The Use of Effective Microorganisms as a Sustainable Alternative to Improve the Quality of Potatoes in Food Processing

Abstract

Background: The ecological approach to agriculture causes the desire to eliminate pesticides. Work is underway to replace them with natural agents. Aim: The aim of the research was to introduce an innovative factor and non-invasively increase the yield of dry matter and starch and thus improve the quality of the raw material for the production of potato-enriched products. Material and methods: The field experiment was carried out in central-eastern Poland, using the randomized sub-block method, in a dependent split-split-plot design in three repetitions. The superior factor of the first order was pre-planting treatments by treating seed potatoes with a microbiological preparation for (a) 10 min, (b) 15 min, and (c) untreated seed potatoes (untreated control). The second-order factor was 14 potato cultivars of all groups of earliness. Qualitative research was carried out under laboratory conditions. Results: Pre-planting treatments with the use of a microbiological preparation had a positive effect on the yield of dry matter and starch compared to the control while modifying the characteristics related to the quality of potato chips. The tested cultivars determined both the quantitative and qualitative characteristics of the chips to the greatest extent. Conclusions: Alternative solutions will allow the effective replacement of pesticides in potato production and processing.

1. Introduction

Biopreparations with effective microorganisms (EMs) are widely used in environmental protection, agriculture, the food industry, and medicine. They are very useful for conditioning seeds, seedlings, and tubers. They can be used by treating seeds or seed potatoes during the growing season, as well as applied to the soil [1,2,3,4,5,6]. Currently, EM biotechnology is used in such fields of agriculture as soil regeneration, plant production, animal production, the agri-food industry, and storage. Such versatile potential use of effective microorganisms is due to the high enzymatic specificity of microorganisms, enabling them to survive in diverse environments. EM technology is currently used in more than 140 countries on most continents, but the largest user is Brazil, where effective microorganisms have proven to be the most appropriate way to replace traditional management methods with natural methods. This reduces the burning and clearing of the Amazon jungle. Thanks to EM technology, farmers around the world can increase the quantity and quality of crops without affecting the environment [7,8,9]. Some biopreparations, e.g., containing Bacillus thuringiensis, are produced on a fair scale using fermenters with a volume of 100,000 m³ [10]. The use of effective microbiologically active solutions (EMASs) has been tested in Japan, China, Malaysia, Russia, Poland, the Czech Republic, Romania, etc., depending on the location and geographical conditions. The main purpose of these technologies is to improve the quality of water, soil, and food [1,3,4,5,11,12,13,14,15,16,17,18]. Thus, they become a tool for correcting and supervising various ecosystems. EM biopreparations are used comprehensively in plant cultivation to vaccinate the soil before sowing or planting plants. They are recommended for use in the form of spraying on catch crops, stubble, and manure before plowing, for treating seeds, tubers, and rhizomes, and directly or foliarly on plants [14,15,18]. Significant production effects are also observed in the use of EM preparations to prepare high-class fertilizers, composts, and plant extracts as strong nutrients [19]. Useful microorganisms can be used to treat potato tubers, sugar beet, and red beet seedlings, carrots, parsley, parsnips, celery, spring onions, and asparagus stumps, as well as the bulbs and rhizomes of ornamental plants. EM preparations consist of groups of microorganisms with different functions, between which there is a constant exchange of nutrients, which promotes their symbiosis. In addition, the EM formulation contains a sugar-based medium (cane molasses) that provides a low pH value. All microorganisms used in this preparation occur naturally in nature. Some types and species of microorganisms are isolated from the soil, others are obtained from the rumen of cows. There are no genetically modified organisms among them, and their reproduction and breeding are carried out in properly controlled conditions. The most famous products from this group are the so-called effective microorganisms (EMs) and their various modifications (EM1, EM5, Ema) [7]. EM preparations are live, beneficial microorganisms for which there is no withdrawal period [20,21,22]. In cultivation, they are used to reduce or completely eliminate the use of chemical plant protection products against crop diseases and pests, as well as during storage in cold stores and warehouses [23,24]. The recently growing demand for biopreparations is related to the development of ecological methods of plant cultivation, including biodynamic and organic farming [25,26,27]. Wu et al. [13] drew attention to the effects of inoculating crops with plant growth-promoting bacteria and endophytes, especially arbuscular mycorrhizal fungi (AMF), as well as the potential use of these microorganisms in creating a sustainable potato cultivation system. However, the direct effect of using EMs in agriculture is an increase in yields and their quality [8,17]. In Europe, this technology is becoming more and more common at the level of individual farms, especially organic farms [5,8,13,28]. Therefore, the conducted research was aimed at introducing an innovative factor aimed at a non-invasive possibility of increasing the yield and improving its quality. The aim of the study was to assess the possible impact of the EM Farma preparation and the length of exposure to this preparation on its ability to improve physiological indicators and thus improve the quality of the raw material for the production of potato-enriched products. In addition, the purpose of the research was to assess the suitability of potatoes produced with this technology for consumption and processing. For this purpose, the conducted research determined the effect of microbiological preparations on genotypic properties and found the cultivar best suited for food processing for refined products, mainly crisps. Therefore, an alternative research hypothesis was put forward that dressing seed potatoes with a potentially probiotic preparation can improve the quality of the raw material for food processing against the null hypothesis that the use of these preparations will not affect this raw material.

2. Material and Methods

The research results were based on a field experiment carried out in 2017–2019 in Parczew (51°38′24″ N; 22°54′02″ E) in Central-Eastern Poland. The experiment was set up using the randomized subblock method in a split-split-plot design in three repetitions. The 1st-order factor was dressing in an aqueous solution of the EM Farming preparation: (a) 10 min exposure, (b) 15 min exposure, (c) control facility with the soaking of seed potatoes in distilled water. The second order factor was 14 potato cultivars, all earliness groups. The experiment was set up on lessive soil, made of sandy loam; World Reference Base for Soil Resources (WRB) [29].

2.1. Characteristics of Potato Cultivars

Fourteen potato cultivars of all earliness groups were tested in the study: ‘Denar’ (very early), ‘Bellarosa’, ‘Star’, ‘Ignacy’, ‘Ovation’, ‘Vineta’ (early), ‘Finezja’, ‘Oberon’, ‘Satina’, ‘Typhoon’ (mid-early), ‘Jelly’, ‘Mondeo’, ‘Syrena’ (mid-late), and ‘Kuras’ (late). Their morphological and consumer characteristics are presented in

Table 1. Description of the potato cultivars grown in the experiment.

Cultivars	Maturity Group	Color of Skin	Color of the Flesh	Shape of the Tubers	Depth of the Tuber Eyes at 9° Scale *
‘Denar’	Very early	Yellow	Light yellow	Round oval	7.0
‘Bellarosa’	Early	Red	Yellow	Round oval	7.0
‘Gwiazda’	Early	Yellow	Yellow	Round oval	7
‘Ignacy’	Early	Yellow	Light yellow	Round oval	6.5
‘Owacja’	Early	Yellow	Light yellow	Round oval	7.0
‘Vineta’	Early	Yellow	Yellow	Round	7.0
‘Finezja’	Medium-early	Yellow	Light yellow	Round oval	7.0
‘Oberon’	Medium-early	Red	Light yellow	Oval	7.0
‘Satina’	Medium-early	Yellow	Yellow	Round oval	7.5
‘Tajfun’	Medium-early	Yellow	Yellow	Oval	7.0
‘Jelly’	Medium-late	Yellow	Yellow	Oval	7.5
‘Mondeo’	Medium-late	Yellow	Creamy	Round oval	7.0
‘Syrena’	Medium-late	Yellow	Yellow	Oval	7.0
‘Kuras’	Late	Yellow	Creamy	Round	6.0

* Depth of the tuber meshes (in the 9° scale): 1°—very deep, 9°—very shallow.

.

