{"type": "FeatureCollection", "features": [{"id": "10.1007/s00216-019-01895-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:18Z", "type": "Journal Article", "created": "2019-06-10", "title": "Simultaneous determination of multiclass antibiotics and their metabolites in four types of field-grown vegetables", "description": "The developed method was evaluated for the determination of 10 antibiotics belonging to four chemical classes (fluoroquinolones, sulfonamides, lincosamides, and metoxybenzylpyrimidines) and six of their metabolites in four vegetable matrices (lettuce, tomato, cauliflower, and broad beans). The reported method detection limits were sufficiently low (0.1-5.8\u00a0ng/g dry weight) to detect target compounds in vegetables under real agricultural practices. Absolute and relative recovery values ranged from 40 to 118% and from 70 to 118%, respectively, for all targeted compounds at the spike level of 100\u00a0ng/g dry weight. Regarding method precision, the highest relative standard deviation (RSD) was obtained for enrofloxacin in lettuce (20%), while for the rest of the compounds in all matrices, the RSD values were below 20% for the same spike level. Matrix effects, due to electrospray ionization, ranged from -\u200926 to 29% for 85% of all estimated values. In a field study, four of the 10 targeted antibiotics were detected in tested vegetables. For the first time, antibiotic metabolites were quantified in vegetables grown under real field conditions. More specifically, decarboxyl ofloxacin and TMP304 were detected in tomato fruits (1.5\u00a0ng/g dry weight) and lettuce leaves (21.0-23.1\u00a0ng/g dry weight), respectively. It is important to remark that the concentration of TMP304 was five times higher than that from the parental compound, emphasizing the importance of metabolite analysis in monitoring studies. Therefore, the method provided a robust, reliable, and simple-to-use tool that could prove useful for routine multiclass analysis of antibiotics and their metabolites in vegetable samples. Graphical abstract.", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "Spectrometry", " Mass", " Electrospray Ionization", "Agricultural Irrigation", "Solid Phase Extraction", "Reproducibility of Results", "LC-ESI-MS/MS", "01 natural sciences", "Anti-Bacterial Agents", "0104 chemical sciences", "3. Good health", "Antibiotics", "Limit of Detection", "Ultrasound-assisted extraction", "Vegetables", "Metabolites", "Chromatography", " Liquid", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Tadi\u0107, \u0110or\u0111e, Matamoros, V\u00edctor, Bayona, Josep M.,", "roles": ["creator"]}]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s00216-019-01895-y.pdf"}, {"href": "https://doi.org/10.1007/s00216-019-01895-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytical%20and%20Bioanalytical%20Chemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00216-019-01895-y", "name": "item", "description": "10.1007/s00216-019-01895-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00216-019-01895-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-06-10T00:00:00Z"}}, {"id": "10.1016/j.aca.2023.341718", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:56Z", "type": "Journal Article", "created": "2023-08-15", "title": "Surveying the mugineic acid family: Ion mobility \u2013 quadrupole time-of-flight mass spectrometry (IM-QTOFMS) characterization and tandem mass spectrometry (LC-ESI-MS/MS) quantification of all eight naturally occurring phytosiderophores", "description": "Phytosiderophores (PS) are root exudates released by grass species (Poaceae) that play a pivotal role in iron (Fe) plant nutrition. A direct determination of PS in biological samples is of paramount importance in understanding micronutrient acquisition mediated by PS. To date, eight plant-born PS have been identified; however, no analytical procedure is currently available to quantify all eight PS simultaneously with high analytical confidence. With access to the full set of PS standards for the first time, we report comprehensive methods to both fully characterize (IM-QTOFMS) and quantify (LC-ESI-MS/MS) all eight naturally occurring PS belonging to the mugineic acid family. The quantitative method was fully validated, yielding linear results for all eight analytes, and no unwanted interferences with soil and plant matrices were observed. LOD and LOQ values determined for each PS were below 11 and 35\u00a0nmol\u00a0L-1, respectively. The method's precision under reproducibility conditions (intra- and inter-day) of measurement was less than 2.5% RSD for all analytes. Additionally, all PS were annotated with high-resolution mass spectrometric fragment spectra and further characterized via drift tube ion mobility-mass spectrometry. The collision cross-sections obtained for primary ion species yielded a valuable database for future research focused on in-depth PS studies. The new quantitative method was applied to analyse root exudates from Fe-controlled and deficient barley, oat, rye, and sorghum plants. All eight PS, including mugineic acid (MA), 3'-hydroxymugineic acid (HMA), 3'-epi-hydroxymugineic acid (epi-HMA), hydroxyavenic acid (HAVA), deoxymugineic acid (DMA), 3'-hydroxydeoxymugineic acid (HDMA), 3'-epi-hydroxydeoxymugineic acid (epi-HDMA) and avenic acid (AVA) were for the first time successfully identified and quantified in root exudates of various graminaceous plants using a single analytical procedure. These newly developed methods can be applied to studies aimed at improving crop yield and micronutrient grain content for food consumption via plant-based biofortification.", "keywords": ["Tandem Mass Spectrometry", "Reproducibility of Results", "Micronutrients", "Poaceae", "Edible Grain"]}, "links": [{"href": "https://doi.org/10.1016/j.aca.2023.341718"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytica%20Chimica%20Acta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.aca.2023.341718", "name": "item", "description": "10.1016/j.aca.2023.341718", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.aca.2023.341718"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-10-01T00:00:00Z"}}, {"id": "10.1016/j.jbiotec.2023.07.008", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:47Z", "type": "Journal Article", "created": "2023-07-25", "title": "Fast and reliable method to estimate global DNA methylation in plants and fungi with high-pressure liquid chromatography (HPLC)-ultraviolet detection and even more sensitive one with HPLC-mass spectrometry", "description": "DNA (Deoxyribonucleic acid) methylation is one of the epigenetic modifications of DNA, acting as a bridge between genotype and phenotype. Thus, disruption of DNA methylation pattern has tremendous consequences for organism development. Current methods to determine DNA methylation suffer from methodological drawbacks like high requirement of DNA and poor reproducibility of chromatograms. Here we provide a fast and reliable method using high-pressure liquid chromatography (HPLC)-ultraviolet (UV) detector and even more sensitive one with HPLC- mass spectrometry (MS) and we test this method with various plant and fungal DNA isolates. We optimized the preparation of the DNA degradation step to decrease background noise, we improved separation conditions to provide reliable and reproducible chromatograms and conditions to measure nucleotides in HPLC-MS. We showed that global DNA methylation level can be accurately and reproducibly measured with as little as 0.2\u00a0\u00b5M for HPLC-UV and 0.02\u00a0\u00b5M for HPLC-MS of methylated cytosine.", "keywords": ["Chromatography", "Plant DNA", "DNA methylation", "ta1183", "ta1182", "Fungi", "610", "Reproducibility of Results", "DNA Methylation", "Mass Spectrometry", "Fungal DNA", "chromatography", "DNA", " Fungal", "ta116", "Chromatography", " High Pressure Liquid"]}, "links": [{"href": "https://doi.org/10.1016/j.jbiotec.2023.07.008"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Biotechnology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jbiotec.2023.07.008", "name": "item", "description": "10.1016/j.jbiotec.2023.07.008", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jbiotec.2023.07.008"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-09-01T00:00:00Z"}}, {"id": "10.1016/j.jhazmat.2009.05.074", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:50Z", "type": "Journal Article", "created": "2009-05-23", "title": "Enrichment Of Marsh Soils With Heavy Metals By Effect Of Anthropic Pollution", "description": "The impact of waste disposal on marsh soils was assessed in topsoil samples collected at eight randomly selected points in the salt marsh in Ramallosa (Pontevedra, Spain) at 4-month intervals for 2 years. Polluted soil samples were characterized in physico-chemical terms and their heavy metal contents determined by comparison with control, unpolluted samples. The results revealed a marked effect of waste discharges on the soils in the area, which have low contents in heavy metals under normal environmental conditions. In fact, the studied soils were found to contain substantial amounts of total and DTPA-extractable Cd, Cu, Pb and Zn. Based on the relationship of the redox potential with the DTPA-extractable Cd, Cu, Pb, and Zn contents of the soils, strongly reductive conditions raised the total contents in these elements by effect of their remaining in the soils as precipitated sulphides. Such contents, however, decreased as oxidative conditions gradually prevailed. The contents in DTPA-extractable metals increased with increasing Eh through the release of the metals in ionic form to the soil solution under oxidative conditions. The contents in heavy metals concentrating in the polluted soils were several times higher than those in the control soils (viz. 2 vs. 6 for Cd, 4 vs. 6 for Cu, 4 vs. 20 for Pb, and 2 vs. 15 for Zn, all in mgkg(-1)). This can be expected to influence the amounts of available heavy metals present in the soils, and hence the environmental quality of the area, in the near future. Based on its geoaccumulation index (Class >/=3 for Cd and Cu, and 1-4 for Pb and Zn), the Ramallosa marsh is highly polluted with Cd and moderately to highly polluted with Cu, Pb and Zn. The enrichment factors obtained confirm that the salt marsh is highly polluted (especially with Cd) as the primary result of anthropic activity.", "keywords": ["Industrial Waste", "Reproducibility of Results", "Agriculture", "Pentetic Acid", "15. Life on land", "Waste Disposal", " Fluid", "01 natural sciences", "6. Clean water", "Ion Exchange", "13. Climate action", "Metals", " Heavy", "Wetlands", "Linear Models", "Potentiometry", "Water Pollution", " Chemical", "Soil