Vinod K. Jindal

The effects of cooking water‐to‐rice (W/R) ratio on the sensory characteristics of cooked rice eating quality of 14 varieties of Thai rice were investigated in relation to their physicochemical properties. Milled rice samples were cooked with five W/R ratios ranging from 1.3 to 2.5 on a weight basis and presented to 12 trained panelists for sensory evaluation. A three‐way analysis of variance and a principal component analysis identified the intensity of sensory hardness as the main characteristic of cooked rice. It decreased with increasing W/R ratio whereas sensory stickiness decreased. The overall acceptability based on appearance, texture and flavor attributes reached peak levels corresponding to optimum W/R ratios for different rice varieties, and was highly correlated with sensory hardness and stickiness. Partial least squares regression models of optimum W/R ratio and peak overall acceptability gave coefficients of determination of 0.991 and 0.980, respectively, thus indicating that the optimum W/R ratio and the acceptability ratings of cooked rice could be reliably predicted from the physicochemical properties such as the apparent amylose content, protein content, gel consistency, alkali‐spreading value and grain elongation ratio of milled rice. PRACTICAL APPLICATIONS: Sensory evaluation of cooked rice eating qualities is a difficult task to carry out routinely on a day‐to‐day basis. Presently, rice varieties are categorized according to grain dimensions and selective physicochemical traits that reflect on the eating quality of cooked rice. Though it has been long realized that the amount of water used for cooking and rice physicochemical properties highly influence the eating quality of cooked rice, no information is currently available on the quantitative evaluation of these factors. Results of this study showed that models could be developed to quantify the optimum amount of water for cooking rice of different varieties with the most desirable sensory eating qualities. The prediction of peak overall sensory acceptability scores that correspond to the optimum cooking water‐to‐rice ratio could be useful for categorizing rice varieties based on their impact on sensory eating quality and for the development of baseline information for consumers by the rice industry.

The crispness of selected snack foods, Pringles potato chips, Paprika extruded snack and Munchy crackers, was evaluated by crushing the snack samples with a pair of pincers, and analyzing the frequency domain spectra of acoustic patterns by the neural networks (NNs). The inputs for training the NNs comprised 102 amplitudes of sound signals in 0–7 kHz frequency range at the intervals of about 69 Hz with moisture content or crispness grades as outputs. Both backpropagation (BPNN) and probabilistic (PNN) models showed good performance in classifying the snack foods into four grades of sensory crispness. The prediction accuracy of PNN models ranged approximately from 96 to 98% and was higher than the accuracy of BPNN models by about 10 to 25%. Results showed that frequency domain spectra of acoustic signals could be successfully analyzed by the NNs for predicting the crispness of snack food products.

Texture degradation in potatoes was investigated during heating of cylindrical test samples, 15 mm diameter and 30 mm long, in water at 60, 70, 80 and 90C by mechanical testing. The rheological parameters obtained from the axial and radial compression, creep and stress relaxation tests decreased exponentially with an increase in heating duration and temperature approaching steady levels corresponding to the remaining texture after prolonged heating. A single first‐order kinetic model described the changes in various rheological parameters due to thermal softening of potatoes using fractional conversion technique indicating very high values of the coefficient of determination (R² > 0.97). In general, the visco‐elastic test parameters were relatively more sensitive to texture degradation in potatoes in comparison with the quasi‐static test parameters. Overall comparison showed that elasticity and viscosity parameters in Kelvin component of the 4‐element model (E₂ and η₂) from creep tests and elasticity moduli from axial and radial compression tests (E_a and E_r) best presented the texture degradation kinetics in potatoes with R² ranging from 0.98 to 0.99.

The changes in the texture of cylindrical samples of potato tissues immersed in water at 60, 70, 80 and 90C for up to 80 min were monitored at each temperature in terms of tangent modulus of elasticity in axial and radial compression tests, and elasticity and viscosity parameters in creep and stress relaxation tests. The magnitude of all mechanical test parameters decreased with an increase in heating time and temperature. The creep and stress relaxation responses of individual potato samples were adequately represented by respective mechanical models (R²= 0.94 to 0.99). The mechanical test parameters followed apparent first‐order degradation kinetics due to the effect of thermal softening, and the rate constant was used as an index of the sensitivity of a mechanical test. The radial compression test was relatively more sensitive than the axial test. Based on an overall comparison, the parameters from creep and stress relaxation tests were found to be the most sensitive in describing the textural changes during thermal softening of potatoes.

Simple and inexpensive tests are described for rapid qualitative assessment of the microbiological quality of raw milk. These tests included the monitoring of dissolved oxygen levels and changes in...