{"type": "FeatureCollection", "features": [{"id": "10.1007/s10661-018-6700-9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:14:57Z", "type": "Journal Article", "created": "2018-05-06", "title": "Improving nitrate load estimates in an agricultural catchment using Event Response Reconstruction", "description": "Low-frequency grab sampling cannot capture fine dynamics of stream solute concentrations, which results in large uncertainties in load estimates. The recent development of high-frequency sensors has enabled monitoring solute concentrations at sub-hourly time scales. This study aimed to improve nitrate (NO3) load estimates using high-resolution records (15-min time interval) from optical sensors to capture the typical concentration response to storm events. An empirical model was developed to reconstruct NO3 concentrations during storm events in a 100-km2 agricultural catchment in Germany. Two years (Jan 2002 to Dec 2002 and Oct 2005 to Sep 2006) of high-frequency measurements of NO3 concentrations, discharge and precipitation were used. An Event Response Reconstruction (ERR) model was developed using NO3 concentration descriptor variables and predictor variables calculated from discharge and precipitation records. Fourteen events were used for calibration, and 27 events from four periods of continuous records of high-frequency measurement were used for validation. During all selected storm events, NO3 concentration decreased during flow rise and increased during the recession phase of the hydrograph. Three storm descriptor variables were used to describe these dynamics: relative change in concentration between initial and minimum NO3 concentrations (rdN), time to maximum change in NO3 concentration (TdN) and time to 50% recovery of NO3 concentration (TN rec ). The ERR consisted of building linear models of discharge and precipitation to predict these three descriptors. The ERR approach greatly improved NO3 load estimates compared to linear interpolation of grab sampling data (error decreased from 10 to 1%) or flow-weighted estimation of load (error is 7%). This study demonstrated that ERR based on a few months of high-resolution data enables accurate load estimates from low-frequency NO3 data.", "keywords": ["Nitrates", "Rivers", "13. Climate action", "Germany", "0208 environmental biotechnology", "Water Pollution", " Chemical", "0207 environmental engineering", "Agriculture", "Nitrogen Oxides", "02 engineering and technology", "Water Pollutants", " Chemical", "6. Clean water", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1007/s10661-018-6700-9"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Monitoring%20and%20Assessment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10661-018-6700-9", "name": "item", "description": "10.1007/s10661-018-6700-9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10661-018-6700-9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-07T00:00:00Z"}}, {"id": "10.1016/j.agee.2005.08.021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:15:17Z", "type": "Journal Article", "created": "2005-10-14", "title": "Nitrous Oxide Emissions From Organic And Conventional Crop Rotations In Five European Countries", "description": "Abstract   Nitrous oxide (N2O) emissions from agriculture are currently estimated from N inputs using emission factors, and little is known about the importance of regional or management-related differences. This paper summarizes the results of a study in which N2O emission rates were recorded on 15\u201326 occasions during a 12-month period in organic and conventional dairy crop rotations in five European countries (Austria, Denmark, Finland, Italy, UK). A common methodology based on static chambers was used for N2O flux measurements, and N2O data were compiled together with information about N inputs (from fertilizers, N2 fixation, atmospheric deposition and excretal returns), crop rotations and soil properties. Organic rotations received only manure as N fertilizer, while manure accounted for 0\u2013100% of fertilizer N in conventional rotations. A linear regression model was used to examine effects of location, system and crop category on N2O emissions, while a second model examined effects of soil properties. Nitrous oxide emissions were higher from conventional than from organic crop rotations except in Austria and, according to the statistical analysis, the differences between locations and crop categories were