The Effect of Cultivation Techniques on the Antioxidant Properties and Phenolic Acid Content in the Roots of Five Sweet Potato (Ipomoea batatas L.) Cultivars Grown Under the Climatic and Soil Conditions of Southeastern Poland

Abstract

This study confirmed that cultivation technologies, cultivar, and meteorological conditions significantly influenced the contents of ascorbic acid, total polyphenols, and phenolic acids in sweet potato roots. Ascorbic acid content ranged from 27.22 to 111.9 mg·100 g⁻¹ DW, with the highest values recorded in the traditional cultivation system (TC), reaching 111.9 mg·100 g⁻¹ DW in ‘Carmen Rubin’ and 111.4 mg·100 g⁻¹ DW in ‘Beauregard’. In contrast, in the ‘Satsumo Imo’ cultivar grown under nonwoven fabric (WC), ascorbic acid content decreased to 49–58% of the values obtained in TC. Genetic factors strongly differentiated the contents of bioactive compounds. The ‘Purple’ cultivar showed the highest contents of total polyphenols (up to 963.5 mg·100 g⁻¹ DW) and phenolic acids (17,067.42 mg·100 g⁻¹ DW), whereas the lowest values were recorded in ‘Satsumo Imo’ (858.82–1225.89 mg·100 g⁻¹ DW). Cultivation under polyethylene film (FC) increased and stabilized phenolic compounds. The ‘Carmen Rubin’ cultivar also exhibited high phenolic acid content (5332.04–5447.60 mg·100 g⁻¹ DW), while ‘Beauregard’ was characterized by high stability of this trait (1535.93–1581.46 mg·100 g⁻¹ DW). From a practical perspective, the results highlight the importance of appropriate cultivar selection and cultivation technology for obtaining raw material with high functional value. These findings may serve as a basis for developing agrotechnical recommendations aimed at producing sweet potatoes with enhanced nutritional and health-promoting qualities under the climatic and soil conditions of Poland.

1. Introduction

In recent years, consumer interest in health-promoting foods, often called functional foods, has increased dramatically. This trend results from growing nutritional awareness and the search for natural sources of bioactive compounds to help prevent lifestyle-related diseases such as obesity, type 2 diabetes, cardiovascular disease, and cancer. In response to these needs, both the food industry and the agricultural sector have intensified efforts to identify and cultivate plant raw materials with high nutritional and biological value. Sweet potato (Ipomoea batatas L.) roots are among such valuable raw materials, due to their rich chemical composition and versatile technological applications, which are increasing their economic and market significance [1,2,3,4]. Sweet potato is a plant of high energetic and nutritional value, providing a valuable source of complex carbohydrates, dietary fiber, vitamins (including vitamin C and B vitamins), and minerals such as potassium, calcium, and magnesium. Particular attention is given to its bioactive compounds, including polyphenols, phenolic acids, carotenoids, and anthocyanins, which exhibit strong antioxidant properties. These compounds neutralize reactive oxygen species, reducing oxidative stress that causes cellular damage and contributes to the development of many chronic diseases. The literature also highlights their anti-inflammatory, anticancer, and antidiabetic effects [5,6,7,8,9,10,11,12,13], which further emphasizes the potential of sweet potato as a functional raw material. The health-promoting properties of roots are largely determined by genetic factors, reflected in the morphological and chemical diversity of cultivars. The color of the skin and flesh (white, cream, yellow, orange, purple) is not only a visual characteristic but also an indicator of specific groups of phytochemicals. Orange-fleshed cultivars are rich in β-carotene, a precursor of vitamin A, while purple-fleshed cultivars are particularly abundant in anthocyanins with strong antioxidant potential [1,6,7,8,9,10,11]. These differences translate into varied antioxidant activity and distinct phenolic acid profiles among genotypes.

Environmental and agronomic factors also significantly influence the quality and biological value of roots. Climatic conditions, soil type, fertilization, and water availability can modify plant metabolism, including the biosynthesis of phenolic compounds. In temperate climates, protective cultivation technologies such as polyethylene (PE) film and polypropylene (PP) nonwoven fabrics are increasingly used in sweet potato cultivation. These materials modify the microclimate around the plant and soil by increasing soil temperature, reducing water loss, and stabilizing growth conditions [2,6]. Such changes may stimulate metabolic processes responsible for bioactive compound accumulation, leading to differences in the chemical composition of roots compared with conventional cultivation. The interaction between genetic factors and cultivation technology can thus significantly determine the quality of the raw material and its suitability for functional food production [2,14]. Despite growing interest in sweet potato cultivation in Poland, comprehensive studies on the antioxidant properties and phenolic acid content of roots from different cultivars grown under the specific climatic conditions of southeastern Poland, including the use of protective cultivation technologies, remain scarce. Addressing this research gap has practical significance for both agricultural producers seeking optimal agronomic solutions and the food industry seeking raw materials of high, consistent health-promoting value. Therefore, this study aimed to determine the effect of cultivation technology (conventional, polyethylene film, and polypropylene nonwoven) and genetic factors on the antioxidant potential and phenolic acid content of roots from five sweet potato cultivars grown in southeastern Poland.

2. Materials and Methods

2.1. The Experimental Site and Design

2.1.1. Location and Climatic Conditions

The field experiment was conducted during 2021–2023 in Żyznów (49°49′ N, 21°50′ E), Poland. The experimental site had a southern exposure, which provided higher solar radiation and faster soil warming in spring. This is important because the studied species, Ipomoea batatas, requires a high sum of active temperatures (SAT) to initiate tuberization. The area is also exposed to late frosts (until the end of May) and early frosts (in September), which justified the investigation of covering technologies—Polyethylene (PE) film cover (FC), Polypropylene (PP) nonwoven fabric (WC)—as methods to protect plants from extreme temperature drops and to improve the thermal balance in the root zone [2,6].

The average annual precipitation in this region is approximately 650–750 mm. However, its distribution is often uneven, which, combined with the medium-loamy soil (luvisol), may lead to periodic water deficits during the intensive root growth phase. The frost-free period in this part of Poland is sufficient for early-maturing cultivars with a short growing season (90–110 days) [15].

2.1.2. Field Experiment

The experiment was established using a randomized split-plot design with three replications. The main factor (Factor I) was the cultivation technology: (a) traditional cultivation without cover (control, TC), (b) polyethylene (PE) film cover (FC), and (c) polypropylene (PP) nonwoven fabric cover (WC). The secondary factor (Factor II) was the sweet potato cultivars: ‘Satsumo Imo’, ‘Beauregard’, ‘Purple’, ‘White Triumph’, and ‘Carmen Rubin’. The characteristics of the cultivars are presented in

Table 1. Characteristics of sweet potato cultivars.

Specification	Cultivars
	‘Satsumo Imo’	‘Beauregard’	‘Purple’	‘White Triumph’	‘Carmen Rubin’
Flesh color	Light yellow	Intense orange	Deep purple	White/Creamy	Light orange
Skin color	Purple	Light orange/Copper	Dark purple	Yellow-white	Red-pink
Root shape	Elongated, regular	Fusiform to elliptical	Oval-oblong	Irregular, blocky	Fusiform, slender

.

2.1.3. Cultivar Characteristics

The selection of cultivars for the study was based on their genetic diversity, primarily manifested in flesh and skin colour, which serve as direct indicators of the dominant bioactive compound profiles (Figure 1). The experiment included the full colour spectrum available within the species, ranging from white-fleshed cultivars to orange-fleshed and deeply purple-fleshed cultivars.

2.1.4. Characteristics of Covering Materials

Polyethylene (PE) film and polypropylene (PP) nonwoven fabric were used in this study to modify the microclimate, which can influence vitamin C synthesis, antioxidant properties, and phenolic acid content. The coverings differ in their physical properties, affecting soil temperature and gas exchange between the soil and the atmosphere [16,17].

Polyethylene Film (PE)

The material exhibited high transmissivity to shortwave solar radiation. In the experiment, perforated polyethylene film (0.04 mm thickness; approx. 100 perforations m⁻²) supplied by Mulan Co., Ltd. (Weifang, China) was applied. This modification was intended to optimize thermal conditions by reducing the risk of plant overheating during periods of high solar radiation, while ensuring gas exchange and allowing precipitation to reach the root system. Compared with non-perforated film, the perforated material alters microclimatic dynamics by enabling partial air exchange.

Polypropylene Nonwoven Fabric (PP)

The polypropylene (PP) nonwoven cover supplied by Rayson Global Co., Ltd. (Foshan, China) features a porous structure that allows the transmission of air, water vapor, and precipitation. Compared with polyethylene (PE) film, PP nonwoven fabric generally results in a lower increase in air and soil temperature while providing improved air circulation. The material reduces the amplitude of temperature fluctuations and offers protection against frost without causing excessive overheating. Its permeability enables rainfall infiltration into the soil, which may be particularly relevant during periods characterized by higher hydrothermal coefficient (K) values (e.g., May 2023). The use of PP nonwoven fabric is associated with more stable growth conditions compared with PE film. Reduced thermal stress amplitude under PP covering may influence the phenolic acid profile in roots; however, this relationship requires further confirmation.

