*Article* **Relationships Linking the Colour and Elemental Concentrations of Blossom Honeys with Their Antioxidant Activity: A Chemometric Approach**

**Monika K ˛edzierska-Matysek 1, Anna Teter 1, Małgorzata Stryjecka 2, Piotr Skałecki 1, Piotr Domaradzki 1, Michał Ruda´s <sup>3</sup> and Mariusz Florek 1,\***


**Abstract:** The antioxidant activity of honey depends on the botanical origin, which also determines their physicochemical properties. In this study, a multivariate analysis was used to confirm potential relationships between the antioxidant properties and colour parameters, as well as the content of seven elements in five types of artisanal honey (rapeseed, buckwheat, linden, black locust, and multifloral). The type of honey was found to significantly influence most of its physicochemical properties, colour parameters, and the content of potassium, manganese and copper. Antioxidant parameters were shown to be significantly positively correlated with redness and concentrations of copper and manganese, but negatively correlated with the hue angle and lightness. The principal component analysis confirmed that the darkest buckwheat honey had the highest antioxidant activity in combination with its specific colour parameters and content of antioxidant minerals (manganese, copper and zinc). The level of these parameters can be potentially used for the identification of buckwheat honey.

**Keywords:** honey; physicochemical properties; colour; minerals; trace elements; ferric reducingantioxidant power assay; radical scavenging activity

#### **1. Introduction**

Bee products are valuable, natural foodstuffs with a wide range of beneficial properties for human health which are exploited in medicine [1]. Honey is the main product of extensive beekeeping in almost all countries worldwide. Owing to the biodiversity of plants and monocultures, multifloral and unifloral honeys are obtained [2,3].

The basis for the multifaceted use of honey in the human diet and therapy is its complex chemical composition, dominated by carbohydrates (70–80%). In the honeys, enzymes, amino acids, vitamins, carotenoids, organic acids, phenolic acids, polyphenols, and flavonoids are present as well [4]. Honey also contains minerals essential for the functioning of the human body, with the content in fresh honey varying depending on the type, geographic origin, and method of honey harvesting and storage [3,5–8]. Excessively long storage affects the composition of honey and alters the biological activity of its components [3,7]. It should be underlined that honey also demonstrates antioxidant [2,9–11], immunomodulatory, and anti-inflammatory properties [12]. In view of the fact that the ageing process and degenerative diseases have their basis in free radicals, one way to counteract these changes and protect against free-radical diseases is to supply the body with appropriate antioxidants, which reduce the number of superoxide radicals

**Citation:** K ˛edzierska-Matysek, M.; Teter, A.; Stryjecka, M.; Skałecki, P.; Domaradzki, P.; Ruda´s, M.; Florek, M. Relationships Linking the Colour and Elemental Concentrations of Blossom Honeys with Their Antioxidant Activity: A Chemometric Approach. *Agriculture* **2021**, *11*, 702. https:// doi.org/10.3390/agriculture11080702

Academic Editor: Alessandra Durazzo

Received: 26 June 2021 Accepted: 24 July 2021 Published: 26 July 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

in varying degrees. Substances with a beneficial effect on the human body include natural antioxidants counted among phenolic compounds [13].

Honey intended for human consumption must meet key criteria for content of fructose and glucose (sum of both), sucrose, moisture, water-insoluble content, electrical conductivity, free acid, diastase activity, and hydroxymethylfurfural [14]. One of the most important criteria is the level of 5-hydroxymethylfurfural (HMF ≤ 40 mg kg<sup>−</sup>1), due to the potential risk for bees and humans. Another parameter is the enzymatic activity of α-amylase (diastase activity ≥8.0 on the Schade scale) naturally occurring in honey. A high diastase number (DN) and low content of 5-HMF are considered a guarantee of high-quality honey. Negative changes in honey are caused by the effects of high temperature during decrystallization and long-term storage in combination with high temperature and exposure to light [15–17].

The botanical origin of honey determines its diversity in terms of physicochemical, organoleptic and biological properties [5–7]. The type of honey is distinguished by a wide range of colours, a characteristic flavour and aroma, chemical composition, form of crystallization, and specific preventive properties against individual disease conditions. Owing to these varied attributes, each consumer can choose honey according to individual needs and preferences. At the same time, due to the rich content of different sugars, honey can be a healthy substitute for white sugar [10].

Multivariate analysis (e.g., principal component analysis, PCA; hierarchical cluster analysis, HCA; linear discriminate analysis, LDA) were previously very often used to evaluate and/or classify honey in relation to its chemical composition, physicochemical or biological properties. Numerous papers have confirmed the suitability of this method for honey evaluation. [2,3,6–8,18].

The antioxidant activity of honey depends on the botanical origin, which also determines its physicochemical properties. This study had two main objectives: (1) to evaluate and compare the physicochemical properties and antioxidant activity of five Polish blossom and multifloral honeys; (2) to identify/investigate potential relationships between the antioxidant properties of the honeys and their colour parameters and content of macroand micro-elements using principal component analysis (PCA).

#### **2. Materials and Methods**

#### *2.1. Sampling*

The study was conducted on 63 honeys harvested in south-eastern Poland (Lublin region) in 2019. The percentage of the predominant pollen grains in the honey samples was determined according to the method recommended by Polish law concerning analytical methods used in the assessment of honey [19]. The following types of honey were distinguished: rapeseed, RS (*Brassica napus* L., *n* = 10), buckwheat, BW (*Fagopyrum esculentum* Moench, *n* = 8), linden, LI (*Tilia spp*. L., *n* = 13), black locust, AC (*Robinia pseudoacacia* L., *n* = 5), and multifloral, MF (no dominant pollen, *n* = 27). The honeys were purchased directly from beekeepers and stored in the dark at room temperature 20–25 ◦C.

#### *2.2. Analyses*

#### 2.2.1. Physicochemical Properties

Water content was determined with a refractometer (Abbe Carl Zeiss, Jena, Germany) based on the refractive index of the honey in its liquid state. Water percentage by weight (% m/m) was read from the table as corresponding to the refractive index [20]. The content of reducing sugars and sucrose was determined by the Lane-Eynon method, according to the Polish Committee for Standardization (PN-88/A-77626. Bee honey).

The electrical conductivity (mS cm<sup>−</sup>1) and pH of the honey were determined according to [20] using a pIONneer 65 Meter (Radiometer Analytical, Villeurbanne, CEDEX-France) with a 4-pole conductivity cell (CDC 30T) and a combined pH electrode (E16M340). The free acidity of the honey was measured by potentiometric titration using a 0.1 M NaOH

solution to obtain pH 8.30 and the result was expressed in milliequivalents per kilogram of honey (mval kg<sup>−</sup>1).

The water activity (aW) of fresh honey was performed using a Rotronic HygroLab C1 analyser (Bassersdorf, Switzerland) equipped with two HC2-AW measurement heads. Duplicate measurements were taken in the AWQ mode with stabilization set to 15 min after previously conditioning the honey samples at room temperature (20 ± 1 ◦C).

The concentration of 5-HMF (5-(hydroxymethyl-)furan-2-carbaldehyde) in mg kg−<sup>1</sup> was determined according to [21]. The absorbance of a clear solution of honey with water relative to a solution of honey with sodium bisulphate was measured at wavelengths 284 and 336 nm. The measurement was made with a Carry 300 Bio spectrophotometer (Varian Australia Pty, Ltd., Mulgrave, Australia).

Diastase activity (diastase number DN, in Schade units per gram of honey) was determined by photometry using Phadebas tablets (Honey Diastase Test, Magle AB, Lund, Sweden). They contained non-soluble starch conjugated with a blue pigment and hydrolysed by the amylase present in the sample. The resulting water-soluble fragments of the starch chain were dyed blue. The absorbance of the coloured solution was measured with a Varian Carry 300 Bio spectrophotometer (Varian Australia PTY, Ltd.) at 620 nm [20].

The honey's colour was measured according to the procedure of [15] with some modifications. Briefly, the colour of three aliquots of each honey sample (previously equilibrated to room temperature) was measured three times in a round optical glass cell CR-A504 (diameter 34 mm) using a portable CM-600d spectrophotometer (Konica Minolta Sensing, Inc., Osaka, Japan) equipped with cell holder CM-A515. The thickness of the honey layer was 20 mm. Samples of multifloral, rapeseed, buckwheat and linden honey were crystallized naturally (set honey), and the black locust samples were in liquid form (strained honey). The results of the measurements (illuminant D65, observer 10◦) were given in the CIE L\*a\*b\* colour space, including the following spectral values: L\* (lightness axis), a\* (red to green axis), b\* (yellow to blue axis), C\* (saturation) and h◦ (hue angle/tint).

For mineral analysis, samples were prepared for mineralization as follows: a 6 mL volume of 65% nitric acid (Suprapur grade; Merck, Germany) was poured over honey samples weighed out to within 0.0001 g and the certified reference material NCS ZC 73014 Tea (to verify the method) in vessels (PFA). All solutions together with a blank sample were mineralized in a MARSXpress 5 microwave digester (CEM Corporation, Matthews, NC, USA). The oven was programmed for mineralization of the samples as follows: power—1600 W/100% max power; temperature increment—20 min/200 ◦C; holding time—20 min. Then the mineralized samples were transferred to volumetric flasks using ultrapure water produced in an HLP 20UV demineralizer (HYDROLAB, Poland). Schinkel buffer (enth./cont. 10 g L−<sup>1</sup> CsCl + 100 g L−<sup>1</sup> La; Merck, Germany) was used to minimize interference during analysis (Mg, K and Na).

K, Na, Mg, Zn, Fe, Mn, and Cu were determined according to the procedure of [3] using a Varian AA240FS spectrometer (Fast Sequential Atomic Absorption Spectrometer, Varian Australia Pty Ltd., Mulgrave, Australia). The elements were atomized in the flame of a burner fed with a mixture of air (oxidizing gas, flow 13 L min−1) and acetylene (combustible gas, flow 2.0 L min−1). The following parameters were used: instrument mode—absorbance; measurement mode—integration; calibration mode—concentration; calibration algorithm—New Rational. Analytical wavelengths (nm): Mg 285.2, Zn 213.9, Fe 248.3, Mn 279.5, Cu 324.7, Na 589.0, and K 766.5. Background correction was used in the determination of Mg, Zn, Fe, Mn and Cu. To plot a standard curve, single-element standard solutions (Merck, Germany) were used for each element (K, Na, Mg, Zn, Cu, Fe and Mn) with a mass concentration of 1000 mg L−1. The following limits of detection (LOD) were used in the analysis: 0.01 mg kg−<sup>1</sup> for Na, Zn, Mn and Cu; 0.04 mg kg−<sup>1</sup> for K; 0.09 mg kg−<sup>1</sup> for Fe; and 0.47 mg kg−<sup>1</sup> for Mg.

