{"type": "FeatureCollection", "features": [{"id": "10.1002/fsn3.1675", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:14:13Z", "type": "Journal Article", "created": "2020-07-15", "title": "Valorization of the green waste parts from sweet potato ( Impoea batatas L.): Nutritional, phytochemical composition, and bioactivity evaluation", "description": "Abstract<p>In the present study, leaves from 13 sweet potato cultivars were collected as raw materials. The nutritional and functional composition, antioxidant activity, and sunscreen activity of different sweet potato leaf samples were determined, and the comprehensive nutritional quality was calculated by gray relational analysis. Results showed that the nutritional and functional components are significantly different between different cultivars. Tainong71 showed the highest comprehensive nutritional quality, followed by Fu22, Ningcai, Fu23, Ecai10, Zhecai726, Ecai1, Fu18, Pushu53, Guangcai5, Shulv1, Guangcai2, and Zhecai1. The antioxidant activity varied from 3.94 to 16.75\uffc2\uffa0g Trolox equivalent/100\uffc2\uffa0g dry weight. Pushu53 showed the highest sunscreen activity, with the sun protection factor 24.65. There was a positive correlation between antioxidant activity and sunscreen activity (r\uffc2\uffa0=\uffc2\uffa0.737, p\uffc2\uffa0=\uffc2\uffa0.004). In conclusion, sweet potato leaves possess high nutritional and functional properties, and have the huge potential to be used as green leafy vegetables and sunscreen agent.</p>", "keywords": ["2. Zero hunger", "0404 agricultural biotechnology", "chemical/nutritional characterization ; antioxidant activity ; correlation analysis ; sunscreen acitvity ; gray relational analysis ; sweet potato leaves", "04 agricultural and veterinary sciences", "0405 other agricultural sciences", "Original Research"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1002/fsn3.1675"}, {"href": "https://doi.org/10.1002/fsn3.1675"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Food%20Science%20%26amp%3B%20Nutrition", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/fsn3.1675", "name": "item", "description": "10.1002/fsn3.1675", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/fsn3.1675"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-14T00:00:00Z"}}, {"id": "10.1007/978-3-030-84144-7_7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:14:20Z", "type": "Report", "created": "2022-04-11", "title": "Potential of Sentinel-2 Satellite and Novel Proximal Sensor Data Fusion for Agricultural Applications", "description": "Open AccessConsidering the importance of crop production for the growing population of the world, timely and accurate information about crop development is essential for successful agricultural monitoring. With an increasing interest of the agricultural community in precision agriculture, there is also a growing interest for using different spectral vegetation indices derived by different sensor devices. They can offer a valuable perspective both at the field-scale and at the plant level. In order to better utilize the spectral reflectance measurements from different sensors for agricultural applications, as well as to promote synergistic use of proximal and remote sensing sensors in this area, this paper aims to compare two novel sensing approaches for crop monitoring; a) the recently developed active multispectral proximal sensor named Plant-O-Meter and b) Sentinel-2 satellite, which carries a multispectral optical instrument. Both sensors and sensing methods are suitable for agricultural applications, following the same basic measurement principles. In general, their operation is based on the estimation of the proportion of radiation that is reflected from the target, which in agricultural systems refers to plants or the soil, at different wavelengths of the spectrum of light. However, each of the two sensing systems shows pros and cons regarding the spatial, spectral and temporal resolutions, the need for corrections and calibrations and the dependency from external parameters such as the weather or illumination conditions. Therefore, their complementary use is expected to bring added value comparing to information retrieved by each sensor separately. In order to correctly address the problem of data fusion, compatibility studies between the two sensors (passive remote and active proximal) are necessary. In this study, a maize field was sensed on several dates in 2018 growing season using both the Plant-O-Meter active proximal sensor and images acquired by Sentinel-2. Numerous vegetation indices based on different spectral channel combinations were calculated and the results were compared using linear regression analysis. First results showed good positive correlations between the indices obtained by the two sensors which signify their joint potential, hence further development and research on this topic are appreciated and expected.", "keywords": ["2. Zero hunger", "crop monitoring", " proximal sensing", " Sentinel-2", " vegetation indices", " correlation", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.1007/978-3-030-84144-7_7"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/978-3-030-84144-7_7", "name": "item", "description": "10.1007/978-3-030-84144-7_7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/978-3-030-84144-7_7"}, {"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": "10.1016/j.agrformet.2018.11.031", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:15:13Z", "type": "Journal Article", "created": "2018-11-29", "title": "Partitioning evapotranspiration of a drip-irrigated