Assessment of acoustic-mechanical measurements for texture of French fries: Comparison of deep-fat frying and air frying

Comprehensive insights into oil absorption in fried foods: The role of surface characteristics

The mechanisms of oil absorption in fried foods remain unclear due to the complex interactions between food surface properties, oil characteristics, and frying conditions. This review systematically examines oil absorption behavior by analyzing food surface characteristics, oil properties, and their interactions. Key factors influencing oil uptake, including food pretreatment, material composition, and frying parameters, are critically evaluated. The review clarifies how food surface characteristics impact oil absorption pathways through multilevel analyses, ranging from qualitative to quantitative and microscopic to macroscopic perspectives. Based on these insights, some aspects, including optimization of food surface characteristics, regulation of oil properties and improvement of frying techniques, should be considered to reduce oil uptake without compromising the quality of fried foods. Additionally, emerging research directions, such as advanced coating materials, intelligent frying equipment, and multi-scale simulation technologies, are discussed. These findings provide a theoretical foundation and technical guidance for developing healthy and low-fat fried foods.

Comparative analysis of quality, structural, and flavor alterations in chestnuts (Castanea mollissima Blume) subjected to different thermal processing techniques

This study investigated the effects of three thermal processing methods-steaming (100 °C), air frying (150 °C), and roasting (200 °C)-on the quality, structure, and flavor profiles of two chestnut (Castanea mollissima Blume) varieties, Dabanhong and Yanshanzaofeng. Nutritional composition, bioactive compounds, crystallinity, texture, color, and taste were assessed using gas chromatography-mass spectrometry (GC-MS), texture profile analysis (TPA), and an electronic tongue (E-tongue). Specifically, TPA effectively identified roasted chestnuts, while the E-tongue further distinguished steamed from air-fried chestnuts. Sensory evaluation was conducted with 110 participants, and principal component analysis (PCA) was used to correlate sensory attributes with physicochemical properties. Air frying preserved nutrients effectively, achieved the highest relative crystallinity, and improved sensory qualities by reducing hardness and undesirable flavors. Dabanhong chestnuts air-fried at 150 °C emerged as the optimal combination, balancing both nutritional and sensory attributes. These findings provide actionable insights for optimizing chestnut thermal processing to enhance consumer satisfaction and product quality.

Big data analytics in food industry: a state-of-the-art literature review

The food industry has experienced rapid growth over the past two decades, driven by technological advancements that have generated vast quantities of complex data. However, the industry's ability to effectively analyze and leverage this data remains limited due to the lack of control over diverse variables. This review addresses a critical gap by exploring how AI-ML-based approaches can be applied to solve key challenges in the food sector.

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.

Causal factors concerning the texture of French fries manufactured at industrial scale

In this paper, we review the physical/chemical phenomena, contributing to the final texture of French fries, as occurs in the whole industrial production chain of frozen par-fried fries. Our discussion is organized following a multiscale hierarchy of these causal factors, where we distinguish the molecular, cellular, microstructural, and product levels. Using the same multiscale framework, we also discuss currently available theoretical knowledge, and experimental methods probing the relevant physical/chemical phenomena. We have identified knowledge gaps, and experimental methods are evaluated in terms of the effort and value of their results. With our overviews, we hope to give promising research directions such to arrive at a multiscale model, encompassing all causal factors relevant to the final texture. This multiscale model is the ultimate tool to evaluate process innovations for effects on final textural quality, which can be balanced against the impacts on sustainability and economics.

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.

Acrylamide formation in air-fried versus deep and oven-fried potatoes

Introduction

Present study investigates the effects of different home pre-treatment processes and cooking techniques on the acrylamide content of fried potatoes.

Methods

Potato sticks were prepared in two different pre-treatment ways (washing and soaking) and cooked with three other techniques (air frying, deep frying, and oven frying). Acrylamide analyses were performed on cooked potatoes using an LC-MS/MS method.

