Acoustic settings combination as a sensory crispness indicator of dry crispy food

Effects of the extrusion conditions, the addition of oil and the food matrix on the physical and sensory characteristics of pre-extrusion flavored products

Thermoplastic extrusion is important in processing a wide variety of food products. In this paper, the effects of different extrusion conditions, addition of vegetable oil and the food matrix itself on the physical and sensory characteristics of corn snacks and meat analogs were evaluated. Cysteine and butyric acid (cheese aroma precursors) and thiamine (a meat aroma precursor) were added to corn grits and soy protein concentrate, respectively, before extrusion. For each matrix, three combinations of moistures of the raw material and extrusion temperatures were used and, after extrusion, vegetable oil was added to one portion of each product and not to another one. The extrusion conditions and the addition of oil affected the physical properties and sensory characteristics of corn snacks more while they had less influence on the properties of the meat analogs. There were similar correlations between the physical and sensory variables, independent of the food matrix used. The sensory acceptance stood out for samples from intermediate and less severe extrusion conditions and with added oil, showing that these factors have an impact on the physical properties and sensory characteristics, with little effect from the food matrix.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-024-05985-3.

Correlation between acoustic characteristics and sensory evaluation of puffed-grain food based on energy analysis

Puffed-grain food is a crispy snack whose consumer satisfaction depends on snack crispness and crunchiness, which can be characterized by the sound and the acoustic signals of food breaking. This study aimed to evaluate whether acoustic characteristics can be used to predict the crispness of various puffed-grain food. Sensory evaluation was performed on puffed-grain products with varying hygroscopic durations and different types. The relation between sensory evaluation and acoustic characteristics of nine different types of food was examined. The Hilbert-Huang transform was used to perform energy segmentation of the acoustic signal of puffed-grain food and observe its energy migration process. The results showed that energy release was more concentrated in the low-frequency range for grain-puffed foods with different hygroscopic durations. No notable correlation was observed between the low-frequency interval and sensory crispness for the different types of puffed-grain foods. However, the acoustic features extracted from their inherent low-frequency intervals showed a significantly improved correlation with sensory crispness. Therefore, it provides a theoretical reference for applying acoustic characteristics to describe food texture.

Antidiabetic Property Optimization from Green Leafy Vegetables Using Ultrasound-Assisted Extraction to Improve Cracker Production

Here we test a method of incorporating of plant extracts into popular snack foods to help control diabetes. Since some fresh vegetables contain antidiabetic compounds, ultrasound-assisted extraction was used to optimize their extraction of from spring onions, bunching onions, and celery for later incorporation into crackers. We compared various concentrations of ethanol used during extraction, after which they were exposed to an ultrasound processor whose amplitude and sonication time were also varied. The optimal extraction conditions were found to be an ethanol concentration of 44.08%, an amplitude of 80%, and a sonication time of 30 min. This resulted in the highest level of α-glucosidase inhibitory activity (i.e., 1,449.73 mmol ACE/g) and the highest extraction yield (i.e., 24.16%). The extract produced from these optimum conditions was then used as a constituent component of crackers at 0.625%, 1.25%, or 2.5% w/w. These biscuits were then produced at baking temperatures of 140°C, 150°C, or 160°C. We then measured the physical characteristics and bioactivities of sample biscuits from each treatment. We found that biscuits containing 2.5% vegetable combination extract and baked at 140°C had the highest total phenolic content, the strongest antioxidant performance, and showed the most substantial antidiabetic and antiobesity effects. Here we establish conditions for the effective extraction of antidiabetic functional ingredients via ultrasound from green leafy vegetables. We also provide a method of using these ingredients to prepare crackers with the aim of developing a functional antidiabetic snack food.

Effects of sensory combination on crispness and prediction of sensory evaluation value by Gaussian process regression

Crispness contributes to the pleasantness and enjoyment of eating foods and is popular with people of wide ages in many countries. Hence, a quantitative evaluation method for crispness is required for food companies developing new food products. In this study, the effects of different sensory combinations on crispness were investigated through sensory evaluation, and a Gaussian process regression model was used to predict the evaluation values of crispness. First, four crispness descriptors in Japanese were selected, and sensory evaluations were conducted with ten participants using commercially available snack foods under three different sensory combinations of force, vibration, and sound to confirm the effects of the three senses. An instrumental system also measured force, vibration, and sound for snack foods under the same conditions. The Gaussian process regression model determined the relationship between the sensory and measurement data and predicted the sensory evaluation values from the measurement data. Cross-validation verified that the Gaussian process regression model accurately predicted the food texture evaluation values from the measurement data even in conditions with different sensory components.

Technological tools for the measurement of sensory characteristics in food: A review

The use of technological tools, in the food industry, has allowed a quick and reliable identification and measurement of the sensory characteristics of food matrices is of great importance, since they emulate the functioning of the five senses (smell, taste, sight, touch, and hearing). Therefore, industry and academia have been conducting research focused on developing and using these instruments which is evidenced in various studies that have been reported in the scientific literature. In this review, several of these technological tools are documented, such as the e-nose, e-tongue, colorimeter, artificial vision systems, and instruments that allow texture measurement (texture analyzer, electromyography, others). These allow us to carry out processes of analysis, review, and evaluation of food to determine essential characteristics such as quality, composition, maturity, authenticity, and origin. The determination of these characteristics allows the standardization of food matrices, achieving the improvement of existing foods and encouraging the development of new products that satisfy the sensory experiences of the consumer, driving growth in the food sector. However, the tools discussed have some limitations such as acquisition cost, calibration and maintenance cost, and in some cases, they are designed to work with a specific food matrix.

