Consumers expect product availability as well as product quality and safety in retail outlets. When designing or re-designing fruit and vegetables supply chain networks one has to take these demands into consideration next to traditional efficiency and responsiveness requirements. In food science literature, much attention has been paid to the development of Time-Temperature Indicators to monitor individually the temperature conditions of food products throughout distribution as well as quality decay models that are able to predict product quality based upon this information. This chapter discusses opportunities to improve the design and management of fruit and vegetables supply chain networks. If product quality in each step of the supply chain can be predicted in advance, good flows can be controlled in a pro-active manner and better chain designs can be established resulting in higher product availability, higher product quality, and less product losses in retail. This chapter works towards a preliminary diagnostic instrument, which can be used to assess supply chain networks on QCL (Quality Controlled Logistics). Findings of two exploratory case studies, one on the tomato chain and one on the mango chain, are presented to illustrate the value of this concept. Results show the opportunities and bottlenecks for quality controlled logistics depend on product—(e.g. variability in quality), process—(e.g. ability to use containers and sort on quality), network- (e.g. current level of cooperation), and market characteristics (e.g. higher prices for better products).
The the agriculture sector in developing countries has a large production share in the global fresh fruit market. Yet, in many cases, the land production yield indices at the orchard level are lower than the values related to more technologically developed countries. This situation leads to economic losses due to poor performance in productivity, efficiency and quality, which in turn is related to a technological and managerial gap. In this chapter, an operations management framework is proposed that tries to balance the market requirements (i.e. quality and quantity) with the capacity of the production system. This is performed through a multi-objective optimization approach that helps orchard managers synchronize the production yields with market demand and quality requirements. The model also allows the production managers to have a forecasting tool based on historical data. The model integrates the full supply chain through a set of sub-models for each stage of the production life cycle. The objective of the model is to minimize cost while maximizing sales. The optimization strategy involves a variant of the so-called NSGA II algorithm. The case study of an exporting lime packaging company is developed to illustrate the proposed framework and its possible impact on performance.