Results

The highest acrylamide content was found in potatoes cooked using the air fryer (12.19 ± 7.03 μg/kg). This was followed by deep frying (8.94 ± 9.21 μg/kg) and oven frying (7.43 ± 3.75 μg/kg). However, the difference between the acrylamide contents of the potatoes according to the cooking methods was not statistically significant. The acrylamide content of the potatoes that were subjected to soaking in all three ways was lower than the potatoes that were not soaked and only washed. In the deep-frying method, it was found statistically significant that the soaked potatoes contained less acrylamide (p = 0.029).

Discussion

It is important to highlight the relatively low acrylamide levels found in oven-frying, lower than air frying in both washing and soaking groups in the present study. Although air fryers, which have become widely used as an alternative to deep frying in recent years, provide French fries with less oil, their role in the formation of acrylamide should be further investigated.

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.

Comparative study of conventional frying and air frying on the quality of potatoes (Solanum tuberosum L.)

The human being has historically consumed fried foods for centuries; however, conventional frying has a disadvantage, immersion in vegetable and/or animal oils, which leads to the search for different options. This is why air frying is a good alternative, which still has a wide field of study. In this work, frozen French fries of a brand marketed in Mexico that were subjected to frying in canola oil and air frying were compared. They were evaluated through the change in the removed moisture content, water activity, color profile, hardness, fracturability, and surface damage by SEM, thermal analysis by MDSC, and chemical by FTIR-ATR spectroscopy. Air-fried French fries were found to contain about 48% less moisture, fewer perceptible color changes, and less surface damage translated into better crunchiness compared with conventionally fried. It was also found that the changes at the chemical level are smaller, mainly attributed to the absence of canola oil and that the thermal transitions are more stable in terms of temperatures and enthalpies, which makes it possible to emphasize that air frying is a good alternative for developing new fried products that allow expanding the variety of these in the market without sacrificing some quality attributes.

Comparative Study of Sensory and Physicochemical Characteristics of Green-Tea-Fortified Cupcakes upon Air Frying and Oven Baking

The air fryer and the oven are common cooking methods in our daily lives. However, previous investigations of the air fryer were limited to its comparison with deep-fat frying. This study compared the differences between air frying and household oven baking (without a fan or other forced airflow inside) on food quality and physicochemical properties using a cupcake model. Results showed that the oven-baked cupcakes were softer in texture (87.15%), greener in color (6.07%), and lower in weight loss (7.78%) and toxic advanced glycation end products (AGEs, 21.40%) when the heating temperature and duration were the same as oven baking. To improve the sensory characteristics and health value, the cupcakes were fortified with green tea. The differences in texture, color, and level of toxicants between the two cooking methods were diminished after the addition of green tea. Moreover, the chemical profiles of green tea catechins in the green-tea-fortified cupcakes remained similar upon thermal cooking, except that the air-fried cupcakes were lower in gallic acid (GA) but higher in (−)-gallocatechin (GC). Collectively, based on the differences in heating mechanisms, our data indicated that oven baking is a better cooking method suitable to prepare cupcakes than air frying from the perspectives of sensory characteristics and food safety, while green tea additives effectively counter the drawbacks of the air fryer.

Rational Food Design Targeting Micronutrient Deficiencies in Adolescents: Nutritional, Acoustic-Mechanical and Sensory Properties of Chickpea-Rice Biscuits

"Hidden hunger", the deficiency of important mineral micronutrients, affects more than 2 billion people globally. Adolescence is unquestionably a period of nutritional risk, given the high nutritional requirements for growth and development, erratic or capricious diets and the increased consumption of snacks. This study applied the rational food design approach to obtain micronutrient-dense biscuits by combining chickpea and rice flours to achieve an optimal nutritional profile, crunchy texture and appealing flavour. The perception of 33 adolescents regarding the suitability of such biscuits as a mid-morning snack was examined. Four biscuits were formulated, with different ratios of chickpea and rice flours (CF:RF): G100:0, G75:25, G50:50 and G25:75. Nutritional content, baking loss, acoustic-texture and sensory analyses were carried out. On average, the mineral content of biscuits with the CF:RF ratio of 100:0 doubled compared with the 25:75 formula. The dietary reference values for iron, potassium and zinc reached 100% in the biscuits with CF:RF ratios of 50:50, 75:25 and 100:0, respectively. The analysis of mechanical properties revealed that samples G100:0 and G75:25 were harder than the others. Sample G100:0 showed the highest sound pressure level (Smax). Sensory analysis showed that increasing the proportion of CF in the formulation augments the grittiness, hardness, chewiness and crunchiness. Most of the adolescents (72.7%) were habitual snack consumers; 52% awarded scores ≥ 6 (out of 9) to biscuit G50:50 for its overall quality, 24% described its flavour as "biscuit" and 12% as "nutty". However, 55% of the participants could not pinpoint any dominant flavour. In conclusion, it is possible to design nutrient-dense snacks that meet the micronutrient requirements and sensory expectations of adolescents by combining flours naturally rich in micronutrients.

