0210 nano-technology", "Oxidation-Reduction", "Electrodes"]}, "links": [{"href": "https://doi.org/2311.04674"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Talanta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2311.04674", "name": "item", "description": "2311.04674", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2311.04674"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-01T00:00:00Z"}}, {"id": "2307.16692", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:01Z", "type": "Journal Article", "created": "2023-11-10", "title": "Femtomolar detection of the heart failure biomarker NT-proBNP in artificial saliva using an immersible liquid-gated aptasensor with reduced graphene oxide", "description": "Measuring NT-proBNP biomarker is recommended for preliminary diagnostics of the heart failure. Recent studies suggest a possibility of early screening of biomarkers in saliva for non-invasive identification of cardiac diseases at the point-of-care. However, NT-proBNP concentrations in saliva can be thousand time lower than in blood plasma, going down to pg/mL level. To reach this level, we developed a label-free aptasensor based on a liquid-gated field effect transistor using a film of reduced graphene oxide monolayer (rGO-FET) with immobilized NT-proBNP specific aptamer. We found that, depending on ionic strength of tested solutions, there were different levels of correlation in responses of electrical parameters of the rGO-FET aptasensor, namely, the Dirac point shift and transconductance change. The correlation in response to NT-proBNP was high for 1.6 mM phosphate-buffered saline (PBS) and zero for 16 mM PBS in a wide range of analyte concentrations, varied from 1 fg/mL to 10 ng/mL. The effects of transconductance and Dirac point shift in PBS solutions of different concentrations are discussed. The biosensor exhibited a high sensitivity for both transconductance (2 uS/decade) and Dirac point shift (2.3 mV/decade) in diluted PBS with the linear range from 10 fg/mL to 1 pg/mL. The aptasensor performance has been also demonstrated in undiluted artificial saliva with the achieved limit of detection down to 41 fg/mL (~4.6 fM).", "keywords": ["Condensed Matter - Materials Science", "Physics - Instrumentation and Detectors", "Condensed Matter - Mesoscale and Nanoscale Physics", "Materials Science (cond-mat.mtrl-sci)", "FOS: Physical sciences", "Biomolecules (q-bio.BM)", "Physics - Applied Physics", "Applied Physics (physics.app-ph)", "Instrumentation and Detectors (physics.ins-det)", "02 engineering and technology", "01 natural sciences", "0104 chemical sciences", "Quantitative Biology - Biomolecules", "FOS: Biological sciences", "Mesoscale and Nanoscale Physics (cond-mat.mes-hall)", "0210 nano-technology"]}, "links": [{"href": "https://doi.org/2307.16692"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microchemical%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2307.16692", "name": "item", "description": "2307.16692", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2307.16692"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "2410.1244", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:02Z", "type": "Report", "title": "Surface plasmon resonance sensor based on a novel prism for the detection of a broad range of polymers", "description": "Open AccessMicroplastics are pervasive pollutants that pose threats to the environment and human health. Detecting them reliably represents a crucial step toward finding solutions. While traditional techniques like vibrational and mass spectroscopies are time-consuming and have limitations in analysing polymers with pigment additives, surface plasmon resonance (SPR) shows promise due to its high sensitivity and rapid detection capabilities.However, existing SPR methods rely on one output variable and fail to determine various microplastic parameters simultaneously. To address this uncertainty between size and polymer type, we propose a prism design that enables SPR resonance in a refractive index range of 1.402-1.56 RIU (Refractive Index Units) for polymer detection. Experimental verification of the prism's dynamic range using refractive index oils presented an agreement of 98.47% with theoretical analysis. Furthermore, we acquired SPR curves from ten different polymer types, including Nitrile, Viton and Tyre rubber. These results demonstrate SPR's potential to identify polymers and its ability to detect even pigmented materials, often challenging for other techniques. The imaging capabilities of the novel prism are presented, indicating its potential for future imaging of microplastics. Our approach holds promise for advancing microplastics analysis by enabling comprehensive assessment of particle parameters, such as polymer type, size, quantity and shape, and expanding the range of detectable polymer types.", "keywords": ["Physics - Instrumentation and Detectors", "FOS: Physical sciences", "Instrumentation and Detectors (physics.ins-det)"], "contacts": [{"organization": "Andrade, Natalia A. Gutierrez, Nie, Yunfeng, Meulebroeck, Wendy, Ottevaere, Heidi,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/2410.1244"}, {"rel": "self", "type": "application/geo+json", "title": "2410.1244", "name": "item", "description": "2410.1244", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2410.1244"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "30592d0c330e6c206aa54bf98d50d122", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:19Z", "type": "Other", "title": "Spectra Fusion of Mid-Infrared (MIR) and X-ray Fluorescence (XRF) Spectroscopy for Estimation of Selected Soil Fertility Attributes", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Previous works indicate that data fusion, compared to single data modelling can improve the assessment of soil attributes using spectroscopy. In this work, two different kinds of proximal soil sensing techniques i.e., mid-infrared (MIR) and X-ray fluorescence (XRF) spectroscopy were evaluated, for assessment of seven fertility