#### 2.2.2. Antioxidant Activity

The capacity of the honeys to scavenge the stable free radical 2,2-diphenyl-1 picrylhydrazyl (DPPH, Sigma Aldrich Co., St. Louis, MO, USA) was tested according to the method of [22]. Samples of the honeys (2 g) were dissolved in 10 mL of distilled water (HLP 20UV, HYDROLAB, Straszyn, Poland), then an aliquot (0.2 mL) of each dilution was mixed with a 1.8 mL solution of 0.1 mM DPPH in methanol (Sigma Aldrich Co., St. Louis, MO, USA). The reaction mixture was left in the dark at room temperature for 60 min. Next, the absorbance of the mixture was measured spectrophotometrically (UV-2600i spectrophotometer, Shimadzu, Japan) at 517 nm against methanol as a blank. All the determinations were performed in triplicates. The calibration curve was plotted in a range from 0.1 to 100 μg mL−<sup>1</sup> of Trolox (Sigma-Aldrich, Co., St. Louis, MO, USA) solution in ethanol. The results were expressed as mM of Trolox equivalent (TE) per 1 kg of honey (mM TE kg−<sup>1</sup> honey).

The total ferric reducing antioxidant power assay (FRAP assay) was performed according to [23]. FRAP reagent was prepared by mixing 25 mL of 0.3 M acetate buffer (pH 3.6) with a 2.5 mL solution of 10 mM TPTZ (Sigma Aldrich Co, St. Louis, MO, USA) in 40 mM HCl, and 2.5 mL of 20 mM ferric chloride (Sigma Aldrich Co, USA). An aliquot (0.2 mL) of each honey dilution (1 g in 10 mL distilled water) was mixed with 1.8 mL of FRAP reagent. The resulting mixture was then pre-warmed at 37 ◦C for 10 min. The absorbance was measured spectrophotometrically (UV-2600i spectrophotometer, Shimadzu, Japan) at 593 nm against a blank that was prepared with distilled water. All the determinations were performed in triplicates. A calibration curve was prepared using the ethanol solution of Trolox (Sigma Aldrich Co., St. Louis, MO, USA) in a range from 25 to 300 nmol mL−1. FRAP values were expressed as mM of Trolox equivalent per kg of honey (mM TE kg<sup>−</sup>1).

#### *2.3. Statistical Analysis*

Statistical analysis of the results was performed in Statistica ver. 13 (TIBCO Software Inc., Palo Alto, CA, USA). One-way analysis of variance (ANOVA) followed by Tukey's (HSD) test was used to compare means of physicochemical traits and colour parameters between honey types (multifloral, rapeseed, buckwheat, linden and black locust). The normality and homogeneity of the variance of minerals were verified by the Kolmogorov– Smirnov test and Levene's F-test, respectively. The influence of the honey type on the elemental concentrations was verified by the Kruskal–Wallis test (comparison of multiple independent groups). Differences between means at confidence levels of 95% and 99% (*p* < 0.05 and *p* < 0.01, respectively) were considered statistically significant. The mean and standard deviation are presented in the tables. The relationship between parameters of antioxidant activity (FRAP and DPPH) and physicochemical traits and mineral contents in the honeys was determined by calculating Pearson's correlation coefficients (r) and Spearman's rank correlation coefficients (rS), respectively. The correlations were further verified by principal component analysis (PCA), separately for two data sets (for antioxidant activity and colour and for antioxidant activity and minerals) to demonstrate the diversity among honey types.

#### **3. Results and Discussion**

#### *3.1. Physicochemical Properties*

The honey type significantly influenced most of its physicochemical parameters (except the content of water, saccharose and reducing sugars), all colour parameters, and the concentrations of K, Mn and Cu (Table 1).

Although the water content in the honeys did not differ significantly, the value of this parameter indicates the maturity of the honey (readiness for harvest). The mean water content was similar, ranging from 17.11% in the linden honey to 17.93% in the rapeseed honey, and thus did not exceed the maximum acceptable content of 20% [14]. Sugars make up the largest proportion of dry matter in honey, and their qualitative and quantitative composition is an important criterion in the quality assessment of honey. The

most important factors for determining the sugar composition of honey include the region of origin, climate conditions, and types of flowers used by the bees [24]. In the present study, the highest content of reducing sugars and the lowest content of saccharose was noted in the black locust honey (77.24% and 1.83%), while the reverse pattern was noted in the linden honey (73.76% and 2.14%). It should be stressed that the saccharose content in the honey did not exceed the acceptable limit of 5 g/100 g of product.

**Table 1.** Parameters of physicochemical traits and antioxidant activity of the honey types (mean values ± standard deviation).


aW, water activity; 5-HMF, 5-(hydroxymethyl-)furan-2-carbaldehyde; L\*, lightness; a\*, redness; b\*, yellowness; C\*, saturation; h◦, hue angle; K, potassium; Na, sodium; Mg, magnesium; Fe, iron; Zn, zinc; Mn, manganese; Cu, copper; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power. Means with different letters in rows differ significantly according to Tukey's test: a, b—*p* < 0.05; A, B—*p* < 0.01.

> All the honeys had a pH < 4. Although regulations do not specify the pH of honey, it is worth noting that honey pH between 3.2 and 4.5, together with titratable acidity, inhibits the growth of microbes [4]. The higher range of pH for the same honey types in this study (from various regions of Poland), i.e., from 4.07 (buckwheat) to 4.23 (linden) was reported earlier [6]. Lower pH than in the present study was reported for Indian blossom honey (3.5) [7], while higher pH (4.38) was found in Slovakian honey [25].

> The honey type significantly influenced its degree of acidity, which ranged from 21.9 mval kg−<sup>1</sup> (rapeseed) to 44.5 mval kg−<sup>1</sup> (buckwheat), without exceeding the limit in EU regulations [14], which is 50 mequivalents acid per kg. Acidity results mainly from the presence of organic acids, amino acids and phenolic acids in honey, as well as from processes taking place during its maturation [13]. Free acidity has been shown to remain practically constant in honey, but with an increase observed during storage for 20 months at room temperature [26] or frozen storage for 18 months [15].

> Specific conductivity is a parameter that can be used to determine the botanical origin of honey, i.e., to distinguish nectar honey (up to 0.8 mS cm−1) from honeydew honey (over 0.8 mS cm−1). This was also confirmed in the present study, as the specific conductivity of the nectar honeys varied significantly (*p* < 0.01) from 0.232 mS cm−<sup>1</sup> (rapeseed) to 0.564 mS cm−<sup>1</sup> (linden). The specific conductivity of Slovakian honey averaged

0.6515 mS cm<sup>−</sup>1, ranging from 0.1345 to 0.9912 mS cm−<sup>1</sup> [25]. Multifloral and acacia honeys from India exhibited lower conductivity (0.25–0.26 mS cm<sup>−</sup>1) [7].

The aW of honey is usually between 0.50 and 0.65, and in the literature, aW values above 0.60 are considered to represent a critical threshold for microbial stability [4] due to the activity of various species of bacteria and osmophilic yeasts resulting in fermentation [12]. In the present study, the honeys did not exceed the critical value for this parameter, but it varied significantly (*p* < 0.01) from 0.546 (linden honey) to 0.582 (rapeseed honey). These honey types also had the lowest (17.11%) and highest (17.93%) water content, which indicates a linear relationship between the two parameters, statistically confirmed in the present study (r = 0.616, *p* = 0.000). Nonetheless, due to the significant influence of temperature, honey type (flower or honeydew), harvesting year, geographical and botanical origin, a universal linear equation for water activity and moisture content could not be established [27]. The wider range of water activity in honeys (0.456 ≤ aW ≤ 0.659) was linked to the varied composition of sugars [25]. Water activity in honey from India ranged from 0.507 to 0.566 [7], and in flower honey from Turkey was between 0.51 and 0.69 [24]. Low water activity (aW) together with low pH, low protein content, and high osmotic pressure has an inhibitory effect on the development of bacteria [13].

An important indicator of the quality and health safety of honey is the content of 5-hydroxymethylfurfural (5-HMF). The values for this parameter in the present study were low, well under the limit of 40 mg kg−<sup>1</sup> [14]. Significantly (*p* < 0.01) the highest content of 5-HMF was noted in the buckwheat honey (14.51 mg kg<sup>−</sup>1); it was more than four times as high as in the linden (3.49 mg kg−1) and rapeseed (3.67 mg kg−1) honeys (*p* < 0.01). The 5-HMF content between 0 and 4.12 mg kg−<sup>1</sup> was reported for Turkish flower honey [24], which was considered fresh honey. Higher 5-HMF content was found in Slovakian honeys 25.76 mg kg−<sup>1</sup> [25], while the level in Indian honeys ranged from 5.49 mg kg−<sup>1</sup> in acacia honey to 22.64 mg kg−<sup>1</sup> in multifloral honey [7]. For Andalusian multifloral honey, the content of 5-HMF was found between 0.19 and 41.16 mg kg−<sup>1</sup> [28].

The diastase number (DN) indicates the amylolytic activity of honey. Alpha-amylase (diastase) is an enzyme that takes part in the hydrolytic degradation of complex sugars. Like 5-HMF, the diastatic activity of honey can be used as an indicator of adulteration, ageing, overheating (increased temperature), and the degree of preservation [16]. All honey types tested in the present study had a diastase number >8, i.e., above the recommended minimum [14]. DN values obtained for Polish regional honeys [29] confirmed the low enzymatic activity of rapeseed (15.32 DN) and higher activity in multifloral (22.15 DN) and linden (31.99 DN) honey. In turn, the diastase number of polyfloral honeys from Andalusia varied widely from 6.05 to 40.89 [28].

The honey type significantly (*p* < 0.01) influenced all parameters in the instrumental assessment of colour (Table 1). The highest lightness value was noted for the rapeseed honey (L\* = 49.47), followed by the multifloral honey (L\* = 44.12), while the darkest was black locust honey (L\* = 31.55) and buckwheat honey (L\* = 30.84). Buckwheat honey also had the highest value for the colour red (a\* = 3.22) and the lowest hue angle (h◦ = 62.70). The hue angle in the other honey types ranged from h◦ = 81.97 (multifloral) to h◦ = 85.94 (rapeseed). Hue angle is defined as starting at the +a\* axis and is expressed in degrees: 0◦ is red (+a\*), 90◦ is yellow (+b\*), 180◦ is green (−a\*), and 270◦ is blue (−b\*). Values between 0◦ and 90◦ are a mixture of red and yellow, resulting in an orange colour.

