Submitted:
11 September 2025
Posted:
12 September 2025
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Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Field Research
2.2. Characteristics of Potato Varieties
2.3. Laboratory Tests
2.3.1. Chips Rating
2.3.2. Determination of Sugars
- − The following were introduced into the volumetric flask: 10 mL of Luff solution
- − 25 mL of sample.
- − The mixture was heated for 10 min in a water bath (95 ± 2°C). After cooling, 10 mL of KI (10%) and 25 mL of H₂SO₄ (25%) were added.
- − Iodine was determined titrimetrically with sodium thiosulfate (0.1 M) against starch.
- − Quality control: Each series was analyzed for:
- − Blank.
- − Positive control (glucose solution).
- − RSD < 5% was assumed for replicates.
2.3.3. Fat Content Determination
2.3.4. Moisture Content Determination
2.4. Soil Conditions
| Year of research |
Content Macronutrients [mg kg-1 soil] |
Humus content [g kg-1] |
pH [KCL] |
Micronutrients content [mg kg-1 soil] |
||||||
| P | K | Mg | Cu | Mn | Zn | Fe | B | |||
| 2015 | 8.9 | 10.9 | 7.8 | 0.94 | 5.9 | 7.51 | 318 | 40.1 | 3760 | 7.24 |
| 2016 | 8.3 | 9.1 | 7.0 | 1.06 | 5.8 | 4.92 | 337 | 56.7 | 3925 | 5.28 |
| 2017 | 10.6 | 9.8 | 6.3 | 1.03 | 6.6 | 8.99 | 166 | 41.1 | 3600 | 6.04 |
| Mean | 9.3 | 9.9 | 7.0 | 1.02 | 7.02 | 273.8 | 45.96 | 3761.7 | 6.17 | |
2.5. Meteorological Conditions
2.6. Statistical Calculations
3. Results
3.1. Evaluation of the Quality of Chips
3.2. Content of Total Sugars and Reducing Sugars
3.3. Multivariate Statistical Analysis of Quality Characteristics of Potato Chips
3.4. Correlations Between Potato Chips Quality Parameters—Statistical Analysis
4. Discussion
4.1. The Effect of Sonification on Potato Metabolism and Chip Quality—Current Mechanisms and Practical Implications
- − The temperature of 42°C favors water absorption, especially at lower ultrasound powers, which may be due to partial denaturation of cell membranes facilitating diffusion.
- − Extraction of reducing sugars is most effective at 35 kHz and 92.5 W kg-1 (31% reduction), which directly translates into a reduction of the Maillard reaction during frying.
- − Changes in colorimetric parameters (↓L, ↑a) confirm the relationship between US treatment and the reduction of non-enzymatic browning.
- − A 90% reduction of acrylamide compared to untreated samples proves that sonication can be a key strategy in the production of healthier chips.
4.2. Optimization of Potato Chip Production Processes Using Ultrasonic Technology
- Ultrasound can be used to pretreat seed potatoes, which can accelerate germination, improve nutrient absorption, and strengthen plant immunity. This can lead to more uniform growth and healthier tubers with the desired reducing sugar content.
- Optimization of Processing:
- − Washing and Cleaning: Ultrasound can assist in removing dirt from potato surfaces, which is more effective than traditional methods and can reduce water consumption.
- − Slicing: Ultrasonic pretreatment before slicing can affect potato texture, facilitate precise cutting and minimize cell damage [55].
- − Blanching: The use of ultrasound during blanching helps shorten the process time, improves the inactivation of enzymes responsible for browning (e.g., polyphenoloxidase), and reduces nutrient loss.
- − Draining/Dewatering Before Frying: Ultrasound can increase the porosity of potatoes, which facilitates the removal of excess water before frying, shortening frying time and reducing fat absorption.
- − Frying: Ultrasound during frying can accelerate the process, resulting in crispy potatoes while reducing fat content. It can also contribute to even heat distribution and reduce acrylamide formation.
- − Reducing Product Darkening: Direct ultrasound exposure can help control the Maillard reaction, reducing excessive browning of chips, which is crucial for consumer acceptance.
- Improved Quality and Shelf Life of the Final Product: Ultrasound can affect the cellular structure of potato flesh, resulting in improved texture and the desired crispness of the chips.
- o Shelf Life: Inactivating microorganisms and enzymes with ultrasound can extend the shelf life of chips by reducing mold growth and spoilage.