2.2. Characteristics of the EM Farming Preparation

The EM Farming preparation was used in the experiment to treat seed potatoes. EM Farming is a yellow-brown liquid with a pH of 3.0–3.5 that includes many strains of common microorganisms. The microbiological composition of EM Farming is protected by patent law and is a trade secret. Therefore, no detailed information is provided on the detailed composition of EM Farming. This formulation is based on effective microorganism (EM) technology, which involves the use of a blend of beneficial microorganisms such as various strains of lactic acid bacteria, yeasts, and other microorganisms to improve soil health, plant growth, and overall ecosystem balance. This product has the Attestation No. PZH/HT-3112/2016 EmFarma Plus and has been positively assessed by the Department of Toxicology and Risk Assessment of the National Institute of Public Health-National Institute of Hygiene in terms of safety for people and the environment, provided that it is used in accordance with its intended use and recommendations given on the label or in the instructions for use. Preparation of the preparation for the dressing of seed potatoes consisted of diluting it with non-chlorinated water. The EM Farming preparation was used at the concentration recommended by the manufacturer [10].

2.3. Field Studies

Potatoes were grown in the stand after winter triticale. After harvesting the forecrop, stubble cultivation was carried out and tended (twice harrowing), then manure in an amount of 30 t ha⁻¹ was brought in in autumn and plowed with deep plowing. In spring, the field was leveled (sweeping) and mineral fertilization was applied in the following amounts: 450 kg NPK ha⁻¹ (1:1:1.5) 90 kg N, 90 kg P, 135 kg K ha⁻¹. All fertilizers were applied once before planting and mixed with the soil using a cultivation unit. Nitrogen was used in the form of 46% urea, while the remaining amounts of nitrogen were used in the form of polyfoska 6-20-30 (NPK). Qualified, class A-potato propagating material was planted manually at the end of April at a spacing of 67.5 × 37 cm. The size of the plots for harvest was 15 m². Care treatments were performed in accordance with the requirements of Good Agricultural Practice. Weeds were destroyed by mechanical and chemical methods. Mechanical tillage treatments were applied to potato emergences and consisted of single hoeing and double hoeing. Plateen 41.5 WG (2.0 kg ha^–1) was applied just before emergence, and Targa Super 050 EC (1.5 dm ha^–1) was used in the 2–3 leaf stage of single-walled weeds. After that, no further care was carried out. During the growing season, the Colorado potato beetle was controlled by performing two to three treatments with available preparations against this pest (Proteus 110 OD at a dose of 0.4 dm ha⁻¹, Actara 25 WG at a dose of 0.08 kg ha⁻¹, Calypso 480 SC at a dose of 0.1 dm ha⁻¹). These sprayings were combined with the control of late blight with the following preparations: Infinito 687.5 SC in a dose (1.6 dm ha⁻¹), Ridomil Gold 67.8 WG in a dose (2.0 kg ha^–1), Pyton Consento 450 SC in a dose (2.0 dm ha^–1), and Acrobat MZ 69 WG in the dose (2.0 kg ha^–1).

2.4. Collection and Taking Samples for Qualitative Research

Potato harvesting was carried out in earliness groups depending on the maturity date. Very early and early cultivars were harvested at the end of August; medium-early and medium-late cultivars around September 15; and late cultivars at the end of September. The total yield of tubers was estimated at the time of harvest. Immediately after harvest, tuber samples were taken from each plot for the determination of dry matter—30 medium-sized tubers from each field repetition. Samples for the determination of starch content were taken from each medium-sized field replicate. Samples for assessing the quality of chips, in the amount of 20 tubers from each field replication, were taken immediately after harvest. These tubers were 5–6 cm in diameter, not green, and undamaged [30].

2.5. Determination of Content and Yield of Dry Matter and Starch

After harvesting, the dry matter content of tubers was determined using the drying-weighing method. Before determining the dry matter, the tubers were washed in cold water, then drained and dried from water at ambient temperature. These analyses were performed in triplicate for each sample. The glass weighing bottle was dried in a dryer at 105 °C for about 2 h, then it was cooled down to room temperature (about 30 min) and then weighed with an accuracy of 0.001 g. Then, the crushed plant material was poured into the dish. The dish, together with fresh, shredded plant material, was placed in a dryer and dried at 60 °C for about 20 h, and then for 2 h at 105 °C. After that, the dish with the dry mass of the sample was placed in the desiccator and then weighed. Drying was considered complete when the difference between two successive weighings did not exceed 0.001 g. The sample obtained in this way was the basis for calculating the dry matter content [31]. The starch content was determined using the Evers polarimetric method [32]. This method is based on measuring the change in the polarization of polarized light as it passes through a starch-containing solution. Starch hydrolysis was carried out in a boiling water bath, and then the protein was precipitated with phosphoric acid. The reading of the starch content was made on the automatic polarimeter Polamat S. Throughout the process of determining the dry matter and starch in potato tubers, good laboratory practices and procedures were followed to obtain accurate results.

2.6. Chip Quality Determination

The chips were made from potato tubers using the single-stage frying method. After manual peeling and rinsing, the tubers were mechanically cut into slices 1.0–1.2 mm thick. After rinsing the potato slices with cold water to remove free starch, the slices were dried, then centrifuged and fried in rapeseed oil at 170 °C in one step until the moisture content was below 2%. Immediately after frying, the color, taste, general appearance of the chips, and their defects, i.e., discoloration and so-called wet places, were assessed. The assessment of the color of the chips was carried out on a 9° scale using the ‘Cards colour’ chart developed by the European Potato Research Association in Wageningen, where 9°—light color; 8°—golden color; 7°—light golden color; 6°—dark golden color; 5°—brown-gold color; 4°—brown color; 3°—dark brown color; 2°—brown color; and 1°—burnt, brown-black color. The desired color of the chips was in the range of 6–9° on a scale of 9°. In addition, a visual and organoleptic evaluation of the chips was made on a 5-point scale, where 5.0–4.5° means a very good result; 4.4–4.0—good; 4.0–3.0°—satisfactory; and 3.0–1.0°—unsatisfactory [33]. The intensity of the visual-taste-smell profiles of the chips was performed by a 10-person team meeting the formal conditions and experienced in the consumer evaluation of potato cultivars, testing in terms of sensory predispositions, in accordance with PN-A-94001 [34]. The fat content in the chips was determined by the Soxhlet method [35].

2.7. Methodology of Soil Sample Evaluation

The physicochemical and chemical properties of the soil collected before the experiment were carried out in accordance with the applicable standards, using the following methods: soil granulometric composition—by laser method [36]; soil reaction—pH in 1 M KCl—electrometrically according to ISO 10390:2005 [37]; and organic carbon content (Corganic)—using the Tiurin method [38]. On this basis, the content of humus in the soil was determined. The content of assimilable P₂O₅ and K₂O forms was determined by the Egner–Riehm method [39,40], the abundance of the soil in assimilable magnesium was determined by the Schachtschabel method [41], and the content of Cu, Mn, Zn, Fe, and B was determined in 1mol of HCl [42,43,44] by atomic absorption spectrometry (AAS). Determination of microelements in solutions was carried out in the Central Research Laboratory of the University of Life Sciences in Lublin on the FAST AAS 280 FE sequential atomic absorption spectrometer, VARIAN company, Melbourne, Australia.

2.8. Soil Conditions

The physical and chemical properties of the soil are presented in

Table 2. Physical and chemical properties of soil in Parczew, Poland (2017–2019).

Year	Content of Assimilable Macronutrients (mg kg−1 Soil)			Content of Humus [%]	pH KCl	Content of Micronutrients (mg kg−1 Soil)
	P2O5	K2O	Mg			Cu	Mn	Zn	Fe	B
2017	207	121	75	0.99	6.10	5.72	311	41.3	3822	6.23
2018	193	111	70	1.04	5.92	4.80	319	50.5	3726	5.74
2019	221	114	68	1.00	5.77	7.98	265	43.2	3676	6.00
Average	207	115	71	1.01	5.93	6.17	298	45.0	3741	5.99

Source: Own experiment results, obtained in the Central Research Laboratory of the University of Life Sciences in Lublin.

