Caesalpinia decapetala extracts as inhibitors of lipid oxidation in beef patties

In this study we investigated the effects of Caesalpinia decapetala (CD) extracts on lipid oxidation in ground beef patties. Plant extracts and butylated hydroxytoluene (BHT) were individually added to patties at both 0.1% and 0.5% (w/w) concentrations. We assessed the antioxidant efficacy of CD by the ferric reducing antioxidant power (FRAP) assay and evaluated their potential as natural antioxidants for meat preservation by thiobarbituric acid reactive substance (TBARS) values, hexanal content, fatty acid composition and color parameters. These were tested periodically during 11 days of refrigerated storage. TBARS levels were significantly lower (p ≤ 0.05) in the samples containing plant extracts or BHT than in the non-treated control. In addition, the beef patties formulated with the selected plant extracts showed significantly (p ≤ 0.05) better color stability than those without antioxidants. These results indicate that edible plant extracts are promising sources of natural antioxidants and can potentially be used as functional preservatives in meat products.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.