2.2. Agronomic Practices

The preceding crop was spring barley. In autumn, organic fertilization (manure, 25 t·ha⁻¹) and mineral fertilization (34.9 kg P·ha⁻¹, 99.6 kg K·ha⁻¹, 80 kg N·ha⁻¹) were applied. Fertilizer doses were calculated based on the results of soil analyses carried out by the District Chemical-Agricultural Station in Rzeszów (Poland) and adjusted to the nutrient requirements of sweet potato, in accordance with standard agronomic recommendations for this crop under temperate climate conditions (Table 3). The planting material consisted of in vitro propagated seedlings produced in the farm greenhouse. Sweet potato seedlings were manually transplanted to the field in May (14 May 2021, 16 May 2022, 13 May 2023) with a spacing of 40 × 75 cm on ridges. According to the experimental design, immediately after transplanting, polyethylene (PE) film and polypropylene (PP) nonwoven covers were applied to the corresponding subplots to modify the microclimate, including regulating soil temperature and providing frost protection. Manual weeding was performed until row closure. After full canopy development, sweet potato plants naturally shade the interrow, limiting weed growth and reducing the need for further weeding. No fungicides or insecticides were applied, as no pests or diseases were observed, which is typical for sweet potato cultivation under Polish conditions. Roots were harvested at BBCH stage 97 (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) [18] using an elevator harvester. Harvest occurred in mid-October (18 October 2021, 16 October 2022, 12 October 2023).

2.3. Meteorological Conditions

Meteorological conditions during the sweet potato growing seasons (May–September) in 2021–2023, based on data from the weather station in Dukla, are summarized in

Table 2. Meteorological conditions during the sweet potato growing seasons of 2021–2023, according to the Dukla Meteorological Station.

Years	Months						Mean
	April	May	June	July	August	September
Rainfalls (mm)
2021	7.2	16.1	14.0	20.9	31.2	41.5	21.82
2022	23.7	61.4	6.5	16.1	13.8	10.2	21.95
2023	23.4	35.7	52.9	11.7	15.30	22.0	26.83
The average sum of long-term (1989–2014)	55.9	956	100.9	116.5	30.1	26.2	70.87
Air Temperature (°C)
2021	16.50	18.88	21.10	21.30	21.60	13.03	18.70
2022	10.60	13.70	22.93	20.20	20.63	12.44	16.80
2023	10.03	12.37	17.13	20.37	21.33	15.53	16.10
Long-term average (1989–2014)	9.2	13.6	16.4	19	19.4	18.6	16.03
Hydrothermal Coefficient *
2021	0.5	0.9	0.7	1	1.4	3.2	1.3
2022	2.2	4.5	0.3	0.8	0.6	0.8	1.5
2023	2.3	2.9	3.1	0.6	0.7	1.4	1.8

* The hydrothermal coefficient was calculated according to the formula: k = 10 P ∑ t [19], where P represents the total monthly precipitation in mm, and Σt is the monthly cumulative air temperature > 0 °C. The index values were categorized as follows: extremely dry (k ≤ 0.4), very dry (0.4 < k ≤ 0.7), dry (0.7 < k ≤ 1.0), rather dry (1.0 < k ≤ 1.3), optimal (1.3 < k ≤ 1.6), rather humid (1.6 < k ≤ 2.0), wet (2.0 < k ≤ 2.5), very humid (2.5 ≤ k ≤ 3.0), and extremely humid (k > 3.0).

.

Analysis of precipitation sums showed that during the study years, rainfall was clearly lower than the long-term average, especially in key summer months. In 2021, very low precipitation was recorded in spring, followed by a marked increase in September. In 2022, May was very wet, whereas June and August experienced precipitation deficits. In 2023, the maximum rainfall occurred in June, while July and August were dry. The average precipitation from April to September was 21.82 mm in 2021, 21.95 mm in 2022, and 26.83 mm in 2023, values that were significantly below the long-term mean.

The average air temperature in 2021 (18.9 °C) exceeded the long-term norm, whereas in 2022 and 2023 it was lower, reaching 16.8 °C and 16.1 °C, respectively, accompanied by a cooler spring and moderately warm summer.

Hydrothermal coefficient values indicated substantial variation in moisture conditions both between years and within the growing season. In 2021, the early season was characterized by dry to very dry conditions, transitioning to very wet in September. In 2022, spring was wet to very wet, while the summer was water-deficient. In 2023, the first part of the season was wet, locally extremely wet, followed by dry conditions in July and August.

These results confirm high variability in meteorological conditions during the study years and frequent deviations from long-term averages, which could have significantly influenced the course of sweet potato (Ipomoea batatas) growth and yield, particularly under periodically occurring water stress (Table 2).

2.4. Soil Conditions

Soil Sampling and Analysis

Assessment of the soil’s basic physicochemical properties was conducted before the start of each growing season (2021–2023). Representative samples were collected from the arable layer (0–30 cm) of each experimental plot, following the guidelines of the Polish Standard [20]. All laboratory analyses were performed at the accredited District Agricultural-Chemical Station in Rzeszów, using standardized analytical methods. Soil pH was determined potentiometrically in 1 M KCl, and organic matter content was measured using the Tiurin method [21]. Available forms of phosphorus, potassium, and magnesium were analysed according to the procedures described by Handzel et al. [22], whereas microelements (Cu, Mn, Zn, Fe) were determined following the methodology proposed by Ostrowska et al. [23]. The results of the physicochemical analyses indicate that the soil used in the experiment was highly suitable for sweet potato (Ipomoea batatas (L.) Lam.) cultivation (Table 3). The soil was classified as a luvisol of quality class IVb, with a pH ranging from slightly acidic to neutral, providing favorable conditions for plant growth and development (Table 3).

Table 3. Chemical composition and soil reaction (2021–2023): macro- and micro-nutrients, humus, calcium carbonate.

Years	Macronutrients (mg·100 g−1)			CaCO3 (g·kg−1)	Humus (g·kg−1)	pH (in 1 M KCI)	Micronutrients (mg·kg−1)
	P2O5	K2O	Mg				Cu	Mn	Zn	Fe
2021	18.6	31.1	24.3	0.03	27.8	5.54	6.7	175.9	13.6	1581
2022	1.9	31.4	2.9	0.04	29.2	6.68	6.1	181.1	15.7	1797
2023	18.2	34.5	26.5	0.06	29.8	6.71	6.7	182.9	16.5	1885

Source: Data prepared based on the results obtained from the District Chemical-Agricultural Station in Rzeszów.

Table 3. Chemical composition and soil reaction (2021–2023): macro- and micro-nutrients, humus, calcium carbonate.

Years	Macronutrients (mg·100 g−1)			CaCO3 (g·kg−1)	Humus (g·kg−1)	pH (in 1 M KCI)	Micronutrients (mg·kg−1)
	P2O5	K2O	Mg				Cu	Mn	Zn	Fe
2021	18.6	31.1	24.3	0.03	27.8	5.54	6.7	175.9	13.6	1581
2022	1.9	31.4	2.9	0.04	29.2	6.68	6.1	181.1	15.7	1797
2023	18.2	34.5	26.5	0.06	29.8	6.71	6.7	182.9	16.5	1885

Source: Data prepared based on the results obtained from the District Chemical-Agricultural Station in Rzeszów.

During the study period, soil pH improved, increasing from slightly acidic in 2021 (pH_KCl = 5.54) to neutral in 2022–2023 (pH_KCl = 6.7). This change was correlated with a twofold increase in calcium carbonate content (from 0.03 to 0.06 g kg⁻¹). Optimizing soil pH is crucial for sweet potato (Ipomoea batatas (L.) Lam.), as it promotes efficient macronutrient uptake and reduces aluminum phytotoxicity. A gradual increase in organic matter content (from 27.8 to 29.8 g kg⁻¹) was also observed, indicating improved soil structure and water-holding capacity, which is particularly important given the recorded rainfall deficits. The soil exhibited stable, high levels of available phosphorus (17.9–18.6 mg 100 g⁻¹) and potassium, with potassium content increasing to 34.5 mg 100 g ⁻¹ in the last year of the study (Table 3). High potassium availability is fundamental for Ipomoea batatas, as it is involved in assimilate transport to roots and the synthesis of sugars and vitamin C. Magnesium levels, despite a temporary decline in 2022 (21.9 mg 100 g⁻¹), remained sufficient to support normal photosynthetic activity. Analysis of microelements showed an increasing trend for all examined elements (Cu, Mn, Zn, Fe). Particularly high iron (1581–1885 mg kg⁻¹) and zinc (13.6–16.5 mg kg⁻¹) concentrations in the luvisol provided a favorable background for producing high-quality, nutrient-rich roots.

2.5. Chemical Analyses

2.5.1. Preparation of Plant Material for Analysis

From each plot, 10 roots were randomly selected. The samples were washed, dried, and sliced into 10 mm thick pieces, then immediately frozen at –35 °C. The samples were freeze-dried (ZIRBUS Technology GmbH, Bad Grund (Harz), Germany), ground in a laboratory mill (Grindomix GM 200), and stored in airtight containers at refrigerated temperatures until analysis.

2.5.2. Determination of Ascorbic Acid Content

Ascorbic acid content was determined according to the method described by Tarrago-Trani et al. [24] with slight modifications. Approximately 5 g of freeze-dried sweet potato samples were weighed into an Erlenmeyer flask, and 50 mL of 3% (w/v) metaphosphoric acid solution was added. Extraction was carried out for 15 min in an ultrasonic bath at 20 °C. The samples were then centrifuged for 10 min at 6000 rpm. The obtained supernatant was filtered through a 0.45 μm membrane filter.

Chromatographic analysis was performed using high-performance liquid chromatography (HPLC) with a Shimadzu Prominence-i system (Shimadzu, Kyoto, Japan) equipped with a ZORBAX Eclipse Plus C18 column (250 × 4.6 mm, 5 μm; (Agilent Technologies, Santa Clara, CA, USA). The mobile phase consisted of 0.1 M phosphoric acid in isocratic mode at a flow rate of 1.0 mL·min⁻¹. The column temperature was maintained at 25 °C. Detection was performed at 245 nm. The retention time of ascorbic acid was approximately 5 min. Results were expressed as mg·100 g⁻¹ dry weight (DW) based on a calibration curve prepared from standard solutions of L-ascorbic acid.