Pollutants", "Oxidation-Reduction", "Algorithms", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.jhazmat.2009.05.074"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hazardous%20Materials", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhazmat.2009.05.074", "name": "item", "description": "10.1016/j.jhazmat.2009.05.074", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhazmat.2009.05.074"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-10-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2021.150818", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:02Z", "type": "Journal Article", "created": "2021-10-11", "title": "A review of the use of microplastics in reconstructing dated sedimentary archives", "description": "Buried microplastics (plastics, <5\u00a0mm) have been documented within the sediment column of both marine and lacustrine environments. However, the number of peer-review studies published on the subject remains limited and confidence in data reliability varies considerably. Here we critically review the state of the literature on microplastic loading inventories in dated sedimentary and soil profiles. We conclude that microplastics are being sequestered across a variety of sedimentary environments globally, at a seemingly increasing rate. However, microplastics are also readily mobilised both within depositional settings and the workplace. Microplastics are commonly reported from sediments dated to before the onset of plastic production and researcher-derived microplastics frequently contaminate samples. Additionally, the diversity of microplastic types and issues of constraining source points has so far hindered interpretation of depositional settings. Therefore, further research utilizing high quality data sets, greater levels of reporting transparency, and well-established methodologies from the geosciences will be required for any validation of microplastics as a sediment dating method or in quantifying temporally resolved microplastic loading inventories in sedimentary sinks with confidence.", "keywords": ["0106 biological sciences", "Geologic Sediments", "550", "Anthropocene", " Microplastic", " Sediment", " Dating", " Critical review", "13. Climate action", "Microplastics", "500", "Reproducibility of Results", "Plastics", "01 natural sciences", "Water Pollutants", " Chemical", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.150818"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2021.150818", "name": "item", "description": "10.1016/j.scitotenv.2021.150818", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.150818"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "10.1016/j.talanta.2016.10.071", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:25Z", "type": "Journal Article", "created": "2016-10-19", "title": "Prediction of alkaline earth elements in bone remains by near infrared spectroscopy", "description": "An innovative methodological approach has been developed for the prediction of the mineral element composition of bone remains. It is based on the use of Fourier Transform Near Infrared (FT-NIR) diffuse reflectance measurements. The method permits a fast, cheap and green analytical way, to understand post-mortem degradation of bones caused by the environment conditions on different skeletal parts and to select the best preserved bone samples. Samples, from the Late Roman Necropolis of Virgen de la Misericordia street and En Gil street located in Valencia (Spain), were employed to test the proposed approach being determined calcium, magnesium and strontium in bone remains and sediments. Coefficients of determination obtained between predicted values and reference ones for Ca, Mg and Sr were 90.4, 97.3 and 97.4, with residual predictive deviation of 3.2, 5.3 and 2.3, respectively, and relative root mean square error of prediction between 10% and 37%. Results obtained evidenced that NIR spectra combined with statistical analysis can help to predict bone mineral profiles suitable to evaluate bone diagenesis.", "keywords": ["Spectroscopy", " Near-Infrared", "Fossils", "Reproducibility of Results", "06 humanities and the arts", "01 natural sciences", "Bone and Bones", "Spain", "Strontium", "Metals", " Alkaline Earth", "Spectroscopy", " Fourier Transform Infrared", "Humans", "Calcium", "Magnesium", "0601 history and archaeology", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/110415/1/TAL_R1.pdf"}, {"href": "https://doi.org/10.1016/j.talanta.2016.10.071"}, {"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": "10.1016/j.talanta.2016.10.071", "name": "item", "description": "10.1016/j.talanta.2016.10.071", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.talanta.2016.10.071"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "10.1021/acs.est.0c08208", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:31Z", "type": "Journal Article", "created": "2021-05-19", "title": "An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry", "description": "<strong>Abstract</strong> The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultra-high resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform <em>via</em> manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from world-wide locations. The method detected &gt;9,600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, pharmaceuticals,<em> </em>among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions, whilst significantly increasing throughput.", "keywords": ["13. Climate action", "1600", "2304", "Reproducibility of Results", "Pesticides", "01 natural sciences", "Chromatography", " High Pressure Liquid", "Mass Spectrometry", "Water Pollutants", " Chemical", "Chromatography", " Liquid", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.bournemouth.ac.uk/36790/1/An%20Automated%20Methodology%20for%20Non-targeted%20Compositional%20Analysis%20of%20Small%20Molecules%20in%20High%20Complexity%20Environmental%20Matrice.pdf"}, {"href": "https://eprints.whiterose.ac.uk/174399/1/acs.est.0c08208.pdf"}, {"href": "https://doi.org/10.1021/acs.est.0c08208"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/acs.est.0c08208", "name": "item", "description": "10.1021/acs.est.0c08208", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/acs.est.0c08208"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-18T00:00:00Z"}}, {"id": "10.1038/nature02053", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:44Z", "type": "Journal Article", "created": "2003-10-22", "title": "Genome-Scale Approaches To Resolving Incongruence In Molecular Phylogenies", "description": "One of the most pervasive challenges in molecular phylogenetics is the incongruence between phylogenies obtained using different data sets, such as individual genes. To systematically investigate the degree of incongruence, and potential methods for resolving it, we screened the genome sequences of eight yeast species and selected 106 widely distributed orthologous genes for phylogenetic analyses, singly and by concatenation. Our results suggest that data sets consisting of single or a small number of concatenated genes have a significant probability of supporting conflicting topologies. By contrast, analyses of the entire data set of concatenated genes yielded a single, fully resolved species tree with maximum support. Comparable results were obtained with a concatenation of a minimum of 20 genes; substantially more genes than commonly used but a small fraction of any genome. These results have important implications for resolving branches of the tree of life.", "keywords": ["0301 basic medicine", "Saccharomyces", "0303 health sciences", "03 medical and health sciences", "Genes", " Fungal", "Regression Analysis", "Reproducibility of Results", "Genomics", "Genome", " Fungal", "Phylogeny"]}, "links": [{"href": "https://doi.org/10.1038/nature02053"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/nature02053", "name": "item", "description": "10.1038/nature02053", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/nature02053"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2003-10-01T00:00:00Z"}}, {"id": "10.1038/s41467-018-04594-x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:46Z", "type": "Journal Article", "created": "2018-05-29", "title": "Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces", "description": "Abstract<p>A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.</p", "keywords": ["Science", "Circular Dichroism", "Q", "Lipid Bilayers", "Membrane Proteins", "Reproducibility of Results", "Biosensing Techniques", "02 engineering and technology", "01 natural sciences", "Article", "0104 chemical sciences", "Membrane Lipids", "Spectroscopy", " Fourier Transform Infrared", "Peptides", "0210 nano-technology", "Protein Binding"]}, "links": [{"href": "https://eprints.gla.ac.uk/164038/1/164038.pdf"}, {"href": "https://www.nature.com/articles/s41467-018-04594-x.pdf"}, {"href": "https://doi.org/10.1038/s41467-018-04594-x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Communications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41467-018-04594-x", "name": "item", "description": "10.1038/s41467-018-04594-x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41467-018-04594-x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-04T00:00:00Z"}}, {"id": "10.1038/s41598-021-02302-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:50Z", "type": "Journal Article", "created": "2021-11-30", "title": "Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections", "description": "Abstract<p>Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses. This paper investigates Near-infrared (NIR) hyperspectral imaging (1000\uffe2\uff80\uff931700\uffc2\uffa0nm) and machine learning to build models to automatically predict the susceptibility of sepals of recently harvested tomatoes to future fungal infections. Hyperspectral images of newly harvested tomatoes (cultivar Brioso) from 5 different growers were acquired before the onset of any visible fungal infection. After imaging, the tomatoes were placed under controlled conditions suited for fungal germination and growth for a 4-day period, and then imaged using normal color cameras. All sepals in the color images were ranked for fungal severity using crowdsourcing, and the final severity of each sepal was fused using principal component analysis. A novel hyperspectral data processing pipeline is presented which was used to automatically segment the tomato sepals from spectral images with multiple tomatoes connected via a truss. The key modelling question addressed in this research is whether there is a correlation between the hyperspectral data captured at harvest and the fungal infection observed 4 days later. Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. The best model found a Pearson correlation of 0.837, showing that there is strong linear correlation between the NIR spectra and the future fungal severity of the sepal. The sepal specific predictions were aggregated to predict the susceptibility of individual tomatoes, and a correlation of 0.92 was found. Besides modelling, focus is also on model interpretation, particularly to understand which spectral features are most relevant to model prediction. Two approaches to model interpretation were explored, feature importance and SHAP (SHapley Additive exPlanations), resulting in similar conclusions that the NIR range between 1390\uffe2\uff80\uff931420\uffc2\uffa0nm contributes most to the model\uffe2\uff80\uff99s final decision.</p", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "0301 basic medicine", "Principal Component Analysis", "0303 health sciences", "Spectroscopy", " Near-Infrared", "Science", "Q", "R", "Reproducibility of Results", "Microbiology", "Article", "Pattern Recognition", " Automated", "Machine Learning", "03 medical and health sciences", "Deep Learning", "Solanum lycopersicum", "Fruit", "Calibration", "Life Science", "Medicine", "Algorithms", "Software", "Plant Diseases"]}, "links": [{"href": "https://www.nature.com/articles/s41598-021-02302-2.pdf"}, {"href": "https://doi.org/10.1038/s41598-021-02302-2"}, {"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/s41598-021-02302-2", "name": "item", "description": "10.1038/s41598-021-02302-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-021-02302-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "10.1038/s41598-022-23318-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:50Z", "type": "Journal Article", "created": "2022-11-05", "title": "Optical photothermal infrared spectroscopy with simultaneously acquired Raman spectroscopy for two-dimensional microplastic identification", "description": "Abstract<p>In recent years, vibrational spectroscopic techniques based on Fourier transform infrared (FTIR) or Raman microspectroscopy have been suggested to fulfill the unmet need for microplastic particle detection and identification. Inter-system comparison of spectra from reference polymers enables assessing the reproducibility between instruments and advantages of emerging quantum cascade laser-based optical photothermal infrared (O-PTIR) spectroscopy. In our work, IR and Raman spectra of nine plastics, namely polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, polycarbonate, polystyrene, silicone, polylactide acid  and polymethylmethacrylate were simultaneously acquired using an O-PTIR microscope in non-contact, reflection mode. Comprehensive band assignments were presented. We determined the agreement of O-PTIR with standalone attenuated total reflection FTIR and Raman spectrometers based on the hit quality index (HQI) and introduced a two-dimensional identification (2D-HQI) approach using both Raman- and IR-HQIs. Finally, microplastic particles were prepared as test samples from known materials by wet grinding, O-PTIR data were collected and subjected to the 2D-HQI identification approach. We concluded that this framework offers improved material identification of microplastic particles in environmental, nutritious and biological matrices.</p", "keywords": ["Science", "Microplastics", "Q", "R", "Reproducibility of Results", "Spectrum Analysis", " Raman", "Polypropylenes", "01 natural sciences", "Article", "0104 chemical sciences", "Spectroscopy", " Fourier Transform Infrared", "Medicine", "Plastics", "Water Pollutants", " Chemical", "Environmental Monitoring"]}, "links": [{"href": "https://www.nature.com/articles/s41598-022-23318-2.pdf"}, {"href": "https://doi.org/10.1038/s41598-022-23318-2"}, {"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/s41598-022-23318-2", "name": "item", "description": "10.1038/s41598-022-23318-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41598-022-23318-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-11-05T00:00:00Z"}}, {"id": "10.1039/d2ay01215d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:53Z", "type": "Journal Article", "created": "2022-09-23", "title": "Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods", "description": "<p>Light scatterometry combined with chemometrics can be a practical approach for the analysis of size and concentration of microplastics in water.</p>", "keywords": ["Polyethylene", "PARTICLE-SIZE DISTRIBUTIONIDENTIFICATIONRELEASEFOOD", "Microplastics", "PARTICLE-SIZE DISTRIBUTION", " IDENTIFICATION", " RELEASE", " FOOD", "Polymethyl Methacrylate", "Polystyrenes", "Reproducibility of Results", "Water", "Chemometrics", "Plastics", "6. Clean water"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/523367/1/Batch%20analysis%20of%20microplastics%20using%20multi-angle%20static%20light%20scattering%20and%20chemometric%20methods.pdf"}, {"href": "http://pubs.rsc.org/en/content/articlepdf/2022/AY/D2AY01215D"}, {"href": "https://doi.org/10.1039/d2ay01215d"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytical%20Methods", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1039/d2ay01215d", "name": "item", "description": "10.1039/d2ay01215d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1039/d2ay01215d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.1111/mec.16716", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:17:46Z", "type": "Journal Article", "created": "2022-10-05", "title": "Metabarcoding for biodiversity inventory blind spots: A test case using the beetle fauna of an insular cloud forest", "description": "Abstract<p>Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly \uffe2\uff80\uff9cdenoise\uffe2\uff80\uff9d and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.</p", "keywords": ["0301 basic medicine", "0303 health sciences", "Reproducibility of Results", "Biodiversity", "Forests", "15. Life on land", "Protect", " restore and promote sustainable use of terrestrial ecosystems", " sustainably manage forests", " combat\u00a0desertification", " and halt and reverse land degradation and halt biodiversity loss", "Coleoptera", "Soil", "03 medical and health sciences", "metabarcoding", "http://metadata.un.org/sdg/15", "Animals", "DNA Barcoding", " Taxonomic", "taxonomic inflation", "Arthropods", "Barcoding", "mesofauna"]}, "links": [{"href": "https://doi.org/10.1111/mec.16716"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Molecular%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/mec.16716", "name": "item", "description": "10.1111/mec.16716", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/mec.16716"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-24T00:00:00Z"}}, {"id": "10.1186/s12302-024-00873-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:17:57Z", "type": "Journal Article", "created": "2024-03-11", "title": "SWAT\u2009+\u2009input data preparation in a scripted workflow: SWATprepR", "description": "Abstract<p>Input data collection, quality assurance and preparation are central but time_consuming steps in environmental modeling. Errors due to manual processing of model input data can result in an incorrect representation of an environmental system and may consequently lead to implausible model simulations. Correct input data preparation and thorough quality check at an early stage of the model setup procedure are essential to build confidence in model simulation results. Typically, in environmental model applications, many steps in the input data preparation phase have to be repeated with the inflow of new, additional or corrected data. In this study, we selected the widely used SWAT\uffe2\uff80\uff89+\uffe2\uff80\uff89ecohydrological model as an illustrative example to investigate challenges related to input data preparation. To assist in these tasks, we developed an R package named SWATprepR, which provides functions for typical and repeating SWAT\uffe2\uff80\uff89+\uffe2\uff80\uff89model input data preparation tasks. The package supports the preparation of weather input files, atmospheric deposition, soil parameters, crop rotations, and observed (control or calibration) data, to name a few, presently with focus on European applications. The SWATprepR functions are integrated in R script workflows and can help SWAT\uffe2\uff80\uff89+\uffe2\uff80\uff89modelers to avoid repetitive tasks, secure reproducibility and transparently document the data processing steps. Application of the package is illustrated with a test case of a SWAT\uffe2\uff80\uff89+\uffe2\uff80\uff89model for a small catchment in central Poland.</p", "keywords": ["Environmental sciences", "SWAT\u2009+\u2009model", "Environmental law", "R package", "0208 environmental biotechnology", "0207 environmental engineering", "GE1-350", "02 engineering and technology", "Input data processing", "K3581-3598", "Reproducibility", "Workflow"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1186/s12302-024-00873-1.pdf"}, {"href": "https://doi.org/10.1186/s12302-024-00873-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s12302-024-00873-1", "name": "item", "description": "10.1186/s12302-024-00873-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s12302-024-00873-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-11T00:00:00Z"}}, {"id": "10.25674/so91201", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:52Z", "type": "Journal Article", "title": "Testing soil nematode extraction efficiency using different variations of the Baermann-funnel method", "description": "soil organisms | comparability | reproducibility | extraction methods", "keywords": ["extraction methods", "QL1-991", "comparability", "Biodiversity", "soil organisms", "15. Life on land", "reproducibility", "Microbiology", "Zoology", "QR1-502", "Taxonomy"]}, "links": [{"href": "https://doi.org/10.25674/so91201"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20organisms", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.25674/so91201", "name": "item", "description": "10.25674/so91201", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.25674/so91201"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.26434/chemrxiv-2022-cr5ws-v2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:53Z", "type": "Journal Article", "created": "2023-04-10", "title": "Quantitative image analysis of microplastics in bottled water using Artificial Intelligence", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The ubiquitous occurrence of microplastics (MPs) in the environment and the use of plastics in packaging materials result in the presence of MPs in the food chain and the exposure of consumers. Yet, no fully validated analytical method is available for microplastic (MP) quantification, thereby preventing the reliable estimation of the level of exposure and, ultimately, the assessment of the food safety risks associated with MP contamination. In this study, a novel approach is presented that exploits