attributes. These soil attributes include pH, organic carbon (OC), phosphorous (P), potassium (K), magnesium (Mg), calcium (Ca) and moisture contents (MC). Three kinds of spectra fusion (SF) (spectra concatenation) approaches of MIR and XRF spectra were compared, namely, spectra fusion-Partial least square (SF-PLS), spectra fusion-Sequential Orthogonalized Partial least square (SF-SOPLS) and spectra fusion-Variable Importance Projection-Sequential Orthogonalized Partial least square (SF-VIP-SOPLS). Furthermore, the performance of SF models was compared with the developed single sensor model (based on individual spectra of MIR and XRF). Compared with the results obtained from single sensor model, SF models showed improvement in the prediction performance for all studied attributes, except for OC, Mg, and K prediction. More specifically, the highest improvement was observed with SF-SOPLS model for pH [R2p = 0.90, root mean square error prediction (RMSEP) = 0.15, residual prediction deviation (RPD) = 3.30, and ratio of performance inter-quantile (RPIQ) = 3.59], successively followed by P (R2p = 0.91, RMSEP = 4.45 mg/100 g, RPD = 3.53, and RPIQ = 4.90), Ca (R2p = 0.92, RMSEP = 177.11 mg/100 g, RPD = 3.66, and RPIQ = 3.22) and MC (R2p = 0.80, RMSEP = 1.91%, RPD = 2.31, RPIQ = 2.62). Overall the study concluded that SF approach with SOPLS attained better performance over the traditional model developed with the single sensor spectra, hence, SF is recommended as the best SF method for improving the prediction accuracy of studied soil attributes. Moreover, the multi-sensor spectra fusion approach is not limited for only MIR and XRF data but in general can be extended for complementary information fusion in order to improve the model performance in precision agriculture (PA) applications.</p></article>", "keywords": ["Electrical and Electronic Engineering", "Biochemistry", "Instrumentation", "Atomic and Molecular Physics", " and Optics", "Analytical Chemistry"], "contacts": [{"organization": "Abdul Mouazen, Lalit Mohan Kandpal, Muhammad Abdul Munnaf, Cristina Cruz,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/30592d0c330e6c206aa54bf98d50d122"}, {"rel": "self", "type": "application/geo+json", "title": "30592d0c330e6c206aa54bf98d50d122", "name": "item", "description": "30592d0c330e6c206aa54bf98d50d122", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/30592d0c330e6c206aa54bf98d50d122"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "50|userclaim___::30592d0c330e6c206aa54bf98d50d122", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:23:53Z", "type": "Other", "title": "Spectra Fusion of Mid-Infrared (MIR) and X-ray Fluorescence (XRF) Spectroscopy for Estimation of Selected Soil Fertility Attributes", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Previous works indicate that data fusion, compared to single data modelling can improve the assessment of soil attributes using spectroscopy. In this work, two different kinds of proximal soil sensing techniques i.e., mid-infrared (MIR) and X-ray fluorescence (XRF) spectroscopy were evaluated, for assessment of seven fertility attributes. These soil attributes include pH, organic carbon (OC), phosphorous (P), potassium (K), magnesium (Mg), calcium (Ca) and moisture contents (MC). Three kinds of spectra fusion (SF) (spectra concatenation) approaches of MIR and XRF spectra were compared, namely, spectra fusion-Partial least square (SF-PLS), spectra fusion-Sequential Orthogonalized Partial least square (SF-SOPLS) and spectra fusion-Variable Importance Projection-Sequential Orthogonalized Partial least square (SF-VIP-SOPLS). Furthermore, the performance of SF models was compared with the developed single sensor model (based on individual spectra of MIR and XRF). Compared with the results obtained from single sensor model, SF models showed improvement in the prediction performance for all studied attributes, except for OC, Mg, and K prediction. More specifically, the highest improvement was observed with SF-SOPLS model for pH [R2p = 0.90, root mean square error prediction (RMSEP) = 0.15, residual prediction deviation (RPD) = 3.30, and ratio of performance inter-quantile (RPIQ) = 3.59], successively followed by P (R2p = 0.91, RMSEP = 4.45 mg/100 g, RPD = 3.53, and RPIQ = 4.90), Ca (R2p = 0.92, RMSEP = 177.11 mg/100 g, RPD = 3.66, and RPIQ = 3.22) and MC (R2p = 0.80, RMSEP = 1.91%, RPD = 2.31, RPIQ = 2.62). Overall the study concluded that SF approach with SOPLS attained better performance over the traditional model developed with the single sensor spectra, hence, SF is recommended as the best SF method for improving the prediction accuracy of studied soil attributes. Moreover, the multi-sensor spectra fusion approach is not limited for only MIR and XRF data but in general can be extended for complementary information fusion in order to improve the model performance in precision agriculture (PA) applications.</p></article>", "keywords": ["Electrical and Electronic Engineering", "Biochemistry", "Instrumentation", "Atomic and Molecular Physics", " and Optics", "Analytical Chemistry"], "contacts": [{"organization": "Abdul Mouazen, Lalit Mohan Kandpal, Muhammad Abdul Munnaf, Cristina Cruz,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|userclaim___::30592d0c330e6c206aa54bf98d50d122"}, {"rel": "self", "type": "application/geo+json", "title": "50|userclaim___::30592d0c330e6c206aa54bf98d50d122", "name": "item", "description": "50|userclaim___::30592d0c330e6c206aa54bf98d50d122", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|userclaim___::30592d0c330e6c206aa54bf98d50d122"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Instrumentation&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Instrumentation&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Instrumentation&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Instrumentation&offset=9", "hreflang": "en-US"}], "numberMatched": 9, "numberReturned": 9, "distributedFeatures": [], "timeStamp": "2026-10-23T10:54:34.268449Z"}