The amount of red was similar for the black locust, linden and rapeseed honeys (0.61 ≤ a\* ≤ 0.90), in contrast to the multifloral honey (a\* = 2.36) and the aforementioned buckwheat honey (a\* = 3.22). In the case of the colour yellow and saturation, the varieties can be divided into two groups with similar values for these parameters, i.e., black locust, buckwheat and linden (5.09 ≤ b\* ≤ 8.74 and 5.14 ≤ C\* ≤ 8.86) vs. rapeseed and multifloral (13.29 ≤ b\* ≤ 16.05 and 13.08 ≤ C\* ≤ 16.25).

A wider range of values for colour components for Polish honey was reported earlier [6], respectively: 26 ≤ L\* ≤ 51; −3.41 ≤ a\* ≤ 7.9; and 5.8 ≤ b\* ≤ 23.7. The differences may have been due to differences in the preparation of samples, which were heated

and homogenized prior to analysis. Nectar contains natural plant pigments such as carotenoids, anthocyanins, flavonoids, and chlorophyll, which determine the colour of the honey through various amounts of colours, including yellow, red, brown and green. The colour of the product is also influenced by honey colloids, polyphenols (e.g., tannins), and melanoidins. Phenolic compounds function not only as pigments but also as antioxidants, insecticides and fungicides [6]. The colour of honey is also largely determined by its degree of crystallization and the conditions in which physicochemical changes take place during storage.

In the present study, the dark buckwheat honey (L\* = 30.84) had a high free acid value (44.5 mval kg−1), while the light rapeseed honey (L\* = 49.47) had significantly (*p* < 0.01) the lowest acidity (21.9 mval kg−1). Dark honeys have been shown to have much higher acidity than light ones [9]. Kaczmarek et al. [6] also reported higher levels of free acids in buckwheat (34.25 meq kg−1), multifloral (34.04 meq kg−1) and linden (31.09 meq kg−1) honey than in acacia (12.8 meq kg<sup>−</sup>1) and rapeseed (10.5 meq kg−1) honey.

In the present study, the highest content of elements was generally found in the buckwheat honey and the lowest in the black locust and rapeseed honey (Table 1). The type significantly influenced the content of Mn and Cu (*p* < 0.01) and K (*p* < 0.05). The highest content of potassium was noted in the linden honey (1258.3 mg kg−1) and the lowest in the rapeseed honey (700.9 mg kg−1). The potassium content in the honey varieties was similar to that obtained in honey from Poland (892.4 mg kg−1) [3] and Malaysia (904.9 mg kg<sup>−</sup>1) [30], but lower than in Hungarian honey (397.88 mg kg−1) [31].

The buckwheat honey had significantly the highest content of Mn and Cu (5.58 and 0.95 mg kg−1). The black locust honey had the lowest level of manganese (0.72 mg kg−1), and the black locust and rapeseed honeys had the lowest content of copper (0.47–0.48 mg kg−1). Wieczorek et al. [32] reported lower values for K (233–782 mg kg−1), Mg (11.6–24 mg kg<sup>−</sup>1), Mn (0.37–1.25 mg kg−1), and Cu (0.04–0.06 mg kg−1) in multifloral, linden and black locust honeys, but higher values for Zn (1.65–6.20 mg kg−1) and Fe (1.9–4.0 mg kg−1) compared to the results of our study, which in turn were in agreement with those obtained by other authors [33] for varietal honeys from Podkarpacie in Poland. They noted the highest content of Zn, Mn and Cu in buckwheat honey, in comparison with linden, rapeseed and multifloral honeys. Our previous research [3] also indicated a higher concentration of these elements in buckwheat honey. For this reason, Deng et al. [34] suggest that the levels of Mn, Zn and Cu in buckwheat honey can potentially be used to distinguish this variety of honey. Many authors also stressed that dark honeys have higher mineral content than light ones [23,30], as well as a stronger flavour [34] and higher content of phenolic compounds, which influence antioxidant activity [7].

#### *3.2. Antioxidant Activity*

The buckwheat honey had the highest content of elements considered to be antioxidants (Zn, Mn and Cu). This is also indicated by the results for antioxidant activity measured in the reaction with DPPH and by the FRAP value (Table 1). Significantly (*p* < 0.01) the highest antioxidant activity was noted in the buckwheat honey (DPPH 2.33 mM TE kg−<sup>1</sup> and FRAP 2.14 mM TE kg−1), and the lowest activity in the black locust (DPPH 0.63 mM TE kg−<sup>1</sup> and FRAP 0.29 mM TE kg−1), rapeseed (DPPH 0.83 mM TE kg−<sup>1</sup> and FRAP 0.47 mM TE kg−1) and linden (DPPH 0.90 mM TE kg−<sup>1</sup> and FRAP 0.53 mM TE kg<sup>−</sup>1) honeys.

The highest antioxidant activity in buckwheat honey from Poland measured in reactions with DPPH and ABTS and the lowest in rapeseed and acacia honeys were reported previously [11]. In the present study, the mean DPPH values in mM TE kg−<sup>1</sup> in the rapeseed, buckwheat, linden and black locust honeys were about twice as high as those reported earlier [2]. Škrovánková et al. [35] analysed total antioxidant capacity (TAC) using the DPPH reagent and found that it was highest in honeydew honey, followed by multifloral, forest, and floral honeys, with the lowest values noted in rape and acacia honeys. The DPPH activity in buckwheat honey from China was 0.304 mg Trolox/g, and the FRAP

value was 0.355 mg Trolox/g [36]. However, it may be difficult to compare our results for antioxidant activity with values reported by other authors due to the differences in their analysis or presentation. Nevertheless, it should be emphasized that many studies indicate that dark honeys show higher activity than light honeys. Piszcz and Głód [37], based on the assessment of total antioxidant potential (TAP), reported the following order for varietal honeys: buckwheat > honeydew > linden > multifloral > acacia. Dzugan et al. [ ˙ 38] found the highest antioxidant activity (DPPH) in buckwheat honey (82.41%) and the lowest in rapeseed honey (21.81%). Other authors [10] also confirmed high antioxidant activity in buckwheat honey (17.0 mmol Trolox/g) compared to soybean, sweet clover, fireweed, and acacia honeys (8.3, 6.1, 3.1 and 3.0 mmol Trolox/g).

#### *3.3. Correlations*

To test the relationships between antioxidant capacity expressed as DPPH and FRAP and physicochemical properties, colour parameters, and concentrations of selected elements, Pearson (r) or Spearman (rS) correlations were calculated. In the case of the first group of properties, DPPH and FRAP were shown to be significantly (*p* < 0.001) and positively correlated with 5-HMF (r = 0.643 and r = 0.676), diastase number (r = 0.612 and r = 0.706), and free acids (r = 0.544 and r = 0.560). The only significant negative correlation was between DPPH and pH (r = −0.320, *p* < 0.05).

Antioxidant activity (DPPH and FRAP) was positively correlated with the colour red (r = 0.452 and r = 0.549, *p* < 0.001) and negatively with lightness (r = −0.309 and r = −0.259, *p* < 0.05) and hue (r = −0.781 and r = −0.706, *p* < 0.001) (Table 2).


**Table 2.** Correlations between antioxidant activity and colour parameters and minerals.

\* *p* < 0.05; \*\* *p* < 0.01; \*\*\* *p* < 0.001; L\*, lightness; a\*, redness; b\*, yellowness; C\*, saturation; h◦, hue angle; K, potassium; Na, sodium; Mg, magnesium; Fe, iron; Zn, zinc; Mn, manganese; Cu, copper; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power.

Ku´s et al. [2], for six Polish single-variety honeys, reported higher correlation coefficients for DPPH and FRAP with colour parameters: for L\* r = −0.955 and −0.961, for a\* r = 0.943 and 0.964, and for b\* r = 0.814 and 0.786. Lower correlation coefficients for these parameters were obtained for honey from Slovenia [23]. The intensity of honey colour may be associated with its antioxidant capacity, as the content of phenols, flavonoids and carotenoids is greater in darker honeys than in lighter ones [5]. Moreover, the acceleration of the Maillard reaction or fructose caramelization can contribute to a darker colour of honey through the production of brown pigments, concomitantly with the formation of HMF as an intermediate product. Similar changes in rape honey, consisting in a reduction in lightness (L\*) but an increase in redness (a\*) and colour intensity (ABS450, mAU) were observed in our previous study [16], which can be directly linked to the presence of pigments such as terpenes, carotenoids, and some flavonoids [7].

High, positive correlation coefficients between colour evaluation (ΔA) and antioxidant capacity were previously reported for ABTS r = 0.8836 and for DPPH r = 0.8937 [35]. Many authors confirm a strongly positive and significant (*p* < 0.01) relationship between colour intensity, expressed as ABS450, and DPPH and FRAP. For instance, Moniruzzaman et al. [39] reported coefficients of r = 0.938 and r = 0.873, and Beretta et al. [40], reported r = 0.889 and r = 0.933. A lower correlation coefficient (r = 0.68) between ABS450 and DPPH was obtained by Kaczmarek et al. [6].

The DPPH and FRAP parameters characterizing antioxidant activity were most strongly and positively correlated with antioxidant minerals: Cu (rS = 0.522, *p* < 0.001 and rS = 0.386, *p* < 0.01) and Mn (rS = 0.457, *p* < 0.001 and rS = 0.370, *p* < 0.01) (Table 2).

To our knowledge, there are few reports on the correlation between the minerals content and antioxidant activity of honeys. In the present study, low and non-significant (*p* > 0.05) correlation coefficients were obtained for parameters of antioxidant activity and elements Na, Fe and Zn. Perna et al. [41] report significant (0.01 < *p* < 0.001) correlation coefficients for DPPH and FRAP with Fe (r = 0.67 and r = 0.73) and Zn (r = 0.32 and r = 0.48) in honey from Italy.

#### *3.4. Principal Component Analysis*

#### 3.4.1. Antioxidant Activity and Colour

For a more in-depth analysis of the results obtained for the antioxidant activity and colour of the honey types, a principal component analysis (PCA) was performed, with 7 variables and 64 cases. Two principal components with eigenvalues exceeding 1 (Kaiser criterion) explained 87.12% of the total variance, with PC 1 accounting for 46.58% and PC 2 for 40.53% (Table S1).

Figure 1a visualizes the projection of variables as a two-factor plane (PC1 × PC2). The first component (PC1) has a positive correlation with L\* (0.828) and h◦ (0.846), but a negative correlation with DPPH (−0.723) and a moderate negative correlation with FRAP (−0628). The second component (PC2) has a negative correlation with most variables, including a\* (−0.897), C\* (−0.740), b\* (−0.708), and FRAP (−0.654) (Table 3).

