The assessment of blueberry fruit quality is traditionally conducted through laboratory equipment. Despite its high accuracy, this method remains destructive, labor-intensive, time-consuming, and costly. Consequently, there is a pressing need for innovative solutions such as image-based and artificial intelligence (AI)-driven analysis. To address these limitations, this study aimed to analyze whether an approach based on mobile image-based analysis combined with machine learning (ML) algorithms could develop a non-destructive framework for evaluating blueberry fruit quality, specifically focusing on total soluble solids (TSS) and firmness. Firstly, we collected numerous blueberry samples during the maturity stage to construct a comprehensive dataset. These samples were meticulously analyzed in a laboratory for diameter, TSS, firmness, and color. Simultaneously, RGB images were captured using a mobile device. These images were processed to extract spectral bands (red, green, and blue). Eight ML algorithms were employed to develop predictive models capable of predicting the qualitative parameters of the blueberries. Initially, correlation analysis demonstrated that RGB images suggestively contribute to fruit quality assessment (r < 0.41). However, the integration of ML algorithms significantly enhanced the predictive accuracy of these models (R² = 0.71–0.99, MAE = 0.003–0.28, and RMSE = 0.004–0.31). This innovative approach differs from existing methods by providing a non-destructive, cost-effective, and efficient alternative to assess blueberry fruit quality. Our findings, therefore, confirm the applicability of mobile images for supporting high-quality blueberry harvesting. These advancements can potentially reduce labor costs, increase yield quality, and support advancements in precision agriculture.

Blueberries are produced worldwide due to their high demand and antioxidant benefits. Berry quality, including texture, flavor, and antioxidant properties, influence consumer preferences and marketability. Harvesting blueberries at shorter intervals is essential for maintaining fruit quality, including firmness and flavor, while also minimizing postharvest losses. This study investigated the effects of delayed harvests on the postharvest quality of ‘Meadowlark’, a highbush blueberry, and ‘Brightwell’, a rabbiteye blueberry, harvested from two different locations in South Georgia in 2022 and 2023. The treatments consisted of harvest dates, with two harvests in 2022 and three harvests in 2023, followed by three storage-duration treatments (7, 14, and 21 days of storage) to evaluate postharvest quality. Fruit firmness, berry diameter, color, total soluble solids, titratable acidity, berry damage (%), and anthocyanin concentration were assessed at harvest and following storage days. In both cultivars, harvest 1 showed higher fruit firmness and storability compared with harvests 2 and 3 in 2023. During storage, the decline in firmness was higher in harvests 2 and 3 compared with harvest 1. Fruit from the delayed harvests exhibited the highest percentage of berry damage both at harvest and after 21 days of storage. Anthocyanin concentration varied across cultivars and years, with berries from harvest 2 having a higher anthocyanin concentration at harvest in 2022 and 2023 in the Brightwell cultivar. Overall, this study highlights the importance of optimizing harvest dates to maintain the postharvest quality and shelf life of blueberries.

Sanitation is a crucial postharvest operation that aims to reduce the microbiological load of harvested produce. Currently, in the southeastern United States, peach packing houses use chemical oxidizers, such as sodium hypochlorite (NaOCl) in their hydrocooling systems to treat the fruit and suppress foodborne pathogens postharvest. This study aims to evaluate the effectiveness and efficiency of a novel sanitation technology called high-oxygen water (HOW) as an alternative to NaOCl. It is based on the generation of stable nanobubbles of oxygen (O ₂ ) in water in combination with gaseous ozone (O ₃ ) without the need for chemicals. The suspended solution has the potential to reduce microorganism loads during the exposure period and prevent the growth of microorganisms during storage. This technology could serve as an effective sanitation treatment for peaches during hydrocooling. Peaches were treated using HOW at various concentrations of dissolved oxygen (10, 20, and 30 mg·L ⁻¹ ) combined with saturated (approximately 8 mg·L ⁻¹ ) O ₃ . These treatments were compared with a standard NaOCl treatment (50 mg·L ⁻¹ of free chlorine). Our team evaluated the effects of HOW by assessing postharvest fruit quality changes and decay incidence over time. The results indicated that while HOW treatments showed potential in maintaining postharvest quality, high concentrations of O ₃ were detrimental to fruit quality, causing increased decay incidence compared with the NaOCl treatment.

Editorial: Postharvest Ripening, Senescence, and Technology