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ARS Home » Pacific West Area » Parlier, California » San Joaquin Valley Agricultural Sciences Center » Commodity Protection and Quality Research » Research » Publications at this Location » Publication #396314

Research Project: Improved Systems-based Approaches that Maintain Commodity Quality and Control of Arthropod Pests Important to U.S. Agricultural Production, Trade and Quarantine

Location: Commodity Protection and Quality Research

Title: Transitioning to machine harvesting blueberries for fresh market

item YANG, WEI - Oregon State University
item TAKEDA, FUMIOMI - Retired ARS Employee
item ZHANG, MENGYUN - Shihezi University
item LI, CHANGYING - University Of Georgia
item SARGENT, STEVEN - University Of Florida
item DEVETTER, LISA - Washington State University
item BEAUDRY, RANDY - Michigan State University
item Obenland, David - Dave
item Saito, Seiya
item Xiao, Chang-Lin

Submitted to: Acta Horticulturae
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/4/2024
Publication Date: 3/5/2024
Citation: Yang, W.Q., Takeda, F., Zhang, M., Li, C., Sargent, S.A., Devetter, L., Beaudry, R., Obenland, D.M., Saito, S., Xiao, C. 2024. Transitioning to machine harvesting blueberries for fresh market. Acta Horticulturae. 1381: 392-400.

Interpretive Summary: Machine harvesting of fresh-market blueberries is becoming increasingly prevalent in the United States but bruising of the berries caused by this method of harvesting is an important consideration. This research helps to describe the relationship between bruising and firmness as well as showing means to sort bruised from undamaged blueberries. To create mechanical damage in the fruit, blueberries were dropped on a rigid plastic plate. A novel imaging system, using various wavelengths of light, was employed to locate and quantify internal bruise damage using machine learning. The effectiveness of the system was confirmed by slicing the same fruit and visually assessing the bruising. Firmness in the bruised areas was found to be significantly less firm than regions of the berry without bruising. In a separate study, prediction of bruising was also possible in machine harvested berries that had been stored in the cold for 3 weeks. The relationship between internal bruise size and firmness in this fruit, however, was weak. This imaging system enables the rapid non-destructive evaluation of machine harvested blueberries for bruising and should be of great value to the blueberry industry.

Technical Abstract: Increasingly more fresh-market blueberries in the United States are machine harvested. Machine-harvested blueberries have more internal bruise damage and shorter shelf life than those harvested by hand. Recent changes by harvester manufacturers, particularly in the fruit catching system, have reduced internal bruise damage. New research is developing the technology to sort bruised blueberries out of the supply chain. This paper describes the relationship between bruise damage and fruit firmness in mechanically impacted blueberries. To create mechanical impact damage in the fruit, blueberries were dropped on a rigid plastic plate. A novel, hyperspectral imaging system (HSI) was employed as a non-destructive method that can locate and quantify internal bruise damage. A reflective HSI distinguished the bruised area from non-bruised area in the fruit and a deep learning-based web application quickly determined the blueberry bruise levels. A FirmTech II instrument measured fruit firmness at the impacted area and 90° and 180° from the bruised area. A visual method verified bruise damage after slicing the fruit through the equatorial axis. FirmTech II measurements indicated that fruit firmness was significantly lower at the impacted zone compared to the other two fruit locations or for non-dropped blueberries. In a separate study, machine-harvested blueberries were cold stored for 3 weeks and analyzed for firmness and internal bruise damage. The linear regression between the bruise area predicted by the non-destructive HSI system and the destructive visual method was highly correlated. The correlation between internal bruise size and fruit firmness in machine-harvested, cold stored blueberries was weak. The combination of these methods and innovative technologies will enable blueberry breeders, growers, and packers to rapidly evaluate berry internal bruises created by mechanical harvesters. The HSI system is a powerful tool for non-destructive separation of bruised and non-bruised fruit in machine-harvested blueberries.