.

The experiment was carried out on lessive soil, made of light loamy sands, weak rye complex, valuation class IVb [45]. The content of humus in the arable layer of the soil was low and amounted to 1.01%. The soil reaction was slightly acidic (5.93 pH in 1 mol KCl). This soil was characterized by a very high abundance of assimilable phosphorus, low in potassium, very low in magnesium (PN-R-04020:1994/Az1:2004), and low in boron (PN-93/R-04018) and iron (PN-R-04018). R-04021).

2.9. Meteorological Conditions

Meteorological conditions in the years of research turned out to be varied. The year 2017 can be considered a wet year, characterized by an optimal supply of water to potatoes, but in May, a significant excess of water was observed. In 2018, only in April and May, an excess of precipitation was observed, while in June, July, and August, there was a significant shortage. The hydrothermal coefficient for September was 2.8, but this rainfall had no effect on the accumulation of potato yield. In 2019, in the first four months of the growing season (April–July), optimal water supply was noted, while the end of the growing season (August–September) was one of the least favorable, with a large rainfall deficit (

Table 3. Rainfall, air temperature, and the hydrothermal coefficient of Sielianinov during the growing season of potatoes, according to the meteorological station in Uhnin, 2017–2019.

Month	Rainfall (mm)			Air Temperature (°C)			Hydrothermal Coefficient of Sielianinov *
	2017	2018	2019	2017	2018	2019	2017	2018	2019
April	43.0	61.8	47.1	11.1	8.8	10.0	1.3	2.3	1.6
May	141.4	120.3	47.9	14.7	12.8	15.3	3.1	3.0	1.0
June	85.2	46.7	87.3	15.9	16.7	19.1	1.8	0.9	1.5
July	69.7	45.2	114.1	21.1	19.4	20.5	1.1	0.8	1.8
August	95.8	6.1	41.0	19.2	21.4	19.5	1.6	0.1	0.7
September	19.6	130.2	11.8	14.6	15.5	15.5	0.4	2.8	0.3
Total	454.7	410.3	349.2	-	-	-	-	-	-

* Coefficient was calculated according to the formula: $k=\frac{10P}{{\displaystyle \sum t}}$. Skowera [46]; where: P—the sum of the monthly precipitation in mm; Σt—monthly total air temperature > 0 °C. Ranges of values of this index were classified as follows: extremely dry, k ≤ 0.4; very dry, 0.4 < k ≤ 0.7; dry, 0.7 < k ≤ 1.0; rather dry, 1.0 < k ≤ 1.3; optimal, 1.3 < k ≤ 1.6; rather humid, 1.6 < k ≤ 2.0; wet, 2.0 < k ≤ 2.5; very humid, 2.5 ≤ k ≤ 3.0; extremely humid, 3.0 > k.

).

2.10. Statistical Calculations

The obtained results were subjected to exact variance (ANOVA), SAS 9.2 2008 [47], and multiple Tukey’s t-tests at the significance level of p_0.05. Multiple comparisons tests of Tukey’s t-tests enable a detailed comparison of mean values by statistically separating individual starting groups of quantities (groups of ‘a’, ‘b’, and ‘c’ sizes) and determining a smaller difference in mean values, which are marked as HSD [48]. In order to determine the share of individual sources of variability and their interactions in the total variability of the examined features, the evaluation of variance components was carried out. The empirical mean square values from the analysis of variance were compared with their expected values. In this way, the estimation of variance components used in individual sources of variability was obtained. Determining the relationship between the assessments of variance components and their percentage structure made it possible to use the assessment of the influence of cultivars and years on the change in dry matter, starch, yield, and the quality characteristics of chips. The study also analyzed a simple Pearson correlation of the obtained test results [48].

3. Results

3.1. Content and Yield of Dry Matter

Pre-planting treatments, in the form of treating tubers with an aqueous solution of EM Farming, and years of research did not have a significant effect on the dry matter content of tubers. Only a tendency to increase the dry matter content of tubers was observed under the influence of exposure to EM Farming in relation to the control object. However, these impacts on the tubers caused a significant increase in the yield of dry matter per area unit, compared to the control object (

Table 4. Dry matter content and yield of tubers (mean 2017–2019).

Experimental Factors		Content of DM (%)	Yield of DM (t.ha−1)
Pre-treatment treatments	Control object	20.2 a	7.57 b
	Exposition I *	20.4 a	9.53 a
	Exposition II **	20.6 a	9.28 a
	HSDp0.05	ns ***	0.42
Cultivars	‘Denar’	16.3 d	7.98 b
	‘Bellarosa’	18.0 c	6.88 c
	‘Gwiazda’	16.5 d	7.35 b
	‘Ignacy’	18.0 c	8.79 b
	‘Owacja’	17.7c	6.56 c
	‘Vineta’	19.3 c	7.86 b
	‘Finezja’	23.9 b	9.56 b
	‘Oberon’	20.8 b	8.26 b
	‘Satina’	21.5 b	10.33 a
	‘Tajfun’	23.0 b	9.88 b
	’Jelly’	20.2 b	8.31 b
	’Mondeo’	22.1 b	10.49a
	’Syrena’	21.0 b	9.42 ab
	’Kuras’	28.0 a	11.41 a
	HSDp0.05	3.8	1.97
Years	2017	20.1 a	9.10 b
	2018	20.7 a	7.35 c
	2019	20.3 a	9.89 a
	HSDp0.05	ns ***	0.42
Mean		20.4	8.79

* 10 min exposure; ** 15 min exposure, *** no significant differences at the level of p_0.05.; Letter indicators (a, b, c, etc.) next to the averages refer to the so-called homogeneous (statistically homogeneous) groups. The occurrence of the same letter indicator next to the means (at least one) means that there were no statistically significant differences at p_0.05 between them.

).

The genetic properties of the tested cultivars most strongly modified both the content and yield of tuber dry matter. The ‘Kuras’ cultivar was characterized by the highest content and yield of tuber dry matter. The second homogeneous group in terms of this feature included the following cultivars: ‘Finezja’, ‘Oberon’, ‘Satina’, ‘Tajfun’, ‘Jelly’, ‘Mondeo’, and ‘Syrena’. The third homogeneous group with a slightly lower content of tuber dry matter included ‘Bellarosa’, ‘Ignacy’, ‘Ovation’, and ‘Vineta’. The lowest tuber dry weight was recorded in cultivars ‘Denary’ and ‘Star’. The yield of dry matter was also significantly affected by the characteristics of the tested cultivars; the tested cultivars were grouped in terms of the amount of this feature in four homogeneous groups. The first group, with the highest dry matter yield, included ‘Satina’, ‘Mondeo’, and ‘Kuras’. Only one cultivar, ‘Syrena’, was included in the second homogeneous group. The third group, with lower tuber dry matter yield, included the following cultivars: ‘Denar’, ‘Gwiazda’, ‘Ignacy’, ‘Vineta’, ‘Finezja’, ‘Oberon’, ‘Tajfun’, and ‘Jelly’. The lowest yield of dry matter per area unit was accumulated by cultivars of the fourth homogeneous group: ‘Bellarosa’ and ‘Owacja’ (Table 4).

Meteorological conditions in the years of the study did not significantly affect the dry matter content, but they had a significant impact on the accumulation of dry matter yield. The highest value of this feature was recorded in 2019 and the lowest in 2018 (Table 4). The tested cultivars responded significantly to the conditions in the study years (Figure 1). The greatest difference in the dry matter content between the years of the study was noted in the case of cultivars ‘Gwiazda’ and ‘Kuras’. In the case of the remaining cultivars, these differences turned out to be insignificant.

