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The objective of this research was to study the influence of different blanching conditions on potato stick color, oil uptake and water activity (A w ), and optimize the process by means of the desirability function. Color was expressed as properties of L*a*b* and L*C*h* spaces, some of which were fitted by Box-Behnken quadratic models. The blanching optimum conditions were as follows: a concentration of ascorbic acid of 0.2 g/100 g potato, a time of 5.5 min and a temperature of 69C. Responses obtained when using these conditions were -1.68 a* value and -86.31°h* value, which represent a hue in potatoes unaffected by the enzymatic browning. Regarding oil uptake, some of the blanched sticks absorbed 31% less oil than the control. Regarding A w , all blanched samples presented lower values than the control, suggesting that blanching increases the shelf life of fried potatoes. PRACTICAL APPLICATIONSThis article presents that the optimized blanching process conditions were able to control the enzymatic browning in potato sticks prior to frying, and thus improved their quality. Furthermore, some blanching conditions were found to decrease by 31% the oil uptake in potato sticks, leading to healthier fried potatoes. Finally, blanching significantly decreased the A w in all fried potato sticks evaluated, suggesting that this process is also a way to increase the shelf life of fried potatoes.

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The estimation of equivalent sweet concentrations of high‐intensity sweeteners is one of the first steps for the substitution of sucrose during the development of low‐calorie products. The aim of this work was to compare two sensory methodologies (paired comparison and magnitude estimation) and two data analysis approaches (logistic regression and survival analysis) to estimate equivalent sweet concentration of high‐intensity sweeteners, using orange/pomegranate juice as case study. Three low‐calorie sweeteners were considered: sucralose, stevia and monk fruit extract. For each sweetener, a series of six orange/pomegranate juice samples with different sweetener concentration were prepared. Three groups of 100 consumers participated in the study. Each group was randomly divided into two groups of 50, each of which evaluated samples using one of the two methodologies (paired comparison and magnitude estimation). Paired comparison and magnitude estimation provided similar estimations for the three high‐intensity sweeteners which were in agreement with published data, regardless of the statistical approach used for data analysis. However, logistic regression and survival analysis differed in the accuracy of the estimations. Practical Applications Paired‐comparison and magnitude estimation provided similar estimations. However, due to its simplicity and perceived ease participants, paired comparison seems to be the recommended approach for the estimation of equivalent sweet concentrations of high‐intensity sweeteners with consumers. Data analysis should be performed using survival analysis to obtain more accurate estimations.