- o Reducing the Use of Chemical Additives: Thanks to the significant effectiveness of ultrasound in blanching and enzyme inactivation, it is possible to reduce or completely eliminate the use of chemical antioxidants or browning inhibitors.
- Sustainability:
- − Reduced Energy and Water Consumption: Process optimization with ultrasound can lead to energy savings and reduced water consumption throughout the production cycle.
- − Waste Reduction: Improving raw material quality and improving production processes can reduce rejection and post-production waste.
4.3. The Effect of Potato Sonication on Sugar Metabolism
- − Stronger academic tone (precise terminology, passive voice where appropriate).
- − Better readability (logical flow, clear cause-effect relationships).
- − Consistent formatting (uniform units, proper citation style).
4.4. The Effect of Ultrasonic Treatment on the Fat Content of Chips
- − Morphological changes in starch: Erosion of the surface of starch granules under the influence of ultrasound (confirmed in microscopic studies) led to the formation of a more compact internal structure of chips. Reduced water mobility in the raw material for the production of chips after US treatment limits moisture migration during frying [8,45]
- − Mechanisms of fat absorption reduction: Modified starch structure creates a barrier limiting oil penetration (confirmed by NMR measurements), while faster water evaporation (up to 25% faster) promotes the formation of a surface layer inhibiting absorption. This in turn leads to reduced surface viscosity of the raw material for chips production (rheological measurements) [36,45,46].
- − US treatment at 35-45 kHz for 5-8 minutes allows us to achieve a reduction of the final fat content by 18-22% [47].
- − The need for optimization for different potato varieties (different starch content).
- − Research on scaling the process with consideration of energy efficiency [46].
- − Glucose content in tubers is usually 80.5–97.6% of the coefficient of variation V for the brightness of French fries and 88.4–94.2% for the brightness of potato chips.
- − The critical range of glucose content for acceptable products in French fries and chips based on color values (L* and a*) is 12–22 mg/100 g and 8–14 mg/100 g, respectively, for the tested varieties [45].
4.5. The Influence of Varieties on the Quality of Chips
4.5.1. Key Parameters Quality and Varieties for Chip Production
4.5.2. Indications for the Processing Industry
- − Optimal Variety Selection: The Tajfun and Syrena varieties continue to demonstrate high reliability in terms of quality parameters of the raw material for the production of chips. However, in the light of ongoing climate change and new research appear as promising alternatives, potentially demonstrating better tolerance to extreme growing conditions. Nevertheless, the recommendation of specific varieties should consider the latest results of field trials in different regions and years, assessing their yield and quality stability under changing conditions.
- − Monitoring of Storage Conditions: Close monitoring of storage conditions remains crucial. The latest research [citations on the effect of controlled atmosphere, humidity and temperature on the long-term quality of potatoes for processing] confirms that even varieties with the best quality potential can be degraded as a result of inappropriate temperature and humidity. It is worth considering the implementation of predictive systems based on modeling the impact of environmental conditions during the growing season on the optimal storage parameters of a given batch of raw material.
- − Further and broader integration of fast and non-destructive measurement technologies, such as near-infrared spectroscopy (NIR) and hyperspectral imaging (HSI), is necessary for routine assessment of reducing sugar content and other key quality parameters of the raw material before processing. The latest achievements in artificial intelligence and machine learning enable the creation of more precise and efficient quality assessment systems in real time, which allows for optimization of the production process and minimization of losses.
- − Holistic Approach to Quality: The latest research [citations integrating the impact of variety, agrotechnics and storage on chip quality] confirms that variety is the foundation of chip quality, but its potential can only be fully exploited with the use of optimal agrotechnical practices (considering adaptation to climate change, e.g., precise irrigation, fertilization) and precise storage conditions. Progress in potato breeding, focused on traits useful for processing and resistance to abiotic stresses, must go hand in hand with the implementation of integrated quality management systems at every stage of the supply chain [7].
- − Implementation of Recommendations: Conscious and consistent implementation of the latest recommendations, based on solid scientific research and innovative technologies, is crucial for significant improvement of production efficiency, cost reduction, ensuring high and stable quality of chips and increasing consumer satisfaction in the face of dynamically changing climatic and market conditions.
4.6. Influence of Climatic Conditions on the Quality of Raw Material for Chip Production
4.6.1. Influence of Temperature During the Vegetation Period
4.6.2. Effects of Water Stress
4.6.3. Extreme Weather Phenomena
4.6.4. Influence of Storage Conditions
- − Climate change is causing an increase in the frequency and intensity of extreme weather events, such as heat waves, droughts, floods, storms and hailstorms. Each of these events can negatively affect the yield and quality of the raw material through mechanical damage, water stress, root hypoxia and increased susceptibility to diseases and pests [6,14,17,40,41].
