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.

中文翻译：

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水果和蔬菜保质期估算的实时监控系统。


控制影响易腐烂产品质量的主要环境因素是食品行业的主要挑战之一。温度是影响品质的主要因素，但相对湿度和气体浓度（主要是C2H4、O2和CO2）等其他因素对于维持园艺产品的采后品质也发挥着重要作用。因此，监测此类环境因素是确保整个保质期内质量和评估损失的关键程序。因此，为了估计易腐产品在储存和运输过程中可能遭受的质量损失，开发了实时监控系统。由于其 Wi-Fi 无线通信架构，该系统可用于所有收获后步骤。以生菜为模型进行了多项实验室试验，以确定不同储存温度条件下保质期内的质量评级标准。因此，提出了一个与温度和最大保质期相关的多重非线性回归（MNLR）模型。该模型将允许预测当储存或运输过程中出现不适当的温度时商品将缩短其理论保质期的天数。该系统是作为基于传感器的工具而开发的，已在欧洲各地的几次陆路运输旅行中进行了测试。