**Figure 1.** Projection of variables (**a**) and projection of cases (**b**) depending on the botanical origin of the honey in a two-factor plane (PC1 × PC2). (**a**): L\*, lightness; a\*, redness; b\*, yellowness; C\*, saturation; h◦, hue angle; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power; (**b**) honey type: RS, rapeseed; BW, buckwheat; LI, linden; AC, black locust; MF, multifloral.


**Table 3.** Correlations between the principal components and the original variables.

L\*, lightness; a\*, redness; b\*, yellowness; C\*, saturation; h◦, hue angle; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power.

As can be seen in Figure 1, three groups of parameters, characterized by their loadings and the length of the directional vectors can be distinguished. The L\*, b\* and C\* variables were distributed in the positive area of PC1 and negative area of PC2, while h◦ is located in positive areas of both components, and a\*, DPPH and FRAP have negative values of PC1 and PC2.

Figure 1b shows the projection of cases depending on the botanical origin of the honey in the coordinate system defined by PC1 × PC2. The buckwheat honey samples are clearly separated and situated in the bottom left area of the plot, i.e., they have negative values of both components. Therefore, the buckwheat honey located in this square of the plot showed the highest values of antioxidant activity and redness (a\*), together with the lowest value of h◦, which was negatively correlated with FRAP and DPPH (Table 2). Among other honey types, the second group is composed of rapeseed samples (RS) in the upper right square of the plot, which is positively correlated with both components and represents the highest values of L\* and h◦. In contrast, the samples of multifloral (MF) honey were more scattered, while the black locust (AC) and linden (LI) samples were generally positively correlated with PC2. Summing up, the data presented in Figure 1 confirm the results given in Tables 1 and 2. Buckwheat honey showed the highest antioxidant activity together with the greatest redness and the lowest value of h◦.

Kaczmarek et al. [6], based on the cluster analysis dendrogram, have distinguished two well-separated clusters of eight types of Polish honeys. The first cluster included dark honeys (nectar-honeydew, buckwheat, honeydew, and heather), while the second one contained light coloured honeys (acacia, rape, linden, and multiforal).

#### 3.4.2. Antioxidant Activity and Minerals

Another PCA analysis (including 9 variables and 64 cases) was conducted on the results obtained for antioxidant activity and the concentrations of selected minerals and trace elements. Three principal components with eigenvalues exceeding 1 (Kaiser criterion) explained 73.46% of the total variance, with PC1 accounting for 40.65%, PC2 for 18.24%, and PC3 for 14.57% (Table S2). Figure 2a visualizes the projection of variables onto a two-factor plot (PC1 × PC2), explaining 58.89% of the total variance. The variables were distributed in two-quarters of the plot. The first area (bottom right quarter) included Cu, Mn, DPPH, FRAP and Fe, positively correlated with PC1 (0.893, 0.808, 0.772, 0.697 and 0.596) (Table 4). The second area (upper right quarter) included K and Mg, which were positively correlated with PC2 (0.725 and 0.708, respectively). The third component was positively correlated with Na and Zn (0.760 and 0.433).

Figure 2b shows the projection of cases depending on the botanical origin of the honey in the coordinate system defined by the first two principal components (PC1 × PC2). With the exception of buckwheat honey, the honey types were characterized by high dispersion of samples in the plot. Samples of buckwheat honey were found only in the bottom right square, i.e., positively correlated with PC1 and negatively with PC2. Thus, buckwheat (BW) honey showed strong antioxidant activity, together with a high concentration of Mn and Cu. Based on analysis of the content of selected minerals and trace elements in various types of Italian honeys, it was confirmed that their botanical origin significantly influenced their chemical composition, particularly in the case of Ca, Na and Mn [18]. Furthermore, PCA analysis indicated correlations between the concentration of minerals and the type of honey, as the highest element concentrations were found in the darkest honeys (honeydew) and the lowest content in light-coloured samples. Similar relationships between mineral concentration (Fe, Zn and Mn) and pine honeydew (dark) and acacia (light) were reported for honeys from Kashmir [7]. The results of our research confirm these dependencies for buckwheat honey from Poland.

**Figure 2.** Projection of variables (**a**) and projection of cases (**b**) depending on the botanical origin of the honey in a two-factor plane (PC1 × PC2). (**a**) K, potassium; Na, sodium; Mg, magnesium; Fe, iron; Zn, zinc; Mn, manganese; Cu, copper; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power; (**b**) honey type: RS, rapeseed; BW, buckwheat; LI, linden; AC, black locust; MF, multifloral.


**Table 4.** Correlations between the principal components and the original variables.

K, potassium; Na, sodium; Mg, magnesium; Fe, iron; Zn, zinc; Mn, manganese; Cu, copper; DPPH, scavenging capacity; FRAP, ferric reducing antioxidant power.

#### **4. Conclusions**

The study demonstrated that the physicochemical properties, instrumental colour parameters, content of some elements, and antioxidant activity of five honey types from Poland were significantly influenced by their botanical origin. Strong relationships were shown between antioxidant activity and parameters of instrumental CIE L\*a\*b\* colour analysis, as well as antioxidant minerals. The principal component analysis allowed the types to be classified in terms of their antioxidant activity in combination with their colour characteristics and content of certain elements. The buckwheat honeys, which were the darkest, had the strongest antioxidant activity, which may have been linked to the fact that they had the highest concentrations of copper, manganese and zinc. These parameters can be potentially used for the identification of buckwheat honeys from other blossom types. However, this requires further studies with honeys of different geographical origins.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/agriculture11080702/s1, Table S1: Eigenvalues and the proportion of variation (%) explained by 7 principal components, Table S2: Eigenvalues and the proportion of variation (%) explained by 9 principal components.

**Author Contributions:** Conceptualization, M.K.-M. and M.F.; methodology, M.K.-M., A.T., M.S. and M.R.; investigation, A.T., M.S., P.D. and M.R.; formal analysis, M.K.-M. and M.F.; data curation, M.S., P.S., P.D. and M.R.; writing original draft, M.K.-M., A.T., M.S., P.D. and M.R.; writing—review & editing, P.S. and M.F.; funding acquisition, P.S.; project administration, P.S.; supervision, M.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded under the program of the Minister of Science and Higher Education under the name "Regional Initiative of Excellence" in 2019–2022 project number 029/RID/2018/19 funding amount 11,927,330.00 PLN.

**Institutional Review Board Statement:** Not applicable.

**Data Availability Statement:** Data sharing not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


### *Article* **Milling and Baking Quality of Spring Wheat (***Triticum aestivum* **L.) from Organic Farming**

**Beata Feledyn-Szewczyk 1, Grazyna Cacak-Pietrzak ˙ 2, Leszek Lenc 3, Karolina Gromadzka <sup>4</sup> and Dariusz Dziki 5,\***


**Abstract:** The quality of grain products from organic agriculture is an important subject of research for food safety and consumer health. The aim of the study was to examine the grain of spring wheat from organic agriculture according to their infestation by *Fusarium* spp., mycotoxin content, and technological value for milling and baking processing. The material was grain of 13 spring wheat varieties cultivated in organic systems in 3 years. The results showed that the intensity of *Fusarium* head blight (FHB) was low and ranged from 0.0% to 5.5% of ears. Grain infestation by *Fusarium* spp. varied between varieties and years from 1.5% to 18.5%. The colonization of grains by *Fusarium* spp. did not reflect the intensity of FHB. The lowest grain infestation by *Fusarium* spp. was noted for the varieties: Waluta, Zadra, and Arabella. Mycotoxin contamination of the grain of tested varieties did not exceed accepted standards. The requirements of the milling and baking industries were generally met by grain and flour of all the tested varieties. On the basis of the 3 year study results related to food safety and processing properties, the varieties most useful for organic production are Arabella, followed by Brawura, Izera, Kandela, Katoda, KWS Torridon, Waluta, and Zadra.

**Keywords:** spring wheat; organic agriculture; *Fusarium* spp.; mycotoxins; quality of grain; flour yield; technological value

#### **1. Introduction**

Spring wheat is a popular crop in both conventional and organic farms, as it is an important consumer cereal in Europe [1,2]. However, in organic agriculture, the choice of proper variety is of great importance because it influences the yield [3–7] and quality of grain [8,9]. Spring wheat varieties vary according to their agricultural traits (morphological features, yielding potential, resistance to disease and pests, weed suppression ability) and technological parameters [5,6,10–13]. The information about the suitability of different varieties for organic farming and food processing according to their susceptibility to *Fusarium* sp. disease and mycotoxin contamination, and the technological value of grain and flour, is desired by producers, advisors, and processors. The common wheat pathogens in organic farming are fungi of the genus *Fusarium*. Some of them, such as Fusarium rot pre- and post-emergence, Fusarium foot rot, and Fusarium leaf blight can lead to a significant drop in yields, while Fusarium head blight (FHB) and grain infestation by *Fusarium* spp. (Fusarium disease kernels—FDK) may contribute to a decrease in yields [14]. The infested ears either do not form grains at all or form fewer grains that are smaller and

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**Citation:** Feledyn-Szewczyk, B.; Cacak-Pietrzak, G.; Lenc, L.; Gromadzka, K.; Dziki, D. Milling and Baking Quality of Spring Wheat (*Triticum aestivum* L.) from Organic Farming. *Agriculture* **2021**, *11*, 765. https://doi.org/10.3390/agriculture 11080765

Academic Editor: Alessandra Durazzo

Received: 25 June 2021 Accepted: 9 August 2021 Published: 11 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

poorly filled that contain less starch and gluten proteins and, therefore, the flour obtained from them has a low baking value [15]. In addition, certain species of fungi of the genus *Fusarium* have the ability to synthesize mycotoxins that accumulate in grains, and these mycotoxins are also present in products derived from them, which can be dangerous to human health [16–18]. The significant contaminants in all cereal grains, including wheat, are deoxynivalenol (DON), zearalenone (ZEA), and fumonisins B1 and B2. Zearalenone is one of the strongest non-steroidal estrogenic substances, which can cause functional changes in the reproductive system similar to those of estrogens [19]. Deoxynivalenol and nivalenol are important toxins from the group of trichothecenes. Deoxynivalenol, similar to other trichothecenes, has a significant effect on biochemical processes. The most frequently observed DON toxicosis symptoms in animals include vomiting and body weight loss with successive numerous physiological changes in internal tissues [20]. Fumonisins, especially fumonisin B1, has caused field outbreaks of leucoencephalomacia in horses, porcine pulmonary oedema in swine, and were found to be hepatotoxic and hepatocancerogenic to rats [21]. Beauvericin and enniatins (EnnA, EnnA1, EnnB, EnnB1) are well-known toxic cyclic hexadepsipeptides with a specific cholesterol acyltransferase inhibitor activity [22]. Beauvericin and enniatins are early emerging mycotoxins, and they are being identified, with an increasing frequency, in cereal grains worldwide. Moniliformin is a potent inhibitor of mitochondrial pyruvate and ketoglutarate oxidation and has caused acute degenerative lesions in the myocardium [23]. EU countries have established and published guidelines for maximum levels of deoxynivalenol (DON), zearalenone (ZEA), and the sum of fumonisins B1 and B2 [24].

