Kiwi Fruit IoT Shelf Life Estimation During Transportation with Cloud Computing

The outlook of maintaining higher quality perishable food sparks a lot of interest in the agriculture business. Food security is an important aspect to meet the demand of the growing population. For instance, postharvest losses amount to 1.3 billion tons a year which amounts to 33 percent of production as stated by the Food and Agriculture Department of United States. Real time monitoring of the supply chain can provide insight on perishable food to better handle pricing and allow respective stakeholders to act accordingly to maintain quality standards. Shelf life is described as the duration of a product to be safely consumed by the microbiological standards and retaining a desired sensory, physico-chemical and nutritional quality. Arrhenius equation is commonly used in the assessment of food quality albeit time consuming. The proposed approach with multiple linear regression (MLR) model is designed to estimate the lowest possible shelf life outcome given the monitoring condition during transportation.