2.5.3. Determination of Total Antioxidant Capacity (FRAP)

The total antioxidant capacity of the samples was determined using the FRAP (Ferric Reducing Antioxidant Power) assay, as described by Benzie and Strain [25]. This method is based on the ability of antioxidants to reduce ferric ions (Fe³⁺) to ferrous ions (Fe²⁺) in an acidic environment (pH 3.6), resulting in the formation of a blue Fe²⁺–TPTZ complex (2,4,6-tris(2-pyridyl)-s-triazine). The absorbance change of the complex was measured spectrophotometrically at 593 nm.

The FRAP reagent was prepared by mixing 300 mM acetate buffer (pH 3.6), 10 mM TPTZ solution in 40 mM HCl, and 20 mM FeCl₃·6H₂O in a 10:1:1 (v/v/v) ratio. The freshly prepared reagent was incubated at 37 °C immediately before use. To 3.995 mL of the FRAP reagent, 5 µL of appropriately diluted plant sample was added, mixed thoroughly, and incubated for 30 min at 37 °C. Absorbance was measured at 593 nm against a blank containing 3.995 mL of FRAP reagent and 5 µL of distilled water. All measurements were performed in triplicate. A calibration curve was prepared using Trolox standard solutions of different concentrations. Results were corrected for dilution and expressed as µmol Trolox equivalents per 100 g dry weight (DW) of the sample. Measurements were performed using a Thermo Scientific EVO 300PC spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).

2.5.4. Free Radical Scavenging Ability Determination Using a Stable ABTS Radical Cation

The free radical-scavenging capacity of the samples was determined using the ABTS radical cation decolorization assay as described by Re et al. [26]. The ABTS radical cation (ABTS·⁺) was generated by reacting 7 mM ABTS solution in water with 2.45 mM potassium persulfate in a 1:1 (v/v) ratio. The mixture was stored in the dark at room temperature for 12–16 h prior to use. The ABTS·⁺ solution was then diluted with methanol to obtain an absorbance of 0.700 ± 0.020 at 734 nm. For the assay, 5 µL of the plant extract was added to 3.995 mL of the diluted ABTS·⁺ solution. After thorough mixing, absorbance was measured after 10 min of incubation. Each measurement included an appropriate blank containing the solvent. A calibration curve was prepared using Trolox standard solutions of different concentrations. All measurements were performed in triplicate using a Thermo Scientific EVO 300PC spectrophotometer (USA). Results were corrected for dilution and expressed as µmol Trolox equivalents per 100 g dry matter (DM).

2.5.5. Determination of Free Radical Scavenging Ability Using the DPPH Method

The total free radical scavenging capacity of sweet potato samples was determined using the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay [27] with slight modifications. This method is based on antioxidants’ ability to reduce the stable DPPH radical, which exhibits a maximum absorbance at 515 nm.

The DPPH solution was prepared by dissolving 2.4 mg of DPPH in 100 mL of methanol. For the assay, 5 µL of appropriately diluted plant extract was added to 3.995 mL of the methanolic DPPH solution. The mixture was thoroughly shaken and incubated for 10 min at room temperature in the dark.

The absorbance of the reaction mixture was measured spectrophotometrically at 515 nm. The absorbance of the DPPH solution without antioxidant addition was used as the blank. All measurements were performed in triplicate.

A calibration curve was prepared using Trolox standard solutions of different concentrations. Results were corrected for dilution and expressed as µmol Trolox equivalents per 100 g dry weight (DW) of the sample.

2.5.6. Determination of Total Phenolic Content (TPC)

Total phenolic content in the extracts was determined using the Folin–Ciocalteu method as described by Shahmohamadi et al. [28], with minor modifications. In brief, 25 µL of the extract (either alcoholic or aqueous) was mixed with 125 µL of 0.2 N Folin–Ciocalteu reagent and incubated at room temperature for 5 min. Then, 100 µL of 75 g·L⁻¹ sodium carbonate solution was added, and the mixture was allowed to react for 2 h at room temperature. The absorbance of the reaction mixture was measured at 760 nm using a Jenway spectrophotometer (Cole-Parmer Ltd., Stone, Staffordshire, UK). Results were calculated based on a calibration curve prepared with gallic acid standards and expressed as mg gallic acid equivalents (GAE) per 100 g dry weight (DW).

2.6. Statistical Analysis

All experiments were performed in triplicate, and the results are presented as the mean ± standard deviation (SD). The data were examined for normality and homogeneity of variance prior to statistical analysis. A one-way analysis of variance (ANOVA) was performed to assess differences among variables. Post hoc comparisons were conducted using Duncan’s multiple range test at a significance level of p ≤ 0.05. To investigate relationships among variables, multivariate analyses were performed, including principal component analysis (PCA), scaled heat map (HM) analysis, and cluster analysis (CA). The data were previously standardized. Statistical analyses for ANOVA and PCA were performed using Statistica version 13.3 (StatSoft, Cracow, Poland), while HM with CA was conducted using RStudio version 4.5.2.

3. Results

3.1. Effect of Cultivation Method, Cultivar, and Year on Ascorbic Acid and Total Phenolics

The results demonstrated significant differences in ascorbic acid content depending on cultivar, cultivation technology, and year of study (three-way ANOVA, p ≤ 0.05). The highest mean ascorbic acid content was recorded in cultivars B and C, regardless of cultivation technology and year, reaching 105.28 and 97.39 mg·100 g⁻¹ DW, respectively. The lowest values were observed in cultivars S and W, accounting for 58–61% of the levels observed in cultivars B and C (

Table 4. Ascorbic Acid and Total Polyphenols in Five Sweet Potato Cultivars as Affected by Cultivation Method and Study Year (2021–2023).

Cultivars	Cultivation Method	Ascorbic Acid mg 100 g−1 d.w.			Total Polyphenols mg 100 g−1 d.w.
		Years of Research			Years of Research
		2021	2022	2023	2021	2022	2023
S	TC **	51.01 ± 0.66 a,A	54.79 ± 1.17 a,A	52.34 ± 1.87 a,A	834.1 ± 0.87 b,A	812.8 ± 1.44 b,B	794.4 ± 1.58 c,C
	FC **	30.62 ± 0.40 b,B	42.95 ± 0.69 a,AB	44.02 ± 0.56 b,A	883.3 ± 2.63 a,A	850.6 ± 1.25 a,B	817.9 ± 1.48 a,C
	WC **	31.62 ± 0.41 b,A	29.34 ± 0.16 c,B	27.22 ± 0.31 c,C	838.9 ± 1.83 b,A	806.5 ± 2.83 c,B	807.5 ± 0.95 b,B
B	TC **	104.0 ± 0.57 a,C	107.8 ± 0.49 a,B	111.4 ± 0.87 a,A	864.5 ± 2.54 c,A	844.5 ± 1.42 b,B	810.8 ± 2.25 c,C
	FC **	99.64 ± 0.50 b,C	103.6 ± 0.57 b,B	105.3 ± 0.80 b,A	910.7 ± 2.47 a,A	861.8 ± 1.58 a,B	853.81 ± 1.28 a,C
	WC **	101.4 ± 0.41 c,C	104.5 ± 0.57 b,B	109.9 ± 1.06 ab,A	895.5 ± 3.76 b,A	860.3 ± 2.33 a,B	820.4 ± 1.46 b,C
P	TC **	57.81 ± 0.48 a,C	64.64 ± 0.26 a,B	68.48 ± 0.51 a,A	888.1 ± 1.59 a,A	845.3 ± 2.67 c,B	810.8 ± 2.58 c,C
	FC **	52.63 ± 0.44 b,C	60.56 ± 0.16 b,B	63.37 ± 1.04 c,A	991.5 ± 2.77 b,A	865.4 ± 2.11 b,C	945.1 ± 2.36 b,B
	WC **	55.01 ± 0.38 ab,B	63.81 ± 0.65 a,AB	65.33 ± 0.83 b,A	934.1 ± 2.28 c,C	890.14 ± 1.36 a,B	963.5 ± 2.84 a,A
W	TC **	40.29 ± 0.57 a,B	42.32 ± 0.38 a,B	48.96 ± 0.68 a,A	68.5 ± 0.48 b,A	59.2 ± 0.85 b,B	48.8 ± 1.04 b,C
	FC **	35.53 ± 0.35 b,B	37.89 ± 0.52 c,B	45.43 ± 0.28 b,A	69.2 ± 0.68 b,A	65.7 ± 0.34 a,AB	58.4 ± 0.76 a,B
	WC **	38.94 ± 0.51 b,B	40.27 ± 0.64 b,A	40.73 ± 0.33 c,A	74.5 ± 0.63 a,A	62.2 ± 0.47 b,B	50.8 ± 0.58 b,C
C	TC **	104.9 ± 1.27 a,C	107.2 ± 0.86 a,B	111.9 ± 0.83 a,A	611.6 ± 0.53 c,A	583.9 ± 1.03 c,B	554.6 ± 1.86 a,C
	FC **	90.96 ± 0.47 c,B	87.37 ± 0.28 b,C	94.99 ± 1.04 b,A	691.9 ± 0.96 a,A	635.3 ± 1.26 a,B	561.8 ± 2.05 a,C
	WC **	99.52 ± 1.03 b,A	87.37 ± 0.43 b,C	92.26 ± 0.84 b,B	651.2 ± 1.56 b,A	605.6 ± 1.75 b,B	558.7 ± 1.16 a,C

S—‘Satsumo Imo’, B—‘Beauregard’, P—‘Purple’, W—‘White Triumph’, C—‘Carmen Rubin’, TC **—traditional cultivation, FC **—cultivation under polyethylene film, and WC **—cultivation under polypropylene nonwoven. Statistical differences were determined using one-way ANOVA with a post hoc test at p ≤ 0.05. Small letters indicate statistically significant differences among cultivation methods, while capital letters indicate significant differences among years of the experiment. Data represent mean values ± standard deviation (SD) from three independent replicates (n = 3); d.w.—dry weight.