significant. Ammonium was significantly related to N2O emissions, although this effect was dominated by observations from a grazing system. Despite the limited number of samplings, annual emissions were estimated by interpolation. Across the two systems and five locations there was a significant relationship between total N inputs and N2O emissions at the crop rotation level which indicated that annually 1.6\u00a0\u00b1\u00a00.2% (mean\u00a0\u00b1\u00a0standard error) of total N inputs were lost as N2O, while there was a background emission of 1.4\u00a0\u00b1\u00a00.3\u00a0kg\u00a0N2O-N\u00a0ha\u22121\u00a0year\u22121. Although this measurement program emphasized system effects at the expense of high temporal resolution, the results indicate that N input is a significant determinant for N2O emissions from agricultural soils.", "keywords": ["2. Zero hunger", "nitrous oxide", "luonnonmukainen maataloustuotanto", "dityppioksidi", "04 agricultural and veterinary sciences", "rotational cropping", "15. Life on land", "typen oksidit", "nitrogen oxides", "13. Climate action", "crop rotations", "soil properties", "luomutuotanto", "0401 agriculture", " forestry", " and fisheries", "p\u00e4\u00e4st\u00f6t", "Ka", "Eurooppa"], "contacts": [{"organization": "Petersen, Soren O., Regina, Kristiina, P\u00f6llinger, Alfred, Rigler, Elisabeth, Valli, Laura, Yamulki, Sirwan, Esala, Martti, Fabbri, Claudio, Syv\u00e4salo, Eija, Vinther, Finn P.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2005.08.021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2005.08.021", "name": "item", "description": "10.1016/j.agee.2005.08.021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2005.08.021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-02-01T00:00:00Z"}}, {"id": "10.1039/d1ra03337a", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:17:12Z", "type": "Journal Article", "created": "2021-09-10", "title": "Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Extensive application of clustering and classification algorithms shows the potential of a CNT-based sensor array in breathomics.</p></article>", "keywords": ["electronic nose", "Linear discriminant analysis", "Principal component analysis", "Breath analysis", "02 engineering and technology", "sensors", "Supported Vectror Machine", "01 natural sciences", "nanotubes", "Ammonia; Biomarkers; Carbon nanotubes; Classification (of information); Clustering algorithms; Molecules; Nitrogen oxides; Principal component analysis; Sulfur compounds; Support vector machines", "0104 chemical sciences", "3. Good health", "breathomics", "Chemistry", "SWCNTs", "COPD", "ta318", "e-nose", "0210 nano-technology", "ta215"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/536855/1/RSC%20Adv._2021.pdf"}, {"href": "https://boa.unimib.it/bitstream/10281/517427/2/d1ra03337a.pdf%3b"}, {"href": "https://publicatt.unicatt.it/bitstream/10807/190102/1/d1ra03337a.pdf"}, {"href": "http://pubs.rsc.org/en/content/articlepdf/2021/RA/D1RA03337A"}, {"href": "https://doi.org/10.1039/d1ra03337a"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/RSC%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1039/d1ra03337a", "name": "item", "description": "10.1039/d1ra03337a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1039/d1ra03337a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.1371/journal.pone.0073450", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-22T16:18:22Z", "type": "Journal Article", "created": "2013-09-03", "title": "Greenhouse Gas Flux And Crop Productivity After 10 Years Of Reduced And No Tillage In A Wheat-Maize Cropping System", "description": "Appropriate tillage plays an important role in mitigating the emissions of greenhouse gases (GHG) in regions with higher crop yields, but the emission situations of some reduced tillage systems such as subsoiling, harrow tillage and rotary tillage are not comprehensively studied. The objective of this study was to evaluate the emission characteristics of GHG (CH4 and N2O) under four reduced tillage systems from October 2007 to August 2009 based on a 10-yr tillage experiment in the North China Plain, which included no-tillage (NT) and three reduced tillage systems of subsoil tillage (ST), harrow tillage (HT) and rotary tillage (RT), with the conventional tillage (CT) as the control. The soil under the five tillage systems was an absorption sink for CH4 and an emission source for N2O. The soil temperature positive impacted on the CH4 