Faisal, SThawdar, YOoi, MPLReutemann, PFletcher, DKuang, YCAbeysekera, SK2026-08-112026-08-112025-08-05Faisal, S., Thawdar, Y., Ooi, M. P. L., Reutemann, P., Fletcher, D., Kuang, Y. C., & Abeysekera, S. K. (2025). Proximal near-infrared hyperspectral imaging dataset for identifying epicuticular wax loss in Masena blueberries to evaluate post-harvest quality. Data in Brief, 62. https://doi.org/10.1016/j.dib.2025.1119462352-3409https://hdl.handle.net/10289/18531The dataset presented in this paper consists of hyperspectral images of Masena blueberries that were harvested on November 24, 2023, from an orchard in Pukehina, New Zealand. Blueberries were hand-harvested with gloves (intact wax), hand-harvested (without gloves), and mechanically aided by picking via a handheld shaker. Some berries were also wiped to eliminate degrading epicuticular wax (EW) for comparison. Imaging was performed within 9 hours of harvest using a Specim FX17e hyperspectral camera (900–1700 nm, 224 bands) under controlled lighting conditions. The data were white and dark reference-normalized, annotated using the in-house HAPPy tool (ENVI Software), and saved in MATLAB (.mat) format for analysis. A total of 49 individual hyperspectral images were captured from 39 blueberry fruits to capture multiple views or surface states. We provide 5 spectral hypercube sets of data collected with the hyperspectral camera: ‘Assisted Harvested Blueberries (AHB)’ (10 images), ‘Hand Harvested Blueberries (HHB)’ (10 images), ‘Perfect EW’ (10 images), ‘No EW’ (9 images), and ‘No EW vs. Perfect EW‘ (10 images: 5 from ‘No EW‘ and 5 from ‘Perfect EW‘). This dataset, collected and archived by the University of Waikato (WaI2M: Waikato Instrumentation and Measurement Research Group, Hyperspectral Imaging Group), enables near-infrared hyperspectral imaging research in agriculture for EW classification and detection, harvesting method classification, and fruit surface property spectral analysis using machine/deep learning methods.enLicence for published version: Creative Commons Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/blueberryclose-range hyperspectral imagingcomputer sciencenon-destructive analysispost-harvest freshnesssmart agricultureBlueberryClose-range hyperspectral imagingNon-destructive analysisPost-harvest freshnessSmart agricultureJournal Article10.1016/j.dib.2025.1119462352-340946 Information and Computing Sciences4603 Computer Vision and Multimedia Computation