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The effect of a mucilage analogue from chia seeds without intrinsic respiratory activity on oxygen diffusion was measured at different water contents during wetting-drying cycles in a diffusion chamber experiment. Artificial soils of various particle size distributions were mixed with various amounts of the mucilage analogue. Additionally, environmental scanning electron microscopy (ESEM) was used to visualize mucilage bridges in the dry soil samples.
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Data represent an intercropping field experiment carried out at CKA in the year 2021. Shoot and root data collection was conducted with one faba bean cultivar and two spring wheat cultivars sown at three sowing densities. FTIR spectroscopy was used to define the root masses of the two species.
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A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain. Please find more information at: https://www.phenobench.org/
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This dataset contains point clouds of sugar beet plants in field conditions. The data was recorded at Bundessortenamt and was manually labeled for leaf instance segmentation. If you want to use the dataset please contact me.
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Shape completion dataset for sweet peppers. A detailed description of the dataset can be found in our technical report: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/magistri2024arxiv.pdf We additionally provide a small set of python script to load this data: https://github.com/PRBonn/shape_completion_toolkit
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Sugar beet shoot and root phenotypic plasticity to nitrogen, phosphorus, potassium and lime omission
Data were collected in 2019 in Dikopshof, Wesseling, Germany
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This data set contains survey data from a framed field experiment that was conducted with German crop farmers between February and April 2022. Major components of the data set: a set of psychographic/attitudinal items, results from an economic business simulation game, sociodemographic and farm structural variables (n=334 after data cleaning).
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µCt images with a resolution of 11µm
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This data set contains online survey data from an experiment investigating German public attitudes towards agricultural robots. Major components are the data set containing 2,269 complete questionnaires (after data cleaning), the according Stata do-file to analyze the data and the output files from the preceding construct validity tests in SPSS.
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The corn Dataset (CN20) was captured using BonnBot-I. This is a challenging dataset for crop monitoring approaches as it is a grass crop.