absorption by the soils of different tillage systems, while a significant negative correlation was observed between the absorption and soil moisture. The main driving factor for increased N2O emission was not the soil temperature but the soil moisture and the content of nitrate. In the two rotation cycle of wheat-maize system (10/2007-10/2008 and 10/2008-10/2009), averaged cumulative uptake fluxes of CH4 under CT, ST, HT, RT and NT systems were approximately 1.67, 1.72, 1.63, 1.77 and 1.17 t ha(-1) year(-1), respectively, and meanwhile, approximately 4.43, 4.38, 4.47, 4.30 and 4.61 t ha(-1) year(-1) of N2O were emitted from soil of these systems, respectively. Moreover, they also gained 33.73, 34.63, 32.62, 34.56 and 27.54 t ha(-1) yields during two crop-rotation periods, respectively. Based on these comparisons, the rotary tillage and subsoiling mitigated the emissions of CH4 and N2O as well as improving crop productivity of a wheat-maize cropping system.", "keywords": ["Crops", " Agricultural", "Greenhouse Effect", "2. Zero hunger", "Science", "Q", "R", "Temperature", "Water", "04 agricultural and veterinary sciences", "15. Life on land", "Zea mays", "6. Clean water", "Soil", "13. Climate action", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Nitrogen Oxides", "Gases", "Seasons", "Methane", "Triticum", "Research Article"], "contacts": [{"organization": "Shenzhong Tian, Na Li, Shuyun Chi, Bingwen Wang, Hongxiang Zhao, Tangyuan Ning, Zengjia Li, Yu Wang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1371/journal.pone.0073450"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLoS%20ONE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1371/journal.pone.0073450", "name": "item", "description": "10.1371/journal.pone.0073450", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1371/journal.pone.0073450"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-09-03T00:00:00Z"}}, {"id": "10.2134/jeq2001.3051659x", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-09-22T16:18:49Z", "type": "Journal Article", "created": "2010-06-14", "description": "ABSTRACT<p>Cover crops are a management option to reduce NO3 leaching under cereal grain production. A 2\uffe2\uff80\uff90yr field lysimeter study was established in Uppsala, Sweden, to evaluate the effect of a perennial ryegrass (Lolium perenne L.) cover crop interseeded in barley (Hordeum vulgare L.) on NO3\uffe2\uff80\uff93N leaching and availability of N to the main crop. Barley and ryegrass or barley alone were seeded in mid\uffe2\uff80\uff90May 1992, in lysimeters (0.3\uffe2\uff80\uff90m diam. \uffc3\uff97 1.2\uffe2\uff80\uff90m depth) of an undisturbed, well\uffe2\uff80\uff90drained, sandy loam soil. Fertilizer N was applied at the same time as labeled 15NH415NO3 (10 atom % 15N) at a rate of 100 kg N ha\uffe2\uff88\uff921 In 1993, barley was reseeded in May in the lysimeters but with nonlabeled NH4NO3 and no cover crop (previous year's cover crop incorporated just prior to seeding). Barley yields and total and fertilizer N uptake in Year 1 (1992) were unaffected by cover crop. Total aboveground N uptake by the ryegrass was 28 kg ha\uffe2\uff88\uff921 at the time of incorporation the following spring. Recovery of fertilizer\uffe2\uff80\uff90derived N in May 1993 was about 100%; 53% in soil, 46% in barley, &lt;2% in ryegrass, and negligible amounts in leachate. In May 1994, the corresponding figures were: 32% in soil, &lt;3% in barley, and, again, negligible amounts in leachate. The cover crop reduced concentrations of NO3\uffe2\uff80\uff93N in the leachate considerably (&lt;5 mg L\uffe2\uff88\uff921, compared with 10 to 18 mg L\uffe2\uff88\uff921 without cover crop) at most sampling times from November 1992 to April 1994, and reduced the total amount of NO3\uffe2\uff80\uff93N leached (22 compared with 8 kg ha\uffe2\uff88\uff921).</p>", "keywords": ["2. Zero hunger", "Nitrogen", "Climate", "Biological Availability", "Agriculture", "Hordeum", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Quaternary Ammonium Compounds", "Lolium", "Soil Pollutants", "0401 agriculture", " forestry", " and fisheries", "Nitrogen Oxides", "Seasons", "Fertilizers", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Lars Bergstr\u00f6m, William E. Jokela,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2134/jeq2001.3051659x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2134/jeq2001.3051659x", "name": "item", "description": "10.2134/jeq2001.3051659x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2134/jeq2001.3051659x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2001-09-01T00:00:00Z"}}, {"id": "10807/190102", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:22:06Z", "type": "Journal Article", "created": "2021-09-10", "title": "Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Extensive application of clustering and classification algorithms shows the potential of a CNT-based sensor array in breathomics.