). Cultivation technology significantly affected ascorbic acid accumulation. Across all cultivars, traditional cultivation (TC) yielded the highest values. The greatest variability was observed in cultivar S, where ascorbic acid content under row cover (WC) and foil tunnel (FC) accounted for 55.76% and 74.36% of the value obtained under TC, respectively. In contrast, cultivar B showed the lowest sensitivity to cultivation method, reaching 95.46% (FC) and 97.71% (WC) of the TC level (Table 4).

The results indicate that the cultivar × cultivation technology interaction significantly affected ascorbic acid accumulation (mean values are shown in Figure 2). Variations in ascorbic acid levels in the sweet potato roots studied were generally significant across the years of the study. In the S cultivar (‘Satsumo Imo’), the highest ascorbic acid level was achieved in traditional cultivation (TC) in 2022 (54.79 mg 100 g⁻¹ d.w.) (Table 4), while in other years the values were lower and statistically insignificant. Cultivation under polyethylene film (FC) reduced the ascorbic acid content compared to TC cultivation (55.9% in 2021, 78.39% in 2022, 80.33% in 2023). In contrast, cultivation under polypropylene nonwoven fabric (WC) resulted in the lowest values throughout the study period (49.7–57.74% relative to TC cultivation).

Total polyphenol content (TPC) also varied significantly across cultivars, cultivation technologies, and years of the study (p ≤ 0.05). A decrease in TPC was observed in most cultivars from 2021 to 2023, particularly pronounced in cultivars S (‘Satsumo Imo’), B (‘Beauregard’), and C (‘Carmen Rubin’). The highest TPC values were obtained in cultivar P (‘Purple’), reaching 991.5 mg 100 g⁻¹ d.w. in FC in 2021 (Table 4). High TPC concentrations were also recorded in the B cultivar under the same cultivation technology. Intermediate levels were observed in the S cultivar, lower levels in the C cultivar, and the lowest levels in the W cultivar, whose values were many times lower than those of the other cultivars (Table 4). Cultivation technologies significantly influenced the total polyphenol content in sweet potato roots. In most cultivars, the use of FC mulch favored the highest accumulation of phenolic compounds, while the absence of TC mulch most often resulted in lower TPC values. Exceptions were certain combinations, e.g., cultivar P in 2023 grown under nonwoven fabric (WC), which confirms the significance of the cultivar × cultivation technology interaction (Table 4). Additionally, our studies observed that, in addition to genetic and agrotechnical factors, environmental conditions in individual years of the study significantly impacted the synthesis of phenolic compounds (Figure 3).

3.2. Analysis of the Correlation Between Antioxidant Activity and Total Polyphenol Content in the Roots of Five Sweet Potato Cultivars

Correlation analyses between antioxidant activity determined by the ABTS, FRAP, and DPPH methods and total polyphenol content show strong positive correlations in most of the studied cultivars, confirming that these methods largely describe the same antioxidant properties of the raw material (

Table 5. Pearson’s correlation coefficients (r) between antioxidant activity (ABTS, FRAP, DPPH) and total polyphenol content in the tested sweet potato cultivars.

Cultivars	Variable	ABTS	FRAP	DPPH	Total Polyphenols
‘Satsumo Imo’	ABTS	-
	FRAP	0.99	-
	DPPH	0.90	0.88	-
	Total polyphenols	0.88	0.86	0.74	-
‘Beauregard’	ABTS	-
	FRAP	0.84	-
	DPPH	0.89	0.69	-
	Total polyphenols	0.98	0.83	0.89	-
‘Purple’	ABTS	-
	FRAP	0.93	-
	DPPH	0.85	0.93	-
	Total polyphenols	0.52	0.28	0.05	-
‘White Triumph’	ABTS	1	0.93	0.91	0.92
	FRAP	0.95	1	0.96	0.90
	DPPH	0.92	0.97	1	0.89
	Total polyphenols	0.93	0.91	0.90	1
‘Carmen Rubin’	ABTS	-
	FRAP	0.86	-
	DPPH	0.83	0.99	-
	Total polyphenols	0.87	0.98	0.95	-

Correlation coefficients are presented in a lower triangular format. “-” indicates a correlation of the variable with itself (r = 1.00); p ≤ 0.05.

). In the ‘Satsumo Imo’, ‘White Triumph’, and ‘Carmen Rubin’ cultivars, very high correlation coefficients were found both between the individual methods for determining antioxidant activity and between these methods and total polyphenol content. Particularly strong correlations were observed between FRAP and DPPH (r = 0.99 in ‘Carmen Rubin’ and 0.96–0.97 in ‘White Triumph’), indicating high agreement between the tests.

In the ‘Beauregard’ cultivar, strong correlations were also noted between ABTS and total polyphenols (r = 0.98) and between DPPH and total polyphenols (r = 0.89), although the FRAP–DPPH correlation was moderate. A different pattern of relationships was observed in the ‘Purple’ cultivar, where, despite a high correlation coefficient between the ABTS, FRAP, and DPPH methods, there was a low correlation with total polyphenol content (Table 5).

3.3. Evaluation of Phenolic Acid Content in Five Sweet Potato Cultivars Depending on Cultivation Technology, Genetic Characteristics of the Cultivars, and Years

An analysis of the phenolic acid composition revealed significant differences among the tested sweet potato cultivars and the cultivation techniques used in each year of the study (

Table 6. Phenolic acid content in mg 100 g⁻¹ dry weight in sweet potato roots of the ‘Satsumo Imo’, ‘Beauregard’, and ‘Purple’ cultivars, depending on cultivation technology and study years (means 2021–2023).

Agronomic Factors	Neochlorogenic Acid	Caffeoyl-Tartaric Acid	Chlorogenic Acid	Cryptochlorogenic Acid	Caffeic Acid	3,4-di-O-Caffeoylquinic Acid	3,5-di-O-Caffeoylquinic Acid	Chicoric Acid	Total of Phenolic Acids
‘Satsumo Imo’
ST1	ND	ND	662.28 ± 0.77	15.73 ± 0.04	395.79 ± 0.40	9.82 ± 0.07	141.50 ± 0.69	0.77 ± 0.08	1225.89
ST2	ND	ND	562.44 ± 0.96	15.72 ± 0.16	291.61 ± 0.47	10.24 ± 0.11	146.23 ± 0.69	0.50 ± 0.07	1129.19
ST3	ND	ND	482.11 ± 0.28	16.47 ± 0.54	211.73 ± 0.24	9.72 ± 0.21	138.23 ± 0.42	0.56 ± 0.03	858.82
SF1	ND	ND	665.13 ± 0.37	17.39 ± 0.04	297.46 ± 0.63	10.01 ± 0.07	144.39 ± 0.47	0.92 ± 0.04	1135.30
SF2	ND	ND	663.29 ± 0.47	15.72 ± 0.19	295.94 ± 0.75	8.91 ± 0.17	141.18 ± 0.53	0.87 ± 0.05	1125.91
SF3	ND	ND	667.47 ± 0.68	16.97 ± 0.43	298.94 ± 0.95	9.74 ± 0.14	147.18 ± 1.09	0.73 ± 0.03	1141.03
SW1	ND	ND	668.83 ± 0.61	18.39 ± 0.04	295.99 ± 0.87	10.94 ± 0.03	142.59 ± 0.36	0.91 ± 0.05	1137.65
SW2	ND	ND	663.95 ± 0.94	17.72 ± 0.09	292.30 ± 1.71	12.71 ± 0.08	141.90 ± 0.45	0.77 ± 0.05	1129.35
SW3	ND	ND	659.83 ± 0.47	19.83 ± 0.43	285.30 ± 1.27	11.71 ± 0.16	144.47 ± 1.16	0.87 ± 0.01	1122.01
‘Beauregard’
BT1	ND	ND	1114.57 ± 0.45	190.80 ± 0.63	ND	39.60 ± 0.98	191.65 ± 0.42	4.75 ± 0.05	1541.37
BT2	ND	ND	1113.85 ± 1.67	196.80 ± 0.49	ND	37.24 ± 0.58	196.33 ± 0.68	4.34 ± 0.05	1548.56
BT3	ND	ND	1117.85 ± 0.96	185.30 ± 0.93	ND	41.24 ± 0.71	186.33 ± 0.36	5.21 ± 0.03	1535.93
BF1	ND	ND	1117.87 ± 2.02	193.11 ± 1.39	ND	40.77 ± 0.26	194.58 ± 0.49	5.00 ± 0.05	1551.33
BF2	ND	ND	1114.19 ± 1.49	192.13 ± 0.89	ND	41.62 ± 0.34	192.84 ± 1.47	4.87 ± 0.06	1545.65
BF3	ND	ND	1115.87 ± 1.59	195.61 ± 0.73	ND	42.43 ± 0.41	196.84 ± 0.76	5.88 ± 0.14	1556.63
BW1	ND	ND	1139.89 ± 1.45	199.28 ± 0.84	ND	42.14 ± 0.47	194.82 ± 1.33	5.33 ± 0.05	1581.46
BW2	ND	ND	1118.85 ± 1.39	197.63 ± 0.97	ND	41.95 ± 0.67	193.97 ± 0.77	5.13 ± 0.35	1557.53
BW3	ND	ND	1119.87 ± 0.97	193.97 ± 0.45	ND	44.95 ± 0.41	189.87 ± 0.54	5.67 ± 0.26	1554.33
‘Purple’
PT1	476.05 ± 0.71	102.00 ± 0.52	11,524.77 ± 2.47	187.43 ± 0.84	167.87 ± 0.33	444.76 ± 0.26	3523.03 ± 0.47	351.12 ± 2.09	16,777.04
PT2	479.38 ± 2.22	104.00 ± 0.49	11,634.43 ± 1.53	198.29 ± 0.61	169.87 ± 0.81	453.44 ± 0.26	3540.67 ± 0.47	342.73 ± 1.43	16,922.81
PT3	483.72 ± 1.86	105.76 ± 0.66	11,728.77 ± 2.76	179.67 ± 0.84	173.55 ± 0.45	461.36 ± 0.34	3560.54 ± 3.61	366.47 ± 2.29	17,059.84
PF1	476.05 ± 1.71	102.00 ± 0.52	11,552.10 ± 7.87	193.23 ± 0.49	171.24 ± 0.55	447.93 ± 0.48	3527.08 ± 3.48	355.61 ± 1.18	16,825.24
PF2	482.72 ± 0.35	106.33 ± 0.36	11,433.09 ± 5.94	191.29 ± 0.07	168.88 ± 0.55	454.15 ± 0.48	3525.00 ± 4.71	350.60 ± 0.27	16,712.06
PF3	486.53 ± 0.55	108.48 ± 0.54	11,736.77 ± 6.43	196.01 ± 0.80	174.88 ± 1.50	461.15 ± 0.96	3539.67 ± 1.47	363.93 ± 0.94	17,067.42
PW1	476.05 ± 0.71	101.56 ± 0.52	11,549.77 ± 1.47	191.26 ± 0.74	170.91 ± 0.59	455.39 ± 0.48	3528.05 ± 2.82	368.92 ± 3.54	16,841.91
PW2	485.38 ± 0.62	104.33 ± 0.06	11,530.45 ± 2.21	187.98 ± 0.49	169.57 ± 0.15	447.16 ± 0.13	3534.00 ± 1.27	362.60 ± 2.76	16,821.47
PW3	493.38 ± 0.47	106.63 ± 0.37	11,599.10 ± 2.23	198.29 ± 0.76	176.20 ± 0.35	462.03 ± 5.34	3543.80 ± 2.88	374.43 ± 1.48	16,953.86