interactive artificial intelligence tools to enable the automation of MP analysis. An integrated method for the analysis of MPs in bottled water based on Nile Red staining and fluorescent microscopy was developed and validated, featuring a partial interrogation of the filter and a fully automated image processing workflow based on a Random Forest classifier, thereby boosting the analysis speed. The image analysis provided particle count, size and size distribution of the MPs. From these data, a rough estimation of the mass of the individual MPs, and consequently of the MP mass concentration in the sample, could be obtained as well. Critical materials, method performance characteristics, and final applicability were studied in detail. The method showed to be highly sensitive in sizing MPs down to 10 \u00b5m, with a particle count limit of detection and quantification of 28 and 85 items/500 mL, respectively. Linearity of mass concentration determined between 10 ppb and 1.5 ppm showed a regression coefficient of (R2) of 0.99. Method precision was demonstrated by repeatability of 9 - 16% RSD (n = 7) and within-laboratory reproducibility of 15 - 27 % RSD (n = 21). Accuracy based on recovery was 92 \u00b1 15 % and 98 \u00b1 23 % at a level of 0.1 and 1.0 ppm, respectively. The quantitative performance characteristics thus obtained complied with regulatory requirements. Finally, the method was successfully applied to the analysis of twenty commercial samples of bottled water, with and without gas and flavor additives, yielding results ranging from values below the limit of detection to 7237 (95% CI [6456, 8088]) items/500 mL.</p></article>", "keywords": ["Fluorescence microscopy", "Artificial intelligence", "Bottled water", "Method validation", "Artificial Intelligence", "Microplastics", "Drinking Water", "Microplastic", "Nile red", "Reproducibility of Results", "Plastics", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.26434/chemrxiv-2022-cr5ws-v2"}, {"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": "10.26434/chemrxiv-2022-cr5ws-v2", "name": "item", "description": "10.26434/chemrxiv-2022-cr5ws-v2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.26434/chemrxiv-2022-cr5ws-v2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-04-10T00:00:00Z"}}, {"id": "10.3389/fsufs.2024.1410205", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:59Z", "type": "Journal Article", "created": "2024-08-26", "title": "Building a solid foundation: advancing evidence synthesis in agri-food systems science", "description": "<p>Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (&amp;gt;50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.</p", "keywords": ["Agricultura--Aspectes econ\u00f2mics", "bias", "330", "systematic reviews", "610", "Ressenyes sistem\u00e0tiques (Investigaci\u00f3 m\u00e8dica)", "01 natural sciences", "Food processing and manufacture", "12. Responsible consumption", "03 medical and health sciences", "0302 clinical medicine", "Blas", "TX341-641", "Agri-food systems", "reproducibility", "0105 earth and related environmental sciences", "Agriculture--Economic aspects", "2. Zero hunger", "Nutrition. Foods and food supply", "Sustainable agriculture", "agri-food systems", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria", "evidence synthesis", "Agriculture", "Systematic reviews", "TP368-456", "Nutrition--Environmental aspects", "Reproducibility", "sustainable agriculture", "Evidence synthesis", "Evidence syntheses"], "contacts": [{"organization": "Pierre Ellssel, Georg K\u00fcstner, Magdalena Kaczorowska-Dolowy, Eduardo V\u00e1zquez, Claudia Di Bene, Honghong Li, Honghong Li, Diego Brizuela-Torres, Diego Brizuela-Torres, Elansurya Elangovan Vennila, Jos\u00e9 Luis Vicente-Vicente, Jos\u00e9 Luis Vicente-Vicente, Daniel Itzamna Avila-Ortega, Daniel Itzamna Avila-Ortega,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3389/fsufs.2024.1410205"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Sustainable%20Food%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fsufs.2024.1410205", "name": "item", "description": "10.3389/fsufs.2024.1410205", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fsufs.2024.1410205"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-26T00:00:00Z"}}, {"id": "10.3390/s20154127", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:12Z", "type": "Journal Article", "created": "2020-07-24", "title": "Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world\u2019s growing population while limiting environmental pollution. The aim of this paper is to describe a multi-sensor Internet of Things (IoT) system for agriculture consisting of a soil probe, an air probe and a smart data logger. The implementation details will focus of the integration element and the innovative Artificial Intelligence based gas identification sensor. Furthermore, the paper focuses on the analytics and decision support system implementation that provides farming recommendations and is enhanced with a feedback loop from farmers and a social trust index that will increase the reliability of the system.</p></article>", "keywords": ["330", "decision support system", "[SPI] Engineering Sciences [physics]", "Social IoT", "Internet of Things", "TP1-1185", "01 natural sciences", "7. Clean energy", "630", "data logger", "Article", "gas sensor", "[SPI]Engineering Sciences [physics]", "Soil", "sensor", "Artificial Intelligence", "social feedback", "data analytics", "agriculture", "2. Zero hunger", "Chemical technology", "Reproducibility of Results", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "0104 chemical sciences", "3. Good health", "13. Climate action", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://doi.org/10.3390/s20154127"}, {"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": "10.3390/s20154127", "name": "item", "description": "10.3390/s20154127", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/s20154127"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-24T00:00:00Z"}}, {"id": "10.5194/bg-19-3505-2022", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:36Z", "type": "Journal Article", "created": "2022-07-28", "title": "Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. In the age of big data, soil data are more available and richer than ever, but \u2013 outside of a few large soil survey resources \u2013 they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.                     </p></article>", "keywords": ["FOS: Computer and information sciences", "0301 basic medicine", "Data Sharing", "Information Systems and Management", "literature review", "1904 Earth-Surface Processes", "Social Sciences", "data set", "01 natural sciences", "Decision Sciences", "Data science", "Life", "QH501-531", "910 Geography & travel", "soil analysis", "database", "QH540-549.5", "2. Zero hunger", "QE1-996.5", "000", "Ecology", "communication", "Physics", "Earth", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "World Wide Web", "10122 Institute of Geography", "soil survey", "Physical Sciences", "Data Reuse", "environment", "Information Systems", "Evolution", "future prospect", "Data management", "Data Sharing and Stewardship in Science", "Database", "Big data", "03 medical and health sciences", "Behavior and Systematics", "Data mining", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Management and Reproducibility of Scientific Workflows", "Metadata", "Data curation", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Acoustics", "15. Life on land", "Computer science", "1105 Ecology", " Evolution", " Behavior and Systematics", "Surface Processes", "Harmonization", "FOS: Biological sciences", "Computer Science", "Environmental Science", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "soil management", "Research Data", "Environmental DNA in Biodiversity Monitoring"]}, "links": [{"href": "https://doi.org/10.5194/bg-19-3505-2022"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-19-3505-2022", "name": "item", "description": "10.5194/bg-19-3505-2022", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-19-3505-2022"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-28T00:00:00Z"}}, {"id": "10261/375649", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:44Z", "type": "Journal Article", "created": "2024-08-26", "title": "Building a solid foundation: advancing evidence synthesis in agri-food systems science", "description": "<p>Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (&amp;gt;50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.</p", "keywords": ["Agricultura--Aspectes econ\u00f2mics", "bias", "330", "systematic reviews", "610", "Ressenyes sistem\u00e0tiques (Investigaci\u00f3 m\u00e8dica)", "01 natural sciences", "Food processing and manufacture", "12. Responsible consumption", "03 medical and health sciences", "0302 clinical medicine", "Blas", "TX341-641", "Agri-food systems", "reproducibility", "0105 earth and related environmental sciences", "Agriculture--Economic aspects", "2. Zero hunger", "Nutrition. Foods and food supply", "agri-food systems", "Sustainable agriculture", "evidence synthesis", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria", "Agriculture", "Systematic reviews", "TP368-456", "Nutrition--Environmental aspects", "Reproducibility", "sustainable agriculture", "Evidence synthesis", "Evidence syntheses"]}, "links": [{"href": "https://doi.org/10261/375649"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Sustainable%20Food%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/375649", "name": "item", "description": "10261/375649", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/375649"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-26T00:00:00Z"}}, {"id": "10261/295770", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:42Z", "type": "Journal Article", "created": "2022-10-05", "title": "Metabarcoding for biodiversity inventory blind spots: A test case using the beetle fauna of an insular cloud forest", "description": "Abstract<p>Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly \uffe2\uff80\uff9cdenoise\uffe2\uff80\uff9d and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.