</p></article>", "keywords": ["electronic nose", "Linear discriminant analysis", "Chemistry", " Multidisciplinary", "Principal component analysis", "02 engineering and technology", "VOLATILE ORGANIC-COMPOUNDS", "sensors", "Supported Vectror Machine", "01 natural sciences", "nanotubes", "E-NOSE", "breathomics", "THIN-FILMS", "SWCNTs", "RANDOM NETWORKS", "COPD", "ta318", "e-nose", "ta215", "WALLED CARBON NANOTUBES", "Science & Technology", "Breath analysis", "SWCNT SENSOR", "34 Chemical sciences", "Ammonia; Biomarkers; Carbon nanotubes; Classification (of information); Clustering algorithms; Molecules; Nitrogen oxides; Principal component analysis; Sulfur compounds; Support vector machines", "0104 chemical sciences", "3. Good health", "Chemistry", "ROOM-TEMPERATURE", "AMMONIA SENSOR", "Physical Sciences", "NO2 DETECTION", "03 Chemical Sciences", "0210 nano-technology", "RESISTIVE SENSORS"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/536855/1/RSC%20Adv._2021.pdf"}, {"href": "https://boa.unimib.it/bitstream/10281/517427/2/d1ra03337a.pdf%3b"}, {"href": "https://publicatt.unicatt.it/bitstream/10807/190102/1/d1ra03337a.pdf"}, {"href": "http://pubs.rsc.org/en/content/articlepdf/2021/RA/D1RA03337A"}, {"href": "https://doi.org/10807/190102"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/RSC%20Advances", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10807/190102", "name": "item", "description": "10807/190102", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10807/190102"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "29732470", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:22:53Z", "type": "Journal Article", "created": "2018-05-06", "title": "Improving nitrate load estimates in an agricultural catchment using Event Response Reconstruction", "description": "Low-frequency grab sampling cannot capture fine dynamics of stream solute concentrations, which results in large uncertainties in load estimates. The recent development of high-frequency sensors has enabled monitoring solute concentrations at sub-hourly time scales. This study aimed to improve nitrate (NO3) load estimates using high-resolution records (15-min time interval) from optical sensors to capture the typical concentration response to storm events. An empirical model was developed to reconstruct NO3 concentrations during storm events in a 100-km2 agricultural catchment in Germany. Two years (Jan 2002 to Dec 2002 and Oct 2005 to Sep 2006) of high-frequency measurements of NO3 concentrations, discharge and precipitation were used. An Event Response Reconstruction (ERR) model was developed using NO3 concentration descriptor variables and predictor variables calculated from discharge and precipitation records. Fourteen events were used for calibration, and 27 events from four periods of continuous records of high-frequency measurement were used for validation. During all selected storm events, NO3 concentration decreased during flow rise and increased during the recession phase of the hydrograph. Three storm descriptor variables were used to describe these dynamics: relative change in concentration between initial and minimum NO3 concentrations (rdN), time to maximum change in NO3 concentration (TdN) and time to 50% recovery of NO3 concentration (TN rec ). The ERR consisted of building linear models of discharge and precipitation to predict these three descriptors. The ERR approach greatly improved NO3 load estimates compared to linear interpolation of grab sampling data (error decreased from 10 to 1%) or flow-weighted estimation of load (error is 7%). This study demonstrated that ERR based on a few months of high-resolution data enables accurate load estimates from low-frequency NO3 data.", "keywords": ["Nitrates", "Rivers", "13. Climate action", "Germany", "0208 environmental biotechnology", "Water Pollution", " Chemical", "0207 environmental engineering", "Agriculture", "Nitrogen Oxides", "02 engineering and technology", "Water