Data represent mean values ± standard deviation (SD) from three independent replicates (n = 3); ND—Not Detected; ST1—traditional cultivation without mulch (TC) of the ‘Satsumo Imo’ cultivar in 2021; ST2—traditional cultivation without mulch (TC) of the ‘Satsumo Imo’ cultivar in 2022; ST3—traditional cultivation without mulch (TC) of the ‘Satsumo Imo’ cultivar in 2023; SF1—cultivation under plastic mulch (FC) ‘Satsumo Imo’ cultivar in 2021; SF2—SF—cultivation under plastic mulch (FC) ‘Satsumo Imo’ cultivar in 2022; SF3—SF—cultivation under plastic mulch (FC) ‘Satsumo Imo’ cultivar in 2023; SW—cultivation under nonwoven fabric (WC) ‘Satsumo Imo’ cultivar, SW1—cultivation under nonwoven fabric (WC) ‘Satsumo Imo’ cultivar, 2021; SW2—cultivation under nonwoven fabric (WC) ‘Satsumo Imo’ cultivar; 2022, SW3—cultivation under nonwoven fabric (WC) ‘Satsumo Imo’ cultivar 2023. BT1—conventional cultivation without overwintering (TC), ‘Beauregard’ cultivar, 2021; BT2—conventional cultivation without overwintering (TC), ‘Beauregard’ cultivar, 2022; BT3—conventional cultivation without overwintering (TC), ‘Beauregard’ cultivar, 2023; BF1—film-covered cultivation (FC) ‘Beauregard’ cultivar 2021, BF2—film-covered cultivation (FC) ‘Beauregard’ cultivar 2022, BF3—film-covered cultivation (FC) ‘Beauregard’ cultivar 2023; BW1—cultivation under nonwoven fabric (WC) ‘Beauregard’ cultivar 2021; BW2—cultivation under nonwoven fabric (WC) ‘Beauregard’ cultivar 2022; BW3—cultivation under nonwoven fabric (WC) ‘Beauregard’ cultivar 2023. PT1—traditional cultivation without cover (TC) ‘Purple’ cultivar, 2021; PT2—traditional cultivation without cover (TC) ‘Purple’ cultivar, 2022; PT3—traditional cultivation without cover (TC) ‘Purple’ cultivar, 2023; PF1—cultivation under plastic film (FC) ‘Purple’ cultivar; 2021; PF2—cultivation under plastic film (FC) ‘Purple’ cultivar; 2022; PF3—cultivation under plastic film (FC) ‘Purple’ cultivar; 2023; PW1—cultivation under nonwoven fabric (WC) ‘Purple’ cultivar, 2021; PW2—cultivation under nonwoven fabric (WC) ‘Purple’ cultivar, 2022; PW3—cultivation under nonwoven fabric (WC) ‘Purple’ cultivar, 2023.

). Chlorogenic acid was the predominant compound in all analysed samples; however, its content varied significantly across cultivars. The lowest values for total phenolic acids were recorded in the ‘Satsumo Imo’ cultivar, where they ranged from 858.82 mg 100 g⁻¹ d.w. to 1225.89 mg 100 g⁻¹ d.w. In this cultivar, the main components of the phenolic fraction were chlorogenic acid and caffeic acid. In conventional cultivation, a clear downward trend in the content of these compounds was observed over the subsequent years of the study—from 662.28 mg 100 g⁻¹ d.w. in 2021 to 482.11 mg 100 g⁻¹ d.w. in 2023 for chlorogenic acid (Table 6). A similar trend was also observed for caffeic acid. Growing the crop under plastic mulch and nonwoven fabric stabilized the levels of the compounds studied, but did not result in a significant increase in their total content. Higher levels of phenolic acids were obtained in the ‘Beauregard’ cultivar. The total content of these compounds ranged from 1535.93 mg 100 g⁻¹ d.w. to 1581.46 mg 100 g⁻¹ d.w. The dominant compound was chlorogenic acid, whose content exceeded 1100 mg 100 g⁻¹ d.w. In this cultivar, cryptochlorogenic acid and 3,5-di-O-caffeoylquinic acid also accounted for a significant proportion. The highest total phenolic acids were recorded in the mulch-covered plot in 2021 (BW1), while the lowest were in the conventional plot in 2023 (BT3). In contrast to the ‘Satsumo Imo’ cultivar, no clear trend of changes was observed in this cultivar over the subsequent years of the study (Table 6).

The highest levels of the analysed phenolic compounds were found in the ‘Purple’ cultivar. The total phenolic acids were more than ten times higher than in the ‘Satsumo Imo’ cultivar and ranged from 16,712.06 mg 100 g⁻¹ d.w. to 17,067.42 mg 100 g⁻¹ d.w. Chlorogenic acid clearly dominated in this cultivar, with a content exceeding 11,500 mg 100 g⁻¹ d.w., and 3,5-di-O-caffeoylquinic acid also accounted for a significant proportion. The highest total phenolic acid content was recorded in the plastic-covered cultivation in 2023 (PF3), while the lowest was in the same cultivation method in 2022 (PF2). In most cases, an upward trend in the content of these compounds was observed in subsequent years of the study. Comparing the cultivation technologies used, it can be concluded that cultivation under nonwoven fabric and under plastic film favored the maintenance or increase in phenolic acid levels, particularly in the ‘Purple’ and ‘Beauregard’ cultivars. The results indicate that both the cultivar factor and the microclimatic conditions created by the cultivation technology used, as well as the variability of weather conditions in individual years of the study, influenced the accumulation of phenolic acids in sweet potato roots (

Table 7. Phenolic acid content in mg per 100 g ⁻¹ of dry weight in sweet potato roots of the ‘White Triumph’ and ‘Carmen Rubin’ cultivars, depending on cultivation methods and the years of the study (averages from 2021–2023).