3.2. Starch Content and Yield

Pre-planting treatments, in the form of treating tubers in an aqueous solution of the EM Farming microbiological preparation, did not significantly affect the starch content, but a positive tendency to increase the starch concentration in tubers was observed in both exposures to pre-planting treatments. However, in the case of starch yield, statistical calculations confirmed a significantly higher starch yield per area unit in the objects with replanting treatments in relation to the control object without seed potato dressing; both of these objects turned out to be homogeneous in terms of the value of this feature (

Table 5. Starch content and yield (mean 2017–2019).

Experimental Factors		Starch Content (%)	Yield of Starch (t·ha−1)
Pre-treatment treatments	Control object	15.2 a	5.73 b
	Exposition I *	15.4 a	7.15 a
	Exposition II **	15.4 a	6.96 a
	HSDp0.05	ns ***	0.33
Cultivars	‘Denar’	12.4 c	6.05 b
	‘Bellarosa’	13.8 c	5.23 c
	‘Gwiazda’	13.3 c	5.71 b
	‘Ignacy’	13.6 c	6.63 b
	‘Owacja’	13.8 c	5.02 c
	‘Vineta’	14.5 bc	5.92 b
	‘Finezja’	18.0 a	7.20 a
	‘Oberon’	15.6 b	6.21 b
	‘Satina’	15.7 b	7.66 a
	‘Tajfun’	17.4 ab	7.46 a
	’Jelly’	14.8 bc	6.17 b
	’Mondeo’	16.2 b	7.82 a
	’Syrena’	15.5 b	7.05 a
	’Kuras’	20.3 a	8.48 a
	HSDp0.05	2.9	1.54
Years	2017	15.1 b	6.84 b
	2018	15.7 a	5.57 c
	2019	15.2 b	7.43 a
	HSDp0.05	0.6	0.33
Mean		15.4	6.61

* 10 min exposure; ** 15 min exposure; *** no significant differences at the level of p_0.05.; Letter indicators (a, b, c, etc.) next to the averages refer to the so-called homogeneous (statistically homogeneous) groups. The occurrence of the same letter indicator next to the means (at least one) means that there were no statistically significant differences at p_0.05.

).

The factor that significantly determined both the starch content in the fresh weight of tubers and its yield per unit was cultivars. The highest starch content was found in the mid-late cultivar ‘Kuras’ and the medium-early ‘Finezja’ cultivar turned out to be homogeneous in terms of the value of this feature. In the second homogeneous group, due to starch content, were the cultivars ‘Mondeo’, ‘Satina’, ‘Oberon’, and ‘Syrena’. In the third homogeneous group were the cultivars ‘Denar’, ‘Bellarosa’, ‘Gwiazda’, ‘Ignacy’, and ‘Owacja’, and the fourth homogeneous group included ‘Vineta’ and ‘Jelly’. The relationships between cultivars changed slightly in the case of starch yield, where the highest value of this feature was obtained by the cultivars ‘Kuras’, ‘Mondeo’, ‘Satina’, ‘Finezja’, and ‘Syrena’. The second homogeneous group included the cultivars ‘Ignacy’, ‘Denar’, ‘Oberon’, ‘Gwiazda’, ‘Vineta’, and ‘Jelly’. The third homogeneous group, in terms of starch yield, were cultivars ‘Bellarosa’ and ‘Owacja’ (Table 5).

Years of research had a significant impact on both the starch content and the yield of this component in tubers. The highest starch content was found in tubers harvested in 2018, and the highest starch yield was recorded in 2019 (Table 5). The highest starch yield in the last year resulted from the fact that the starch yield is the result of the starch content and the total yield of tubers, which was the highest in 2019. The yield of tubers depends on many factors, such as rainfall, sunlight, temperature, humidity, soil quality, fertilization, and the selection of cultivars.

3.3. Quality of Chips

Chips were produced from the tubers obtained from the field experiment. Their qualitative characteristics are presented in

Table 6. Influence of technology, cultivars, and years of cultivation on the quality of chips.

Experiment Factors		Color (Scale 9°)	Organoleptic Assessment (Scale 5°)	Visual Assessment (5° Scale)	Moisture (%)	Wet Places (%)	Fat Content (%)
Pre-planting treatments	Control object	7.90 a	4.20 a	4.00 a	2.10 b	1.90 c	25.90 a
	Exposition I	7.90 a	3.60 b	3.70 b	2.20 a	3.60 a	21.70 b
	Exposition II	7.90 a	3.60 b	3.70 b	1.90 c	2.30 b	21.91 b
	HSDp0.05	ns *	0.19	0.20	0.10	0.13	1.16
Cultivars	‘Denar’	7.80 a	3.67 bc	3.78 b	2.06 bc	3.44 d	27.44 a
	‘Bellarosa’	7.76 a	2.89 d	3.00 c	2.58 a	6.56 a	24.89 a
	‘Gwiazda’	7.63 a	3.72 b	3.39 c	2.64 a	5.00 c	24.01 a
	‘Ignacy’	8.08 a	3.17 c	3.94 b	2.39 ab	2.56 e	23.55 b
	‘Owacja’	6.93 bc	3.89 b	3.94 b	1.89 c	1.67 f	24.65 a
	‘Vineta’	8.26 a	3.89 b	4.11 b	2.11 b	1.67 f	21.92 b
	‘Finezja’	8.09 a	3.83 b	4.00 b	2.44 a	1.06 g	21.24 b
	‘Oberon’	7.68 a	3.83 b	3.67 bc	1.67 c	1.33 g	23.16 b
	‘Satina’	8.54 a	4.50 a	4.22 ab	1.50 d	0.00 i	21.05 b
	‘Tajfun’	7.53 b	3.33 c	3.17 c	2.17 b	3.33 d	21.20 b
	‘Jelly’	8.71 a	4.89 a	4.89 a	1.60 d	0.56 h	21.05 b
	‘Mondeo’	7.94 a	4.06 b	3.83 b	2.17 b	3.22 d	23.67 b
	‘Syrena’	8.11 a	4.00 b	3.72 b	1.67 d	0.56 h	23.02 b
	‘Kuras’	7.58 b	3.56 c	3.50 c	2.11 b	5.44 b	23.50 b
	HSDp0.05	1.13	0.60	0.63	0.34	0.43	4.02
Years	2017	8.06 a	4.05 a	4.01 a	2.24 a	2.85 a	23.56 a
	2018	7.67 a	3.51 c	3.61 b	1.88 b	2.02 b	22.07 b
	2019	7.96 a	3.84 b	3.78 b	2.17 a	2.93 a	23.89 a
	HSDp0.05	ns *	0.19	0.20	0.10	0.13	1.16
Mean		7.90	3.80	3.80	2.07	2.60	23.17

ns * differences insignificant at the level of p_0.05.; Letter indicators (a, b, c, etc.) next to the averages refer to the so-called homogeneous (statistically homogeneous) groups. The occurrence of the same letter indicator next to the means (at least one) means that there were no statistically significant differences at p_0.05.

.

Pre-planting treatments applied in the form of dressing tubers in an aqueous solution of EM Farming and years of research did not have a significant effect on the color of chips. It turned out to be an extremely stable feature (V = 96%) related only to the genetic features of the tested cultivars. The brightest color was found in chips made from ‘Jelly’ tubers, and the darkest chips were made from ‘Tajfun’ and ‘Kuras’ tubers; the cultivars ‘Denar’, ‘Bellarosa’, ‘Gwiazda’, ‘Ignacy’, ‘Vineta’, ‘Finezja’, ‘Oberon’ ‘Satina’, ‘Jelly’, ‘Mondeo’, and ‘Syrena’ did not differ significantly in relation to the value of this trait from the best cultivars (Table 6).