Pollutants", " Chemical", "6. Clean water", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/29732470"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Monitoring%20and%20Assessment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "29732470", "name": "item", "description": "29732470", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/29732470"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-07T00:00:00Z"}}, {"id": "2799460907", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:22:48Z", "type": "Journal Article", "created": "2018-05-06", "title": "Improving nitrate load estimates in an agricultural catchment using Event Response Reconstruction", "description": "Low-frequency grab sampling cannot capture fine dynamics of stream solute concentrations, which results in large uncertainties in load estimates. The recent development of high-frequency sensors has enabled monitoring solute concentrations at sub-hourly time scales. This study aimed to improve nitrate (NO3) load estimates using high-resolution records (15-min time interval) from optical sensors to capture the typical concentration response to storm events. An empirical model was developed to reconstruct NO3 concentrations during storm events in a 100-km2 agricultural catchment in Germany. Two years (Jan 2002 to Dec 2002 and Oct 2005 to Sep 2006) of high-frequency measurements of NO3 concentrations, discharge and precipitation were used. An Event Response Reconstruction (ERR) model was developed using NO3 concentration descriptor variables and predictor variables calculated from discharge and precipitation records. Fourteen events were used for calibration, and 27 events from four periods of continuous records of high-frequency measurement were used for validation. During all selected storm events, NO3 concentration decreased during flow rise and increased during the recession phase of the hydrograph. Three storm descriptor variables were used to describe these dynamics: relative change in concentration between initial and minimum NO3 concentrations (rdN), time to maximum change in NO3 concentration (TdN) and time to 50% recovery of NO3 concentration (TN rec ). The ERR consisted of building linear models of discharge and precipitation to predict these three descriptors. The ERR approach greatly improved NO3 load estimates compared to linear interpolation of grab sampling data (error decreased from 10 to 1%) or flow-weighted estimation of load (error is 7%). This study demonstrated that ERR based on a few months of high-resolution data enables accurate load estimates from low-frequency NO3 data.", "keywords": ["Nitrates", "Rivers", "13. Climate action", "Germany", "0208 environmental biotechnology", "Water Pollution", " Chemical", "0207 environmental engineering", "Agriculture", "Nitrogen Oxides", "02 engineering and technology", "Water Pollutants", " Chemical", "6. Clean water", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/2799460907"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Monitoring%20and%20Assessment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2799460907", "name": "item", "description": "2799460907", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2799460907"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-07T00:00:00Z"}}, {"id": "589b366d-2b5d-4a9f-a7fd-2f563ec61957", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[5.81, 47.26], [5.81, 54.76], [15.77, 54.76], [15.77, 47.26], [5.81, 47.26]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil"}, {"id": "Nitrogen"}, {"id": "Greenhouse gases"}, {"id": "Nitrogen oxides"}, {"id": "carbon dioxide"}, {"id": "Field experimentation"}, {"id": "Temperature"}, {"id": "Air temperature"}, {"id": "Soil temperature"}, {"id": "Organic amendments"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}, {"id": "field trial"}, {"id": "static closed chamber method"}, {"id": "high carbon organic amendments"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}, {"id": "Landwirtschaftliche Anlagen und Aquakulturanlagen"}, {"id": "Treibhausgasemissionen"}, {"id": "Treibhausgas"}, {"id": "Kohlendioxid"}, {"id": "Stickstoffkreislauf"}, {"id": "Biogeochemischer Kreislauf"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}], "license": "CC BY", "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata.(e.g. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data re-used from the BonaRes Data Centre www.bonares.de. This data were created as part of BonaRes Module A-Project - Inplamint's research activities.