Long time series with spatially highly resolved crop data are important for research projects on numerous future challenges in the environment and food sector. In this publication, we describe a dataset with crop-yield and area data for Germany from 1979 to 2021. The data are spatially resolved to 397 districts, which have an average size of 900 km, and include the crops spring barley, winter barley, grain maize, silage maize, oats, potatoes, winter rape, rye, sugarbeet, triticale and winter wheat. The crop-yield data cover, on average, about 9.5 million hectares per year and 80% of Germany's total arable land. The dataset contains 214,820 yield and area data points. These were obtained by collecting and digitizing crop data from multiple statistical sources and transforming the data to match the district boundaries in 2020. Potential applications of the data include the analysis of interactions between agricultural yields and environmental factors, such as weather; the validation of yield prediction methodologies or the analysis of yield-loss risks in agriculture.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10798971 | PMC |
| http://dx.doi.org/10.1038/s41597-024-02951-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Augmented prediction of vertebral collapse after osteoporotic vertebral compression fractures through parameter-efficient fine-tuning of biomedical foundation models.
Sci Rep
December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
View Article and Find Full Text PDFImpact of body composition and muscle health phenotypes on survival outcomes in colorectal cancer: a multicenter cohort.
Sci Rep
December 2024
Postgraduate Program in Health Sciences, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, RN, Brazil.
Body composition abnormalities are prognostic markers in several types of cancer, including colorectal cancer (CRC). Using our data distribution on body composition assessments and classifications could improve clinical evaluations and support population-specific opportune interventions. This study aimed to evaluate the distribution of body composition from computed tomography and assess the associations with overall survival among patients with CRC.
View Article and Find Full Text PDFScreening and identification of evaluation indicators of low phosphorus tolerant germplasm in Gleditsia sinensis Lam.
Sci Rep
December 2024
Institute for Forest Resources and Environment of Guizhou, College of Forestry, Guizhou University, Guiyang, 550025, Guizhou, China.
This study aims to explore the low phosphorus (P) tolerance of saplings from different Gleditsia sinensis Lam. families. It also seeks to screen for Gleditsia sinensis families with strong low P tolerance and identify key indicators for evaluating their tolerance.
View Article and Find Full Text PDFSpatial co-distribution of tuberculosis prevalence and low BCG vaccination coverage in Ethiopia.
Sci Rep
December 2024
School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia.
While bacille-calmette-guerin (BCG) vaccination is one of the recommended strategies for preventing tuberculosis (TB), its coverage is low in several countries, including Ethiopia. This study investigated the spatial co-distribution and drivers of TB prevalence and low BCG coverage in Ethiopia. This ecological study was conducted using data from a national TB prevalence survey and the Ethiopian demographic and health survey (EDHS) to map the spatial co-distribution of BCG vaccination coverage and TB prevalence.
View Article and Find Full Text PDFDeep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.
Sci Rep
December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!