- − Elevated CO₂ Levels: Increased atmospheric carbon dioxide concentration can modify plant physiology, often stimulating photosynthesis, but at the same time potentially reducing protein and micronutrient content (so-called dilution effect). Increased atmospheric CO₂ concentration, as a result of CO₂ fertilization, stimulates photosynthesis. Plants, having more substrate (CO₂) to build sugars, increase their growth rate and produce more biomass (carbohydrates, such as starch). However, this increase in carbohydrate production is often not accompanied by increased nitrogen uptake from the soil, which is essential for protein synthesis [54]. As a result, despite an overall increase in yield, the concentration of proteins and some micronutrients (e.g., molybdenum, iron) per unit of plant mass decreases. This is known as the dilution effect. Although the plant is larger, it is “diluted” in terms of nutrient content, which has consequences for the nutritional value of the crop [54].
- − Phenological Changes: Higher temperatures can accelerate plant development cycles, shortening the vegetation period, which can lead to lower yields and changes in the chemical composition of the raw material [17].
- − Pest Spread: Climate change can promote the migration and increased activity of pests and pathogens, which indirectly worsens the quality of crops through damage and the need for more intensive plant protection. The observation regarding the ‘Satina’ variety is particularly important, which, despite its recognized stability in terms of reducing sugar content, may be susceptible to heat stress. Current knowledge in this area focuses on:
- − Physiological Mechanisms: High temperatures during tuber formation and maturation accelerate respiration and starch metabolism. Under conditions of extreme heat stress, the rate of starch synthesis may be lower than its decomposition into simple sugars (glucose and fructose) and then sucrose. Additionally, heat stress may disrupt the activity of enzymes key to starch synthesis [6,16,17].
- − Genotype-Environment Interaction (GxE): Studies [6,15,16,40,41] confirm a strong interaction between genotype and environment. Potato genotype determines the chemical composition of tubers, including the potential content of dry matter, starch and sugars. However, environmental conditions such as temperature, soil moisture, sunlight or fertilization can significantly modify these values. The right proportion of starch and sugars is crucial for obtaining chippy, non-burning chips with the desired color. Some potato genotypes can accumulate the ideal amount of dry matter, starch and reducing sugars only in specific climatic conditions, which is confirmed by the results of the conducted research. In addition, genetics is largely responsible for the shape and size of potato tubers. The environment in which the tubers grow can also affect their uniformity. Uniform, shapely potato tubers are easier to cut into slices of equal thickness, which translate into even frying and better texture of chips. Some genotypes may be more susceptible to deformation in unfavorable soil conditions [7]. Dry matter content: Genotype and environment jointly affect the dry matter content of potatoes. Higher dry matter content usually means lower water content, which is desirable for chip production because it shortens frying time and reduces oil absorption, leading to chips and less greasy chips. Some varieties can only achieve high dry matter content under specific irrigation conditions [7,13,16,42]. Disease and pest resistance: Genetically determined resistance to diseases and pests is crucial for healthy tubers. However, pathogen and pest pressure can vary depending on the environment. A variety that is resistant in one region may be susceptible to another due to different climatic conditions favoring the development of specific pathogens. Healthy potato plants are essential for the production of high-quality chips [6,14,40]. Both genotype and environment can affect the content of phenolic compounds, which can affect the taste and shelf life of chips. Some potato genotypes naturally have higher levels of these compounds, but their levels can be further modified by growing conditions such as water stress, salt stress, or sunlight [7]. A strong interaction between genotype and environment means there’s no single potato variety that’s universally best for making chips. The ideal variety depends heavily on the specific growing conditions. The quality of chips depends largely on whether a given genotype is grown in its optimal environmental conditions. Chip producers, striving to obtain a product of high and stable quality, must consider this complex interaction, carefully selecting both potato varieties, their growing regions, and the agricultural practices used. The studies conducted provide concrete examples of how specific combinations of genotype and environment affect specific quality traits of chips.