The technological value of wheat grains is determined not only by genetic factors but also by habitat conditions and the crop management treatments applied, which are limited in the organic production system [8,16]. Agrotechnical treatments have a significant impact on the quantity as well as the fractional composition of protein, which is commonly considered as one of the basic indicators of the suitability of wheat grains for processing [8,16,25]. The response of individual wheat varieties to the applied cultivation conditions is not the same. It is important to select wheat varieties with the lowest possible variability of grain quality traits for organic farming. In Poland, as in other EU countries, no separate quality requirements have been defined for wheat grain from organic farming, so it has to meet the general quality requirements for wheat grain [26], and the direction of its use should be selected taking into account the requirements of the processing industry [27].

The aim of the study was to examine 13 spring wheat varieties (*Triticum aestivum* L.) cultivated in organic farming due to their susceptibility to *Fusarium* spp. diseases and technological parameters of grain, flour, and bread. Moreover, mycotoxin content in the grain of two selected spring wheat varieties was analyzed.

The hypothesis was that it is possible to obtain wheat grains in organic farming that met processing criteria.

#### **2. Materials and Methods**

#### *2.1. Sites Characteristics, Experimental Design and Agronomic Practices*

The experiment with the varieties of spring wheat was carried out in the years 2014– 2016 in the organic farm of the Institute of Soil Science and Plant Cultivation—State Research Institute (IUNG-PIB), located in Osiny, central-eastern part of Poland (Table 1).


**Table 1.** The characteristics of habitat conditions of the experiment.

Spring wheat varieties were cultivated in a randomized complete block design, with four replications. The area of each plot of replication for sowing and harvesting was 30 m2. Thirteen spring wheat varieties (*Triticum aestivum* L.) included in the Common Catalogue of Varieties of Agricultural Plant Species [29]—Arabella, Brawura, Cytra, Ethos, Izera, KWS Torridon, Kandela, Katoda, Koksa, Korynta, Ostka Smolicka, Waluta, and Zadra—were cultivated in organic system. Sowing treatments were performed in accordance with good agricultural practice at the optimum time for each region. The sowing rates were the same for each variety—450 grains m−2. The row spacing was 12 cm and the planting depth 3.5 cm. According to organic agriculture rules, mineral fertilizers and chemical plant protection products were not used [30]. Harvests were undertaken in the first week of August.

The experimental site belongs to a moderately continental climate zone. The characteristics of the meteorological condition in the location of the experiment in the 3 years of the study are presented in Table 2. In 2014 and 2015, high precipitation occurred in May (more than twice the multi-annual average). The 2016 growing season was warm and dry. The temperatures from March to August exceeded the multi-annual average, and the amount of precipitation was below the average (except in August).


**Table 2.** Total precipitation and average monthly temperatures in the experiment.

#### *2.2. Fusarium sp. Occurrence*

An assessment of Fusarium head blight was performed at the milk-dough stage of spring wheat (BBCH 77-83). From each experimental combination, 4 × 50 randomly selected ears were analyzed, and the percentage of their infestation was determined.

After the harvest, a mycological analysis of the grain was performed. From each combination, 4 × 100 grains were taken at random. After rinsing under running water, decontaminating for 2.5 min in 1% NaCl, and rinsing three times in sterile water, the grains were placed into PDA (Potato Dextrose Agar) (pH = 5.5) and incubated at 20 ◦C for 6 days. The growing colonies of fungi were grafted onto slants of PDA and identified according to mycological keys [31,32].

#### *2.3. Analysis of Mycotoxins*

In the first year of research (2014), five toxins synthesized by *Fusarium* species were analyzed—zearalenone (ZEA), deoxynivalenol (DON), nivalenol (NIV), beauvericin (BEA), and moniliformin (MON)—whereas, in the second and third year (2015–2016), twelve mycotoxins—zearalenone (ZEA), deoxynivalenol (DON), nivalenol (NIV), beauvericin (BEA), moniliformin (MON), enniatins (EnnA, EnnA1, EnnB, EnnB1) and fumonisins (FB1, FB2, FB3)—were measured in the wheat grains of two selected varieties—Kandela and Ostka Smolicka. These varieties were chosen because they showed greater infection of the grain by Fusarium spp. in the first year of research; the same varieties were tested for the next 2 years. Moreover, Ostka Smolicka was the only bristly variety among tested varieties, and we aimed to check its susceptibility to *Fusarium* infection.

In order to achieve effective extraction, the mycotoxins were divided into 3 groups with similar physico-chemical properties: I. ZEA, DON, NIV—extracted with an acetonitrilewater solution (8:2 *v*/*v*); II. Enns, FBs—extracted with a methanol-water solution (3:1 *v*/*v*); III. MON, BEA—extracted with an acetonitrile–methanol–water solution (16:3:1 *v*/*v*/*v*).

Grain material was extracted using 2.5 mL of solvent per 1 g of sample; then, it was homogenized in a Ultraturrax model T25 basic (IKA Werke, Freiburg, Germany) for 4 min at 13,500 rpm. The content of mycotoxins was determined using the chromatographic system with a Waters 2695 high performance liquid chromatograph, a Waters 2475 Multi λ Fluorescence Detector, and/or a Waters 2996 Photodiode Array Detector (Waters Corporation, Milford, PA, USA). The quantification limits (LOQ) were determined by multiplying the detection limits (LOD) by 3.3. The LOD of the methods were calculated by a signal-to-noise ratio of 3:1. Mycotoxin analyses were performed in triplicate. The presented concentration values are the average of the obtained results.

The extract of ZEA was purified on an immunoaffinity column according to the method described by Visconti and Pascale [33]. Zearalenone content was determined using the fluorescence detector. The excitation and emission wavelengths were 274 and 440 nm, respectively. The reserve-phase column was a C-18 Nova Pak column (3.9 × 150 mm), while the mobile phase was acetonitrile–water–methanol (46:46:8, *v*/*v*/*v*) at a flow rate of 0.5 mL·min−1. Quantification of ZEA was performed by measuring the peak areas at the ZEA retention time according to the relevant calibration curve (correlation coefficient R = 0.9998). The limit of zearalenone detection was 3 <sup>μ</sup>g·kg<sup>−</sup>1. The recovery of zearalenone was measured in triplicate by extracting ZEA from blank samples spiked with 5–100 ng·g−<sup>1</sup> of the compound. The results of the experiments confirmed the literature data on ZEA recovery in the range of 97% to 99%. The relative standard deviation (R.S.D.) was below 1%. In order to confirm the presence of zearalenone, the photodiode array detector was used. To analyze the trichothecenes (DON, NIV), extracts were purified by filtration on a column (Celite 545:charcoal, Darco G-60:neutral alumina, 3:9:5 *w*/*w*/*w*) according to the method described by Tomczak et al. [34]. Deoxynivalenol and nivalenol were quantified by HPLC using a C-18 Nova Pak column (3.9 × 300 mm) and a photodiode array detector (λmax = 224 nm for DON and NIV). DON and NIV were eluted from the column with a 25% water solution of methanol (flow rate 0.7 mL·min<sup>−</sup>1). The detection limit for DON and NIV was 10 <sup>μ</sup>g·kg<sup>−</sup>1. Positive results (on the basis of retention times) will be confirmed by HPLC analysis and by comparison with the relevant calibration curve (correlation coefficients for NIV and DON are 0.9994 and 0.9997, respectively). The recovery rates for NIV and DON were 75% are 87%, respectively, estimated in triplicate by extracting mycotoxins from blank samples spiked with 10–100 ng·g−<sup>1</sup> of the compounds. The relative standard deviation (R.S.D.) was below 5% for DON and NIV. Enniatins and beauvericin were identified and quantified as reported by Logrieco et al. [23]. Extracts were prepurified once on a C18 column (500 mg, 3 mL, 40 μm), concentrated to 1 mL, and filtered through an Acrodisk filter (pore size, 0.22 μm) before HPLC analysis. HPLC analyses were performed using a

diode array detector and C18 column (250 × 4.6 mm, 5 μm). HPLC conditions included a constant flow at 1.5 mL·min−<sup>1</sup> and acetonitrile–water (65:35, *<sup>v</sup>*/*v*) as the starting eluent system. The starting ratio was kept constant for 5 min and then linearly modified to 70% acetonitrile over 10 min. After 1 min at 70% acetonitrile, the mobile phase was returned to the starting conditions in 4 min. Beauvericin and enniatins were detected at 205 nm. Mycotoxins were identified by comparing retention times and UV spectra of samples with those of authentic standards. Mycotoxins were quantified by comparing peak areas from samples to a calibration curve of standards. The detection limits were 5.0 <sup>μ</sup>g·kg−<sup>1</sup> for EnnA, 1.8 <sup>μ</sup>g·kg−<sup>1</sup> for EnnA1, 1.0 <sup>μ</sup>g·kg−<sup>1</sup> for EnnB1, 0.5 <sup>μ</sup>g·kg−<sup>1</sup> for EnnB, and 1.0 <sup>μ</sup>g·kg−<sup>1</sup> for beauvericin determination. The calculated standard deviation was always less than 5%. The extract of MON was purified on a Florisil column according to the method described by Kostecki et al. [35]. Moniliformin was quantified by HPLC using a C-18 Nova Pak column (3.9 × 300 mm) and a photodiode array detector (λmax = 229 nm). MON was eluted from the column with the acetonitrile–water solvent (15:85, *v*/*v*) buffered with 10 mL of 0.1 M K2HPO4 in 40% t-butyl-ammonium hydroxide in 1 L of solvent (flow rate 0.6 mL·min−1). The detection limit for MON was 8 <sup>μ</sup>g·kg−1. Positive results (on the basis of retention times) were confirmed by HPLC analysis and by comparison with the relevant calibration curve (correlation coefficients 0.9990). The recovery rate for MON is 90%, estimated in triplicate by extracting mycotoxin from blank samples spiked with 10–100 ng·g−<sup>1</sup> of the compound. The relative standard deviation (R.S.D.) was below 7%. The detailed procedure of extraction and purification of FBs was reported by Wa´skiewicz et al. [36]. The fumonisin B1, B2, and B3 standards (5 μL) or extracts (20 μL) were derivatized with 20 or 80 μL of the ophosphoric acid (OPA) reagent. After 3 min, the reaction mixture (10 μL) was injected onto an HPLC column. Methanol sodium dihydrogen phosphate (0.1M in water) solution (77:23, *v*/*v*) adjusted to pH 3.35 with o-phosphoric acid, after filtration through a 0.45 μm Waters HV membrane was used as the mobile phase with a flow rate of 0.6 mL·min−1. A HPLC with a C-18 Nova Pak column (3.9 × 150 mm) and a fluorescence detector (λEX = 335 nm and λEM = 440 nm) were used in the metabolite quantitative determination. The detection limit of FB1, FB2, and FB3 determination was 10.0 <sup>μ</sup>g·kg−1. Positive results (on the basis of retention times) were confirmed by HPLC analysis and compared with the relevant calibration curve (the correlation coefficients for FB1, FB2, and FB3 were 0.9967, 0.9983, and 0.9966, respectively). The recovery rates for FB1, FB2, and FB3 were 93, 96, and 87%, respectively. The relative standard deviation (R.S.D.) was below 5%.

