Efficient storage and transport of fresh produce are critical for maintaining product quality and minimising postharvest losses across the supply chains. Temperature fluctuations and package/container gas compositions, particularly of oxygen (O2) and carbon dioxide (CO2), can accelerate respiration, leading to spoilage and economic loss. Existing controlled atmosphere systems often rely on gas sensors, complex control units and infrastructure, making them economically unfeasible for low-cost storage or transport applications. Modified Atmosphere (MA) systems, including perforated packages and membrane-based storage boxes, are ineffective under dynamic/variable environmental conditions, such as temperature, O2 and CO2 composition, as they are unable to modify the gas transmission rates or their permeability in real-time. This study addressed this gap through the development and validation of a stand-alone, compact, microcontroller-based gas control system that dynamically regulated dual gases such as O2 and CO2 without the need for gas sensors or external gas cylinders, making it suitable for MA storage and transport of different types of fruit and vegetables. The system includes a miniature air blower and tube for fresh air exchange to regulate O2, a second blower to direct air through a soda-lime reactor within the box for CO2 removal, and a thermistor to monitor the fresh produce temperature. A Teensy microcontroller was used to run a temperature-dependent mathematical model to predict the respiration rate of the stored produce and calculate the required blower ON frequency (BOF) for both O2 and CO2 control. An e-paper display provided real-time updates of temperature, predicted gas concentrations and respiration rate. The research was structured into four hypotheses. The first hypothesis included the development of a mathematical model to predict respiration rates based on dynamic temperature and gas composition. This model integrated the Arrhenius equation to capture the effects of temperature, the Michaelis–Menten kinetics to describe O2 dependence and an uncompetitive inhibition term to test the influence of CO2. The internal gas composition was governed by the mass balance of gases between the fresh produce respiration and the blower airflow. This model enabled the calculation of blower ON time to regulate O₂ concentration in real-time based on fresh produce temperature inside the box. Experimental validation using 25 kg of broccoli in a 190L box demonstrated that the system could maintain O₂ at 3.8 ± 0.29% under fluctuating temperatures (4–23°C) for 8 days, while also preserving product quality with minimal weight loss (<3%) and acceptable color change (ΔE < 5). The second hypothesis focused on evaluating the model’s sensitivity in regulating the O2 concentration. It investigated the effect of variations in key parameters, including product respiration rate, supply chain temperature, gas diffusion rate, product mass and storage volume, on the model’s performance and stability in maintaining O2 within the storage/transport box. Monte Carlo simulations revealed that over 80% of BOF variability was driven by just a few key parameters, particularly product weight and respiration rate. The sensitivity analysis identified the most influential parameters, which affected BOF values, and BOF followed a normal distribution with a mean of 47.84 ± 3.69 seconds, highlighting the need to prioritize these factors. Despite the variability, the system maintained O2 concentration at 3.8 ± 0.29 % and CO2 at 14.4 ± 0.66 % and proved the robustness of the model using the validation experiment, containing a 70-litre box with 16 kg of broccoli. The sensitivity analysis paved the way for the development of a respiration model using minimal-data with only impactful parameters, with fewer experiments for their estimation, to make it easy for practical application in the real-time supply chain. The elevated CO2 concentration observed in the storage box prompted the need to find out the control mechanism for CO2. The third hypothesis involved integrating a CO₂ control strategy using soda-lime in an active adsorption reactor. CO₂ adsorption kinetics were modelled using the Weibull function, with temperature dependence described by the Arrhenius equation. Experiments showed that soda-lime maintained CO₂ levels at 4.3 ± 1.8% in a 70L box containing 16 kg of broccoli, provided relative humidity was maintained above 80%. Moisture availability and temperature were found to significantly influence the reaction rate and adsorption efficiency. The final hypothesis combined O2 and CO2 control in a single system, tested on 30 kg of apples over 21 days under dynamic temperatures (5–23°C). The respiration model with minimal-data approach required only four experiments for parameter estimation and proved effective. The system automatically maintained O2 at 1.9 ± 0.4% and CO2 at 3.0 ± 0.5% without gas sensors and generators, by dynamically adjusting the blower operation. This research offered a scalable, gas sensor-independent, moderately precise MA system for dynamic control of O2 and CO2 for extending produce freshness during storage and transport. The approach can be extended to different commodities by adjusting for respiration parameters and CO₂ sensitivity.
Yogesh Bhaskar Kalnar (Thu,) studied this question.