An investigation of sugar extraction methods and the use of microwave power for date syrup processing: efficiency and color related considerations.

This study investigates the effect of extraction methods on the color of date syrup and the potential use of microwave power for syrup processing. Sugar solutions were extracted from dates by boiling, soaking and blending. Color and sugar content of the extracted solutions were measured, and the percentage of sugar extracted form the total fruit sugar determined. Boiling was found to be the most efficient method of extraction whereby 74% of total samples sugar was extracted. In contrast, only 54.2% of fruit sugar was extracted by blending and 42% by soaking. In addition, solutions extracted by soaking and blending had a foaming problem in the subsequent concentration process. The extraction method had no effect on the product final color. The extracted solution was concentrated using two heating methods: conventional and microwave heating at a 600 W capacity and a frequency of 2450 MHz applied at three power levels: 10, 7, and 6. In the heating process, 180 minutes were needed to achieve a 77% degrees Brix using convective heating, while it took 81, 138, and 166 minutes of microwave heating at power level 10, 7, and 6, respectively to achieve the same concentration. Water activity of the syrup was measured within a sugar content range of 50 to 80% degrees Brix and the sugar concentration at which the product is shelf stable was determined at 76%.     

Itemset trees for targeted association querying

Association mining techniques search for groups of frequently co-occurring items in a market-basket type of data and turn these groups into business-oriented rules. Previous research has focused predominantly on how to obtain exhaustive lists of such associations. However, users often prefer a quick response to targeted queries. For instance, they may want to learn about the buying habits of customers that frequently purchase cereals and fruits. To expedite the processing of such queries, we propose an approach that converts the market-basket database into an itemset tree. Experiments indicate that the targeted queries are answered in a time that is roughly linear in the number of market baskets, N. Also, the construction of the itemset tree has O(N) space and time requirements. Some useful theoretical properties are proven.