</p", "keywords": ["0301 basic medicine", "0303 health sciences", "Reproducibility of Results", "Biodiversity", "Forests", "15. Life on land", "Protect", " restore and promote sustainable use of terrestrial ecosystems", " sustainably manage forests", " combat\u00a0desertification", " and halt and reverse land degradation and halt biodiversity loss", "Coleoptera", "Soil", "03 medical and health sciences", "metabarcoding", "http://metadata.un.org/sdg/15", "Animals", "DNA Barcoding", " Taxonomic", "taxonomic inflation", "Arthropods", "Barcoding", "mesofauna"]}, "links": [{"href": "https://doi.org/10261/295770"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Molecular%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/295770", "name": "item", "description": "10261/295770", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/295770"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-24T00:00:00Z"}}, {"id": "11573/1419330", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:56Z", "type": "Journal Article", "created": "2020-06-05", "title": "Variability in pulmonary diffusing capacity in heart failure", "description": "As pulmonary diffusing capacity is related to mortality risk and prognosis in patients with heart failure (HF), it is measured frequently. As such, it would be essential to know the week-to-week variability (reproducibility) of pulmonary diffusing capacity for carbon monoxide (DLCO) and nitric oxide (DLNO). This variability would let clinicians understand what a clinically measurable change in DLCO and DLNO would be in these patients.On three different days spanning over ten weeks, 40\u2009H\u2009F patients underwent testing for DLCO and DLNO. DLCO was determined after a 4\u2009s and 10\u2009s breath-hold maneuver, while DLNO was determined after a 4\u2009s breath-hold maneuver.Forty heart failure patients (66\u2009\u00b1\u200910 years; BMI\u2009=\u200928.4\u2009\u00b1\u20094.6\u2009kg\u2219m-2; 28 males), that were referred to our clinic were able to complete the protocol. DLCO (4\u2009s breath-hold) and DLNO (4\u2009s breath-hold) were 79\u2009\u00b1\u200919 % and 59\u2009\u00b1\u200914 % predicted, respectively. Fifty percent of patients (n\u2009=\u200920) were below the lower limit of normal (LLN, below the 5th percentile) for predicted DLCO (4\u2009s), while 78 % of patients (n\u2009=\u200931) were below the LLN for predicted DLNO. All 16 patients that were below the LLN for DLCO were also below the LLN for DLNO. Over a ten week period, the reproducibility of DLNO (4\u2009s) DLCO (4\u2009s) and DLCO (10\u2009s) was 18.9, 8.2, and 5.9\u2009mL\u2009min\u2009mmHg-1, respectively.The week-to-week fluctuation in DLNO (4\u2009s), as a percentage, is less than DLCO (4\u2009s) in patients with HF. The reproducibility of DLNO in patients with HF is like that of healthy subjects.", "keywords": ["Male", "DLCO; DLNO; lung function; heart failure; reproducibility", "Physiology (science-metrix)", "Heart Disease (rcdc)", "Pulmonary Diffusing Capacity (mesh)", "3208 Medical physiology (for-2020)", "Heart failure", "Nitric Oxide", "Lung (rcdc)", "DLCO", "DLCO; DLNO; Heart failure; Lung function; Reproducibility;", "Clinical Research (rcdc)", "03 medical and health sciences", "0302 clinical medicine", "1102 Cardiorespiratory Medicine and Haematology (for)", "Middle Aged (mesh)", "Reproducibility of Results (mesh)", "Humans", "32 Biomedical and Clinical Sciences (for-2020)", "Male (mesh)", "3202 Clinical Sciences (for-2020)", "Carbon Monoxide (mesh)", "Aged", "DLNO", "Heart Failure", "Humans (mesh)", "Carbon Monoxide", "Cardiovascular (hrcs-hc)", "Aged (mesh)", "3201 Cardiovascular medicine and haematology (for-2020)", "Reproducibility of Results", "Heart Failure (mesh)", "Middle Aged", "1109 Neurosciences (for)", "Lung function", "Reproducibility", "3. Good health", "1116 Medical Physiology (for)", "4.2 Evaluation of markers and technologies (hrcs-rac)", "Female (mesh)", "Nitric Oxide (mesh)", "Pulmonary Diffusing Capacity", "Cardiovascular (rcdc)", "Female"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/743296/2/agostoni%203.pdf"}, {"href": "https://doi.org/11573/1419330"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Respiratory%20Physiology%20%26amp%3B%20Neurobiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11573/1419330", "name": "item", "description": "11573/1419330", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11573/1419330"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-01T00:00:00Z"}}, {"id": "20.500.11850/562259", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:14Z", "type": "Journal Article", "created": "2022-07-28", "title": "Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. In the age of big data, soil data are more available and richer than ever, but \u2013 outside of a few large soil survey resources \u2013 they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.</p></article>", "keywords": ["FOS: Computer and information sciences", "0301 basic medicine", "Data Sharing", "Information Systems and Management", "literature review", "1904 Earth-Surface Processes", "Social Sciences", "data set", "01 natural sciences", "Decision Sciences", "Data science", "Life", "QH501-531", "910 Geography & travel", "soil analysis", "database", "QH540-549.5", "2. Zero hunger", "QE1-996.5", "000", "Ecology", "communication", "Physics", "Earth", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "World Wide Web", "10122 Institute of Geography", "soil survey", "Physical Sciences", "Data Reuse", "environment", "Information Systems", "Evolution", "future prospect", "Data management", "Data Sharing and Stewardship in Science", "Database", "Big data", "03 medical and health sciences", "Behavior and Systematics", "Data mining", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Management and Reproducibility of Scientific Workflows", "Metadata", "Data curation", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "Acoustics", "15. Life on land", "Computer science", "1105 Ecology", " Evolution", " Behavior and Systematics", "Surface Processes", "Harmonization", "FOS: Biological sciences", "Computer Science", "Environmental Science", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "soil management", "Research Data", "Environmental DNA in Biodiversity Monitoring"]}, "links": [{"href": "https://doi.org/20.500.11850/562259"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/562259", "name": "item", "description": "20.500.11850/562259", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/562259"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-28T00:00:00Z"}}, {"id": "20.500.14243/523367", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:17Z", "type": "Journal Article", "created": "2022-09-23", "title": "Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Light scatterometry combined with chemometrics can be a practical approach for the analysis of size and concentration of microplastics in water.</p></article>", "keywords": ["Polyethylene", "PARTICLE-SIZE DISTRIBUTIONIDENTIFICATIONRELEASEFOOD", "Microplastics", "PARTICLE-SIZE DISTRIBUTION", " IDENTIFICATION", " RELEASE", " FOOD", "Polymethyl Methacrylate", "Polystyrenes", "Reproducibility of Results", "Water", "Chemometrics", "Plastics", "6. Clean water"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/523367/1/Batch%20analysis%20of%20microplastics%20using%20multi-angle%20static%20light%20scattering%20and%20chemometric%20methods.pdf"}, {"href": "https://biblio.vub.ac.be/vubirfiles/97942982/88500032.pdf"}, {"href": "http://pubs.rsc.org/en/content/articlepdf/2022/AY/D2AY01215D"}, {"href": "https://doi.org/20.500.14243/523367"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytical%20Methods", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14243/523367", "name": "item", "description": "20.500.14243/523367", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14243/523367"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "20.500.14017/fd1879c3-ab01-40b3-a4f5-12da309de638", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:16Z", "type": "Journal Article", "created": "2022-09-23", "title": "Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Light scatterometry combined with chemometrics can be a practical approach for the analysis of size and concentration of microplastics in water.</p></article>", "keywords": ["Polyethylene", "PARTICLE-SIZE DISTRIBUTIONIDENTIFICATIONRELEASEFOOD", "Microplastics", "PARTICLE-SIZE DISTRIBUTION", " IDENTIFICATION", " RELEASE", " FOOD", "Polymethyl Methacrylate", "Polystyrenes", "Reproducibility of Results", "Water", "Chemometrics", "Plastics", "6. Clean water"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/523367/1/Batch%20analysis%20of%20microplastics%20using%20multi-angle%20static%20light%20scattering%20and%20chemometric%20methods.pdf"}, {"href": "http://pubs.rsc.org/en/content/articlepdf/2022/AY/D2AY01215D"}, {"href": "https://doi.org/20.500.14017/fd1879c3-ab01-40b3-a4f5-12da309de638"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytical%20Methods", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14017/fd1879c3-ab01-40b3-a4f5-12da309de638", "name": "item", "description": "20.500.14017/fd1879c3-ab01-40b3-a4f5-12da309de638", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14017/fd1879c3-ab01-40b3-a4f5-12da309de638"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "3215851315", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:54Z", "type": "Journal Article", "created": "2021-11-30", "title": "Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections", "description": "Abstract<p>Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses. This paper investigates Near-infrared (NIR) hyperspectral imaging (1000\uffe2\uff80\uff931700\uffc2\uffa0nm) and machine learning to build models to automatically predict the susceptibility of sepals of recently harvested tomatoes to future fungal infections. Hyperspectral images of newly harvested tomatoes (cultivar Brioso) from 5 different growers were acquired before the onset of any visible fungal infection. After imaging, the tomatoes were placed under controlled conditions suited for fungal germination and growth for a 4-day period, and then imaged using normal color cameras. All sepals in the color images were ranked for fungal severity using crowdsourcing, and the final severity of each sepal was fused using principal component analysis. A novel hyperspectral data processing pipeline is presented which was used to automatically segment the tomato sepals from spectral images with multiple tomatoes connected via a truss. The key modelling question addressed in this research is whether there is a correlation between the hyperspectral data captured at harvest and the fungal infection observed 4 days later. Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. The best model found a Pearson correlation of 0.837, showing that there is strong linear correlation between the NIR spectra and the future fungal severity of the sepal. The sepal specific predictions were aggregated to predict the susceptibility of individual tomatoes, and a correlation of 0.92 was found. Besides modelling, focus is also on model interpretation, particularly to understand which spectral features are most relevant to model prediction. Two approaches to model interpretation were explored, feature importance and SHAP (SHapley Additive exPlanations), resulting in similar conclusions that the NIR range between 1390\uffe2\uff80\uff931420\uffc2\uffa0nm contributes most to the model\uffe2\uff80\uff99s final decision.