Submitted:
25 April 2025
Posted:
27 April 2025
Read the latest preprint version here
Abstract
Keywords:
1. Introduction
2. Materials and Metod
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
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- The following were introduced into the volumetric flask: 10 mL of Luff solution
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- 25 mL of sample.
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- 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.
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- Iodine was determined titrimetrically with sodium thiosulfate (0.1 M) against starch.
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- Quality control: Each series was analyzed for:
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- Blank.
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- Positive control (glucose solution).
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- RSD < 5% was assumed for replicates.
2.3.3. Fat Content Determination
2.3.4. Moisture Content Determination
|
Year of research |
Content Macronutrients [mg kg-1 soil] |
Humus ccontent [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 | |
2.4. Soil Conditions
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
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- 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.
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- Extraction of reducing sugars is most effective at 35 kHz and 92.5 W/kg (31% reduction), which directly translates into a reduction of the Maillard reaction during frying.
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- Changes in colorimetric parameters (↓L, ↑a) confirm the relationship between US treatment and the reduction of non-enzymatic browning.
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- 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. The Effect of Potato Sonication on Sugar Metabolism
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- Stronger academic tone (precise terminology, passive voice where appropriate).
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- Better readability (logical flow, clear cause-effect relationships).
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- Consistent formatting (uniform units, proper citation style).
4.3. The Effect of Ultrasonic Treatment on the Fat Content of Chips
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- 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]
- -
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- 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].
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- 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].
- ◦
- ◦
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- The need for optimization for different potato varieties (different starch content).
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- Research on scaling the process with consideration of energy efficiency [46].
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- 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.
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- 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].
4.4. The Influence of Varieties on the Quality of Chips
4.4.1. Key Parameters of Chip Quality
4.4.2. Best Varieties for Chip Production
4.4.3. Indications for the Processing Industry
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- 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 [include the latest citations on the resistance of varieties to abiotic stresses, e.g. heat and water], Lenora and Adelina 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.
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- 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.
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- Integration of Advanced Measurement Technologies: 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.
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- 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].
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- 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.
4.5. Influence of Climatic Conditions on the Quality of Raw Material for Chip Production
4.5.1. Influence of Temperature During the Vegetation Period
4.5.2. Effects of Water Stress (Drought/Excessive Rainfall)
4.5.3. Extreme Weather Phenomena
4.5.4. Influence of Storage Conditions (Interaction with Meteorology)
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- 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].
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- 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).
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- 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].
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- 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:
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- 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].
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- 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 chipy, 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 [Zarzycka et al. 2021, Sawicka et al. 2021]. 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]. In summary, studies confirming the strong interaction of genotype and environment in the context of potato chips suggest that there is no single "universally best" potato variety. 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.
4.6. Ality Evaluation Relationships
4.7. Research Perspectives
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- Extension of AI Models: Development of advanced predictive models based on artificial intelligence and multi-factor analysis, which will combine detailed meteorological data (temperature, precipitation, humidity, sunlight in different growth stages) with tuber characteristics (reducing sugar content, starch, dry matter, texture) and ultrasonic processing parameters. These models should consider the influence of different climatic conditions on the susceptibility of tubers to quality optimization using ultrasound.
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- Optimization of Ultrasonic Parameters: Study of the influence of different ultrasonic parameters (frequency, power, exposure time, medium temperature) used at different stages of the chip production process (e.g. before cutting, after cutting, before frying) on key quality indicators such as reducing sugar content, oil absorption, texture (chipness, hardness), color and sensory properties of the finished product. Predictive models should assist in the selection of optimal ultrasound parameters depending on the characteristics of the raw material and meteorological conditions during its growth.
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- Controlled Stress Conditions with Pre- and Post-Harvest Ultrasound Treatment: Testing the resistance of new and promising potato varieties to simulated abiotic stress conditions (e.g. drought, high temperatures in foil tunnels) with simultaneous assessment of the potential of ultrasound techniques to mitigate the negative effects of stress on the quality of raw material for the production of chips. The studies should include the application of ultrasound both before harvest (e.g. growth stimulation, improvement of resistance) and after harvest (e.g. reduction of reducing sugars, improvement of texture before processing).
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- Genotype-Environment-Ultrasound Interaction Analysis (GxE+U): Study of the interaction between genotype (variety), environment (stress conditions) and the use of ultrasonic techniques at different stages of chip production. The aim is to identify varieties that, under specific stress conditions, respond best to ultrasonic treatment in terms of improving the quality of chips.
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- Mechanisms of Ultrasound Action on Raw Material and Final Product Quality: Cellular and Molecular Level Studies: Detailed studies of the mechanisms of ultrasound action at the cellular and molecular level in potato tissue. The effect of ultrasound on the activity of enzymes responsible for sugar and starch metabolism, cell wall structure, cell membrane permeability and the release of phenolic compounds and other antioxidants should be studied. Understanding these mechanisms will allow for more informed and effective use of ultrasonic techniques.
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- Influence of Ultrasound on Chip Microstructure: Study of the effect of ultrasonic treatment on the microstructure of fried chips (porosity, cell structure) and its correlation with texture and oil absorption.
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- Optimization of Ultrasonic Process in Chip Production at Semi-Industrial and Industrial Scale: Scalability and Cost-Effectiveness: Investigation into the scalability and cost-effectiveness of using ultrasonic techniques in industrial production of chips. Optimal configurations of ultrasonic devices should be developed and integrated into existing production lines.
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- Life Cycle Assessment and Sustainability: Analysis of the life cycle and environmental impact of using ultrasonics in chips production, including energy consumption and potential benefits in terms of reducing oil consumption and improving product quality.
4.8. The study identified a particularly problematic relationship
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- Raw material selection (reducing sugar content)
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- Moisture management during processing
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4.9. Prospects for the Application of Ultrasonic Technology in the Potato Industry
- 1.
- Enzyme inactivation: Effective inhibition of polyphenoloxidase, preventing browning [56].
- 2.
- 3.
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- -
- Increased efficiency by increasing the efficiency of thermal processes by 15-20%.
- 4.
- Sustainable development:
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- -
- -
- 5.
- Comprehensive production approach:
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- Pre-planting phase: Treatment of seed potatoes (40 kHz, 300 W, 15 min) stimulates germination and metabolism [17].
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- Processing process: Ultrasound improves frying parameters and sensory quality [14].
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- Final product: better texture, color and storage stability are achieved [14].
- 6.
- Directions of technology development:
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- Integration with membrane processes in the production of concentrates.
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- Use of high-pressure ultrasound for starch modification.
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- Development of continuous processing systems for industrial applications.
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- Automation and optimization of sonication parameters.
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- Research on the impact on the nutritional value of potato products.
- 7.
- Implementation of ultrasonic technology in the production of chips requires:
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- Standardization of processing parameters for different potato varieties.
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- Economic analysis of investment and operating costs.
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- Long-term studies of agrotechnical effects.
4.10. Limitations of Ultrasound Technology
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
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 |
| All terms are consistent with the nomenclature used in | IUPAC (International Union of Pure and Applied Chemistry), Food Chemistry (Elsevier), Journal of Agricultural and Food Chemistry. |
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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 | [40,41] |
| Storage temperature | Optimum: 6–8°C (↑ below 4°C & above 10°C) | [14,40,42] |
| Harvest time | July harvest → 5× higher sugar content than August | [43] |
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