Background. Blueberries are considered an important source of health benefits. This work studied six blueberry cultivars: “Duke,” “Brigitta”, “Elliott”, “Centurion”, “Star,” and “Jewel”, measuring quality parameters such as °Brix, pH, moisture content using standard techniques and shape, color, and fungal presence obtained by computer vision. The storage conditions were time (0–21 days), temperature (4 and 15°C), and relative humidity (75 and 90%). Results. Significant differences ( ) were detected between fresh cultivars in pH, °Brix, shape, and color. However, the main parameters which changed depending on storage conditions, increasing at higher temperature, were color (from blue to red) and fungal presence (from 0 to 15%), both detected using computer vision, which is important to determine a shelf life of 14 days for all cultivars. Similar behavior during storage was obtained for all cultivars. Conclusion. Computer vision proved to be a reliable and simple method to objectively determine blueberry decay during storage that can be used as an alternative approach to currently used subjective measurements. 1. Introduction Blueberries have an increasing demand for popular consumption because of their nutraceutical properties [1, 2], including their high content of phenolic compounds with a wide spectrum of biochemical activities such as antioxidant, antimutagenic, cardiovascular protection, antidiabetic, vision improvement properties, and carcinogenesis inhibition [3]. Blueberries are little blue fruits of the genus Vaccinium that have short shelf life. It has been stated that under refrigeration temperatures (0°C), the shelf life of blueberries is about 14–20 days [4, 5]. The main quality indicators of the fruit are appearance (color, size, and shape), firmness or texture, flavor (soluble solids and pH), and nutritive value [6]. The color ranges from light blue to deep black blue depending on the cultivar and the presence of an epicuticular wax, which gives its attractive appearance [4]. Color changes during storage may have a profound effect on consumer acceptability [7]. Consumers demand high quality fruits which are dependent on harvest methods, cultivar characteristics, postharvest handling, and storage temperatures [1]. Computer vision (CV) is a nondestructive technology used for acquiring and analyzing digital images to obtain information of heterogeneous products. It has been regarded as a valuable tool which helps to improve the automatic assessment of food quality [8, 9]. CV has been recently used in the food industry for quality and color
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