Potato exposure to EM Farming, regardless of the length of application, contributed on the one hand to the deterioration of their organoleptic and visual evaluation, and on the other hand, significantly reduced the number of wet spots on chips and contributed to a significant reduction in fat absorption by chips compared to the control object. The moisture content of chips depended on the length of tuber exposure to pre-planting treatments. Longer exposure significantly lowered the humidity of the chips compared to the control, as did the shorter exposure of tubers to EM Farming (Table 6). The genetic properties of the tested cultivars shaped the quality of potato chips to the greatest extent. The organoleptic evaluation of chips is a measure of their sensory quality, i.e., how the product looks, tastes, and smells. However, the organoleptic assessment is subjective and based on the individual sensory perceptions of the person making the assessment. During the organoleptic evaluation of chips, several factors are usually considered, such as appearance, texture, taste, smell, and overall quality of the taste sensation. For example, chips with a golden, even color and a crunchy texture, with a taste and smell in accordance with the manufacturer’s declaration, will receive a high organoleptic rating. On the other hand, chips with an unpleasant odor, too soft or too hard a consistency, or with defects in appearance will receive a lower rating. This divides the tested cultivars into four homogeneous groups, and the best-quality group of cultivars included only two cultivars: ‘Jelly’ and ‘Satina’; however, the ‘Jelly’ cultivar received a higher score. The second homogeneous group consisted of the cultivars ‘Syrena’, ‘Mondeo’, ‘Oberon’, ‘Finezja’, ‘Vineta’, ‘Owacja’, and ‘Gwiazda’. The third homogeneous group, in terms of the value of this trait, were the cultivars ‘Ignacy’, ‘Tajfun’, and ‘Kuras’. The early cultivar ‘Bellarosa’ obtained the lowest organoleptic score. In terms of visual evaluation, the highest score was awarded to the cultivar ‘Jelly’, only half a degree lower was awarded to the cultivar ‘Satina’, and the second homogeneous group included the following cultivars: Vineta’, ‘Finezja’, ‘Denar’, ‘Ignacy’, ‘Owacja’ ‘, ‘Mondeo’, and ‘Syren’. The third, homogeneous group consisted of cultivars ‘Bellarosa’, ‘Gwiazda’, ‘Tajfun’, and ‘Kuras’, and ‘Oberon’ was in the intermediate group (bc), as was ‘Satina’ (ab) (Table 6).

In terms of the moisture content of chips, the tested cultivars were divided into four homogeneous groups. Chips produced from the cultivars ‘Satina’, ‘Jelly’, and ‘Syrena’ turned out to be the least moist. In the second homogeneous group, in terms of the value of this feature, were the cultivars ‘Oberon’ and ‘Owacja’. Chips made from cultivars ‘Mondeo’, ‘Kuras’, and ‘Vineta’ were more moist, and chips made from cultivars: ‘Gwiazda’ and ‘Bellarosa’ were the moistest. Chips from the ‘Denar’ and ‘Ignacy’ cultivars were included in the intermediate groups (bc) and (ab), respectively.

In terms of moist spots in chips, the greatest varietal diversity was observed and as many as eight homogeneous groups were distinguished. A lack of moist spots was not observed only in the chips produced from the ‘Satina’ cultivar; the second place in this respect was taken by the cultivars ‘Jelly’ and ‘Syrena’; the next homogeneous groups were: Finezja’ and ‘Oberon’; ‘Ovation’ and ‘Vineta’; ‘Ignatius’; ‘Typhoon’, ‘Mondeo’, and ‘Denar’; ‘Star’; ‘Kuras’; and the last place in terms of the value of this feature was taken by the early cultivar ‘Bellarosa’.

In terms of fat content in chips, only two homogeneous groups were distinguished: the group of cultivars absorbing less fat when frying chips included ‘Ignacy’, ‘Vineta’, ‘Finezja’, ‘Oberon’, ‘Satina’, ‘Tajfun’, ‘ Jelly’, ‘Mondeo’, ‘Syrena’, and ‘Kuras’. The remaining cultivars were in the group that absorbed significantly more fat during frying, which was associated with a deterioration in the quality of chips and higher fat consumption (Table 6).

Meteorological conditions in the years of research had a significant impact on all quality features of this product, except for color. The best scores for the quality of chips, in terms of organoleptic and visual evaluation, humidity, moist places, and fat absorbency, were obtained in 2017, which was optimal in terms of temperature and precipitation. The value of chips in the remaining years (2018 and 2019) turned out to be homogeneous. These years were characterized by abnormal weather conditions.

3.4. Variability of Features and Their Contribution to the Total Variance

The structure of the variance components indicates a different share of years, cultivars, cultivation technologies, and their interactions in the total variability of each of the studied traits (

Table 7. The impact of individual sources of variability and the percentage share of variance in the total variance of some quantitative and qualitative characteristics of potatoes.

Specification	Significance of Effect							Percentage Contribution of the Variance of Total Variance
	Year	Treatment	Cultivar	Year x Treatment	Year x Cultivar	Treatment x Cultivar	T x Y x C	Year	Treatment	Cultivar	Year x Treatment	Year x Cultivar	Treatment x Cultivar	T x Y x C
Content of DM (%)	ns **	ns	**	ns	ns	ns	ns	6.9	7.7	37.7	13.0	18.1	17.8	3.2
Content of starch (%)	**	ns	**	ns	ns	ns	ns	23.3	6.2	18.6	25.3	18.5	9.2	2.1
Yield of DM (t ha−1)	**	**	**	*	ns	ns	ns	19.5	20.5	24.4	15.9	6.8	7.9	6.2
Yield of starch	**	**	**	*	*	ns	ns	16.3	16.4	32.8	30.6	15.6	6.8	0.9
Color (scale 9°)	ns	ns	**	ns	ns	ns	ns	16.5	14.5	40.3	9.1	8.0	6.5	4.9
Organoleptic ass. (scale 5°)	**	**	**	ns	ns	ns	ns	25.7	18.8	29.4	12.9	5.3	7.0	1.6
Visual assessment (5° scale)	**	**	**	ns	ns	ns	ns	16.9	17.4	32.2	18.7	8.1	4.0	2.1
Moisture (%)	**	**	**	ns	ns	ns	ns	33.7	14.6	23.4	12.8	7.9	7.1	2.4
Wet places (%)	**	*	**	*	ns	ns	ns	35.4	11.9	29.9	13.6	7.4	6.9	1.7
Fat content (%)	**	*	**	ns	ns	ns	ns	23.1	12.1	39.2	13.1	5.8	6.1	1.1

*—significant at p_0.05, **—significant at p_0.01, ns—not significant at p_0.05.

). The dominant role in the variability of total dry matter, starch, the color of chips, their organoleptic and visual assessment, and the fat content in this product was played by genotypic variability. The percentage share of the value of this feature in the total variance ranged from 18.6 to 40.3%. In the case of the humidity of the chips and moist places in the chips, environmental variability was the dominant source (Table 7).

The descriptive characteristics of the dry matter, starch, yield, and physicochemical properties of the chips are presented in

Table 8. Descriptive statistics of the content of dry matter, starch, yield, and quality characteristics of chips.

Specification	x1	x2	x3	x4	x5	x6	x7	x8	x9	x10
Mean	20.38	8.79	15.36	6.61	7.90	3.80	3.80	2.07	2.60	23.17
Median	20.13	8.74	15.10	6.57	7.87	3.83	3.81	2.11	2.11	23.33
Standard deviation	3.00	2.54	2.18	1.86	0.43	0.49	0.45	0.25	0.93	1.75
Kurtosis	0.48	−0.46	0.44	−0.50	0.13	0.24	0.54	−1.12	−0.74	0.22
Skewness	0.68	0.26	0.69	0.25	−0.16	0.32	0.44	−0.04	0.58	0.69
Range	14.53	11.55	10.90	8.60	1.78	2.00	1.89	1.14	6.56	6.39
Minimum	14.53	3.78	10.90	2.90	6.93	2.89	3.00	1.50	0.00	21.05
Maximum	29.07	15.33	21.80	11.50	8.71	4.89	4.89	2.64	6.56	27.44
Coefficient of variation (%)	14.70	28.85	14.22	28.12	5.50	12.85	11.93	12.07	35.78	7.55

x1—dry matter content (%); x2—yield of dry matter (t·ha⁻¹); x3—starch content (%); x4—starch yield (t·ha⁻¹); x5—color of chips (9° scale); x6—organoleptic assessment of chips (on a scale of 5); x7 (visual assessment of chips (5° scale); x8—moisture content of chips (%); x9—moist places (%); x10—fat content in chips (%).