wheat crop: Inter-comparing eddy covariance-, sap flow-, lysimeter- and FAO-based methods", "description": "Abstract   A precise estimate of the evapotranspiration (ET) partitioning is fundamental for determining the crop water needs and optimizing irrigation management. The plant transpiration (T) is generally considered to be the most desirable component, while reducing the soil evaporation (E) could be one of the most important water-saving actions in semi-arid agricultural regions. Given the lack of reference method to estimate the E/T partitioning of wheat crop, this study inter-compares four different methods based on eddy covariance, sap flow and lysimetry measurements and FAO modeling. The objectives are: i) to quantify the systematic and random uncertainty in E and T observations, ii) to evaluate the partitioning ratio (T/ET) at the daily/field scale and iii) to assess the performance of the FAO model over two drip irrigated wheat fields. Results indicate that despite the small surface sensed by mini-lysimeters, the partitioning ratio is evaluated more precisely (19% relative error) with lysimetry than with the other systems (any combination of eddy covariance, lysimetry and sap flow measurements). Moreover, stem-scale T measurements from sap flow sensors are subject to representativeness issues at the field scale, and to systematic errors during water-stress and senescence periods. The lysimeter-derived partitioning ratio increases from about 0.50 to 0.85 during the growth stage and rapidly drops towards 0 during senescence. Its dynamics is found to be significantly correlated (R>0.7) with the 5-cm soil moisture. By comparing FAO simulations with observations, it is found that the FAO method overestimates T and underestimates E, while keeping satisfying ET estimates for drip irrigated wheat. This study suggests that different independent measurement techniques should be implemented to both quantify and reduce uncertainties in the T/ET ratio, and that accurate observations are still needed to improve the modeling of E/T components.", "keywords": ["FAO-56", "0106 biological sciences", "2. Zero hunger", "550", "Lysimeter", "Eddy correlation", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "01 natural sciences", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Sap flow", "Wheat", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Evaporation-transpiration"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2018.11.031"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2018.11.031", "name": "item", "description": "10.1016/j.agrformet.2018.11.031", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2018.11.031"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-01T00:00:00Z"}}, {"id": "10.3390/microorganisms9071457", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:27Z", "type": "Journal Article", "created": "2021-07-07", "title": "Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>There are almost 9500 biogas plants in Germany, which are predominantly operated with energy crops and residues from livestock husbandry over the last two decades. In the future, biogas plants must be enabled to use a much broader range of input materials in a flexible and demand-oriented manner. Hence, the microbial communities will be exposed to frequently varying process conditions, while an overall stable process must be ensured. To accompany this transition, there is the need to better understand how biogas microbiomes respond to management measures and how these responses affect the process efficiency. Therefore, 67 microbiomes originating from 49 agricultural, full-scale biogas plants were taxonomically investigated by 16S rRNA gene amplicon sequencing. These microbiomes were separated into three distinct clusters and one group of outliers, which are characterized by a specific distribution of 253 indicative taxa and their relative abundances. These indicative taxa seem to be adapted to specific process conditions which result from a different biogas plant operation. Based on these results, it seems to be possible to deduce/assess the general process condition of a biogas digester based solely on the microbiome structure, in particular on the distribution of specific indicative taxa, and without knowing the corresponding operational and chemical process parameters. Perspectively, this could allow the development of detection systems and advanced process models considering the microbial diversity.</p></article>", "keywords": ["580", "anaerobic digestion", "0301 basic medicine", "2. Zero hunger", "NMDS", "0303 health sciences", "QH301-705.5", "biogas microbiome", "anaerobic digestion; biogas microbiome; taxonomic profiling; 16S rRNA gene amplicon sequencing; NMDS; indicative taxa; Pearson correlations", "Pearson correlations", "7. Clean energy", "Article", "6. Clean water", "660.6", "03 medical and health sciences", "13. Climate action", "indicative taxa", "taxonomic profiling", "Biology (General)", "16S rRNA gene amplicon sequencing"]}, "links": [{"href": "http://www.mdpi.com/2076-2607/9/7/1457/pdf"}, {"href": "https://www.mdpi.com/2076-2607/9/7/1457/pdf"}, {"href": "https://doi.org/10.3390/microorganisms9071457"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microorganisms", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/microorganisms9071457", "name": "item", "description": "10.3390/microorganisms9071457", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/microorganisms9071457"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "21.11116/0000-0008-DFA2-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:42Z", "type": "Journal