Classification of crispness of food materials by deep neural networks

Crispness is a textural characteristic that influences consumer choices, requiring a comprehensive understanding for product customization. Previous studies employing neural networks focused on acquiring audio through mechanical crushing of crispy samples. This research investigates the representation of crispy sound in time intervals and frequency domains, identifying key parameters to distinguish different foods. Two machine learning architectures, multi-layer perceptron (MLP) and residual neural network (ResNet), were used to analyze mel frequency cepstral coefficients (MFCC) and discrete Fourier transform (DFT) data, respectively. The models achieved over 95% accuracy "in-sample" successfully classifying fried chicken, potato chips, and toast using randomly extracted audio from ASMR videos. The MLP (MFCC) model demonstrated superior robustness compared to ResNet and predicted external inputs, such as freshly toasted bread acquired by a microphone or ASMR audio of toast in milk. In contrast, the ResNet model proved to be more responsive to variations in DFT spectrum and unable to predict the similarity of external audio sources, making it useful for classifying pretrained "in-samples". These findings are useful for classifying crispness among individual food sources. Additionally, the study explores the promising utilization of ASMR audio from Internet platforms to pretrain artificial neural network models, expanding the dataset for investigating the texture of crispy foods.

Mechanical approach for the evaluation of the crispiness of food granular products

Crispiness of food products is a key parameter for consumer acceptance. Available methods to evaluate this attribute are subjective and have limitations. They are particularly difficult to implement when granular products are considered. The present study aims to provide a physical characterization of the crispiness of food granular products (gari and grinded corn flakes) based on the compression cycle modeling and the determination of the Py (yield pressure) parameter of the Heckel model. High Py values attributed to the brittle behavior, are indicative of product crispiness. Furthermore, Py parameter showed sensitivity to the plasticizing effect of water. This developed physical method was validated through sensory analysis and acoustic measurements which are both considered as reference methods for crispiness evaluation. The brittle/plastic behavior attributed to crispy/non crispy products respectively was confirmed through image analysis using X-ray microcomputed tomography. The latter made it possible to distinguish the brittle from the plastic behavior through the particle size distribution evolution. This work suggests that the Py value is a relevant indicator for the crispiness evaluation of granular products. This physical characterization is expected to contribute in food engineering as an alternative method for granular products crispiness in a simpler and a more objective way.

A Review on the Commonly Used Methods for Analysis of Physical Properties of Food Materials

The chemical composition of any food material can be analyzed well by employing various analytical techniques. The physical properties of food are no less important than chemical composition as results obtained from authentic measurement data are able to provide detailed information about the food. Several techniques have been used for years for this purpose but most of them are destructive in nature. The aim of this present study is to identify the emerging techniques that have been used by different researchers for the analysis of the physical characteristics of food. It is highly recommended to practice novel methods as these are non-destructive, extremely sophisticated, and provide results closer to true quantitative values. The physical properties are classified into different groups based on their characteristics. The concise view of conventional techniques mostly used to analyze food material are documented in this work.

Influence of formulation on the quality and stability of a freeze-dried Mandarin product

Consumers demand products of high quality, healthy, safe, and easy to manage. A freeze-dried fruit snack can meet this demand, but this kind of product may collapse rapidly, becoming highly sticky. To avoid this, adding biopolymers can improve their stability. Nevertheless, these biopolymers can negatively affect other quality characteristics such as the color, texture, and flavor. Therefore, selecting the best biopolymer or combination of biopolymers is an indispensable task to offer freeze-dried fruit. The aim of this study was to know the impact of gum Arabic, starch modified with octenyl succinic anhydrous, bamboo fiber and milk protein isolate on the color, glass transition temperature, and stability of some textural related properties of a freeze-dried mandarin snack. The study showed the convenience of incorporate mixtures of the considered biopolymers to mandarin puree as to ensure the crispy character of the snack, associated with its glassy state, without this having a significant impact on the product color. The best formulation was that obtained with a mix of gum Arabic and bamboo fiber.

•

Freeze-drying process is adequate to obtain mandarin snacks with good quality.

•

Biopolymers must be added to improve mandarin crispness snacks.

•

The Gum Arabic-bamboo fiber mix gives the best properties to the snack.

Quick assessment of the potato chip crispness using the mechanical-acoustic measurement method

Traditional assessment method for the food crispness was sensory analysis which was time consuming and needed experienced panelists. Aiming to to develop a quick evaluation of the food crispness, a mechanical-acoustic testing method was proposed where two parameters-maximum force (Fmax) and maximum acoustic energy in unit time (SEmax) were applied to assess the crispness of dried potato chips. It was found the mechanical-acoustic testing was completed in about 1.2 s and the potato chips had a statistic distributions for Fmax and SEmax. The brand A potato chips had a statistic average Fmax of 13.48 N and SEmax of 93.51 mV·ms. Three kinds of potato chips can be effectively differentiated according to the statistic average SEmax and Fmax. Sensory “crispness” had a good correlation with the statistic average SEmax. This work shows that it is feasible for a quick measurement of the food crispness using this mechanical-acoustic method.