</p", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "0301 basic medicine", "Principal Component Analysis", "0303 health sciences", "Spectroscopy", " Near-Infrared", "Science", "Q", "R", "Reproducibility of Results", "Microbiology", "Article", "Pattern Recognition", " Automated", "Machine Learning", "03 medical and health sciences", "Deep Learning", "Solanum lycopersicum", "Fruit", "Calibration", "Life Science", "Medicine", "Algorithms", "Software", "Plant Diseases"]}, "links": [{"href": "https://www.nature.com/articles/s41598-021-02302-2.pdf"}, {"href": "https://doi.org/3215851315"}, {"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": "3215851315", "name": "item", "description": "3215851315", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3215851315"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "2117/421452", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:22Z", "type": "Journal Article", "created": "2024-08-26", "title": "Building a solid foundation: advancing evidence synthesis in agri-food systems science", "description": "<p>Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (&amp;gt;50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.</p", "keywords": ["Agriculture--Economic aspects", "Agricultura--Aspectes econ\u00f2mics", "2. Zero hunger", "bias", "330", "Nutrition. Foods and food supply", "agri-food systems", "systematic reviews", "610", "evidence synthesis", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria agroaliment\u00e0ria", "TP368-456", "Nutrition--Environmental aspects", "Ressenyes sistem\u00e0tiques (Investigaci\u00f3 m\u00e8dica)", "01 natural sciences", "Food processing and manufacture", "12. Responsible consumption", "sustainable agriculture", "03 medical and health sciences", "0302 clinical medicine", "Evidence syntheses", "TX341-641", "ddc:570", "reproducibility", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/2117/421452"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Sustainable%20Food%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2117/421452", "name": "item", "description": "2117/421452", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2117/421452"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-26T00:00:00Z"}}, {"id": "2535425885", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:29Z", "type": "Journal Article", "created": "2016-10-19", "title": "Prediction of alkaline earth elements in bone remains by near infrared spectroscopy", "description": "An innovative methodological approach has been developed for the prediction of the mineral element composition of bone remains. It is based on the use of Fourier Transform Near Infrared (FT-NIR) diffuse reflectance measurements. The method permits a fast, cheap and green analytical way, to understand post-mortem degradation of bones caused by the environment conditions on different skeletal parts and to select the best preserved bone samples. Samples, from the Late Roman Necropolis of Virgen de la Misericordia street and En Gil street located in Valencia (Spain), were employed to test the proposed approach being determined calcium, magnesium and strontium in bone remains and sediments. Coefficients of determination obtained between predicted values and reference ones for Ca, Mg and Sr were 90.4, 97.3 and 97.4, with residual predictive deviation of 3.2, 5.3 and 2.3, respectively, and relative root mean square error of prediction between 10% and 37%. Results obtained evidenced that NIR spectra combined with statistical analysis can help to predict bone mineral profiles suitable to evaluate bone diagenesis.", "keywords": ["Spectroscopy", " Near-Infrared", "Fossils", "Reproducibility of Results", "06 humanities and the arts", "01 natural sciences", "Bone and Bones", "Spain", "Strontium", "Metals", " Alkaline Earth", "Spectroscopy", " Fourier Transform Infrared", "Humans", "Calcium", "Magnesium", "0601 history and archaeology", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/110415/1/TAL_R1.pdf"}, {"href": "https://doi.org/2535425885"}, {"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": "2535425885", "name": "item", "description": "2535425885", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2535425885"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "27837852", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:31Z", "type": "Journal Article", "created": "2016-10-19", "title": "Prediction of alkaline earth elements in bone remains by near infrared spectroscopy", "description": "An innovative methodological approach has been developed for the prediction of the mineral element composition of bone remains. It is based on the use of Fourier Transform Near Infrared (FT-NIR) diffuse reflectance measurements. The method permits a fast, cheap and green analytical way, to understand post-mortem degradation of bones caused by the environment conditions on different skeletal parts and to select the best preserved bone samples. Samples, from the Late Roman Necropolis of Virgen de la Misericordia street and En Gil street located in Valencia (Spain), were employed to test the proposed approach being determined calcium, magnesium and strontium in bone remains and sediments. Coefficients of determination obtained between predicted values and reference ones for Ca, Mg and Sr were 90.4, 97.3 and 97.4, with residual predictive deviation of 3.2, 5.3 and 2.3, respectively, and relative root mean square error of prediction between 10% and 37%. Results obtained evidenced that NIR spectra combined with statistical analysis can help to predict bone mineral profiles suitable to evaluate bone diagenesis.", "keywords": ["Spectroscopy", " Near-Infrared", "Fossils", "Reproducibility of Results", "06 humanities and the arts", "01 natural sciences", "Bone and Bones", "Spain", "Strontium", "Metals", " Alkaline Earth", "Spectroscopy", " Fourier Transform Infrared", "Humans", "Calcium", "Magnesium", "0601 history and archaeology", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/110415/1/TAL_R1.pdf"}, {"href": "https://doi.org/27837852"}, {"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": "27837852", "name": "item", "description": "27837852", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/27837852"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "2805867715", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:32Z", "type": "Journal Article", "created": "2018-05-29", "title": "Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces", "description": "Abstract<p>A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.</p", "keywords": ["Science", "Circular Dichroism", "Q", "Lipid Bilayers", "Membrane Proteins", "Reproducibility of Results", "Biosensing Techniques", "02 engineering and technology", "01 natural sciences", "Article", "0104 chemical sciences", "Membrane Lipids", "Spectroscopy", " Fourier Transform Infrared", "Peptides", "0210 nano-technology", "Protein Binding"]}, "links": [{"href": "https://eprints.gla.ac.uk/164038/1/164038.pdf"}, {"href": "https://www.nature.com/articles/s41467-018-04594-x.pdf"}, {"href": "https://doi.org/2805867715"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Communications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2805867715", "name": "item", "description": "2805867715", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2805867715"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-04T00:00:00Z"}}, {"id": "3044974791", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:44Z", "type": "Journal Article", "created": "2020-07-24", "title": "Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world\u2019s growing population while limiting environmental pollution. The aim of this paper is to describe a multi-sensor Internet of Things (IoT) system for agriculture consisting of a soil probe, an air probe and a smart data logger. The implementation details will focus of the integration element and the innovative Artificial Intelligence based gas identification sensor. Furthermore, the paper focuses on the analytics and decision support system implementation that provides farming recommendations and is enhanced with a feedback loop from farmers and a social trust index that will increase the reliability of the system.</p></article>", "keywords": ["330", "decision support system", "[SPI] Engineering Sciences [physics]", "Social IoT", "Internet of Things", "TP1-1185", "01 natural sciences", "7. Clean energy", "630", "data logger", "Article", "gas sensor", "[SPI]Engineering Sciences [physics]", "Soil", "sensor", "Artificial Intelligence", "social feedback", "data analytics", "agriculture", "2. Zero hunger", "Chemical technology", "Reproducibility of Results", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "0104 chemical sciences", "3. Good health", "13. Climate action", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://doi.org/3044974791"}, {"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": "3044974791", "name": "item", "description": "3044974791", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3044974791"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-24T00:00:00Z"}}, {"id": "3161788824", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:49Z", "type": "Journal Article", "created": "2021-05-19", "title": "An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry", "description": "<strong>Abstract</strong> The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultra-high resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform <em>via</em> manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from world-wide locations. The method detected &gt;9,600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, pharmaceuticals,<em> </em>among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions, whilst significantly increasing throughput.", "keywords": ["13. Climate action", "1600", "2304", "Reproducibility of Results", "Pesticides", "01 natural sciences", "Chromatography", " High Pressure Liquid", "Mass Spectrometry", "Water Pollutants", " Chemical", "Chromatography", " Liquid", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.bournemouth.ac.uk/36790/1/An%20Automated%20Methodology%20for%20Non-targeted%20Compositional%20Analysis%20of%20Small%20Molecules%20in%20High%20Complexity%20Environmental%20Matrice.pdf"}, {"href": "https://eprints.whiterose.ac.uk/174399/1/acs.est.0c08208.pdf"}, {"href": "https://doi.org/3161788824"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3161788824", "name": "item", "description": "3161788824", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3161788824"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-18T00:00:00Z"}}, {"id": "37709429", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:23:01Z", "type": "Journal