#### *2.4. Quality Traits of Grains, Flour, and Bakery Products*

The evaluation of the quality traits of the grain of the tested spring wheat varieties, different laboratory tests were carried out according to the methods commonly used to evaluate cereal grain and cereal products [37]. As part of the physico-chemical evaluation of grains, grain selectness, uniformity, glassiness, and hardness were determined using a farinograph adapter (Brabender, Duisburg, Germany).

The laboratory milling of the grain was carried out in a two-passage laboratory mill Quadrumat Senior (Brabender, Duisburg, Germany). Before milling, the grains were cleaned on granules (Brabender, Duisburg, Germany) and conditioned to 14.5% humidity. Based on the milling balance, the total flour yield was calculated. As part of the evaluation of the physical and chemical characteristics of the flour, the following determinations were made: total ash content according to the AACC Method 08-01.01 [33]; total protein content using Kjeldahl's method (N·5,83) in a Kjeltec apparatus 8200 (Foss, Hillerød, Sweden) according to the AACC Method 46-11.02 [38]; wet gluten yield and gluten index (IG) in a Glutomatic 2200 apparatus (Perten Instruments, Hägersten, Stockholm, Sweden) according to the AACC Method 38-12.02 [38]; and the falling number, with the Hagberg–Perten method in a Falling Number 1400 apparatus (Perten Instruments, Hägersten, Stockholm, Sweden) according to the AACC Method 56-81.03 [38].

The suitability of flour for the production of bakery products was determined by conducting a laboratory test baking. Dough (160% yield) was prepared directly from 500 g of flour with a moisture content of 14.0%, 300 cm3 of water, 15 g of baker's yeast, and 7.5 g of kitchen salt in an SP-800A mixer (SPAR Food Machinery, Taiwan). The time of dough kneading was 4 min. Fermentation was carried out in two stages, with piercing of the dough after 60 and 90 min. The final expansion of the dough was carried out in moulds. Baking took place in a Svena Dahlen DC-32E oven (Sveba Dahlen, Fristad, Sweden) at 230 ◦C for 30 min.

The evaluation of the baking process was carried out on the basis of calculations of bread yields. The analysis of bread quality was carried out 24 h after baking (the bread was stored in room conditions). It included an evaluation of bread volume, crumb porosity, and an organoleptic evaluation using the point method according to the standard [39]. The assessment team consisted of 20 people. The evaluation included the following quality characteristics of the bread: external appearance of the loaf, colour and thickness of the crust, elasticity, porosity and sliceability of the crumb, taste, and smell.

#### *2.5. Statistical Analysis*

For all tested features, analysis of variance (ANOVA) and the post-hoc Tukey's test was done, where varieties and years of the research were the factors of the experiment. The research on *Fusarium* spp. on ears and grain infestation were conducted in 4 replications (*n* = 3 years × 4 replications = 12), whereas the study of baking quality traits was conducted in 3 replications (*n* = 3 years × 3 replications = 9). Due to the lack of significant years × cultivar interactions for the features related to the technological value of grain, flour, and bread, these results were presented in the form of means from 3 years of research for each variety. All tests were performed at the significance level of α = 0.05.

#### **3. Results**

#### *3.1. Infestation of Spring Wheat Ears and Grain by Fusarium spp.*

In the 3 years of the experiment, the intensity of Fusarium head blight (FHB) of spring wheat was low and ranged from 0.0% to 5.5% of ears (Table 3, Figure 1A). The low level of infestation of ears in all years of research was a result of the weather conditions (warm and dry in the phase of ears ripening) (Table 2). The analysis of variance showed significant differences among the wheat varieties only in 2015, when the infestation of Izera variety ears was lower than Katoda variety. No significant interaction year × variety for the occurrence of FHB on the ears was detected.

**Table 3.** The occurrence of FHB on the ears of spring wheat varieties (% of ears infested by *Fusarium* spp.).


<sup>1</sup> Different letters indicate significant differences between varieties according to Tukey's test at α = 0.05; <sup>2</sup> Different capital letters indicate significant differences between years according to Tukey's test at α = 0.05. Interaction year × variety non-significant (*p* > 0.05).

Grain infestation by *Fusarium* spp. varied between varieties and years from 1.5% to 18.5% (Table 4, Figure 1B,C). The significant interaction year × variety was found. The highest grain infestation was observed in 2014 (Table 4), when the precipitation was high in May, June, and August (Table 2). Waluta, Zadra, and Arabella varieties in each year of the study belonged to the group of varieties with the lowest percentage of infected grains. In the first year of research, the highest infestation of the grains was noted for Kandela and Ostka Smolicka varieties. On average, the largest amount of *Fusarium* spp. was isolated from grains of KWS Torridon and Cytra (Table 4).


**Table 4.** The infestation of the grains (%) of spring wheat varieties.

<sup>1</sup> Different letters indicate significant differences between varieties according to Tukey's test at α = 0.05; <sup>2</sup> Different capital letters indicate significant differences between years according to Tukey's test at α = 0.05. Significant interaction year × variety (*p* = 0.032).

**Figure 1.** (**A**) Fusarium head blight; (**B**) Fusarium disease on grains; (**C**) infestation of grains by *Fusarium* sp.

The results of the research indicated that the lack of *Fusarium* disease symptoms on the ears does not mean that the grain is not infected by *Fusarium* spp. In all years, *F. poae* was the most frequently isolated species from grains, which does not cause the symptoms on ears (Table 5). The domination of *F. poae* explains the differences between the intensity of *Fusarium* spp. symptoms on ears and the colonization of grain. Other species—*F. avenaceum*, *F. culmorum*, *F. equiseti*, *F. graminearum*, *F. langsethiae*, *F. sporotrichioides* and *F. tricinctum*—were isolated occasionally, but to a lesser extent.

**Table 5.** Species from *Fusarium* genus isolated from grains of spring wheat varieties (% of infested grains).


#### *3.2. Mycotoxin Content in the Spring Wheat Grains*

The content of mycotoxins in the tested samples of wheat grain varied depending on the year and variety (Table 6). In 2014, when five toxins were analyzed, the presence of DON was found only in one sample (Ostka Smolicka—181.5 <sup>μ</sup>g·kg−1). The content of this toxin did not exceed the maximum contamination level of (1250 <sup>μ</sup>g·kg−1) set by EU regulations [24]. The second of the tested trichothecenes—NIV—was found in the grain of a Kandela variety in the amount of 334.7 <sup>μ</sup>g·kg−1. Both of these toxins were found in the tested grains only in the first year of the study (Table 6), which was the wettest year (Table 2).

The presence of ZEA was detected in two of the six tested samples; one from 2015 and one from 2016 (Table 6). Contamination of grains with this mycotoxin at levels of 24.1–62.9 <sup>μ</sup>g· kg−<sup>1</sup> did not exceed the accepted standard of 100 <sup>μ</sup>g·kg−<sup>1</sup> [24]. Due to the fact that *F. poae* was the dominant fungus isolated from the grain, accompanied by *F. avenaceum* and *F. tricinctum*, BEA and MON produced by these species were also examined. Mycotoxins BEA and MON were found in larger amounts in the examined grains. The concentration of BEA in the grains of both of the tested cultivars was over 6300 <sup>μ</sup>g·kg−1, while the concentration of MON in the grains of both tested varieties was over 200 <sup>μ</sup>g·kg−<sup>1</sup> (Table 6).

In the second and third year of the study, 12 metabolites synthesized by *Fusarium* fungi were analyzed (Table 6). Additionally, enniatins (A1, A, B, and B1) and fumonisins (FB1, FB2, and FB3) were included in the study. In 2015 and 2016, very high BEA contents were found (respectively, over 13,000 <sup>μ</sup>g·kg−<sup>1</sup> in 2015 and over 89,000 <sup>μ</sup>g·kg−<sup>1</sup> in 2016). No correlation was observed between the number of synthesized toxins and the infestation of variety. No MON was found in 2015, but it was found in both wheat varieties in 2016. Of the analyzed enniatins, only enniatin A1 was present in all wheat samples from 2015 and 2016. In 2015, this toxin remained relatively stable, and its amount ranged from 23.430 to 25.380 <sup>μ</sup>g·kg−1. In the last year of the study, its concentration increased significantly (97,426.8 <sup>μ</sup>g·kg−<sup>1</sup> for variety Ostka Smolicka and 81,635.9 <sup>μ</sup>g·kg−<sup>1</sup> for variety Kandela). In 2015 and 2016, the grains were also tested for concentrations of fumonisins. Only one sample from 2015 showed the presence of FB1 (Kandela 20.3 <sup>μ</sup>g·kg<sup>−</sup>1), while none of them had the other fumonisins, FB2 and FB3. The correlation analysis showed no relationship between the infestation of grain by *Fusarium* spp. and the concentration of fumonisins.


**Table 6.** Mycotoxin content in spring wheat grains.

\* According to the Commissions Regulations (EC) No 1881/2006 of 19 December 2006, setting maximum levels for certain contaminants in foodstuffs [24]. 'nd'—not detected; 'na'—no analysis; '-' maximum level not set for wheat in the EU regulations.

> *3.3. Assessment of the Technological Value of Grains of Spring Wheat Varieties and Their Suitability for Processing*

The grains of spring wheat cultivars from organic cultivation showed significant differences in terms of all of the assessed physico-chemical characteristics, i.e., selectness and uniformity, glassiness and hardness, and ash content (Table 7). During the three year study period, the average grain selectness ranged from 74.7% to 90.0%. The grain selectness

of the majority of the examined wheat varieties (except for Izera and Koksa) coincided with grain uniformity, which proved their high plumpness. The most plump were wheat grains of the varieties Katoda, Waluta, Arabella, KWS Torridon, and Kandela, while the least plump were grains of the varieties Ethos and Koksa.