\"Although every care has been taken in preparing and testing the data, BonaRes Module A-Project - Inplamint and BonaRes Data Centre cannot guarantee that the data are correct; neither does BonaRes Module A-Project - Inplamint and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project - Inplamint and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner / author.", "updated": "2021-03-23", "type": "Dataset", "created": "2019-11-14", "language": "eng", "title": "V140 Kiel: Greenhouse gas emissions and supporting temperatures 2015-2018", "description": "Nitrate surplus after harvest of winter oilseed rape and faba beans is a serious issue regarding groundwater pollution and GHG emission. Stimulation of microbial N immobilization by organic amendments might be an option to prevent N-losses and optimize N use efficiency on crop rotation level.\nIn this trial two crop rotations were established in a split plot design. The soil microbial activity is manipulated in field scale by post-harvest application of different organic amendments: preceding crop residues, winter wheat straw and spruce sawdust.\nThis file provides greenhouse gas emission rates from trial V140 on exeprimental farm Hohenschulen, Achterwehr, Germany. The trial is conducted by Uni Kiel, Institute of Crop Science and Plant Breeding, Agronomy and Crop Science. Geographical reference for the trial plots can be found in  V140_Parzellen_neu.shp (join by 'Plot_ID' and 'id'). UKiel_V140_Plot_Description_2015_2018_BonaResDataCenter.csv contains detailed information about the experimental setup and the treatment of the individual plots.\nThe emissions have been sampled from harvest of the preceding crops till the first fertilizer application on winter wheat plots. Sampling has been done with the static closed chamber method. Calculation of flux rates has been done in R with the package 'gasfluxes'.", "formats": [{"name": "CSV"}], "keywords": ["Soil", "Nitrogen", "Greenhouse gases", "Nitrogen oxides", "carbon dioxide", "Field experimentation", "Temperature", "Air temperature", "Soil temperature", "Organic amendments", "opendata", "field trial", "static closed chamber method", "high carbon organic amendments", "Boden", "Landwirtschaftliche Anlagen und Aquakulturanlagen", "Treibhausgasemissionen", "Treibhausgas", "Kohlendioxid", "Stickstoffkreislauf", "Biogeochemischer Kreislauf", "Boden"], "contacts": [{"name": "Steffen Rothardt", "organization": "CAU Kiel", "position": "Scientific staff", "roles": ["author"], "phones": [{"value": "+494318804398"}], "emails": [{"value": "rothardt@pflanzenbau.uni-kiel.de"}], "addresses": [{"deliveryPoint": ["Hermann-Rodewald-Str. 9"], "city": "Kiel", "administrativeArea": "Schleswig-Holstein", "postalCode": "24118", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Nicolas Br\u00fcggemann", "organization": "CAU Kiel", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "Br\u00fcggemann@pflanzenbau.uni-kiel.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Henning Kage", "organization": "CAU Kiel", "position": "Professor", "roles": ["supervisor"], "phones": [{"value": "+494318804398"}], "emails": [{"value": "kage@pflanzenbau.uni-kiel.de"}], "addresses": [{"deliveryPoint": ["Hermann-Rodewald-Str. 9"], "city": "Kiel", "administrativeArea": "Schleswig-Holstein", "postalCode": "24118", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "CAU Kiel", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=589b366d-2b5d-4a9f-a7fd-2f563ec61957", "rel": "download"}, {"href": "https://metadata.bonares.de:443/smartEditor/preview/Inplamint_1_hohenschulen_v140_kiel.PNG", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/fce012ef-309c-4b96-b12c-ae04c15a428b", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "589b366d-2b5d-4a9f-a7fd-2f563ec61957", "name": "item", "description": "589b366d-2b5d-4a9f-a7fd-2f563ec61957", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/589b366d-2b5d-4a9f-a7fd-2f563ec61957"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-23T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Nitrogen+Oxides&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=Nitrogen+Oxides&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=Nitrogen+Oxides&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Nitrogen+Oxides&offset=9", "hreflang": "en-US"}], "numberMatched": 9, "numberReturned": 9, "distributedFeatures": [], "timeStamp": "2026-09-22T21:43:00.558231Z"}