Article", "created": "2023-08-15", "title": "Surveying the mugineic acid family: Ion mobility \u2013 quadrupole time-of-flight mass spectrometry (IM-QTOFMS) characterization and tandem mass spectrometry (LC-ESI-MS/MS) quantification of all eight naturally occurring phytosiderophores", "description": "Phytosiderophores (PS) are root exudates released by grass species (Poaceae) that play a pivotal role in iron (Fe) plant nutrition. A direct determination of PS in biological samples is of paramount importance in understanding micronutrient acquisition mediated by PS. To date, eight plant-born PS have been identified; however, no analytical procedure is currently available to quantify all eight PS simultaneously with high analytical confidence. With access to the full set of PS standards for the first time, we report comprehensive methods to both fully characterize (IM-QTOFMS) and quantify (LC-ESI-MS/MS) all eight naturally occurring PS belonging to the mugineic acid family. The quantitative method was fully validated, yielding linear results for all eight analytes, and no unwanted interferences with soil and plant matrices were observed. LOD and LOQ values determined for each PS were below 11 and 35\u00a0nmol\u00a0L-1, respectively. The method's precision under reproducibility conditions (intra- and inter-day) of measurement was less than 2.5% RSD for all analytes. Additionally, all PS were annotated with high-resolution mass spectrometric fragment spectra and further characterized via drift tube ion mobility-mass spectrometry. The collision cross-sections obtained for primary ion species yielded a valuable database for future research focused on in-depth PS studies. The new quantitative method was applied to analyse root exudates from Fe-controlled and deficient barley, oat, rye, and sorghum plants. All eight PS, including mugineic acid (MA), 3'-hydroxymugineic acid (HMA), 3'-epi-hydroxymugineic acid (epi-HMA), hydroxyavenic acid (HAVA), deoxymugineic acid (DMA), 3'-hydroxydeoxymugineic acid (HDMA), 3'-epi-hydroxydeoxymugineic acid (epi-HDMA) and avenic acid (AVA) were for the first time successfully identified and quantified in root exudates of various graminaceous plants using a single analytical procedure. These newly developed methods can be applied to studies aimed at improving crop yield and micronutrient grain content for food consumption via plant-based biofortification.", "keywords": ["Tandem Mass Spectrometry", "Reproducibility of Results", "Micronutrients", "Poaceae", "Edible Grain"]}, "links": [{"href": "https://doi.org/37709429"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Analytica%20Chimica%20Acta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "37709429", "name": "item", "description": "37709429", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/37709429"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-10-01T00:00:00Z"}}, {"id": "36197789", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:59Z", "type": "Journal Article", "created": "2022-10-05", "title": "Metabarcoding for biodiversity inventory blind spots: A test case using the beetle fauna of an insular cloud forest", "description": "Abstract<p>Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly \uffe2\uff80\uff9cdenoise\uffe2\uff80\uff9d and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.</p", "keywords": ["Coleoptera", "0301 basic medicine", "Soil", "0303 health sciences", "03 medical and health sciences", "Animals", "Reproducibility of Results", "DNA Barcoding", " Taxonomic", "Biodiversity", "Forests", "15. Life on land", "Arthropods"]}, "links": [{"href": "https://doi.org/36197789"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Molecular%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "36197789", "name": "item", "description": "36197789", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/36197789"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-24T00:00:00Z"}}, {"id": "37487270", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:23:01Z", "type": "Journal Article", "created": "2023-04-10", "title": "Quantitative image analysis of microplastics in bottled water using Artificial Intelligence", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The ubiquitous occurrence of microplastics (MPs) in the environment and the use of plastics in packaging materials result in the presence of MPs in the food chain and the exposure of consumers. Yet, no fully validated analytical method is available for microplastic (MP) quantification, thereby preventing the reliable estimation of the level of exposure and, ultimately, the assessment of the food safety risks associated with MP contamination. In this study, a novel approach is presented that exploits interactive artificial intelligence tools to enable the automation of MP analysis. An integrated method for the analysis of MPs in bottled water based on Nile Red staining and fluorescent microscopy was developed and validated, featuring a partial interrogation of the filter and a fully automated image processing workflow based on a Random Forest classifier, thereby boosting the analysis speed. The image analysis provided particle count, size and size distribution of the MPs. From these data, a rough estimation of the mass of the individual MPs, and consequently of the MP mass concentration in the sample, could be obtained as well. Critical materials, method performance characteristics, and final applicability were studied in detail. The method showed to be highly sensitive in sizing MPs down to 10 \u00b5m, with a particle count limit of detection and quantification of 28 and 85 items/500 mL, respectively. Linearity of mass concentration determined between 10 ppb and 1.5 ppm showed a regression coefficient of (R2) of 0.99. Method precision was demonstrated by repeatability of 9 - 16% RSD (n = 7) and within-laboratory reproducibility of 15 - 27 % RSD (n = 21). Accuracy based on recovery was 92 \u00b1 15 % and 98 \u00b1 23 % at a level of 0.1 and 1.0 ppm, respectively. The quantitative performance characteristics thus obtained complied with regulatory requirements. Finally, the method was successfully applied to the analysis of twenty commercial samples of bottled water, with and without gas and flavor additives, yielding results ranging from values below the limit of detection to 7237 (95% CI [6456, 8088]) items/500 mL.</p></article>", "keywords": ["Fluorescence microscopy", "Artificial intelligence", "Bottled water", "Method validation", "Artificial Intelligence", "Microplastics", "Drinking Water", "Microplastic", "Nile red", "Reproducibility of Results", "Plastics", "6. Clean water"]}, "links": [{"href": "https://doi.org/37487270"}, {"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": "37487270", "name": "item", "description": "37487270", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/37487270"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-04-10T00:00:00Z"}}, {"id": "37499875", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:23:01Z", "type": "Journal Article", "created": "2023-07-25", "title": "Fast and reliable method to estimate global DNA methylation in plants and fungi with high-pressure liquid chromatography (HPLC)-ultraviolet detection and even more sensitive one with HPLC-mass spectrometry", "description": "DNA (Deoxyribonucleic acid) methylation is one of the epigenetic modifications of DNA, acting as a bridge between genotype and phenotype. Thus, disruption of DNA methylation pattern has tremendous consequences for organism development. Current methods to determine DNA methylation suffer from methodological drawbacks like high requirement of DNA and poor reproducibility of chromatograms. Here we provide a fast and reliable method using high-pressure liquid chromatography (HPLC)-ultraviolet (UV) detector and even more sensitive one with HPLC- mass spectrometry (MS) and we test this method with various plant and fungal DNA isolates. We optimized the preparation of the DNA degradation step to decrease background noise, we improved separation conditions to provide reliable and reproducible chromatograms and conditions to measure nucleotides in HPLC-MS. We showed that global DNA methylation level can be accurately and reproducibly measured with as little as 0.2\u00a0\u00b5M for HPLC-UV and 0.02\u00a0\u00b5M for HPLC-MS of methylated cytosine.", "keywords": ["Plant DNA", "DNA methylation", "ta1183", "ta1182", "Fungi", "610", "Reproducibility of Results", "DNA Methylation", "Mass Spectrometry", "Fungal DNA", "chromatography", "DNA", " Fungal", "ta116", "Chromatography", " High Pressure Liquid"]}, "links": [{"href": "https://doi.org/37499875"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Biotechnology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "37499875", "name": "item", "description": "37499875", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/37499875"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-09-01T00:00:00Z"}}, {"id": "PMC4698961", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:21Z", "type": "Journal Article", "created": "2015-06-14", "title": "Validation of the Written Administration of the Short Literacy Survey", "description": "Most health literacy assessments are time consuming and administered verbally. Written self-administration of measures may facilitate more widespread assessment of health literacy. This study aimed to determine the intermethod reliability and concurrent validity of the written administration of the 3 subjective health literacy questions of the Short Literacy Survey (SLS). The Rapid Estimate of Adult Literacy in Medicine (REALM) and the shortened test of Functional Health Literacy in Adults (S-TOFHLA) were the reference measures of health literacy. Two hundred ninety-nine participants completed the written and verbal administrations of the SLS from June to December 2012. Intermethod reliability was demonstrated when (a) the written and verbal SLS score did not differ and (b) written and verbal scores were highly correlated. The written items were internally consistent (Cronbach's \u03b1\u00a0=\u00a0.733). The written total score successfully identified persons with sixth-grade equivalency or less for literacy on the REALM (AUROC\u00a0=\u00a00.753) and inadequate literacy on the S-TOFHLA (AUROC\u00a0=\u00a00. 