4.7. Ality Evaluation Relationships
- − Defects and discolorations (visual: r = -0.71; sensory: r = -0.67)
- − Moisture spots (visual: r = -0.54; sensory: r = -0.58)
4.8. The Study Identified a Particularly Problematic Relationship
4.9. Directions and Trends in Ultrasound Applications in Food Processing
4.10. Limitations of Ultrasound Technology
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| US | Ultrasonic treatment/sonication |
| ROS | Reactive Oxygen Species |
| SOD | Superoxide Dismutase |
| CAT | Catalase |
| Genes related to carbohydrate metabolism: | |
| InvInh2 (invertase inhibitor) | regulates sucrose breakdown |
| UGPase (UDP-glucose pyrophosphorylase) | key enzyme in starch synthesis |
| Amyl (amylase genes) | control starch degradation |
| PPO | Polyphenol Oxidase |
| NMR | Nuclear Magnetic Resonance |
| SEM | Scanning Electron Microscopy |
| MALDI-TOF | Matrix-Assisted Laser Desorption/Ionization Time-of-Flight |
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| Year | Month | Rainfall [mm] | Air temperature [°C] | ||||||
| Decade | Month | Decade | Mean | ||||||
| 1 | 2 | 3 | 1 | 2 | 3 | ||||
| 2015 | April | 14.6 | 5.9 | 41.3 | 61.8 | 5.4 | 8.6 | 12.4 | 8.8 |
| May | 23.4 | 13.9 | 83.0 | 120.3 | 12.6 | 12.0 | 13.7 | 12.8 | |
| June | 5.4 | 16.5 | 24.8 | 46.7 | 17.7 | 16.3 | 16.1 | 16.7 | |
| July | 10.5 | 21.6 | 13.1 | 45.2 | 19.6 | 18.7 | 19.9 | 19.4 | |
| August | 0.4 | 0.00 | 5.7 | 6.1 | 23.4 | 20.6 | 20.3 | 21.4 | |
| September | 32.4 | 32.6 | 65.2 | 130.2 | 16.0 | 17.7 | 12.8 | 15.5 | |
| Total | 410.3 | ||||||||
| 2016 | April | 11.5 | 22.2 | 13.4 | 47.1 | 10.9 | 10.1 | 9.0 | 10.0 |
| May | 4.9 | 2.8 | 38.6 | 46.3 | 14.4 | 17.8 | 12.9 | 15.3 | |
| June | 10.1 | 43.2 | 34.0 | 87.3 | 16.6 | 17.5 | 23.0 | 19.1 | |
| July | 22.4 | 30.8 | 60.9 | 114.1 | 19.5 | 20.1 | 21.9 | 20.5 | |
| August | 22.8 | 17.7 | 0.5 | 41.0 | 20.7 | 17.1 | 20.4 | 19.5 | |
| September | 7.6 | 0.10 | 4.1 | 11.8 | 19.5 | 15.5 | 11.5 | 15.5 | |
| Total | 347.6 | ||||||||
| 2017 | April | 6.4 | 7.2 | 38.2 | 51.8 | 10.6 | 6.8 | 6.9 | 8.1 |
| May | 45.1 | 1.3 | 19.1 | 65.5 | 10.5 | 13.0 | 17.4 | 13.7 | |
| June | 1.9 | 9.2 | 12.0 | 23.1 | 16.6 | 17.7 | 20.7 | 18.3 | |
| July | 10.1 | 80.9 | 41.0 | 132.0 | 17.9 | 19.0 | 21.0 | 19.4 | |
| August | 0.4 | 24.4 | 2.2 | 27.0 | 22.8 | 21.3 | 17.1 | 20.3 | |
| September | 38.7 | 35.9 | 8.7 | 83.3 | 16.3 | 15.3 | 12.8 | 14.8 | |
| Total | 382.7 | ||||||||
| Experimental Factors | Chips evaluation parameters | |||
| Color on a 9º scale | Visual assessment on a 5º scale |
Organoleptic evaluation on a 5º scale |
||
| Technologies | Traditional | 6.79 a* | 3.60 a | 3.72 a |
| Ultrasounds | 7.50 b | 4.18 b | 4.22 b | |
