The control of the main environmental factors that influence the quality of perishable products is one of the main challenges of the food industry. Temperature is the main factor affecting quality, but other factors like relative humidity and gas concentrations (mainly C2H4, O2 and CO2) also play an important role in maintaining the postharvest quality of horticultural products. For this reason, monitoring such environmental factors is a key procedure to assure quality throughout shelf life and evaluate losses. Therefore, in order to estimate the quality losses that a perishable product can suffer during storage and transportation, a real-time monitoring system has been developed. This system can be used in all post-harvest steps thanks to its Wi-Fi wireless communication architecture. Several laboratory trials were conducted, using lettuce as a model, to determine quality-rating scales during shelf life under different storage temperature conditions. As a result, a multiple non-linear regression (MNLR) model is proposed relating the temperature and the maximum shelf life. This proposed model would allow to predict the days the commodities will reduce their theoretical shelf-life when an improper temperature during storage or in-transit occurs. The system, developed as a sensor-based tool, has been tested during several land transportation trips around Europe.
Monitoring the main environmental conditions during storage and transportation of perishable foods is necessary to predict quality losses throughout shelf life. By far, temperature is the main factor affecting quality and shelf life, but there are other variables that would greatly affect quality losses such us relative humidity, O2, CO2, ethylene, etc. Thus, the real-time knowledge of the evolution of these parameters during the whole supply chain allows suppliers to prevent for food losses. This paper deeply describes the design of a flexible monitoring system with real-time communication to be used in the supply chain of perishable commodities, using Wi-Fi wireless communication as collaborative networks between different measurement points. Aspects such as consumption, performance and feasibility of the system are described in detail to check the adaptability of its use.