Currently, optical imaging techniques are extensively employed to automatically sort agricultural products based on various quality parameters such as size, shape, color, ripeness, sugar content, and acidity. This methodological review article examined different machine vision techniques, with a specific focus on exploring the potential of fluorescence imaging for non-destructive assessment of agricultural product quality attributes. The article discussed the concepts and methodology of fluorescence, providing a comprehensive understanding of fluorescence spectroscopy and offering a logical approach to determine the optimal wavelength for constructing an optimized fluorescence imaging system. Furthermore, the article showcased the application of fluorescence imaging in detecting peel defects in a diverse range of citrus as an example of this imaging modality. Additionally, the article outlined potential areas for future investigation into fluorescence imaging applications for the quality assessment of agricultural products.

Three blueberry cultivars (‘San Joaquin’, ‘Jewel’, and ‘Snowchaser’) were harvested at commercial maturity and subjected to different degrees of fruit surface bloom removal (full natural bloom (FB), partial bloom (PB), and removed bloom (RB)) to assess the importance of the bloom to consumer preference. Sensory evaluation assessed flavor, appearance, and overall acceptance under different conditions (darkness and light). Panelists preferred berries with at least some degree of bloom, as influenced by appearance for all varieties, and in ‘Snowchaser’ and ‘Jewel’, flavor acceptance declined when the evaluation allowed the fruit to be visualized. Panelists were prompted to select the attribute most influencing their affective evaluations to better understand the basis for the differences due to the presence of bloom. FB and PB were rated as more appealing, except for ‘Jewel’, where PB was deemed unattractive. At the same time, bloom presence influenced firmness choices, and sweetness and tartness preferences were affected by both variety and evaluation conditions, suggesting complex interactions in multisensory perception. Principal component analysis reinforced the idea that treatments with bloom removal were less accepted overall, while ‘Snowchaser’ samples were consistently well-liked relative to the other two varieties. These findings highlight the importance of bloom presence in blueberry quality perception and consumer behavior.