PARTICLE-SIZE ANALYSIS OF TOMATO POWDER

Particle‐size information is a measure of the quality of processed food products. In this investigation, a study has been made for the particle‐size analysis (PSA) of blanched and unblanched samples of tomato powder. The outcome indicates that the standard percentile reading D (v, 0.5), D (v, 0.1) and D (v, 0.9) for blanched and unblanched tomato‐powder samples are 260.30, 308.78 and 100.49 μm and 108.57, 609.24 and 521.76 μm, respectively. Volume mean diameter [D 4,3] is higher for unblanched sample (335.87 μm) compared with blanched tomato powder (288.41 μm). Surface area mean diameter [D 3,2] is also higher for unblanched sample (200.51 μm) than blanched tomato powder (158.71 μm). Furthermore, the specific surface area (Aw) is higher for blanched sample (0.0378 m²/g) as compared with unblanched sample (0.0299 m²/g). The blanching treatment slightly affects the grinding/milling quality/size‐reduction characteristics and results in uniform particle size, which is depicted by a narrow range of particle‐size distribution of tomato‐powder samples. Blanched tomato powder is finer as compared with unblanched tomato powder. The narrow range of particle sizes of the blanched sample of tomato powder shows stability during particle‐size settlement, as it is a very important and much desirable parameter for its use in processing of another product preparation.     

PACKAGING, HANDLING and STORAGE of LIPOXYGENASE-FREE FULL-FAT SOY FLOUR

Lipoxygenase-free full-fat soy flour was prepared by hot water blanching and hot-air-oven heat treatment to raw soybeans. Whole soybeans, splits and flours of raw and treated soybeans were used to evaluate their packaging and handling characteristics in polythene bags up to 400 μm thickness. Storage quality of differently processed soy flours was judged in polythene bags of 100 μm. Polythene bags of 50 μm film thickness were judged suitable by stack load test for packaging of whole soybean, soy-splits and soy flours. For safe handling, however, the minimum film thickness of 200 μm was found to be safe as decided by the drop test. 100 μm film thickness of polythene bags was considered appropriate for safe storage up to 45 days in ambient conditions (5-36C; 6–97% rh) on account of FFA rise and change in moisture content. the lipoxygenase-free full-fat soy flour produced by dry heat was found to have better storage quality over raw and blanched soy flour. Overall, the polythene bag film thickness of 200 μm is considered for safe packaging, handling and storage of full-fat soy flour up to 45 days under ambient conditions.     

An approach to the detection of synthetic milk in dairy milk: 2. Detection of detergents

This work reports on methods to detect and estimate anionic detergents, which are important ingredients of synthetic milk formulations, based on the extraction of a detergent-Methylene Blue complex in chloroform which can be subsequently quantified by measuring the optical density at 653 nm. A base value of 0.52 for optical density was found to represent pure cows' milk. Any result above this value suggested the presence of an anionic detergent in milk.     

ANALYSIS OF BISTABLE AND OSCILLATING REACTION SYSTEMS IN PRESENCE OF AN EXTERNAL NOISE

The paper analyses a bistable and an oscillatory reaction system in the presence of an external noise. The analysis of a bistable system shows that in the normal way the inclusion of noise destroys all the deterministic solutions. In other words, the stochastic system does not admit any solution. With imposition of certain restraints it is possible, however, to get stochastic solutions in a certain region of parameter space, which in general shrinks with the extent of noise. The modality of diminishing the region of solutions is different for white and nonwhite noise and has been discussed

The paper also evaluates the influence of white and nonwhite noise on the behavior of an oscillating system and illustrates it by considering two case examples. One example indicates the conflicting role of white and nonwhite noise in bringing about the transitions from the oscillatory behavior while the second example shows no influence of white and nonwhite noise on the oscillating solution

The implications of the role of noise in analysing bistable and oscillatory systems is discussed.     

DETECTION OF ADULTRATION OF THE SPICE POPPY SEEDS (PAPAVER SOMNIFERUM) WITH AMARANTHUS PANICULATAS (RAJGEERA) SEEDS

Analysis of fat and squalene content is evaluated for determining the presence and content of Amaranthus paniculatas seeds which is used as an adulterant of the spice poppy seeds. Also evaluated are some simple physical methods to detect this adulteration. Puffing or popping at 185–195°C with stirring for 1 min could distinguish poppy seeds and its adulterant, rajgeera readily.     

ECG data compression using fast Walsh transform and its clinical acceptability

Data compression techniques can be grouped into three categories, direct and transformation compression and parameter extraction. The principles and details of ECG data compression implementation using fast Walsh transform are presented. Performance evaluation has been made on the basis of compression ratio and visual comparison. To know the extent to which the clinical information preserved in the reconstructed signal, peak and boundary measurements were made on both the reconstructed and original signal, and then compared. As the number of fast Walsh transform coefficients are reduced, the compression ratio increases. At higher compression ratios deviations in the R-peak are found to be higher than those in the other ECG peaks. Peak and boundary measurements reveal clinical acceptability of the compression algorithm, because the errors are quite tolerable. It is also worth noting that artefacts such as electromyographic noise are better eliminated because of filtering, and this also makes the signal compatible to cardiologists for visual examination. The experimental results show that a compression ratio of four is acceptable to preserve the clinical information.     

Daily prediction of short-term trends or crude oil prices using neural networks exploiting multimarket dynamics

This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predictions of crude oil prices, short-term prediction with time horizons of 1-3 days posits an important problem that is quite different from what has been studied in the literature. The problem of such short-term predicability is tackled through two aspects. The first is to examine the existence of linear or nonlinear dynamic processes in crude oil prices. This sub-problem is addressed with statistical analysis involving the Brock-Dechert-Scheinkman test for nonlinearity. The second aspect is to test the capability of artificial neural networks (ANN) for modeling the implicit nonlinearity for prediction. Four experimental models are designed and tested with historical data: (1) using only the lagged returns of filtered crude oil prices as input to predict the returns of the next days; this is used as the benchmark, (2) using only the information set of filtered crude oil futures price as input, (3) combining the inputs from the benchmark and second models, and (4) combing the inputs from the benchmark model and the intermarket information. In order to filter out the noise in the original price data, the moving averages of prices are used for all the experiments. The results provided sufficient evidence to the predictability of crude oil prices using ANN with an out-of-sample hit rate of 80%, 70%, and 61% for each of the next three days’ trends.