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.

The dataset RGB-varCereals-LTFT-Bonn contains 16717 RGB images of 17 time points 14. apr - 29. jul 2021 of barley, rye and wheat from long-term field fertilizer trial Dikopshof at University of Bonn. The images are annotated with crop, genotype 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 RGB-HydroBarley3 contains 12258 RGB images of 6 time points 22. jun - 10. jul 2020 of four genotypes of spring barley from a hydroponic experiment in greenhouse at University of Bonn including single-nutrient deficiencies of all 14 essential mineral nutrients plus Al and Mn toxicity. The images are annotated with genotype and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.

The dataset RGB-HydroBarley2 contains 15647 RGB images of 8 time points 19. March - 16. April 2020 of four genotypes of spring barley from a hydroponic experiment in greenhouse at University of Bonn including single-nutrient deficiencies of all 14 essential mineral nutrients plus Al toxicity. The images are annotated with genotype and fertilizer management and have been taken for a Deep Learning approach for nutrient deficiency recognition.