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Joint measurements of NDVI and crop production data-set related to combination of management zones delineation and nitrogen fertilisation levels
This research compared four nitrogen (N) management strategies (uniform N rate: UR, variable N rate based on crop proximal sensing: VR-PS, variable N rate based on management zones: VR-MZ and variable N rate based on integrating crop sensing and MZ: VR-PSMZ), evaluating their effect on maize grain y...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6965702/ https://www.ncbi.nlm.nih.gov/pubmed/31970270 http://dx.doi.org/10.1016/j.dib.2019.104968 |
Sumario: | This research compared four nitrogen (N) management strategies (uniform N rate: UR, variable N rate based on crop proximal sensing: VR-PS, variable N rate based on management zones: VR-MZ and variable N rate based on integrating crop sensing and MZ: VR-PSMZ), evaluating their effect on maize grain yield, partial factor productivity (PFP(N)), and net return above N fertiliser cost (RANC). The study provided a practical tool for choosing the fertilisation strategy that best performs in each agro-environment. These datasets are a supplementary material to the research paper by [3]. Data were collected over seven site-years experiments conducted in North-Eastern Colorado (USA). In dataset 1, for each site-year, data includes geo-referred points where grain yield and Normalised Difference Vegetation Index (NDVI) were measured, each one associated with its respective N rate, management zone (MZ), PFP(N), RANC, and N management strategy. In order to group the observations reflecting homogeneous crop vigour, NDVI values were clustered within NDVI classes. In dataset 2, the main soil properties measured in several geo-referred points in each location are provided. |
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