Practical method for table grape selection using multicriteria decision analysis

Abstract

The São Francisco Valley (Pernambuco-PE, Brazil) is of great importance for the local economy, since the region represents a large portion of Brazilian production and export of fresh grapes. Traditional methods of feasibility analysis involve only cost or productivity analyses, but for the grape growers there must be techniques and methods that assist decision making involving other criteria with characteristics of the grape. Yet, there is a noticeable lack of multi-criteria methods that assist the grower in making decisions for selection of commercial table grape cultivars for the feasibility analysis. Thus, the aim of the present study is to select table grape cultivars through multiple criteria, using a new method for eliciting scale constants: the Flexible and Interactive Tradeoff (FITradeoff), for the purpose of assisting a rural producer to expand production while minimizing inconsistencies in the decision-making process. With the assistance of a decision maker, the Decision Matrix and Consequence Table were constructed on Microsoft Excel® – composed by 11 criteria and 3 alternatives, all closed source grape cultivars (with patents). Then, the data were applied on the FITradeoff software for the ranking problematic. Thus, it was possible to arrive at a ranking of the best alternatives, where the cultivar Timpson (SNFL) (U2) was found to be the optimal solution proposed for the rural producer. The application of FITradeoff provided a satisfactory result with little time and effort spent, leading to a final suggestion for the decision maker. In addition, at the end of the process, it provided graphical visualization of the performance and dominance of each criterion selected, as well as a ranking of the grape cultivars through the Hasse Diagram, with the order of the best alternatives. Ordering the grape genotypes considering Multi-Criteria Decision Analysis methods is crucial to selection of commercial table grape cultivars. The method can be applied to other segments of agriculture that require multi-criteria evaluations.