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Article

Exploring the Influence of Diverse Viticultural Systems on Soil Health Metrics in the Northern Black Sea Region

by
Valeria Gabechaya
1,
Irina Andreeva
1,
Dmitriy Morev
1,
Alexis Yaroslavtsev
1,*,
Alexander Neaman
2 and
Ivan Vasenev
1
1
Ecology Department, Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, Timiryazevskaya Street 49, Moscow 127550, Russia
2
Departamento de Recursos Ambientales, Facultad de Ciencias Agronómicas, Universidad de Tarapacá, Arica 1000000, Chile
*
Author to whom correspondence should be addressed.
Soil Syst. 2023, 7(3), 73; https://doi.org/10.3390/soilsystems7030073
Submission received: 30 May 2023 / Revised: 26 July 2023 / Accepted: 10 August 2023 / Published: 15 August 2023
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Abstract

:
The present study investigates the functionalecological status of typical light clay soils in vineyards in the southern region of Crimea, using both traditional (including fallow soils) and organic land-use systems. This analysis was carried out by examining agrochemical indicators, microbial respiratory activity, microbial biomass, and the ecological status of the microbial community. In organic vineyard soils, the mean substrate-induced respiration, microbial biomass carbon and the ratio of microbial biomass to organic carbon were found to be 2.8, 4.0, and 4.1 times higher, respectively, compared to conventional farm soils. On the contrary, the microbial metabolic coefficient was 1.4 times lower, signifying more favorable conditions for the functioning of the soil microbiota. The increased mobile sulfur content in organic vineyard soils (18.3 mg kg−1 vs. 8.0 mg kg−1 in traditional farms) and inadequate mobile phosphorus supply in some farms present potential risks. The suboptimal functional state of the microbiome in fallow soils previously under traditional plant protection necessitates comprehensive ecotoxicological analyses before development. Assessing the soil functional ecological status through an ecophysiological evaluation of the microbiome is vital for understanding ampelocenosis soils and making informed decisions on vineyard management practices.

