The dataset RGB-MiniplotBarley contains 22164 RGB images of 11 time points 21. jun - 7. jul 2022 of two genotypes of spring barley grown under single-nutrient deficiencies of N, P, K, S, B and one multi-nutrient deficient treatment from miniplot fertilizer trial at Campus Klein-Altendorf of University of Bonn. The images are annotated with plot number, genotype and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

Barley plants of variety Barke, Criewener, Hanna and Ragusa have been grown in nutrient solutions that were deficient in N, P, K, Mg, Ca, S, B, Cl, Cu, Fe, Mn, Mo, Ni or Zn or had a toxic concentration of Al or Mn. The plant development was documented twice a week by RGB images for four weeks. The nutrient treatment and genotype per image are documented in the images annotations.

The dataset RGB-SoilPotWheat contains 39463 RGB images of 10 time points 23. Feb - 22. March 2021 of four genotypes of winter wheat from a pot experiment in greenhouse at University of Bonn. The images are annotated by potnumber which encodes genotype and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset RGB-divCrops-LTFT-Halle1 contains 8689 RGB images of 16 time points 9. apr - 19. aug 2021 of barley, potatoe, rye, sugar beet and wheat from long-term field fertilizer trial at University of Halle. The images are annotated with crop and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

Our hypothesis relied on the importance of phenotypic traits in the influence of root and rhizosphere microbiome. That is because high-throughput cultivation of microbes from soil, applied to Wild Type and root mutant of maize. Soil for this experiment is collected from one of the oldest Long-Term Experiments – Dikopshof field. Low Phosphate content of this soil allows it to identify phosphate solubilizing microbes from the natural environment.

The dataset RGB-Wheat-LTFT-Bonn contains 7361 RGB images of 22 time points 6. Feb. - 12. June 2020 of winter wheat variety 'Boss' from long-term field fertilizer trial at University of Bonn. The images are annotated with crop, variety and fertilizer management, including single-nutrient omission of N, P and K, a treatment without liming, an unfertilized treatment, ctrl and ctrl plus manure, and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset RGB-varWheat-LTFT-Bonn contains 5678 RGB images of 6 time points 8. may - 12. jun 2020 of various not annotated winter wheat varieties from long-term field fertilizer trial at University of Bonn. The images are annotated with crop and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset RGB-divCrops-LTFT-Halle2 contains 6434 RGB images of 2 time points 3.+ 15. jun 2022 of barley, potatoe, rye, sugar beet and wheat from long-term field fertilizer trial at University of Halle. The images are annotated with crop and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset RGB-SoilPotBarley contains 35,343 RGB images of 8 time points 22. dec 2020 - 21. jan 2021 of four genotypes of spring barley from a pot experiment in greenhouse at University of Bonn. The images are annotated by potnumber which encodes genotype and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset NutriDat-HydroBarley3 contains nutrient concentration and morphpogical trait data of four genotypes of spring barley from a hydroponic experiment in greenhouse at University of Bonn in 2020 including single-nutrient deficiencies of all 14 essential mineral nutrients plus Al and Mn toxicity.