 Development of DNA sequence comparison technique is an active research activity in computational biology application.Commonly techniques studied are dynamic programming and heuristic algorithms. Exhaustive dynamic programming algorithm produces optimal result but requires longer time and bigger space. Heuristic algorithm gives approximate results with much faster processing. We have developed a new model that improves the speed of large scale DNA sequence similarity search and at the same time the best possible alignment result is retained. The model is known as a guided dynamic programming approach for DNA sequence similarity search (FRA-Search). Two approaches are used to complete the FRA-Search model: an automaton based exact string matching algorithm is employed to skip irrelevant database sequences from being computed for dynamic programming alignment processing and; the rough sets theory has been employed to classify and reduct the dataset. This paper discusses the parallel model for FRA-Search application. The parallel FRA-Search model is implemented on PC-based cluster system. It is developed on a single program multiple data (SPMD) architecture and MPJ Express software is used as a communication interface protocol between processors.

Green and cured (seven days at 29°C and 90% RH) 'Centennial' sweet potato roots were used to make and evaluate frozen and canned mashes and canned whole roots. Fried patties and pies were made from each of the processed products. The frozen mash from green roots was higher in pH while the canned mash from green and cured roots was lower in pH and higher in viscosity. The canned mash had the lowest 'L' and 'a' readings but was rated the highest in color score when made into pies. However, the fried patties were scored higher in color when made from frozen mashes or canned whole roots. Moreover, pies made from low viscous mashes were scored low in texture.

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