Effects of Air Frying on French Fries: The Indication Role of Physicochemical Properties on the Formation of Maillard Hazards, and the Changes of Starch Digestibility

This study focused on the formation of Maillard hazards in air fried fries, highlighting the correlation between the resultant physical properties of the fries and the formation of Maillard hazards. In the meantime, the effects of air frying on the in vitro starch digestibility of fries were explored. Potato strips were fried at various temperatures (180-200°C) and time (12-24 min). Results indicated that the extent of browning, hardness, and the contents of Maillard hazards (acrylamide, 5-hydroxymethylfurfural, methylglyoxal, and glyoxal) all increased steadily with air frying temperature and time. Moisture content were negatively correlated (p < 0.001) with Maillard hazards content and physicochemical properties except for L^* with the correlation coefficients range from -0.53 to 0.94, and positively correlated with L^* value with correlation coefficient was 0.91, hence, reducing the Maillard hazard exposure while maintaining the desired product quality can be achieved by controlling the moisture content of the air fried French fries. Compared with deep frying (180°C-6 min), air frying decreased acrylamide and 5-hydroxymethylfurfural content with the maximum reduction rate were 47.31 and 57.04%, respectively. In addition, the in vitro digestion results suggested that air frying resulted in higher levels of slowly digestible starch (48.54-58.42%) and lower levels of resistant starch (20.08-29.34%) as compared to those from deep frying (45.59 ± 4.89 and 35.22 ± 0.65%, respectively), which might contribute to more balanced blood sugar levels after consumption. Based on the above results, it was concluded that air frying can reduce the formation of food hazards and was relatively healthier.

Effect of lyophilized chive (Allium wakegi Araki) supplementation to the frying batter mixture on quality attributes of fried chicken breast and tenderloin

Batter mixtures for frying chicken breasts and tenderloins were supplemented with different amounts (0, 3, 5, and 7%) of lyophilized chives (Allium wakegi Araki). The viscosity of the batter mixture, crispness of the fried batter, fat and ash contents, caloric value, coating pickup, and frying yield were directly proportional, whereas the lightness, redness, yellowness, and pH were inversely proportional, to the amount of lyophilized chives in the batter. Principal component analysis revealed that the aromatic profiles varied between the 0%, 3%, and 5% lyophilized chive-supplemented groups in both the breast and tenderloin samples. However, the aromatic profiles of the 7% and 5% lyophilized chive-supplemented samples were similar. The taste profile of the 7% lyophilized chive-supplemented sample was different from those of the 0%, 3%, or 5% lyophilized chive-supplemented samples. The sensory characteristics of the 5% lyophilized chive-supplemented breast samples and 3% or 5% lyophilized chive-supplemented tenderloin samples received the best scores by sensory panelists.

Machine learning-based modeling in food processing applications: State of the art

Food processing is a complex, multifaceted problem that requires substantial human interaction to optimize the various process parameters to minimize energy consumption and ensure better-quality products. The development of a machine learning (ML)-based approach to food processing applications is an exciting and innovative idea for optimizing process parameters and process kinetics to reduce energy consumption, processing time, and ensure better-quality products; however, developing such a novel approach requires significant scientific effort. This paper presents and evaluates ML-based approaches to various food processing operations such as drying, frying, baking, canning, extrusion, encapsulation, and fermentation to predict process kinetics. A step-by-step procedure to develop an ML-based model and its practical implementation is presented. The key challenges of neural network training and testing algorithms and their limitations are discussed to assist readers in selecting algorithms for solving problems specific to food processing. In addition, this paper presents the potential and challenges of applying ML-based techniques to hybrid food processing operations. The potential of physics-informed ML modeling techniques for food processing applications and their strategies is also discussed. It is expected that the potential information of this paper will be valuable in advancing the ML-based technology for food processing applications.

