Thu Ha Nguyen, Fiona H M Tang, Giulia Conchedda, Leon Casse, Griffiths Obli-Laryea, Francesco N Tubiello, Federico Maggi
{"title":"NPKGRIDS:173 种作物的氮、五氧化二磷和氧化钾施肥量的全球地理参照数据集。","authors":"Thu Ha Nguyen, Fiona H M Tang, Giulia Conchedda, Leon Casse, Griffiths Obli-Laryea, Francesco N Tubiello, Federico Maggi","doi":"10.1038/s41597-024-04030-4","DOIUrl":null,"url":null,"abstract":"<p><p>We introduce NPKGRIDS, a new geospatial dataset, providing for the first time data on application rates for all three main plant nutrients, nitrogen (N), phosphorus (P, in terms of phosphorus pentoxide, P<sub>2</sub>O<sub>5</sub>) and potassium (K, in terms of potassium oxide, K<sub>2</sub>O) across 173 crops as of 2020, with a geospatial resolution of 0.05° (approximately 5.6 km at the equator). Development of NPKGRIDS adopted a data fusion approach to integrate crop mask information with eight published datasets of fertilizer application rates, compiled from either georeferenced data or national and subnational statistics. Furthermore, the total applied mass of N, P<sub>2</sub>O<sub>5</sub>, and K<sub>2</sub>O were benchmarked against the country level information from FAO and the International Fertilizers Association (IFA) and validated against data available from National Statistical Offices (NSOs). NPKGRIDS can be used in global modelling, and decision and policy making to help maximize crop yields while reducing environmental impacts.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"11 1","pages":"1179"},"PeriodicalIF":5.8000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526156/pdf/","citationCount":"0","resultStr":"{\"title\":\"NPKGRIDS: a global georeferenced dataset of N, P<sub>2</sub>O<sub>5</sub>, and K<sub>2</sub>O fertilizer application rates for 173 crops.\",\"authors\":\"Thu Ha Nguyen, Fiona H M Tang, Giulia Conchedda, Leon Casse, Griffiths Obli-Laryea, Francesco N Tubiello, Federico Maggi\",\"doi\":\"10.1038/s41597-024-04030-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We introduce NPKGRIDS, a new geospatial dataset, providing for the first time data on application rates for all three main plant nutrients, nitrogen (N), phosphorus (P, in terms of phosphorus pentoxide, P<sub>2</sub>O<sub>5</sub>) and potassium (K, in terms of potassium oxide, K<sub>2</sub>O) across 173 crops as of 2020, with a geospatial resolution of 0.05° (approximately 5.6 km at the equator). Development of NPKGRIDS adopted a data fusion approach to integrate crop mask information with eight published datasets of fertilizer application rates, compiled from either georeferenced data or national and subnational statistics. Furthermore, the total applied mass of N, P<sub>2</sub>O<sub>5</sub>, and K<sub>2</sub>O were benchmarked against the country level information from FAO and the International Fertilizers Association (IFA) and validated against data available from National Statistical Offices (NSOs). NPKGRIDS can be used in global modelling, and decision and policy making to help maximize crop yields while reducing environmental impacts.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"11 1\",\"pages\":\"1179\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526156/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-024-04030-4\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-04030-4","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
NPKGRIDS: a global georeferenced dataset of N, P2O5, and K2O fertilizer application rates for 173 crops.
We introduce NPKGRIDS, a new geospatial dataset, providing for the first time data on application rates for all three main plant nutrients, nitrogen (N), phosphorus (P, in terms of phosphorus pentoxide, P2O5) and potassium (K, in terms of potassium oxide, K2O) across 173 crops as of 2020, with a geospatial resolution of 0.05° (approximately 5.6 km at the equator). Development of NPKGRIDS adopted a data fusion approach to integrate crop mask information with eight published datasets of fertilizer application rates, compiled from either georeferenced data or national and subnational statistics. Furthermore, the total applied mass of N, P2O5, and K2O were benchmarked against the country level information from FAO and the International Fertilizers Association (IFA) and validated against data available from National Statistical Offices (NSOs). NPKGRIDS can be used in global modelling, and decision and policy making to help maximize crop yields while reducing environmental impacts.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.