Agronomic Factors	Neochlorogenic Acid	Caffeoyl-Tartaric Acid	Chlorogenic Acid	Cryptochlorogenic Acid	Caffeic Acid	3,4-di-O-Caffeoylquinic Acid	3,5-di-O-Caffeoylquinic Acid	Chicoric Acid	Total of Phenolic Acids
‘White Triumph’
WT1	ND	ND	1097.10 ± 1.41	48.71 ± 0.44	109.02 ± 0.66	201.97 ± 1.12	476.27 ± 1.56	25.67 ± 0.42	1958.74
WT2	ND	ND	1124.10 ± 1.53	49.71 ± 0.28	110.02 ± 1.06	206.79 ± 0.87	479.97 ± 1.23	24.63 ± 0.23	1995.22
WT3	ND	ND	1136.10 ± 0.82	53.04 ± 0.62	114.06 ± 0.96	210.79 ± 1.15	483.97 ± 1.87	26.23 ± 0.61	2024.19
WF1	ND	ND	1106.51 ± 3.49	51.01 ± 0.35	110.90 ± 0.40	204.89 ± 1.46	488.49 ± 2.43	26.91 ± 0.76	1988.71
WF2	ND	ND	1097.79 ± 4.74	49.42 ± 1.08	109.70 ± 1.33	209.44 ± 0.86	478.20 ± 2.55	25.50 ± 0.28	1970.05
WF3	ND	ND	1099.18 ± 5.19	54.04 ± 1.29	115.70 ± 0.67	212.44 ± 1.22	493.80 ± 2.33	28.90 ± 0.89	2004.06
WW1	ND	ND	1102.02 ± 3.47	51.21 ± 1.07	110.59 ± 0.38	203.56 ± 1.33	492.84 ± 4.33	28.61 ± 0.47	1988,83
WW2	ND	ND	1097.77 ± 4.72	49.90 ± 0.62	112.71 ± 0.67	201.15 ± 0.78	490.63 ± 4.42	27.83 ± 0.35	1979.99
WW3	ND	ND	1099.02 ± 2.53	50.68 ± 1.00	118.71 ± 1.43	208.15 ± 1.51	497.63 ± 2.38	29.83 ± 0.78	2004.02
‘Carmen Rubin’
CT1	ND	ND	3911.57 ± 4.53	115.67 ± 1.23	226.80 ± 1.30	70.29 ± 1.07	971.15 ± 2.26	39.48 ± 0.45	5334.96
CT2	ND	ND	3900.90 ± 4.71	117.60 ± 0.68	234.45 ± 0.70	73.23 ± 0.87	968.03 ± 2.65	37.83 ± 0.63	5332.04
CT3	ND	ND	3933.57 ± 3.47	118.83 ± 1.26	243.45 ± 0.92	78.54 ± 0.62	977.03 ± 2.04	40.83 ± 0.62	5392.25
CF1	ND	ND	3954.57 ± 4.11	115.82 ± 1.23	230.91 ± 0.83	72.12 ± 0.97	974.47 ± 1.41	39.51 ± 0.42	5387.40
CF2	ND	ND	3940.57 ± 4.47	116.60 ± 0.20	226.79 ± 1.53	71.45 ± 1.47	968.80 ± 3.28	38.80 ± 0.47	5363.01
CF3	ND	ND	3956.23 ± 5.47	119.00 ± 1.54	236.79 ± 0.75	75.44 ± 0.82	981.57 ± 9.43	40.43 ± 0.92	5409.46
CW1	ND	ND	3968.2 ± 5.47	120.10 ± 0.86	229.78 ± 1.29	75.07 ± 0.87	992.70 ± 2.71	42.43 ± 0.47	5428.31
CW2	ND	ND	3946.23 ± 3.89	118.93 ± 1.12	232.46 ± 0.89	73.18 ± 0.97	986.03 ± 1.71	40.43 ± 0.53	5397.26
CW3	ND	ND	3972.57 ± 3.47	119.93 ± 0.88	236.46 ± 1.46	77.18 ± 0.76	996.03 ± 2.41	45.43 ± 0.74	5447.60

Data represent mean values ± standard deviation (SD) from three independent replicates (n = 3); ND—Not Detected; WT1—traditional cultivation without over (TC) ‘White Triumph’ cultivar, 2021; WT2—traditional cultivation without over (TC) ‘White Triumph’ cultivar, 2022; WT3—traditional cultivation without over (TC) ‘White Triumph’ cultivar, 2023; WF1—cultivation under plastic mulch (FC) ‘White Triumph’ cultivar; 2021; WF2—cultivation under plastic mulch (FC) ‘White Triumph’ cultivar; 2022; WF3—cultivation under plastic mulch (FC) ‘White Triumph’ cultivar; 2023; WW1—cultivation under nonwoven fabric (WC) ‘White Triumph’ cultivar, 2021; WW2—cultivation under nonwoven fabric (WC) ‘White Triumph’ cultivar, 2022; WW3—cultivation under nonwoven fabric (WC) ‘White Triumph’ cultivar, 2023; CT1—traditional cultivation (TC) ‘Carmen Rubin’ cultivar, 2021; CT2—traditional cultivation (TC) ‘Carmen Rubin’ cultivar, 2022; CT3—traditional cultivation (TC) ‘Carmen Rubin’ cultivar, 2023; CF1—plastic mulch cultivation (FC) ‘Carmen Rubin’ cultivar 2021; CF2—plastic mulch cultivation (FC) ‘Carmen Rubin’ cultivar 2022; CF3—plastic mulch cultivation (FC) ‘Carmen Rubin’ cultivar 2023; CW1—cultivation under nonwoven fabric (WC) ‘Carmen Rubin’ cultivar, 2021; CW2—cultivation under nonwoven fabric (WC) ‘Carmen Rubin’ cultivar, 2022; CW3—cultivation under nonwoven fabric (WC) ‘Carmen Rubin’ cultivar, 2023.

).

For the ‘White Triumph’ cultivar, the chlorogenic acid content ranged from 1097.10 to 1136.10 mg 100 g⁻¹ dry weight, with the highest values recorded in the conventional cultivation in 2023 (WT3). A similar trend was observed for most of the other analysed phenolic compounds, such as cryptochlorogenic acid, caffeic acid, and 3,4-di-O-caffeoylquinic acid. The total phenolic acid content in this cultivar ranged from 1958.74 mg 100 g⁻¹ d.w. to 2024—19 mg 100 g⁻¹ d.w. The highest value was recorded in the traditional cultivation system in 2023 (WT3), while the lowest was observed in the same system in 2021 (WT1) (Table 7). The use of plastic mulch and nonwoven fabric cultivation resulted in slight fluctuations in the tested compound content, but the differences between the technologies were relatively small.

Significantly higher levels of all the phenolic acids analysed were found in the ‘Carmen Rubin’ cultivar. The chlorogenic acid content in this cultivar ranged from 3900.90 mg 100 g⁻¹ d.w. to 3972.57 mg 100 g⁻¹ d.w., with the highest values recorded in the nonwoven fabric-covered plot in 2023 (CW3). A similar trend was observed for caffeic acid, whose content increased in subsequent years of the study, reaching a peak of 243.45 mg 100 g⁻¹ d.w. in traditional cultivation in 2023 (CT3). High values were also observed for 3,5-di-O-caffeoylquinic acid, particularly in the nonwoven fabric cultivation system, where it reached 996.03 mg 100 g⁻¹ d.w. in 2023. The total phenolic acids in the ‘Carmen Rubin’ cultivar were more than twice as high as in the ‘White Triumph’ cultivar and ranged from 5332.04 mg 100 g⁻¹ d.w. to 5447.60 mg 100 g⁻¹ d.w. The highest value was recorded in the polypropylene-fabric-covered plot in 2023 (CW3), while the lowest was in the traditional plot without covers in 2022 (CT2) (Table 7).

The results indicate that the cultivar, cultivation technology, and conditions prevailing in each year of the study all influenced the phenolic acid content in sweet potato roots. Significantly higher levels of these compounds characterized the ‘Carmen Rubin’ cultivar compared to the ‘White Triumph’ cultivar. Furthermore, an upward trend in phenolic acid content was observed in 2023, particularly under polypropylene nonwoven fabric cover.

3.4. Principal Component Analysis (PCA) of Phenolic Compounds in the Roots of Five Sweet Potato Cultivars

The application of principal component analysis (PCA) enabled not only dimensionality reduction of the dataset, but primarily a comparative assessment of the effects of cultivation technology and growing season on phenolic acid profiles among sweet potato cultivars (Figure 4). The analysis revealed both shared structural features of phenolic profiles and clear cultivar-dependent differences, resulting from distinct metabolic strategies and variable responses to microclimate modification.

PCA explained a high proportion of the total variance in phenolic acid profiles, with the first two principal components (PC1 and PC2) jointly accounting for 75.71% to 96.14% of the variability, depending on the cultivar (Figure 4). This enabled a quantitative evaluation of the relative contribution of cultivation technology (PC1) and growing season (PC2) to phenolic profile differentiation.

3.4.1. Comparison of Cultivar Responses to Cultivation Technologies (PC1)

In all examined cultivars, the first principal component (PC1) was the dominant axis, explaining between 41.20% and 77.22% of the total variance. Such a broad range indicates substantial cultivar-specific differences in the strength of the cultivation system effect.

The highest PC1 contribution was observed in ‘Beauregard’ (77.22%), followed by ‘Carmen Rubin’ (66.59%), indicating that in these cultivars more than two-thirds of the total variability in phenolic profiles was directly associated with the cultivation system. In both cases, traditional cultivation (T) and cultivation under nonwoven fabric (W) occupied opposite positions along PC1, while polyethylene film (F) was located intermediately, indicating a gradual rather than abrupt response to microclimate modification.

In the case of ‘White Triumph’, PC1 also explained 66.59% of the variance, but sample distribution along this axis was more dispersed, particularly for the film-covered treatment, suggesting moderate stability of the phenolic profile combined with susceptibility to protective cultivation techniques.

Significantly lower PC1 contributions were recorded for ‘Satsumo Imo’ (47.20%) and ‘Purple’ (41.20%), indicating that less than half of the total variability in these profiles was related to cultivation technology. This pattern suggests greater internal metabolic variability and a relatively higher contribution of other factors, particularly seasonal effects.

3.4.2. Comparison of Growing Season Effects (PC2)

The second principal component (PC2) explained between 18.92% and 34.51% of the total variance and consistently reflected interannual variability across the study years (2021–2023), with clear quantitative differences among cultivars.