Grain uniformity ranged from 74.7% to 90.0% on average (Table 7). During the three year research period, the greatest uniformity, as with selectness, was observed in the grains of wheat varieties Katoda, Waluta, Arabella, KWS Torridon, and Kandela.


**Table 7.** Results of the assessment of grain milling value (averages over 2014–2016).

<sup>1</sup> BU—conventional units in Brabender scale; <sup>2</sup> Different letters indicate significant differences between varieties according to Tukey's test at α = 0.05.

> The glassiness and hardness of grains indicate the structure of the endosperm. In the milling industry, glassy grains with a glassiness above 60% are classified as floury when the number of glassy grains is below 40%. In the 3 year testing period, the glassiness of grains was between 15% and 51% on average (Table 7). The highest percentage of grains with a glassy structure of the endosperm was observed in the following varieties: Ethos, Cytra, Koksa, and Korynta. The most floury grains were the Kandela, Katoda, and Waluta varieties.

> During the 3 year testing period, the average grain hardness of the tested wheat varieties ranged from 563 BU to 670 BU (Table 7). Grains of Ethos, KWS Torridon, and Brawura wheat varieties had the hardest white, while grains of the Kandela and Zadra varieties had the softest.

> The average content of mineral substances (total ash) in grains of the wheat varieties ranged from 1.75% d.m. to 1.93% d.m. (Table 7). The lowest ash content was found in grains of wheat varieties including Waluta, Brawura, Katoda, Arabella, Izera, and Korynta, while the highest total ash content was found in the grains of wheat varieties Koksa, Kandela, and Cytra.

> During the three year research period, the average flour yields (extracts) ranged from 74.7% to 78.0% (Table 7). The obtained flour yields were high and comparable to those obtained in industrial mills. The largest flour extracts (above 77%) were obtained from milling grains of wheat varieties Zadra, Waluta, Kandela, Izera, Arabella, and Ethos.

> During the three year testing period, the total protein content of the flours tested was, on average, from 9.5% d.m. to 11.2% d.m. (Table 8). The highest levels of this component were recorded from flours from the grain varieties Koksa, Korynta, Ethos, KWS Torridon, and Cytra.


**Table 8.** Results of the evaluation of the baking value of flour (averages over 2014–2016).

During the 3 year study period, the average yields of wet gluten ranged from 21.2% to 29.9% (Table 8). The highest levels of gluten proteins were contained in flours from the grains of the following wheat varieties: Ethos, Cytra, KWS Torridon, Koksa, and Korynta, which were also characterized by the highest total protein content. As required by standards [40], the amount of gluten in low-extraction wheat flours should not be lower than 25%. The gluten yield meeting this requirement was recorded in flours obtained from the grains of varieties Cytra, Ethos, Koksa, Korynta, KWS Torridon, and Zadra.

The average values of the gluten index (GI) ranged from 40 to 98 (Table 8). Flours from most wheat varieties were distinguished by optimal gluten quality (GI values from 60 to 90). Regardless of the year of wheat harvest, exceptionally strong gluten was found in flours from the grains of the Arabella, Kandela, and Waluta varieties, while exceptionally weak gluten was found in the Cytra variety.

During the 3 year study period, the mean values of the falling number, which is the amylolytic enzyme activity index, ranged from 256 s to 314 s (Table 8). The optimal activity of amylolytic enzymes in flour intended for baking should be at an average level (a falling number in the range 220–280 s) [27]. This requirement was met by flours from the grain of Izera, Kandela, Koksa, and Zadra varieties. In wheat grain flours from the remaining varieties, the activity of amylolytic enzymes was lower. Before baking, it can be increased, e.g., by adding malt, which is a source of amylolytic enzymes.

The average bread yield (the amount of bread obtained from 100 parts of flour by weight) was not very diversified, ranging from 139.1% to 143.0% (Table 8). Bread with the highest yield was obtained from flour of the following varieties: Koksa, Ethos, Izera, and Ostka Smolicka.

Breads from the laboratory test baking had the correct taste and smell, typical of wheat bakery products. The shape of the loaves was correct, typical for bread baked in tins. The bread crust had the right thickness, the color ranging from light to dark brown. The growth of the loaves was varied. During the three year research period, the volume of the loaves was, on average, from 357 cm3·100 g−<sup>1</sup> to 420 cm3·100 g−<sup>1</sup> (Table 8). The largest volume of bread was obtained from flour of the wheat varieties Katoda, Arabella, Waluta, Izera, and Kandela, while the least risen bread loaves were obtained from Ostka Smolicka, Koksa, KWS Torridon, and Zadra.

Bread crumb was characterized by very good or good flexibility. It was varied in its porosity (Table 8, Figure 2). The crumb of bread from Arabella, Kandela, Katoda, and Waluta varieties was the most evenly distributed. The lowest rated in this aspect was the crumb of breads from flour from the varieties Ethos, Ostka Smolicka, and Zadra.

**Figure 2.** Comparison of crumb porosity in 2016: (**A**) variety Izera, porosity coefficient 70; (**B**) variety Kandela, porosity coefficient 65; (**C**) variety Cytra, porosity coefficient 50; (**D**) variety Zadra, porosity coefficient 45.

> During the organoleptic evaluation, the highest value was given to bread made from flour from the grains of the following varieties: Katoda, Arabella, Izera, and Korynta, while the lowest value was from Cytra, Zadra, and Ostka Smolicka (Table 8). Based on the total number of points awarded, breads made from flour from the grains of the Cytra, Zadra, and Ostka Smolicka varieties were graded to the second quality level. Bakery products made of flour from grains of the other wheat varieties were graded to the first quality group.

On the basis of the results of a 3 year study on spring wheat varieties from organic systems that are recommended for the production of bakery products, it was concluded that the requirements of the baking industry were met, to the greatest extent, by flours from the grains of varieties Arabella, Izera, Kandela, Katoda, and KWS Torridon.

#### **4. Discussion**

In organic agriculture, chemical products are forbidden; thus, other agrotechnical, mechanical, and biological methods, such as choice of a proper variety, are used to achieve a high yield of good quality [4,16,41]. One of the important features of wheat varieties that should be taken into account when evaluating their usefulness for cultivation in organic agriculture and food processing is their susceptibility to fungal diseases. Fusarium head blight (FHB) and grain infestation by *Fusarium* spp. (FDK—Fusarium disease kernels) may be caused by various species of *Fusarium* that have different climatic requirements and different toxin formations [17,18]. The most dangerous mold fungi for wheat ears include *Fusarium culmorum*, *F. avenaceum*, and *F. graminearum*. Factors that influence the occurrence of FHB and fungal infestation of the grain primarily include the weather (rainfall and temperature) during the stages from BBCH 55 to BBCH 73, as well as crop management treatments applied, crop rotation, nitrogen fertilisation, variety, plant protection products, and the quantity of inoculum of *Fusarium* spp. on a given field [17,42–46]. The severity of the disease symptoms in this experiment in the years 2014–2016 was low, which was probably influenced by the weather conditions, and especially by the low rainfall in the 2015 and 2016. Significant differences among the wheat varieties were observed in each year of the study according to infestation of grain and, in one year, due to the infestation of ears, as other agricultural factors were not differentiated in the experiment.

Mycotoxins most commonly accumulated in grains during wheat growth include deoxynivalenol, zearalenone, T-2 and HT toxins, and nivalenone. The risk is even more significant because certain amounts of mycotoxins have also been found in grains harvested from ears without symptoms of FHB [47]. The content of mycotoxins during the analyzed period was low and did not exceed the standards permitted by the European Union [24]. However, due to their high level of harmfulness, there is a need for constant monitoring of their content.

The profile of fungi inhabiting the territory of Poland has changed in the last years. Therefore, the toxins in cereals have also changed. Many of them were not standardized because they appeared sporadically. Therefore, it is necessary to update these standards allowing for the presence of individual compounds and to determine their toxicity to humans and animals. In Poland, such species as *Fusarium subglutinans*, *Fusarium poae*, and *Fusarium verticilioides* occur, which primarily produce fumonisins, beauvericin, group A and B trichothecenes, and enniatins [48]. The same shift in species was also found in other countries of central Europe [49].

According to Gromadzka et al. [50], the highest amount of BEA content was recorded in 2015, with a maximum concentration of 1,731,550.0 <sup>μ</sup>g·kg<sup>−</sup>1. In China, 82.3% of the wheat samples were contaminated by BEA, in the range from 0.04 <sup>μ</sup>g·kg−<sup>1</sup> to 1006.56 <sup>μ</sup>g·kg−1, followed by EnnA, with the levels ranging from 0.06 <sup>μ</sup>g·kg−<sup>1</sup> to 16.61 <sup>μ</sup>g·kg<sup>−</sup>1, and EnnB1, with the levels ranging from 0.07 <sup>μ</sup>g·kg−<sup>1</sup> to 3.33 <sup>μ</sup>g·kg−<sup>1</sup> [51]. According to Chelkowski et al. [52], F. *poae* contributed to an accumulation of a high number of mycotoxins; namely, toxic hexadepsipeptides—both BEA (up to 46,000 <sup>μ</sup>g·kg−1) and enniatins EnnA (up to 37,000 <sup>μ</sup>g·kg−1), EnnB (up to 46,000 <sup>μ</sup>g·kg−1) and EnnB1 (up to 75,000 <sup>μ</sup>g·kg−1). On the other hand, MON was found in 25,32, and 76% of the Norway samples of barley, oats, and wheat, respectively. The maximum MON concentrations in barley, oats, and wheat were 380, 210, and 950 <sup>μ</sup>g·kg<sup>−</sup>1, respectively [53].

In the research of Orlando et al. [54], conducted in France, F. *tricinctum* or F. *poae* affected enniatin content. F. *tricinctum* was the leading enniatin producer in spring barley (23% to 37%). F. *avenaceum* produced large amounts of enniatins in wheat (1% to 18%). F. *poae* made a minor contribution, never accounting for more than 2% of total enniatin

content. According to these authors, enniatins were highly prevalent in French small grain cereals and were mostly produced by F. *avenaceum* and F. *tricinctum.*

The presence and concentration of mycotoxins in grains can be influenced by many factors. One of the most important factors is the potential ability of fungi to form mycotoxins, as only a part of the isolates of a given species has the capacity to form secondary metabolites. Moreover, other grain-infesting fungi and weather conditions may affect the number of mycotoxins produced [55]. In plant protection, the breeding of varieties with increased resistance to *Fusarium* fungi has great importance. In our research, the varieties with the smallest colonization of the grain by *Fusarium* spp. were Waluta, Zadra, and Arabella. The grains of the following cultivars were the most infested: Cytra, Kandela, and KWS Torridon.