Influence of Frying Methods on Quality Characteristics and Volatile Flavor Compounds of Giant Salamander (Andrias davidianus) Meatballs

Effects of deep fat frying and hot air frying on texture, color difference, sensory score, yield, fat content, and volatile flavor compounds of giant salamander meatballs before and after frying were investigated. The results showed that, compared with the deep fat frying group, hot air-fried giant salamander meatballs had higher hardness, elasticity, and L ${}^{\ast }$ ( $p<0.05$ ), but lower a ${}^{\ast }$ , b ${}^{\ast }$ value, fat content, and yield ( $p<0.05$ ). There was little distinction in sensory score, cohesiveness, and chewiness between the two frying methods ( $p>0.05$ ). Gas chromatography ion migration chromatography (GC-IMS) was used for flavor compound analysis, and 50 flavor compounds were analyzed, containing 22 aldehydes, 11 ketones, 6 olefins, 4 acids, 3 esters, 3 alcohols, and 1 phenol. Compared with the samples before frying, the relative contents of aldehydes and ketones of fried giant salamander meatballs increased significantly, while the relative contents of esters and alkenes decreased significantly. Principal component analysis showed that the GC-IMS spectra of volatile flavor compounds before and after deep fat frying and hot air frying varied greatly, and the cumulative contribution rate of the two principal components reached 86.1%, indicating that the GC-IMS technology might be used to distinguish giant salamander meatballs before and after frying, or with different frying methods. These results may offer a note for development and quality control of the precooked giant salamander meatballs in the future.

Crispness, the Key for the Palatability of "Kakinotane": A Sensory Study with Onomatopoeic Words

Crispness is among the most important food textures that contribute significantly to palatability. This study investigated the association between the perceived crispness and palatability of five types of Japanese rice crackers known as “kakinotane.” Two experiments were conducted using the temporal dominance of sensations (TDS) and temporal drivers of liking (TDL) methods. As descriptors for the TDS evaluation, we used 10 Japanese onomatopoeias to indicate various attributes of crispness. We also measured the mastication sounds and electromyography (EMG) activity during mastication. Principal component analysis data revealed that principal component 1, representing moisture characteristics, contributed more than 60% in both experiments. The palatability of the stimulus, which was described as having a very soft, moist, and sticky texture, BETA-BETA, was significantly lower than the others. However, there was no significant relationship between the amplitude of mastication sound or EMG activity and palatability. We demonstrated that naïve university students can discriminate the fine nuances of the crispness of “kakinotane” using the TDS and TDL methods. Our findings also suggested that the onomatopoeias used as descriptors in the TDS method had a greater influence on describing the nuances of food texture than the physiological data.

Sum of variance for quantifying the variation of multiple sequential data for the crispness evaluation of chicken nugget

Crispness is one of the words most frequently used to describe the texture of fried or dried food in addition to being a key to the determination of freshness for many non-fried foods. In this study, a new feature value called the sum of variance was assessed for its contribution to the estimation of crispness. Dynamic time warping and its averaging algorithms were employed to determine the sum of variance from a set of sequential force data measured using an instrument. The sum of variance is a feature value that expresses the variance of multiple sequential data. In an experiment, seven chicken nugget samples were prepared, and five panels evaluated their texture according to six Japanese word descriptors. An instrument experiment determined the six feature values, including the sum of variance from the measurement data, whereas multiple linear regression was applied to determine the relationship between the sensory values and feature values. For three of the six textures, the sum of variance reduced the error between the sensory values and their estimated values by up to 50%, confirming that this feature contributes to the textural estimation of food crispness.