The highest PC2 contributions were observed in ‘Purple’ (34.51%) and ‘Satsumo Imo’ (31.84%), indicating that nearly one-third of the total variability in phenolic profiles in these cultivars was associated with seasonal conditions. In both cases, samples were ordered along the PC2 axis, indicating directional rather than random seasonal variability.

In ‘White Triumph’, PC2 explained 22.49% of the variance, suggesting a moderate but significant seasonal effect, particularly pronounced under nonwoven fabric cultivation.

The lowest PC2 contributions were observed in ‘Beauregard’ (18.92%) and similarly low in ‘Carmen Rubin’, indicating that seasonal differences accounted for less than one-fifth of the total variability and that phenolic profile structure remained relatively stable across years.

3.4.3. Quantitative Relationship Between PC1 and PC2

Each sample analyzed by PCA was evaluated along two principal directions, with PC1 reflecting cultivation-related variability and PC2 representing time-related variability (2021–2023). The PC1:PC2 ratio therefore served as a quantitative indicator of phenolic profile stability.

Comparison of PC1 and PC2 revealed clear cultivar-specific differences in the stability of phenolic acid profile structure, defined as the preservation of relative proportions among individual compounds in response to cultivation technology and seasonal variation. The highest structural stability was observed in ‘Beauregard’, where the PC1:PC2 ratio exceeded 4:1, indicating a strong dominance of cultivation technology effects and a limited seasonal contribution. A similarly high, though slightly lower, level of stability was observed in ‘Carmen Rubin’, where the PC1:PC2 ratio was approximately 3:1, confirming maintenance of an ordered profile structure with moderate seasonal modulation. A comparable ratio (~3:1) was also recorded for ‘White Triumph’, indicating moderately high structural stability of the phenolic acid profile, with a dominant but not exclusive influence of cultivation technology on relative compound proportions.

A markedly different variability pattern was observed in ‘Satsumo Imo’, for which the PC1:PC2 ratio decreased to approximately 1.5:1, indicating limited structural stability of the phenolic profile and a nearly equal contribution of cultivation technology and interannual variability. The most complex pattern was found in ‘Purple’, where PC1 and PC2 contributions were similar (41.20% vs. 34.51%), reflecting a multifactorial regulation of phenolic acid profiles without clear dominance of a single environmental factor.

3.4.4. Quantitative Structure of Phenolic Acid Correlations

Analysis of PCA correlation plots across all cultivars revealed a recurrent separation of phenolic acids into two opposing groups, characterized by long vectors and high absolute loadings along PC1:

Monoester and free derivatives of caffeic acid (chlorogenic acid and caffeic acid), Di-esterified CQA forms and chicoric acid, often including cryptochlorogenic acid.

In ‘Beauregard’, ‘White Triumph’, and ‘Carmen Rubin’, strong positive correlations were observed between chlorogenic and caffeic acids, accompanied by clear negative correlations with di-CQAs and chicoric acid, indicating a highly ordered phenolic profile structure. In ‘Satsumo Imo’, these relationships were quantitatively weaker, confirming greater metabolic variability in this cultivar.

3.5. Cluster Analysis and Heat Map

The heat map shown in Figure 5 graphically illustrates the relationships between the average values of the studied variables over three years (1—ascorbic acid, 2—total polyphenols, 3—ABTS, 4—DPPH, 5—FRAP, 6—neochlorogenic acid, 7—caffeoyl-tartaric acid, 8—chlorogenic acid, 9—cryptochlorogenic acid, 10—caffeic acid, 11—3,4-di-O-caffeoylquinic acid, 12—3,5-di-O-caffeoylquinic acid, 13—chicoric acid) and five sweet potato cultivars. The colour scale in the visualization illustrates the distribution of scaled values, enabling the assessment of similarities and differences between samples and variables.

The dendrogram above the heat map shows a clear division of the samples into five clusters, each corresponding to one of the tested sweet potato cultivars across three cultivation variants (T, F, W). This indicates the diversity of metabolic profiles among the individual cultivars. Samples of the P (‘Purple’) and C (‘Carmen Rubin’) cultivars exhibit an above-average analytical profile. In contrast, samples of the B (‘Beauregard’), W (‘White Triumph’), and S (‘Satsumo Imo’) cultivars are characterized by a below-average profile within the entire tested set. When analyzing the heat map of the interrelationships between the results of individual parameters (side dendrogram) and their clustering, it is observed that the richest phenolic acid profile is found in the P and C cultivars. The dendrogram also indicates relationships between variables, e.g., total polyphenols and FRAP (variables 2 and 5), and ascorbic acid and cryptochlorogenic acid (variables 1 and 9). Most phenolic acids formed a separate cluster, showing mutual correlations.

The dendrogram above the heat map shows the hierarchical clustering of all cultivation variants of the five sweet potato cultivars. It reveals a clear division of the samples into five main clusters, each corresponding to a single cultivar across three cultivation systems (T, F, W). This indicates that, in the analysed dataset, genotype is the dominant differentiating factor, and the three-year average values of the examined parameters allow for unambiguous grouping of the cultivar variants. Samples of the ‘Purple’ (P) and ‘Carmen Rubin’ (C) cultivars form clusters located in zones corresponding to variable values above the average for the entire dataset, reflecting the presence of more intense antioxidant and phenolic signals in these cultivars. In contrast, samples of the ‘Beauregard’ (B), ‘White Triumph’ (W), and ‘Satsumo Imo’ (S) cultivars cluster in areas with values lower than the average level of the analysed variables.

The side dendrogram (variables) shows clusters of traits with similar value patterns. Variables 2 (total polyphenols) and 5 (FRAP) form a common cluster, reflecting the similar distributions of their signal intensities in the profile of the analysed variants. A similar relationship is observed between variables 1 (ascorbic acid) and 9 (cryptochlorogenic acid). Most phenolic acids (variables 6–13) form a compact, distinct cluster, indicating a similar nature of their variability across the entire set of cultivars and cultivation technologies.

The heat map enables direct comparison of signal intensities for specific parameters across cultivars and cultivation systems. The highest values of many compounds are observed in the ‘Purple’ (PF, PW, PT) and ‘Carmen Rubin’ (CF, CW, CT) cultivars. In contrast, the S, B, and W cultivars exhibit lower intensities in most of the analysed variables. The color scheme confirms the distinctiveness of the metabolic profiles of cultivars with high and low phenol and antioxidant concentrations. In contrast, slight differences between cultivation systems within individual cultivars are mainly visible as color gradations within a single cluster.

4. Discussion

4.1. The Effect of Cultivation Technology on the Antioxidant Properties and Phenolic Acid Content in the Roots of Five Sweet Potato Cultivars

Our own research has demonstrated that the cultivation technology used affects the regulation of antioxidant metabolism. The highest levels of ascorbic acid were observed in the traditional, uncovered (TC) treatment, which may be related to greater plant exposure to abiotic stress, leading to increased synthesis of antioxidant compounds. The relationship between the intensity of environmental stress and levels of phenolic compounds and antioxidant activity in sweet potato leaves was demonstrated by Shi et al. [29], who reported dynamic changes in polyphenol accumulation during plant growth. Similar conclusions regarding the variability in phenolic composition under different environmental conditions were reported by Sun et al. [30], who demonstrated significant differences in antioxidant potential among cultivars. The reduction in stress factors in protected-culture technologies (polyethylene (PE) film cover—FC, polypropylene (PP) nonwoven fabric cover—WC) may have resulted in lower activation of defense mechanisms and reduced biosynthesis of ascorbic acid. In the study by Laveriano-Santos et al. [31], it was emphasized that genotype, environmental conditions, and agrotechnical practices strongly modulate the levels of bioactive compounds in sweet potatoes. The higher polyphenol content in the FC technology may be associated with the altered microclimate under cover, which favors the activation of secondary metabolite biosynthesis pathways. The increase in phenol levels under environmental stress conditions and their close relationship with antioxidant activity were confirmed by Shi et al. [29], indicating that environmental changes significantly modulate the antioxidant potential of plants. The downward trend in polyphenol content over subsequent years of the study may indicate reduced stress pressure in later growing seasons, consistent with the observations of Sun et al. [30]. The observed cultivar × technology × year interaction confirms the complex nature of secondary metabolism regulation in Ipomoea batatas L., in which genetic factors interact with agrotechnical and environmental conditions [31,32]. In our experiment, covers (especially plastic film) most often increased phenolic content relative to conventional cultivation, although the effect’s strength depended on the growing year (strongest in the warmer 2021) and on the cultivar. This is consistent with a vast body of scientific literature showing that covering root crops with plastic film, especially during periods of lower temperatures, increases the concentration of secondary metabolites; in particular, the black color of the film influences the formation of temperature, humidity, and radiation balance in the root zone and between rows, which statistically significantly increases yield and modifies crop quality in numerous vegetable species, including root vegetables [33,34]. The relationship regarding the effect of cover application on yield and root quality of sweet potato cultivars grown under Polish agro-climatic conditions has been presented in previous publications by Krochmal-Marczak et al. [2,6] and is cited here to support the interpretation of the relationship between yield and root quality traits. Regarding sweet potatoes, field trials in China and the U.S. indicate that mulching with multicolored materials (including white, black, and composite) improves emergence, growth dynamics, root size distribution, and yield. In the case of purple cultivars, a parallel increase in anthocyanin content was observed (which is consistent with our results for the ‘Purple’ cultivar and—to a lesser extent—‘Carmen Rubin’) [35,36]. At the same time, the characteristics of the cover matter: white or composite films create a different radiation regime than black ones, and color effects also influence soil temperature, weed density, and water use efficiency. The results of these studies were described in detail in a meta-analysis encompassing 97 studies and 789 observations across 25 plant species, which explains the varied responses in phenolic content to cultivation techniques using plastic film and nonwoven fabric observed in our results [33,34,35]. Plastic mulch increases temperatures and reduces evaporation, leading to earlier vegetation onset, faster growth, and potentially greater synthesis of secondary metabolites. Its effects are generally more pronounced than those of nonwoven fabric [33,34,35,37]. The use of nonwoven fabric affects microclimatic conditions in the epipedal zone by reducing wind impact, altering radiation flux, and providing protection against low temperatures. However, its effect on phenolic compound content can vary and depends on diurnal temperature patterns, sunlight exposure, and humidity. Additionally, recent studies indicate that mulch modifies the soil microbiome (carbon activity, functional diversity), which may indirectly regulate nutrient availability and stress signaling, and consequently shape the phenolic profile [35,38,39,40,41].