.

The median is a measure of the location of the sample that divides it into two equal parts. The median is the middle value that is separated from the other observations by half of the sample. This means that 50% of the sample values are greater than and 50% less than the median. The median is used as an alternative measure of the central tendency to the arithmetic mean when the sample contains extreme values or when the distribution of sample values is skewed. This indicator of statistical characteristics is less sensitive to extremes than the mean because it does not depend on the value of each observation but depends only on the position of the value in the sample (Table 8).

The standard deviation is expressed in the same units as the sample values for ease of interpretation. The larger the standard deviation, the greater the dispersion of the data in the sample, i.e., the more they are distributed around the mean. On the other hand, the smaller the standard deviation, the lower the variability in the sample. The standard deviation allowed us to easily determine how much the results differ from the mean value (Table 8).

Kurtosis is a measure of the shape of a sample distribution that measures how much the distribution is flattened or conical compared to a normal distribution. Kurtosis compares the tails (that is, the areas at the ends of the distribution) with the density near the center. The kurtosis is the fourth standardized moment of the sample and tells us how ‘pointy’ or ‘flat’ the distribution is. The kurtosis value of the normal distribution is 3, which means that it is ‘neutral’ and is neither flat nor a cone. Kurtosis values greater than 3 mean the distribution is more conical in shape, and less than 3 means that the distribution is flatter. Positive kurtosis values mean that the distribution is more centered around the mean, and the tails are longer and thicker, which may indicate a greater concentration of values around the mean. Negative values of kurtosis (in our research, these are: dry matter and starch yield, the moisture content of chips, and moist places in chips) mean that their distribution is more flattened, which may indicate greater variability in the data or the presence of extreme values. Kurtosis is one measure of the shape of a distribution and is used to determine whether a sample is more flat or conical than a normal distribution.

Skewness is a measure of the asymmetry of the sample distribution, which is how much the distribution is shifted in one direction from the mean value. It also tells you whether the distribution is more concentrated around one side of the mean or the other. If the sample distribution is symmetric, the skewness is 0. However, if the values at one end of the distribution are more clustered than the other, then the distribution is skewed. Skewness can be positive or negative, depending on the direction of the asymmetry. Positive skewness means that the distribution is shifted to the right and the tails of the distribution are longer on the right side. The mean values are then lower than the median and outliers appear on the right. On the other hand, negative skewness (color and moisture of the chips) means that the distribution is shifted to the left, and the tails of the distribution are longer on the left side. The mean values are then higher than the median and outliers appear on the left. Skewness is one of the parameters characterizing the distribution of the sample and may affect the interpretation of the test results (Table 8).

The coefficient of variation (CV) is a measure of sample variation or dispersion that is used to compare the variation between different data sets. The coefficient of variation is expressed as a percentage of the mean, meaning that the higher the coefficient of variation, the greater the relative variability of the sample relative to its mean. It is especially useful when comparing variabilities between data sets with different average values. The smaller the coefficient of variation, the lower the relative variation of the sample. The most stable feature among those assessed was the color of the chips (V = 5.5%). Similar variability was observed for the fat content in the chips (V = 7.5%), and the most variable feature was the moist places in the chips (V = 35, 78%). The variability of dry matter and starch and their yields were very similar (V = 14.7% for DM and 14.22% for starch, respectively; for dry matter yield V = 28.85%, and for starch yield V = 28.12%). The variability of the sensory and physical characteristics of the chips also turned out to be similar and ranged from 11.93 to 12.85%.

3.5. Interaction of Features

The interaction of the examined features, i.e., the content and yield of dry matter and starch, with the quality features of chips produced from tubers of the tested potato cultivars, was assessed (

Table 9. Values of Pearson’s correlation coefficients.

Specification	x1	x2	x3	x4	x5	x6	x7	x8	x9	x10
x1	1.00
x2	0.50 **	1.00
x3	0.97 **	0.44 **	1.00
x4	0.48 **	0.99 **	0.44 **	1.00
x5	0.03	0.16	0.00	0.14	1.00
x6	0.08	0.10	0.05	0.08	0.55 **	1.00
x7	−0.06	0.03	−0.09	0.01	0.64 **	0.83 **	1.00
x8	−0.12	−0.12	−0.08	−0.09	−0.32 *	−0.72 **	−0.57 **	1.00
x9	−0.02	−0.06	0.00	−0.05	−0.48 **	−0.72 **	−0.75 **	0.73 **	1.00
x10	−0.49 **	−0.19	−0.49 **	−0.18 *	−0.48 **	−0.42 **	−0.28 *	0.26 *	0.42 **	1.00

x1—dry matter content (%); x2—yield of dry matter (t·ha⁻¹); x3—starch content (%); x4—starch yield (t·ha⁻¹); x5—color of chips (9° scale); x6—organoleptic assessment of chips (on a scale of 5); x7 (visual assessment of chips (5° scale); x8—moisture content of chips (%); x9—moist places (%); x10—fat content in chips (%); *—significant at p_0.05, **—significant at p_0.01.

).

The highest positive correlations were found for starch content and dry matter content as well as starch yield and dry matter content (r = 0.97 and 0.99, respectively). These features were generally not correlated with the quality of chips, apart from the fat content in chips, where the relationship turned out to be negative with the content of dry matter and starch (r = −0.49), i.e., with the decrease in dry matter and starch in potato tubers, the absorbency increased the fat in the chips. The color of the chips turned out to be quite strongly positively dependent on the sensory evaluation of the chips (taste and smell and their intensity), which could have resulted from the internal intercorrelation of these features. This feature also showed a strong negative relationship between the moisture content of chips and the number of wet spots in this product (Table 9).

The organoleptic evaluation of chips was strongly positively related to the organoleptic evaluation (r = 0.83), which may also result from the internal intercorrelation of these two features. The remaining three relationships turned out to be a negative relationship with the moisture content of the chips and moist places, as well as with the fat absorption of the chips (r = −0.72, −0.72, and −0.42, respectively). The visual evaluation (appearance) of the chips was negatively correlated with moisture and wet spots in this product (r = −0.57 and −0.75). The moisture content of the chips turned out to be strongly positively correlated with the moist spots in the chips (r = 0.73), while the moist spots in this product were positively correlated with the fat content in the chips (r = 0.42) (Table 9).

