Psychophysical comparisons seem to show that obese individuals experience normal sweet and fat sensations, they like sweetness the same or less, but like fat more than the non-obese do. These psychophysical comparisons have been made using scales (visual analogue or category) that assume intensity labels (e.g. extremely) which denote the same absolute perceived intensity to all. In reality, the perceived intensities denoted by labels vary because they depend on experiences with the substances to be judged. This variation makes comparisons invalid. Valid comparisons can be made by asking the subjects to rate their sensory/hedonic experiences in contexts that are not related to the specific experiences of interest. Using this methodology, we present the evidence that the sensory and hedonic properties of sweet and fat vary with body mass index. The obese live in different orosensory and orohedonic worlds than do the non-obese; the obese experience reduced sweetness, which probably intensifies fat sensations, and the obese like both sweet and fat more than the non-obese do. Genetic variation as well as taste pathology contribute to these results. These psychophysical advances will impact experimental as well as clinical studies of obesity and other eating disorders.

Although human perception of food flavors involves integration of multiple sensory inputs, the most salient sensations are taste and olfaction. Ortho- and retronasal olfaction are particularly crucial to flavor because they provide the qualitative diversity so important to identify safe versus dangerous foods. Historically, flavor research has prioritized aroma volatiles present at levels exceeding the orthonasally measured odor threshold, ignoring the variation in the rate at which odor intensities grow above threshold. Furthermore, the chemical composition of a food in itself tells us very little about whether or not that food will be liked. Clearly, alternative approaches are needed to elucidate flavor chemistry. Here we use targeted metabolomics and natural variation in flavor-associated sugars, acids, and aroma volatiles to evaluate the chemistry of tomato fruits, creating a predictive and testable model of liking. This nontraditional approach provides novel insights into flavor chemistry, the interactions between taste and retronasal olfaction, and a paradigm for enhancing liking of natural products. Some of the most abundant volatiles do not contribute to consumer liking, whereas other less abundant ones do. Aroma volatiles make contributions to perceived sweetness independent of sugar concentration, suggesting a novel way to increase perception of sweetness without adding sugar.

Fresh strawberries (Fragaria x ananassa) are valued for their characteristic red color, juicy texture, distinct aroma, and sweet fruity flavor. In this study, genetic and environmentally induced variation is exploited to capture biochemically diverse strawberry fruit for metabolite profiling and consumer rating. Analyses identify fruit attributes influencing hedonics and sensory perception of strawberry fruit using a psychophysics approach. Sweetness intensity, flavor intensity, and texture liking are dependent on sugar concentrations, specific volatile compounds, and fruit firmness, respectively. Overall liking is most greatly influenced by sweetness and strawberry flavor intensity, which are undermined by environmental pressures that reduce sucrose and total volatile content. The volatile profiles among commercial strawberry varieties are complex and distinct, but a list of perceptually impactful compounds from the larger mixture is better defined. Particular esters, terpenes, and furans have the most significant fits to strawberry flavor intensity. In total, thirty-one volatile compounds are found to be significantly correlated to strawberry flavor intensity, only one of them negatively. Further analysis identifies individual volatile compounds that have an enhancing effect on perceived sweetness intensity of fruit independent of sugar content. These findings allow for consumer influence in the breeding of more desirable fruits and vegetables. Also, this approach garners insights into fruit metabolomics, flavor chemistry, and a paradigm for enhancing liking of natural or processed products.

This paper deals with experimental designs used in conjoint analysis. The described approach permutes the structure of the underlying fractional experimental design to make different sets of combinations. The resulting experimental designs, suggested to be called Isomorphic Permuted Experimental Designs (IPED), are statistically equivalent to each other while combining diverse sets of the variables and levels into different designs. By facilitating distinctive individual designs (for each respondent), IPEDs reduce a bias caused by some possibly unusually strong performing combinations, and allow detection and estimation of interactions among variables, as well as identification of pattern‐based segments emerging from individual models of utilities. This paper examines the theoretical foundation of the approach, formalizes the methodology for algorithmic implementation and shows a practical example of utilization. PRACTICAL APPLICATIONS Isomorphic Permuted Experimental Design (IPED) allows for overcoming multiple interlinked statistical problems that affect the traditional conjoint analysis approaches, thus leading to more reliable and targeted results in practice. IPED facilitates individual respondents' models based on unique designs, thus allowing for pattern‐based segmentation. The approach also allows for the detection of any and all interactions between the elements (features) of the experiments, thus increasing the reliability of conjoint analysis results. It has been utilized in many practical applications, such as for message optimization, early stage new product development, advertising, package and website optimization.