The highest phenol levels in our studies were recorded in 2021 (the warmest year), consistent with the phenylpropanoid pathway. Scientific reviews and experimental studies indicate that moderately elevated temperatures (provided water is available) activate PAL (Phenylalanine Ammonia-Lyase) and subsequent steps in the pathway, intensifying CQA/diCQA biosynthesis as part of a response to environmental stimuli and in a protective-antioxidant function [42,43]. At the same time, water deficit may reverse this trend—in field studies of sweet potato genotypes grown in drier regions, decreases in CQA/anthocyanins were observed under severe water stress, which was interpreted as a shift in metabolic priorities (turgor maintenance, changes in allocation patterns) [44]. The results of our own research are consistent with more recent studies on phenylpropanoids in stress tolerance, which emphasize the flexibility of regulation (including the involvement of transcriptional regulators and links to stress signaling) and the nonlinear nature of phenolic responses to thermal and light stimuli (the balance between “stimulation” and “overload” of the system) [42,43]. During warm but not extremely dry seasons, an increase in phenolic compounds is expected. In seasons with water deficits, the shielding effect may mitigate declines by improving the soil’s hydrothermal balance. However, the direction of change in phenolic compounds will remain genotype- and season-dependent [36,44]. The scientific literature has documented that elevated temperatures (both during cultivation—microclimate—and during processing) can lead to the isomerization of 5-CQA to 3- and 4-CQA and of 3,5-diCQA to 3,4- and 4,5-diCQA, as well as to partial losses through oxidation (limited by the presence of reduced compounds, e.g., ascorbic acid) [45]. More recent scientific studies also indicate that evaporation, roasting, and some laboratory procedures may increase the detectable levels of CQA/neoCQA and antioxidant activity (release from the matrix and concentration effects). However, the specific effect depends on the cultivar [46,47,48].

In light of our own results, the relationships outlined on the PCA biplot may have two implications: 1. Changes in the microclimate under the covers may have modulated the proportions of isomers as early as the field stage; 2. possible differences in the parameters of sample preparation (time, temperature, antioxidant protection) may have influenced the distribution of individual isomers in the PCA space (mono- vs. diester forms). Both mechanisms are consistent with classical observations of CQA/diCQA isomerization and shifts in factor systems [45,46]. The PCA biplots in our study consistently separated the monoester forms of CQA (3-, 4-, 5-CQA) from diCQA and chicoric acid. In contrast, free caffeic acid (CA) positioned itself in opposition to most esters, forming a bimodal pattern well-known from chemometric analyses of phenol-rich plants [49]. Mechanistically, this corresponds to the separation of esterification branches in the phenylpropanoid pathway, in which HQT (hydroxycinnamoyl-CoA: quinic acid hydroxycinnamoyltransferase) and HCT play key roles. Changes in their activity and/or expression (as well as transcriptional regulation, including by MYB family transcription factors) direct the flow of metabolites toward mono- or di-esterified forms of CQA [50,51,52,53]. In light of molecular findings from model and medicinal plants (including Lonicera spp.), which have been functionally validated (up-regulation/silencing of HQT/HCT, expression and localization analyses), such a “chemo-metric signature” is expected and further explains the strong varietal variation in the response of phenolic acids to environmental factors [50,53].

4.2. The Effect of Genetic Characteristics of Sweet Potato Cultivars on Antioxidant Properties and Phenolic Acid Content in Sweet Potato Roots

The results confirm a significant genetic influence on ascorbic acid accumulation in sweet potato roots (Ipomoea batatas L.). The highest values of this trait in the ‘Beauregard’ and ‘Carmen Rubin’ cultivars, across all cultivation technologies and years of the study, indicate strong genotypic control of ascorbic acid biosynthesis. Varietal variation in the content of bioactive compounds, including antioxidants, in sweet potatoes was confirmed by García-Martínez et al. [54], who demonstrated significant differences in the phenolic profile and antioxidant activity among genotypes. Wan et al. [32] also reported distinct metabolomic differences between cultivars with varying flesh colors, underscoring the importance of the genetic factor in regulating secondary metabolism. In our own studies, the highest level of phenolic acids was found in the purple-fleshed cultivar ‘Purple’. In contrast, in the cultivars ‘Beauregard’ (orange-fleshed), ‘White Triumph’ (white), and ‘Satsumo Imo’ (light-colored), the concentration was lower. These observations are consistent with the results of metabolomic studies and inter-varietal comparisons: purple sweet potatoes typically accumulate the highest levels of CQA mono- and di-esters and anthocyanins, which translates into higher antioxidant activity and a distinct chemometric response (PCA) [55,56]. The ‘Beauregard’ cultivar is often described as having moderate but stable levels of phenolics in the roots—a finding confirmed by American and European studies [57,58]. Under Central European conditions (temperate climate), a strong genetic component is also evident in the assimilation apparatus—an analysis of leaves from 9 cultivars revealed significant differences in the levels of 3-CQA, 4-CQA, 5-CQA, and diCQA between genotypes and developmental stages [14]. In practical applications, if the goal is a raw material with a high CQA/diCQA content (e.g., for functional foods), selecting a purple cultivar, such as ‘Purple’, is more justified, especially when the microclimate is “enhanced” by covers [55,59].

4.3. The Effect of Growing Years on the Antioxidant Properties and Phenolic Acid Content in the Roots of Five Sweet Potato Cultivars

Seasonal variations in climatic conditions significantly influenced the accumulation of secondary metabolites in the studied sweet potato cultivars, including phenolic content and antioxidant activity. Our results showed the highest phenolic levels in 2021, which correlated with higher temperatures that season and a favorable microclimate, consistent with observations indicating that moderately elevated temperatures activate the phenylpropanoid pathway and CQA/diCQA biosynthesis [42,43]. In subsequent years, under lower stress, a downward trend in polyphenol concentrations was observed, suggesting reduced stimulation of plant defense mechanisms and decreased synthesis of secondary metabolites [30]. Annual phenolic variability was also modulated by water conditions—in water-deficient seasons, decreases in CQA and anthocyanins were observed, interpreted as an adaptive shift in metabolic priorities (turgor maintenance, resource allocation). In contrast, in warmer and not extremely dry years, an increase in phenolics was expected [36,44]. The covers may have partially mitigated the negative effects of water stress by improving the soil’s hydrothermal balance; however, the direction of these changes depended on genotype and the specific seasonal conditions [36,44]. PCA biplot analysis revealed seasonal shifts in the distribution of CQA mono- and di-esters and chicoric acid, indicating that interannual environmental variability affected both the proportions of phenolic acid isomers and the total antioxidant potential of the samples. The observed annual differences confirm the sensitivity of sweet potato’s phenolic profile to climatic factors and highlight the importance of the year × cultivar × cultivation technology interaction in shaping bioactive compound content [30,54].

5. Conclusions

The study confirmed that cultivation technologies, cultivar, and meteorological conditions significantly influenced the contents of ascorbic acid, total polyphenols, and phenolic acids in sweet potato roots. Ascorbic acid content ranged from 27.22 to 111.9 mg·100 g⁻¹ DW, with the highest values recorded under the traditional cultivation system (TC) in ‘Carmen Rubin’ (111.9 mg·100 g⁻¹ DW) and ‘Beauregard’ (111.4 mg·100 g⁻¹ DW). In contrast, in ‘Satsumo Imo’ grown under nonwoven fabric (FW), ascorbic acid decreased to 49–58% of TC values. Genotypic effects strongly differentiated bioactive compound accumulation. ‘Purple’ exhibited the highest contents of total polyphenols (up to 963.5 mg·100 g⁻¹ DW) and phenolic acids (17,067.42 mg·100 g⁻¹ DW), whereas the lowest values were recorded in ‘Satsumo Imo’ (858.82–1225.89 mg·100 g⁻¹ DW). Cultivation under polyethylene film (FC) increased and stabilized phenolic compound levels compared with TC and FW systems. The highest phenolic responses to FC were observed in ‘Purple’ and ‘Carmen Rubin’, while ‘Beauregard’ showed high stability across all cultivation systems. In contrast, ‘Satsumo Imo’ exhibited strong sensitivity to environmental variation. Additionally, ‘White Triumph’ achieved the highest phenolic compound levels under FC, whereas FW increased interannual variability of secondary metabolites. Overall, the results highlight that appropriate cultivar selection combined with FC cultivation is an effective strategy for enhancing the functional quality of sweet potato roots under temperate climate conditions. These findings may serve as a basis for developing agrotechnical recommendations for producing sweet potatoes with improved nutritional and health-promoting value in Poland.