Article", "created": "2021-07-07", "title": "Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>There are almost 9500 biogas plants in Germany, which are predominantly operated with energy crops and residues from livestock husbandry over the last two decades. In the future, biogas plants must be enabled to use a much broader range of input materials in a flexible and demand-oriented manner. Hence, the microbial communities will be exposed to frequently varying process conditions, while an overall stable process must be ensured. To accompany this transition, there is the need to better understand how biogas microbiomes respond to management measures and how these responses affect the process efficiency. Therefore, 67 microbiomes originating from 49 agricultural, full-scale biogas plants were taxonomically investigated by 16S rRNA gene amplicon sequencing. These microbiomes were separated into three distinct clusters and one group of outliers, which are characterized by a specific distribution of 253 indicative taxa and their relative abundances. These indicative taxa seem to be adapted to specific process conditions which result from a different biogas plant operation. Based on these results, it seems to be possible to deduce/assess the general process condition of a biogas digester based solely on the microbiome structure, in particular on the distribution of specific indicative taxa, and without knowing the corresponding operational and chemical process parameters. Perspectively, this could allow the development of detection systems and advanced process models considering the microbial diversity.</p></article>", "keywords": ["580", "anaerobic digestion", "2. Zero hunger", "0301 basic medicine", "NMDS", "0303 health sciences", "QH301-705.5", "biogas microbiome", "Pearson correlations", "7. Clean energy", "Article", "6. Clean water", "660.6", "03 medical and health sciences", "13. Climate action", "indicative taxa", "taxonomic profiling", "Biology (General)", "16S rRNA gene amplicon sequencing"]}, "links": [{"href": "http://www.mdpi.com/2076-2607/9/7/1457/pdf"}, {"href": "https://www.mdpi.com/2076-2607/9/7/1457/pdf"}, {"href": "https://doi.org/21.11116/0000-0008-DFA2-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microorganisms", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-0008-DFA2-6", "name": "item", "description": "21.11116/0000-0008-DFA2-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-0008-DFA2-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-07T00:00:00Z"}}, {"id": "10.5281/zenodo.3548796", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-21T16:21:06Z", "type": "Journal Article", "created": "2021-01-30", "title": "On the dose dependence prior and after stimulation with visible light of E' and Al-hole centres in sedimentary quartz: correlation and mechanisms", "description": "E\u2019 and Al-hole centres are some of the most common and abundant paramagnetic defects in sedimentary quartz. Here we investigate the dose dependence of these defects before and after exposure to light by electron spin resonance (ESR). Unlike the Al-hole centre, known to have only radiation-induced formation mechanisms, the E\u2019 seems to possess a response to gamma dose characterised by predominantly radiation-induced annihilation at lower doses (about 1000 Gy) and a predominantly radiation-induced formation at higher doses, at least in our investigated dose range (up to 40 kGy). We propose these dose response mechanisms to be governed by electron trapping by E\u2019 itself and by hole trapping by the oxygen deficiency centre (ODC), known to be the main precursor of E\u2019. We show that the ESR signals of both defects are linearly correlated during their formation as well as during their dissociation under both irradiation and sunlight exposure. We further show that there is a clear correlation between the light sensitive Al-hole centres (also known as the Al-hole bleachable part), and the amount of E\u2019 produced after prolonged light exposure. This indicates a correlation between the holes released from Al-hole and those trapped by one of the two electrons in the ODCs producing E\u2019. As such, the origin of the unbleachable part of the Al-hole signal resides in the availability of oxygen deficiency centres which are also dependent on the accumulated gamma dose.", "keywords": ["03 medical and health sciences", "0302 clinical medicine", "electron spin resonance; E' centres; Al-hole centres; gamma dose response; mechanisms; bleaching; correlation", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3548796"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Radiation%20Measurements", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3548796", "name": "item", "description": "10.5281/zenodo.3548796", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3548796"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "10.5281/zenodo.7079648", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:21:19Z", "type": "Report", "created": "2022-04-11", "title": "Potential of Sentinel-2 Satellite and Novel Proximal Sensor Data Fusion for Agricultural Applications", "description": "Open AccessConsidering the importance of crop production for the growing population of the world, timely and accurate information about crop development is essential for successful agricultural monitoring. With an increasing interest of the agricultural community in precision agriculture, there is also a growing interest for using different spectral vegetation indices derived by different sensor devices. They