It could be assumed that crops in organic farming are more vulnerable to diseases as they lack chemical protection. However, there are reports in the literature that, under this cropping system, the intensity of *Fusarium* spp. is not higher and is often even lower than with conventional system [56–60]. According to a review of the literature, *Fusarium* diseases are found less often in cereals grown in the organic system than in the conventional one (this also applies to mycotoxin content) [61,62].

Bernhoft et al. [63,64] report that using crop rotation, as in the organic system, reduced both the occurrence of *Fusarium* spp. in grains, and the mycotoxin content, while the lack of mineral fertilization and herbicides reduced the occurrence of F. *graminearum*. They also found increased levels of *Fusarium* spp. and mycotoxins in the case of plant lodging, which often occurs in conventional cultivation as a result of high mineral fertilization. Other factors determining the lower pressure of *Fusarium* sp. in the organic system, as compared to the conventional one, were: higher overall biodiversity, lower compactness of the canopy for better aeration, and ear structure of individual varieties.

However, it should be taken into account that our research included as many as 12 metabolites of *Fusarium* sp. fungi. Additionally, compounds that were naturally synthesized in significant quantities were analyzed. Therefore, the results obtained constitute an important supplement to the world literature and are the basis for further detailed research.

The basic direction of the use of wheat grains is the production of various types of flour, which are primarily raw materials for the production of bread, but also pastries, pasta, noodles, dumplings, pancakes, etc. [27]. Wheat grains that are commercially marketed, irrespective of the farming system, must be healthy, clean, ripe, and free from foreign odors or pests [26]. The moisture content of the grains must not exceed 15.0%, while the bulk density must not be lower than 72.0 kg/hl. The maximum total content of impurities should not exceed 15% at the grain buying, including harmful and/or toxic seeds 0.5%, and ergot 0.05%. The activity of amylolytic enzymes, determined on the basis of the falling number, should not be lower than 160 s [16,27]. The grains from all the tested organic spring wheat varieties, regardless of the year of harvest, met the general quality requirements, which indicates that they could be marketed.

Depending on the type of intended processing, specific quality requirements for wheat grains are determined. The requirements of the milling industry mainly concern grain size and grain uniformity, the structure of the endosperm (glassiness, hardness), and the maximum ash content [27,65]. The larger (more plump) the grains are, the higher the share of the endosperm and the smaller the share of the peripheral layers. From such raw material, higher flour yields with a low ash content can potentially be obtained [65]. In addition to being more mature, grains should also have a degree of sizing uniformity of not less than 75%. This high level of uniformity facilitates the cleaning (removal of impurities) and conditioning of grains [27]. It could be assumed that grains from organic farming, where the use of mineral fertilizers is forbidden, will be smaller than grain from conventional farming. Data from the literature indicates, however, that organic farming produces wheat grain of comparable size to that of conventional farming [16,25,66–70]. The possibility of obtaining grains of organic wheat of high maturity and uniformity is also indicated by the results obtained in this work, in which the average values of grain

selectness and uniformity ranged from 74.0% to 90.0%. As in previous studies [16,25,66], both grain selectness and uniformity were significantly dependent on varietal traits. In terms of these parameters, in this study, the highest ratings were given to the grains of the varieties Katoda, Waluta, and Arabella.

Hardness and glassiness (flouriness) are considered to be the basic indicators for assessing the structural and mechanical properties of grains, especially their basic anatomical part—endosperm. The greater the hardness and glassiness of the grains, the greater the resistance to grinding, which translates into higher energy consumption [69]. The glassiness and flouriness are related to the chemical composition of grains, especially the protein–starch ratio. Glassy grains have a higher protein content than floury grains and a more compact structure, which makes them more resistant to mechanical stress. From glassy grains, large quantities of flour from grinding passages are produced. Flours from these passages exhibit low ashiness and light color [65]. The grains of the tested organic wheat cultivars were characterized by a floury structure of the endosperm; the percentage of glassy grains ranged from 15% to 51% and depended significantly on varietal traits. According to Marzec et al. [25], grains of wheat from organic farming exhibit lower glassiness and hardness of the endosperm than grains from intensive farming due to a lower content of protein substances that form the matrix surrounding the starch grains.

Ash content is one of the basic parameters characterizing wheat grain in terms of milling. The ash content of the grains determines, to a large extent, the ashiness of the flour obtained from it. A good raw material for the milling industry is wheat grain with a low ash content (maximum 1.75–1.80% dry matter), especially with a low ash content of the endosperm [65]. The ash content in the grain of the examined wheat varieties was relatively high, ranging from 1.75% to 1.93% d.m. An ash content not exceeding 1.80% d.m. was found in the grains of four wheat varieties: Brawura, Izera, Katoda, and Waluta. According to the literature data [8,16,25,66], ash content in the grains of wheat from organic farming may be slightly higher than in the grains from intensive farming. Spring wheat grains generally contain more ash than winter wheat [65].

The yields of flours obtained from milling the grains of the tested wheat varieties from organic farming were high (over 74%). According to many authors [16,66,70], the yields of flour obtained from grains of organic wheat are comparable to those of grains from intensive cultivation, which indicates that it is a suitable raw material for milling into low-extraction flours.

Flours obtained from the milling of grains should have the appropriate utility traits that are desirable for further processing. In the case of wheat flour intended for the production of bread, the quantity and quality of protein substances are particularly important [27,71,72]. The protein content of wheat grain, which is the raw material for flour production, is favorably influenced by mineral nitrogen fertilizers, which, however, cannot be used in an organic production system [6]. As a result, the protein content in the flour of organic wheat grains is lower than that of intensive cultivation, as indicated by many authors [16,70,71,73,74]. The flours tested in this study had a relatively low protein content, ranging from 9.5% to 11.2% d.m. Significant differences in the content of this component indicate that some varieties (Koksa, Korynta, Ethos, Cytra, KWS Torridon) better used the nitrogen available in the soil for protein synthesis than other varieties (Ostka Smolicka, Kandela, Brawura).

Among the proteins present in wheat flour, gluten proteins are of particular importance. They have a structuring function in bread due to their ability to form a branched structure, which, when the dough is mixed, envelops the swollen starch grains and enables the retention of gases produced during dough fermentation [72]. The results of many studies [16,68,70,71,73,74] indicate that organic wheat grain flours have a lower gluten protein content, as well as total protein content, than intensive grain flours. In this study, depending on the variety, the amount of wet gluten isolated from the tested flours ranged from 21.2% to even 29.9%. The gluten washed out of most flours, except for grain flour of Cytra variety (GI 40), was of good quality (GI 71 to 98).

An important parameter in assessing the baking value of wheat is also the falling number, which is an indicator of α-amylase activity. Flours for baking purposes should have the average activity of this enzyme (falling number of 220–280 s) [27]. The organic flours tested in this study showed medium or low amylolytic activity, none of them having an increased value of this parameter. According to some authors [70,72], the activity of amylolytic enzymes in organic wheat grain flour may be higher than in intensive wheat grain flour, and, according to others [16,68], it is at a similar level.

The best method of evaluating the value of baked flour is to carry out laboratory baking combined with an evaluation of the quality of the baked goods obtained, including a sensory evaluation. Breads obtained from the tested organic flours were highly rated in terms of sensory quality. They exhibited an intensive smell and taste typical of wheat bread; there were no major objections to the external appearance of the loaf and crumb. The loaves were generally well-risen; the volume per 100 g of bread was in the range of 363–420 cm3, which met the requirement set out in Polish standard (no less than 260 cm3·100 g−1) [75]. Data from the literature [16,66,67,71] indicate that flours from organic wheat grains can be used to make bread of a similar volume to that made of flour from intensively farmed wheat. However, there are also reports [73,74] that indicate that bread made from organic grains has a smaller volume. In addition to the volume of the loaf, the porosity of the crumb is an important quality feature. Wheat bread should have an even, finely porous crumb with thin walls, which adheres well to the crust. The porosity of the crumb of bread obtained from the tested organic flours varied. The crumb with the best porosity was noted for breads made of flour from grains of the following wheat varieties: Arabella, Kandela, Katoda, and Waluta.

An evaluation of the technological value of the grains showed that the grains of the tested spring wheat varieties generally met the quality requirements for the milling and baking industries. In the presented ranking of spring wheat varieties, the Arabella variety, a quality bread variety, was ranked the highest. Arabella has been noted since 2009 in the Polish Varieties Register carried out by Research Centre for Cultivar Testing (COBORU) [76]. This variety is also useful for late autumn sowing. It tolerates slight soil acidification, which makes it suitable for cultivation on poorer, sandy soils. This variety was also ranked high according to the agricultural traits and yield in our previous research [10] so it can be especially recommended for organic production.

#### **5. Conclusions**

The presented study is in line with the current trends in the greening of agriculture and the organic agriculture development according to the recent European Union strategies, such as the European Green Deal, the Farm to Fork strategy, and the European Biodiversity Strategy for 2030, which aim to increase the share of organic farming to 25% area of agricultural land in Europe by 2030. Our results give information about the traits of spring wheat varieties that are suitable for an organic system and food processing. The most resistant varieties to the threat of infection by *Fusarium* spp. were Waluta, Zadra, and Arabella. Mycotoxin contamination of the grain of two examined wheat varieties did not exceed maximum accepted levels. However, we observed that the colonization of grains by *Fusarium* spp. did not reflect the intensity of FHB; thus, the lack of symptoms of disease on ears does not mean the lack of grain infestation by mycotoxins. Therefore, there is a need for constant monitoring of phytosanitary condition of the canopy and wheat grain in organic farming. On the basis of the results of a 3 year study, the varieties most useful for organic production and processing were found to be Arabella, followed by Brawura, Izera, Kandela, Katoda, KWS Torridon, Waluta, and Zadra. The research results could be applied by farmers, advisors, and food processors that carry out crop production and processing in organic agriculture sector. Future research will focus on the suitability of other wheat varieties, in particular winter varieties, for organic farming and food processing.

**Author Contributions:** Conceptualization, B.F.-S., G.C.-P., L.L., K.G.; methodology, B.F.-S., G.C.-P., L.L., K.G., D.D.; validation, B.F.-S., G.C.-P., D.D.; investigation, B.F.-S., G.C.-P., L.L., K.G.; data

curation, B.F.-S., G.C.-P., L.L.; writing—original draft preparation, B.F.-S.; G.C.-P., L.L., K.G.; writing review and editing, B.F.-S., G.C.-P., L.L., D.D.; visualization, B.F.-S., G.C.-P., L.L.; supervision, B.F.-S., G.C.-P., D.D.; project administration, B.F.-S.; funding acquisition, B.F.-S., D.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** The study was supported by the Polish Ministry of Agriculture and Rural Development under the grant for the research on organic crop production No HORre-msz-078-23/16(243).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available upon request from the first author.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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