4. Discussion

4.1. Influence of Cultivation Technology on Yield of Dry Matter and Starch and Quality of Chips

Microbiological preparations are part of or supplementary to innovative potato cultivation technologies aimed mainly at reducing the occurrence of pests and improving the quantity and quality of the crop. They do not act directly to reduce diseases, but through their soil or foliar application, they increase the biological activity of the soil. According to [23,49,50], they eliminate or reduce the sources of infections in the soil that reduce the yield of crops. In the technology used in this work, nitrogen-fixing bacteria play a large role in converting indigestible forms of nitrogen into forms available for plants. According to many authors [5,23], EM significantly contributes to the improvement of soil structure. Mucilage substances released by EM adhere to humus and mineral particles, forming soil lumps, thus improving its structure [10,23,28,51]. Microorganisms also produce bioactive material useful for plants, such as hormones and growth stimulators that trigger cell division [20,22]. In the conducted research, the EM Farma microbiological preparation used in the form of dressing seed potatoes with an aqueous solution of the EM Farma preparation significantly increased the yield of dry matter and starch but also the quality characteristics of chips produced from the tested potato cultivars. On the one hand, the pre-planting treatments had a positive effect on the quality of the chips by reducing the fat absorption of the chips and reducing their moisture, but on the other hand, they worsened the organoleptic and visual evaluation of this product. This is partly attributable to the increased content of reducing sugars in potato tubers. However, not all reasons for this potato reaction are known, and further research is needed to clarify this issue in depth. EM preparations complement other agrotechnical activities aimed at reducing the occurrence of pests. They do not directly reduce diseases, but by applying them to the soil, they increase the microbiological activity of the soil [52]. According to Sawicka et al. [17,18], an important phenomenon occurring after the use of EM is the conversion of putrefactive processes causing the development of diseases and pests, auto-oxidation, and regeneration. Thanks to this, post-harvest residues treated with EM preparations cease to be a source of pathogen development and become food for beneficial microorganisms, which convert them into nutrients that supplement plants.

The assessment of the effect of potato cultivars and biodynamic preparations (BD) 500 and 501 on the concentration of phenolic compounds, the quantitative and qualitative composition of anthocyanins and phenolic acids, and the antioxidant activity of colored potato tubers was carried out in Lithuania by Jariene et al. [26]. These authors showed that after spraying with the BD 501 preparation, the concentration of total phenolic compounds in tubers of ‘Blue Congo’ and ‘Red Emmalie’ cultivars was significantly higher (20.1 and 5.4%); anthocyanins were 59.8 and 10.4% higher, respectively, and the antioxidant activity was about 1.3 times higher in both cultivars than in the control without the use of biodynamic preparations. The use of both preparations (BD500 and BD501) had a significant effect on the accumulation of anthocyanins in ‘Blue Congo’ and ‘Vitelotte’ tubers. However, preparation 500 tended to decrease the concentration of antioxidant compounds and antioxidant activity in tubers of all potato cultivars. The cultivar was the dominant factor influencing phenolic antioxidants and the highest concentration of phenolic compounds, anthocyanins, and phenolic acids, as well as the highest antioxidant activity in ‘Vitelotte’ tubers. Malvidin and petunidin compounds were identified as the main anthocyanins in ‘Blue Congo’ and ‘Vitelotte’ tubers, and pelargonidin compounds in Red Emmalie tubers. The dominant phenolic acid was chlorogenic acid.

The exposure of seed potatoes to pre-planting treatments resulted both positively (increase in the yield of dry matter and starch, decrease in fat absorption, and decrease in chip moisture) and negatively (deterioration of organoleptic and visual evaluation of chips). The study by Polivanova et al. [53] evaluated the effect of the increased exposure of H. tuberosus tubers to pre-planting treatments. It was proven that the activity of antioxidant defense enzymes, such as catalase and peroxidase, was poorly correlated with exposure to pre-planting treatments. In contrast, ascorbate peroxidase activity was strongly positively correlated with exposure to this treatment. The tubers with constant low exposure were characterized only by an increased concentration of ascorbic acid and water-soluble phenolic compounds compared to the untreated control. Our own research, conducted on 14 potato cultivars, may therefore be useful to understand the mechanisms underlying the adaptive reactions of plants under longer exposure to pre-planting treatments.

To summarize, it should be emphasized that microbiological preparations in agriculture should not be used thoughtlessly because their too-frequent application and in too-high doses cause, for example, high numbers of bacteria in the decomposition of straw, which can lead to a significant impoverishment of the soil humus. On the other hand, microbiological preparations, such as EM, create less stress for plants than chemical preparations. They also do not have a grace period, and some stimulate plants to develop faster; they also often facilitate access to nutrients contained in the soil.

4.2. Influence of Biotic and Abiotic Factors on the Quality of Chips

Potato chips are one of the most popular snack foods. They are obtained from peeled, raw potatoes cut into thin slices and fried in deep vegetable fat. Good-quality chips are a processed potato product with a straw-yellow color, a specific taste and smell, and a crunchy, delicate texture, fried to a moisture content of approx. 2%, containing the right amount of fat (33–40%). Potato chips with such qualities can be obtained during the frying process and with the use of a properly selected raw material. Among the organoleptic features, the consistency of potato chips is considered to be the most important determinant of the quality of potato chips. The right consistency depends on the content of fat, starch, and dry matter in the raw material but also on the parameters of frying (especially time) and the thickness of the slices. The taste and smell of chips are shaped by the technological process. The correct taste and smell are limited by the high content of starch and dry matter and the low content of reducing sugars. Color is also closely related to the content of reducing sugars [54,55,56].

The color of chips, in the conducted research, depended only on varietal characteristics and turned out to be the most stable feature among the evaluated features. In addition to the varietal characteristics of the raw material from which they are made, the color of the chips may be related to various factors, such as the production process and the additives that are used in their production. For example, green-colored chips can be made using dried kale or spinach leaves, while red-colored chips can be made using red peppers or beets. Other factors that may affect the color of chips include the method of thermal processing, time, and temperature of frying [57], the type of oil used for frying, as well as flavor and coloring additives, such as paprika, turmeric, or powdered vegetables [56,58]. It is worth noting, however, that some artificial colors can be used to give chips an intense color, which can have a significant impact on their quality and nutritional value [57].

The organoleptic evaluation of chips is a measure of their sensory quality, i.e., how the product looks, tastes, and smells. The organoleptic assessment is subjective and is based on the individual senses of the person making the assessment. During the organoleptic evaluation of chips, several factors are usually considered, such as the appearance, texture, taste, smell, and overall quality of the taste sensation. For example, chips with a golden, even color and a crunchy texture, with a taste and smell in accordance with the manufacturer’s declaration, will receive a high organoleptic rating. On the other hand, chips with an unpleasant odor, too soft or too hard a consistency, or with defects in appearance will receive a lower rating. Therefore, this feature is extremely important for the evaluation of chips [55].

The water content not only affects the consistency of potato chips, it is also a major factor in the shelf life of the product. The increase in humidity leads to the degradation of the fat contained in the product. Changes (oxidation, hydrolysis, polymerization) occur in the fat during frying and continue during storage. As a result of oxidation processes, a series is formed [31,54,56,58].

The content and quality of fat in fried potato chips and the compounds that give the chips the taste and smell of rancid fat, with far-reaching decomposition, also risk the formation of toxic compounds. These changes are limited by proper storage temperature, packaging with appropriate barrier properties, packaging in a nitrogen atmosphere, and the introduction of antioxidant additives [56]. Due to the specific structure and the high degree of dehydration of the chips, they absorb significant amounts of the fat used for frying, which significantly increases the costs and increases their energy value. This can be achieved by introducing blanching solutions using cellulose derivatives that reduce the level of absorbed fat by up to 85%, drying the potato slices before frying, or drying them after frying [54,56]. It is also possible to conduct the process at much lower temperatures (even by several dozen °C) compared to frying in standard conditions, thanks to which the losses of biologically active substances are much lower [31]. The factors limiting the absorption of fats by chips include agrotechnical treatments in the cultivation of this raw material. In the conducted research, the use of tuber dressing before planting contributed to the reduction in fat absorption by chips in both exposures. Due to the unfavorable changes in fats during frying and the high fat content in the finished product, eating chips raises many nutritional controversies. It has been proven that there is a relationship between high consumption of fats, especially saturated fatty acids and trans isomers, and the development of lifestyle diseases such as obesity, hypertension, atherosclerosis, diabetes, and some cancer diseases, and, therefore, research on reducing the fat content in chips has been conducted for years [56].