can offer a valuable perspective both at the field-scale and at the plant level. In order to better utilize the spectral reflectance measurements from different sensors for agricultural applications, as well as to promote synergistic use of proximal and remote sensing sensors in this area, this paper aims to compare two novel sensing approaches for crop monitoring; a) the recently developed active multispectral proximal sensor named Plant-O-Meter and b) Sentinel-2 satellite, which carries a multispectral optical instrument. Both sensors and sensing methods are suitable for agricultural applications, following the same basic measurement principles. In general, their operation is based on the estimation of the proportion of radiation that is reflected from the target, which in agricultural systems refers to plants or the soil, at different wavelengths of the spectrum of light. However, each of the two sensing systems shows pros and cons regarding the spatial, spectral and temporal resolutions, the need for corrections and calibrations and the dependency from external parameters such as the weather or illumination conditions. Therefore, their complementary use is expected to bring added value comparing to information retrieved by each sensor separately. In order to correctly address the problem of data fusion, compatibility studies between the two sensors (passive remote and active proximal) are necessary. In this study, a maize field was sensed on several dates in 2018 growing season using both the Plant-O-Meter active proximal sensor and images acquired by Sentinel-2. Numerous vegetation indices based on different spectral channel combinations were calculated and the results were compared using linear regression analysis. First results showed good positive correlations between the indices obtained by the two sensors which signify their joint potential, hence further development and research on this topic are appreciated and expected.", "keywords": ["2. Zero hunger", "crop monitoring", " proximal sensing", " Sentinel-2", " vegetation indices", " correlation", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7079648"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7079648", "name": "item", "description": "10.5281/zenodo.7079648", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7079648"}, {"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": "2902175533", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:56Z", "type": "Journal Article", "created": "2018-11-29", "title": "Partitioning evapotranspiration of a drip-irrigated wheat crop: Inter-comparing eddy covariance-, sap flow-, lysimeter- and FAO-based methods", "description": "Abstract   A precise estimate of the evapotranspiration (ET) partitioning is fundamental for determining the crop water needs and optimizing irrigation management. The plant transpiration (T) is generally considered to be the most desirable component, while reducing the soil evaporation (E) could be one of the most important water-saving actions in semi-arid agricultural regions. Given the lack of reference method to estimate the E/T partitioning of wheat crop, this study inter-compares four different methods based on eddy covariance, sap flow and lysimetry measurements and FAO modeling. The objectives are: i) to quantify the systematic and random uncertainty in E and T observations, ii) to evaluate the partitioning ratio (T/ET) at the daily/field scale and iii) to assess the performance of the FAO model over two drip irrigated wheat fields. Results indicate that despite the small surface sensed by mini-lysimeters, the partitioning ratio is evaluated more precisely (19% relative error) with lysimetry than with the other systems (any combination of eddy covariance, lysimetry and sap flow measurements). Moreover, stem-scale T measurements from sap flow sensors are subject to representativeness issues at the field scale, and to systematic errors during water-stress and senescence periods. The lysimeter-derived partitioning ratio increases from about 0.50 to 0.85 during the growth stage and rapidly drops towards 0 during senescence. Its dynamics is found to be significantly correlated (R>0.7) with the 5-cm soil moisture. By comparing FAO simulations with observations, it is found that the FAO method overestimates T and underestimates E, while keeping satisfying ET estimates for drip irrigated wheat. This study suggests that different independent measurement techniques should be implemented to both quantify and reduce uncertainties in the T/ET ratio, and that accurate observations are still needed to improve the modeling of E/T components.", "keywords": ["FAO-56", "2. Zero hunger", "0106 biological sciences", "550", "Lysimeter", "Eddy correlation", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "01 natural sciences", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Sap flow", "Wheat", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Evaporation-transpiration"]}, "links": [{"href": "https://doi.org/2902175533"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2902175533", "name": "item", "description": "2902175533", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2902175533"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+correlation&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=+correlation&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=+correlation&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=+correlation&offset=8", "hreflang": "en-US"}], "numberMatched": 8, "numberReturned": 8, "distributedFeatures": [], "timeStamp": "2026-09-22T05:54:20.926104Z"}