869). The written administration of the SLS is reliable, valid, and is effective in identifying persons with limited health literacy.", "keywords": ["Adult", "Male", "Writing", "4. Education", "Reproducibility of Results", "Middle Aged", "Health Literacy", "3. Good health", "03 medical and health sciences", "0302 clinical medicine", "Surveys and Questionnaires", "Humans", "Female", "0305 other medical science", "Aged"]}, "links": [{"href": "https://doi.org/PMC4698961"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Health%20Communication", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC4698961", "name": "item", "description": "PMC4698961", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC4698961"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-06-14T00:00:00Z"}}, {"id": "PMC5986821", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:22Z", "type": "Journal Article", "created": "2018-05-29", "title": "Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces", "description": "Abstract<p>A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.</p", "keywords": ["Science", "Circular Dichroism", "Q", "Lipid Bilayers", "Membrane Proteins", "Reproducibility of Results", "Biosensing Techniques", "02 engineering and technology", "01 natural sciences", "Article", "0104 chemical sciences", "Membrane Lipids", "Spectroscopy", " Fourier Transform Infrared", "Peptides", "0210 nano-technology", "Protein Binding"]}, "links": [{"href": "https://eprints.gla.ac.uk/164038/1/164038.pdf"}, {"href": "https://www.nature.com/articles/s41467-018-04594-x.pdf"}, {"href": "https://doi.org/PMC5986821"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Communications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC5986821", "name": "item", "description": "PMC5986821", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC5986821"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-04T00:00:00Z"}}, {"id": "PMC7436003", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:23Z", "type": "Journal Article", "created": "2020-07-24", "title": "Smart Multi-Sensor Platform for Analytics and Social Decision Support in Agriculture", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world\u2019s growing population while limiting environmental pollution. The aim of this paper is to describe a multi-sensor Internet of Things (IoT) system for agriculture consisting of a soil probe, an air probe and a smart data logger. The implementation details will focus of the integration element and the innovative Artificial Intelligence based gas identification sensor. Furthermore, the paper focuses on the analytics and decision support system implementation that provides farming recommendations and is enhanced with a feedback loop from farmers and a social trust index that will increase the reliability of the system.</p></article>", "keywords": ["330", "decision support system", "[SPI] Engineering Sciences [physics]", "Social IoT", "Internet of Things", "TP1-1185", "01 natural sciences", "7. Clean energy", "630", "data logger", "Article", "gas sensor", "[SPI]Engineering Sciences [physics]", "Soil", "sensor", "Artificial Intelligence", "social feedback", "data analytics", "agriculture", "2. Zero hunger", "Chemical technology", "Reproducibility of Results", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "0104 chemical sciences", "3. Good health", "13. Climate action", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://www.mdpi.com/1424-8220/20/15/4127/pdf"}, {"href": "https://doi.org/PMC7436003"}, {"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": "PMC7436003", "name": "item", "description": "PMC7436003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC7436003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-24T00:00:00Z"}}, {"id": "PMC8277131", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:24Z", "type": "Journal Article", "created": "2021-05-19", "title": "An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry", "description": "<strong>Abstract</strong> The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultra-high resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform <em>via</em> manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from world-wide locations. The method detected &gt;9,600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, pharmaceuticals,<em> </em>among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions, whilst significantly increasing throughput.", "keywords": ["ultrahigh-resolution mass spectrometry", "Compound Discoverer", "1600", "2304", "Reproducibility of Results", "non-targeted analysis", "01 natural sciences", "Mass Spectrometry", "13. Climate action", "Pesticides", "liquid chromatography\u2212mass spectrometry", "Chromatography", " High Pressure Liquid", "Water Pollutants", " Chemical", "Chromatography", " Liquid", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.bournemouth.ac.uk/36790/1/An%20Automated%20Methodology%20for%20Non-targeted%20Compositional%20Analysis%20of%20Small%20Molecules%20in%20High%20Complexity%20Environmental%20Matrice.pdf"}, {"href": "https://eprints.whiterose.ac.uk/174399/1/acs.est.0c08208.pdf"}, {"href": "https://doi.org/PMC8277131"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "PMC8277131", "name": "item", "description": "PMC8277131", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC8277131"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-18T00:00:00Z"}}, {"id": "PMC8633320", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:24Z", "type": "Journal Article", "created": "2021-11-30", "title": "Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections", "description": "Abstract<p>Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses. This paper investigates Near-infrared (NIR) hyperspectral imaging (1000\uffe2\uff80\uff931700\uffc2\uffa0nm) and machine learning to build models to automatically predict the susceptibility of sepals of recently harvested tomatoes to future fungal infections. Hyperspectral images of newly harvested tomatoes (cultivar Brioso) from 5 different growers were acquired before the onset of any visible fungal infection. After imaging, the tomatoes were placed under controlled conditions suited for fungal germination and growth for a 4-day period, and then imaged using normal color cameras. All sepals in the color images were ranked for fungal severity using crowdsourcing, and the final severity of each sepal was fused using principal component analysis. A novel hyperspectral data processing pipeline is presented which was used to automatically segment the tomato sepals from spectral images with multiple tomatoes connected via a truss. The key modelling question addressed in this research is whether there is a correlation between the hyperspectral data captured at harvest and the fungal infection observed 4 days later. Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. The best model found a Pearson correlation of 0.837, showing that there is strong linear correlation between the NIR spectra and the future fungal severity of the sepal. The sepal specific predictions were aggregated to predict the susceptibility of individual tomatoes, and a correlation of 0.92 was found. Besides modelling, focus is also on model interpretation, particularly to understand which spectral features are most relevant to model prediction. Two approaches to model interpretation were explored, feature importance and SHAP (SHapley Additive exPlanations), resulting in similar conclusions that the NIR range between 1390\uffe2\uff80\uff931420\uffc2\uffa0nm contributes most to the model\uffe2\uff80\uff99s final decision.</p", "keywords": ["Crops", " Agricultural", "0301 basic medicine", "2. Zero hunger", "Principal Component Analysis", "0303 health sciences", "Spectroscopy", " Near-Infrared", "Science", "Q", "R", "Reproducibility of Results", "Microbiology", "Article", "Pattern Recognition", " Automated", "Machine Learning", "03 medical and health sciences", "Deep Learning", "Solanum lycopersicum", "Fruit", "Calibration", "Life Science", "Medicine", "Algorithms", "Software", "Plant Diseases"]}, "links": [{"href": "https://www.nature.com/articles/s41598-021-02302-2.pdf"}, {"href": "https://doi.org/PMC8633320"}, {"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": "PMC8633320", "name": "item", "description": "PMC8633320", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC8633320"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "PMC9637219", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:24:26Z", "type": "Journal Article", "created": "2022-11-05", "title": "Optical photothermal infrared spectroscopy with simultaneously acquired Raman spectroscopy for two-dimensional microplastic identification", "description": "Abstract                   <p>In recent years, vibrational spectroscopic techniques based on Fourier transform infrared (FTIR) or Raman microspectroscopy have been suggested to fulfill the unmet need for microplastic particle detection and identification. Inter-system comparison of spectra from reference polymers enables assessing the reproducibility between instruments and advantages of emerging quantum cascade laser-based optical photothermal infrared (O-PTIR) spectroscopy. In our work, IR and Raman spectra of nine plastics, namely polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, polycarbonate, polystyrene, silicone, polylactide acid  and polymethylmethacrylate were simultaneously acquired using an O-PTIR microscope in non-contact, reflection mode. Comprehensive band assignments were presented. We determined the agreement of O-PTIR with standalone attenuated total reflection FTIR and Raman spectrometers based on the hit quality index (HQI) and introduced a two-dimensional identification (2D-HQI) approach using both Raman- and IR-HQIs. Finally, microplastic particles were prepared as test samples from known materials by wet grinding, O-PTIR data were collected and subjected to the 2D-HQI identification approach. We concluded that this framework offers improved material identification of microplastic particles in environmental, nutritious and biological matrices.</p", "keywords": ["Science", "Microplastics", "Q", "R", "Reproducibility of Results", "Spectrum Analysis", " Raman", "Polypropylenes", "01 natural sciences", "Article", "0104 chemical sciences", "Spectroscopy", " Fourier Transform Infrared", "Medicine", "Plastics", "Water Pollutants", " Chemical", "Environmental Monitoring"]}, "links": [{"href": "https://www.nature.com/articles/s41598-022-23318-2.pdf"}, {"href": "https://doi.org/PMC9637219"}, {"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": "PMC9637219", "name": "item", "description": "PMC9637219", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PMC9637219"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-11-05T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Reproducibility&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=Reproducibility&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=Reproducibility&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Reproducibility&offset=42", "hreflang": "en-US"}], "numberMatched": 42, "numberReturned": 42, "distributedFeatures": [], "timeStamp": "2026-09-21T13:52:39.017830Z"}