| Varieties | ’Denar’ ’Lord’ ’Owacja’ ’Vineta’ ’Satina’ ’Tajfun’ ‘Syrena’ ‘Zagłoba’ |
5.94 a 6.34 ba 6.42 ba 7.96 d 7.28 c 8.36 d 8.17 d 6.70 bc |
3.33 ba 3.06 a 3.28 ba 4.50 d 3.94 c 4.72 d 4.61 d 3.69 bc |
3.44 ba 3.31 a 3.08 a 4.53 d 4.0 c 4.78 d 4.81 d 3.83 bc |
|
Years |
2015 2016 2017 |
7.69 c 6.53 a 7.22 b |
4.11 c 3.68 a 3.89 b |
4.34 b 3.75 a 3.82 a |
| Mean | 7.15 | 3.89 | 3.97 | |
| Experiment Factors | Chips evaluation parameters [%] | |||||
| Discoloration | Humidity | Moist areas | Content of fat | |||
| Technologies | Traditional | 9.35 b* | 2.19 a | 3.43 b | 28.25 b | |
| Ultrasounds | 4.64 a | 2.28 a | 1.78 a | 27.27 a | ||
| Cultivars | ’Denar’ ’Lord’ ’Owacja’ ’Vineta’ ’Satina’ ’Tajfun’ ‘Syrena’ ‘Zagłoba’ |
6.17 ba 19.61 c 9.83 b 2.44 a 8.61 b 2.78 a 2.72 a 3.78 a |
2.44 ab 3.19 b 2.16 ab 1.92 a 2.26 ab 1.96 a 1.87 a 2.08 ab |
1.72 abc 5.67 e 3.11 dbc 0.28 a 4.78 de 0.56 a 0.83 ab 3.89 dec |
24.30 a 25.30 ab 25.90 b 26.75 b 27.48 b 29.42 b 31.25 b 31.68 b |
|
| Years | 2015 2016 2017 |
2.88 a 8.92 b 9.19 b |
1.90 a 2.13 ab 2.68 b |
0.60 a 3.27 b 3.94 b |
27.06 a 27.81 a 27.62 a |
|
| Mean | 6.99 | 2.24 | 2.60 | 26.39 | ||
| Specification | y1 | x1 | x2 | x3 | x4 | x5 | x6 | x7 | x8 |
| Average | 7.15 | 3.89 | 3.97 | 2.24 | 6.99 | 2.60 | 27.59 | 1.05 | 0.53 |
| Median | 7.40 | 4.00 | 4.00 | 2.00 | 5.00 | 0.00 | 27.01 | 0.72 | 0.46 |
| Standard deviation | 1.41 | 0.92 | 0.93 | 1.24 | 9.76 | 4.11 | 2.69 | 0.76 | 0.33 |
| Kurtosis | -0.72 | 0.18 | 0.27 | 78.76 | 7.50 | 3.96 | -1.37 | -1.10 | -1.08 |
| Skewness | -0.51 | -0.71 | -0.73 | 7.76 | 2.53 | 1.89 | 0.28 | 0.65 | 0.48 |
| Range | 5.20 | 4.00 | 4.00 | 14.00 | 50.00 | 20.00 | 7.99 | 2.41 | 1.06 |
| Minimum | 3.80 | 1.00 | 1.00 | 1.00 | 0.00 | 0.00 | 24.01 | 0.18 | 0.09 |
| Maximum | 9.00 | 5.00 | 5.00 | 15.00 | 50.00 | 20.00 | 32.00 | 2.59 | 1.15 |
| Variation coefficient V (%) | 19.71 | 23.54 | 23.29 | 55.52 | 139.52 | 157.79 | 9.74 | 72.86 | 63.15 |
| Specification | y1 | x1 | x2 | x3 | x4 | x5 | x6 | x7 | x8 |
| y1 | 1.00 | ||||||||
| x1 | 0.87 | 1.00 | |||||||
| x2 | 0.78 | 0.88 | 1.00 | ||||||
| x3 | -0.14 | -0.25 | -0.26 | 1.00 | |||||
| x4 | -0.62 | -0.71 | -0.67 | 0.18 | 1.00 | ||||
| x5 | -0.38 | -0.54 | -0.58 | 0.20 | 0.67 | 1.00 | |||
| x6 | 0.34 | 0.38 | 0.43 | -0.20 | -0.30 | -0.11 | 1.00 | ||
| x7 | 0.44 | -0.29 | -0.28 | -0.06 | 0.18 | 0.17 | -0.04 | 1.00 | |
| x8 | -0.54 | -0.38 | -0.37 | 0.01 | 0.22 | 0.19 | -0.17 | 0.94 | 1.00 |
| Factors | Effect | Source |
| Weather conditions | ↑ in cold and humid periods | [39,41,51] |
| Storage temperature | Optimum: 6–8°C (↑ below 4°C & above 10°C) | [12,41,43] |
| Harvest time | July harvest → 5× higher sugar content than August | [43,53] |
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