4.3. Phenotypic Variability of Potato and Its Products

Most of the characteristics of the potato, which are important from the point of view of the consumer and producer, are subject to high phenotypic variability depending on the action of other environmental factors and genotypes [26,55,56]. The obtained results, based on 3 years of research and long-term observations, indicate that genetic factors most strongly determined the content and yield of dry matter and starch, the color of chips and their organoleptic and visual evaluation, as well as the fat content in this product. In the case of the humidity of chips and moist places in chips, environmental variability was the dominant source. The large influence of hereditary factors on the content of dry matter and starch and their yield per unit area is confirmed by studies by Kołodziejczyk [3,4], Vaitkevičienė [9], Vaitkevičienė et al. [8], Jariene et al. [26], and Krzysztofik et al. [55]. The high content of dry matter is also due to the length of the period from planting to emergence, which means that the longer the period of assimilation, the more dry matter and starch accumulate in the tubers. This is also confirmed by the strong positive correlation between dry matter and starch content and their yield. Vaitkevičienė [9], examining the relationship between the content and yield of starch and the ripening time of European potato cultivars, came to the conclusion that there is a close relationship between dry matter and ripening time, namely that the dry matter increases by 1.15% for each of the following groups of the earliness of cultivars: mid-late and late. In the conducted research, these differences were much higher and amounted to over 2%. The study by Jariene et al. [26] found that the cultivar was the dominant factor influencing both the basic yield components and the phenolic compounds, anthocyanins, and phenolic acids in the tubers of cultivars with purple flesh. These authors also found a very strong positive correlation between antioxidant activity and the concentration of total phenolic compounds. The dominant phenolic acid was chlorogenic acid. Grudzińska and Zgórska [54] presented the characteristics of the quality of crisps as highly genetically determined. This is also confirmed by Krzysztofik [55].

Currently, intensive breeding and technological work are underway to obtain potato cultivars intended for potato processing, in particular for the production of chips. According to Lisińska [54], Mozolewski [33], and Grudzińska and Zgórska [31], the optimal dry matter content of tubers intended for the production of chips should be at the level of 22–23%, and the starch content should be within the range of 15–17%. The tested cultivars of potato met the above-mentioned requirements in terms of starch content and most of them met the requirements as regards the dry matter content of tubers. It should be emphasized that the study included cultivars from all earliness groups, and very early and early cultivars by nature have a different composition than mid-early or late cultivars. The obtained results prove that the technology implemented with the use of treating tubers with an aqueous solution of EM Farming contributed to a significant increase in the yield of dry matter by 20.6% and starch by 19.9% under the influence of EM Farming. The highest increase in the values of these features was noted in the EM application during 10 min. In the second exposure (15 min), this increase in the yield of dry matter and starch components was significantly higher than in the control object but did not differ significantly between the exposures.

4.4. Relationship between Qualitative Features and Yield of Dry Matter and Starch

The studies showed a very strong positive relationship between starch and dry matter and, to a lesser extent, starch yield and dry matter content. The content of dry matter and starch in tubers turned out to be related to the quality of the chips. The lower the content of these components in the tubers, the more fat the chips absorbed during frying. The characteristics of the chips, i.e., their color, consistency, smell, and taste, were generally negatively related to the physical characteristics (humidity, moist places), as well as to the fat absorption of the chips. Their value could also be related to the content of total sugars and reducing sugars, as suggested by Lisińska [54], Grudzińska and Zgórska [31], Kita and Figiel [58], Khayatnezhad et al. [59], and Zychnowska et al. [56].

The studies by Jariene et al. [26] and Zychnowska et al. [56] also proved a strong, positive relationship between the antioxidant activity and the concentration of total phenolic compounds (r = 0.953) and total phenolic acids (r = 0.951). In the opinion of most authors [31,54,55,56,57,58], the consistency of chips (crunchiness) depends on several factors, such as slice thickness—the thinner the chip, the more fragile and delicate it is. The humidity of the raw material for frying chips is important—too-moist potato cultivars can lead to less crispy chips. An important aspect of the production of chips is the temperature and time of frying—frying the chips at the right temperature and time is important to get their crispy texture. Too little time can lead to undercooked chips, while too much time can lead to overcooking and loss of crispiness. Moreover, the deterioration of the oil quality during the frying can affect their crunchiness. Old or contaminated oils can lead to less crispy chips. Chip flavorings such as salt, spices, and sauces can affect the texture of the chips. Some additives can make the chips less crispy. All of these factors affect the consistency of the chips, and adjusting them properly can help result in perfectly crunchy, optimal chips [54,57].

The interaction of the various features assessed in this paper may affect the statistical analysis or modeling, as it may lead to the falsification of the results. For example, if two variables are highly correlated, one may be redundant for analysis because the information it carries is already contained in another variable. In this case, a collinearity analysis should be performed to assess whether the variables are correlated and can be included in the analysis. The interplay of features can also be beneficial when creating predictive models, as variables that tend to occur together can help predict outcomes. In this case, however, it is important to identify which variables are correlated to avoid overfitting the model and increasing prediction errors [48,58,59].

5. Orientation towards the Future

Microbiological preparations in agriculture are generally useful; however, in addition to advantages, they also have disadvantages. The former include less stress for plants than chemical preparations, no withdrawal period, and a stimulating effect on plants by stimulating them to develop faster and often facilitating access to nutrients contained in the soil. Their disadvantages include sensitivity to inappropriate weather conditions during and after use; a weaker effect than in the case of chemical preparations with a maximum of 70% effectiveness; and, finally, troublesome storage of these preparations. We concluded that it is also worth isolating the most effective microbial strains in the process of microbial diversity research. It is also worth using flavonoids and other stimulants to promote the growth of beneficial microbes, as recent evidence suggests that these compounds may stimulate native mycorrhizal activity and subsequent potato yield. Potato exposure to microbial preparations in a biological system can activate a series of signals that start with energy absorption and can lead to damage, but this reaction is nevertheless rare [26]. The main target of exposure to microbiological preparations is water molecules present in all organisms. According to Dighton et al. [60], the basic reactions are excitation and ionization, resulting in the formation of ionized water molecules (H₂O•+), H₂O₂, and OH• radicals. In living organisms, this type of ionization starts chain reactions, and as a result of the capture of H•, secondary reactive oxygen species are formed. OH• radicals actively interact with cell macromolecules, including lipids, proteins, and DNA [61]. Therefore, changes in the metabolism of proteins and carbohydrates in plants growing under conditions of exposure to external factors may be related to the influence of free radicals. Often, these metabolic changes are related to antioxidant systems directly involved in the neutralization of free radicals [60,61,62]. The effect of microbiological preparations on the activity of antioxidant defense enzymes is ambiguous and probably depends on the time of exposure, dose, plant species, and other coexisting factors. Therefore, there are many problems ahead of us. Around 8% of farms in the EU will receive support to participate in producer groups and organizations, short supply chains, and quality schemes, which will help to strengthen their position in the value chain [63].

6. Conclusions

The experiment confirmed the research hypothesis that the application of EM Farming modifies the yield of dry matter and starch and most of the quality characteristics of potato chips, which will have a beneficial effect on the food supply chain. The use of EM Farming, regardless of the length of application, did not modify the color of the chips; however, on the one hand, it significantly reduced the fat content in the chips and the number of wet spots in this product in relation to the control object, and on the other hand, it contributed to the deterioration of the sensory experience of this product.

Genetic features of the tested cultivars had a significant impact on the assessed parameters of tubers and their products, regardless of the technology used and conditions in the years of research. Phenotypic variability determined all potato yield characteristics. The most stable was the fat content in the chips, and the most variable were the moist places in this product.

Meteorological conditions in the years of the study significantly modified the content and yield of dry matter and starch, as well as the quality of chips produced from the tested potato cultivars.

The interplay of features can be beneficial when creating predictive models because variables that tend to occur together can help predict outcomes. However, it is important to identify which variables are correlated to each other to avoid overfitting the model and increasing prediction errors.