Combining Experiments and Mechanistic Modeling to Compare Ventilated Packaging Types for Strawberries from Farm to Retailer

Soft fruits like strawberries are highly perishable and susceptible to postharvest decay caused by fungal infestation. Elevated temperatures in the cold chain favor mold growth and water condensates in the packaging that is induced by temperature fluctuations at high relative humidity. Optimal packaging for these products is required to improve homogenous fruit cooling and ventilation inside the package along the entire supply chain. This study analyzed three packaging types (top sealed paperboard, open and closed plastic clamshell) through laboratory storage experiments and simulations. We tested the different packages in a climate chamber, with conditions representing an actual supply chain from farm to retailer. We evaluated the performance of these packages by quality measurements. We measured the fruit mass loss, total soluble solids and acidity content, firmness, color change, and incidence of decay. We also built physics-based models for the strawberries and packaging to gain complementary information that is difficult to quantify experimentally. These models rely on mechanistic simulations and sensor data to capture fruit’s hygrothermal and physiological evolution. To this end, we used monitored sensor data from the lab experiments as input for these physics-based digital fruit twins. We quantified in-silico the time of wetness due to condensation, respiration-driven overall fruit quality, and remaining shelf life along the simulated supply chain. Altogether, our simulation findings revealed that the top sealed paperboard packaging had the best performance in terms of respiration-dependent quality, mass loss and time of wetness. Furthermore, this package showed the least heterogeneities of fruit quality attributes inside the packaging, most likely due to the presence and position of ventilation holes. No clear differences were observed during laboratory experiments in rot incidence and traditional measured quality metrics (i.e., total soluble solids, acidity, color). Combining experiments with mechanistic modeling provides a deeper understanding of how fruit evolves in a supply chain. Also, it can capture packaging evaluating metrics, including moisture loss, time of wetness, or risk for microbial decay in a spatiotemporal manner. This paper presents a dual approach aiming to evaluate the packaging performance of a ventilated clamshell (open & closed) and a top sealed paperboard tray for strawberry fruits. To this end, we combine laboratory experiments with physics-based simulation in order to evaluate complementary metrics of fruit quality and marketability. We link the experiment and simulations with sensor data for hygrothermal environmental conditions representing an actual supply chain from farm to retailer, so spanning a large part of the postharvest supply chain. We analyze the impact of a commercial import supply chain, having segments with different hygrothermal conditions, on condensation occurrences and fruit quality. Classical quality parameters (i.e., total soluble solids (TSS), acidity, mass loss, firmness, color) and the amount of decay of naturally infected strawberries (cv. 'Murano') are assessed with storage and shelf life experiments. By physics-based digital twin models built for strawberries and tested packages, additional parameters are determined (i.e., volume-averaged fruit temperature, respiration-driven fruit quality, mass loss, and residence time of the condensate). Thereby, we gain complementary insights regarding the spatial heterogeneity within a package and critical areas with a high risk of condensation, among others. This information is unique and otherwise difficult to assess experimentally. Furthermore, we propose a concept for future packaging analyses that include experiments in climacteric chambers with enhanced control of hygrothermal conditions using real monitoring sensor data. Combined with simulation experiments, this will improve future packaging evaluations to identify and design an optimal package type from farm to fork.