1. Introduction

The Crimean peninsula is characterized by distinct soil, climatic and agroecological conditions that support contemporary grape cultivation and the production of various types of wine and brandy wine materials. Grape cultivation in the northern Black Sea region can be traced back to the early settlements of the ancient Greeks and Romans, reflecting deep historical roots and cultural traditions in the area [1]. Currently, a key objective for Crimean winemaking is to expand the range of high-quality wines with geographical status. However, the development of winemaking on the peninsula faces specific challenges due to regional climatic changes and inherent agricultural intensification factors, such as high pesticide loads, the long-term cultivation of genetically homogeneous plants over vast areas, reduced biodiversity, and the risk of erosion resulting from the predominant location of vine plantations on sloping terrain with varying steepness and exposure.
Meteorological observations suggest that the peninsula’s climate changes are primarily associated with a general trend of rising temperatures, which is not synchronous and is complicated by a wide variety of climatic conditions, increased aridity in certain areas, and increased frequency of adverse weather phenomena (return frosts, heavy rainfalls, squally winds, droughts, dust storms, etc.) [2,3].
The negative climatic trends necessitate a systemic adaptation of viticulture agrotechnology to the consequences of regional climate changes, and primarily, plant protection systems. The growth of average winter temperatures (the average January temperature over the last 30 years has increased to +0.6 °C) [3] and the absence of frosts in the winter period have led to the activation of traditional pests and the emergence of new plant disease pathogens that were previously incapable to winter under these conditions.
On 16 May 1985, the Soviet Union issued a decree on “Intensification of the Fighting against Alcoholism”, which reduced the production of wine materials considerably, eventually destroying 30 percent of Crimean vineyards. Most of these areas have remained empty or developed slowly in tourism infrastructure over the past 30 years.
According to the publication on of the International Organisation of Vine and Wine (OIV) published at the end of September 2021, the conversion rate of vineyards to organic products “significantly increased”; the world’s total organic vineyard area was 6.2% of the world’s vineyard area; and it was estimated that by 2019, 63 countries of all continents would participate in organic farming. It was also noted that certified organic vineyards increased by an average of 13 percent annually between 2005 and 2019, while non-organic vineyards declined by an average of 0.4 percent annually during the same period [4].
Currently, about 40 hectares (1%) of vineyards in Crimea are already certified according to local standards as organic. There are several vineyards cultivated organically but without certification or under conversion (over 20 hectares) [5].
One of the characteristics of ampelocenoses is the active use of copper-containing pesticides to control fungal diseases in grapes. Copper-based pesticides are also approved for use on organic farms. The history of this group of pesticides is over 100 years old, and despite the emergence of a wide range of new generation fungicides, the popularity of copper-containing pesticides for vine treatments has not diminished. This is largely due to the fact that these products do not cause resistance and are low in toxicity, while being obviously effective and affordable from an economic point of view. For example, when the concentration of mobile copper in soil solution increases four times and the treatment rules are followed, the remaining amounts of copper in grape biomass do not exceed the maximum permitted level [6]. The copper and other metals’ accumulation in the upper soil horizons is due to the fact that their compounds, unlike organic pesticides, are not biodegradable and can leave the root zone only by leaching, erosion processes and biological absorption. While both erosion and leaching cause contamination of adjacent environments [7], erosion is also associated with the risk of ingress and movement of copper through the food chain [8].
Organic grape production is governed by several parameters that may differ according to the certification system. However, the basic principles of organic agriculture are the use of natural resources for the protection and fertilization (mineral products and plant products) and the rejection of pesticides and synthetic fertilizers [9].
In a study by Isabella Ghiglieno et al., the actual differences between conventional and organic vineyard management in terms of greenhouse gas emissions were determined, comparing multiannual data from 25 wineries in northern Italy [10]. No statistically significant differences were found between the overall mean values of conventional and organic management. In organically farmed vineyards, a higher incidence of fuel consumption was observed, while in conventionally farmed vineyards, higher emissions were observed due to the use of products such as pesticides and fertilizers. Increased fuel consumption in organic systems vs. the conventional one can be expected in relation to the high number of tractor transits in organic systems [11,12]. In fact, non-synthetic copper-based fungicides are largely lost in the foliar wash from treated vine leaves due to the action of rainfall [13], with the consequent need for numerous interventions in rainy periods and hence increased diesel consumption. Similarly, herbicide avoidance imposes the need for more tillage operations, such as hoeing and mowing, for mechanical weed control. At the same time, some papers showed that concentrations of copper in the organic vineyards were higher than in the conventional vineyards of the studies. Ecological indices corresponding to moderate-to-heavy contamination and moderate ecological risk in organic farms were higher than ones in conventional farms [14].
All of the above mentioned are intrinsically linked to soil, which is responsible for generating and maintaining biodiversity, as well as providing environmental, regulatory, protective, and informational functions. The properties directly influence the quantity and quality of products, particularly in industries such as viticulture and winemaking.
The effectiveness of soils in the performance of their ecological functions is highly dependent on the condition of the soil microbiome [15], which provides a broad array of nutritional, regulatory, and support ecosystem services [16,17]. The soil microbiota facilitates ongoing processes of organic matter synthesis and degradation, humus formation, the cycling of plant ash and nitrogen nutrients, atmospheric nitrogen fixation and incorporation into the biological cycle (approximately 100 megatons annually), as well as the detoxification of various pollutants. Disruptions in the functioning of the soil microbial community may result in reduced quantity and quality of the products obtained.
Soil scientists used to speak of soil quality, a concept expressing a soil «fitness for purpose». Soil quality is a rather abstract concept, and in recent years, the term has been replaced by soil health. One consequence of this change is an increasing focus on the state of the soil’s biology, or life in the soil—an emphasis that is expressed through the promotion of organic and biodynamic systems of farming.
The Cornell Soil Health Assessment provides a more balanced assessment of soil health [18]. The underlying concept is that soil health is an integral expression of soil’s chemical, physical, and biological attributes, which determine how well a soil provides various ecosystem functions.
According to Lehmann et al., soil chemical and biological attributes such as organic carbon and microbial biomass are vital in terms of representing soil health and quality [19].
In a 2023 study, Higo Forlan Amaral and colleagues determined how different grape-vine-growing seasons (organic or conventional) affect soil chemical and microbial characteristics compared to the soil characteristics of adjacent natural forests [20]. Variations in microbiological and chemical attributes during different seasons are specific to each vineyard management system. Soil under vineyard organic management maintained organic carbon and microbial biomass indices like those of a forest, of which were higher and more stable than those of a conventional system.
Soil microbiological indicators are used in conjunction with physicochemical and geochemical characteristics to evaluate the ecological functions of soils [21,22]. The soil microbial community responds rapidly to the presence of pollutants, showing alterations in the total number of microorganisms, species diversity, soil enzyme activity, soil respiration, and processes influencing the cycling of essential nutrients [23].
Microbial ecophysiological indicators, which characterize the specific activity of the microbiome (respiratory and enzymatic activity per unit biomass), are highly informative for evaluating organic matter decomposition efficiency, reflecting a wide range of ecosystem services, exhibiting considerable reliability and recognition, and possessing standardized and relatively straightforward methods for their determination [24].
Several authors have highlighted the high variability of soil microbiological parameters, with the most significant factors being climate [25], landscape position [26], land-use patterns [27], and vegetation composition [28]. At the same time, soil respiration measurements can be performed under laboratory-controlled conditions, mitigating the influence of abiotic and biotic factors (e.g., plant root effects) and enabling the standardization of environmental conditions.
The respiration of microorganisms serves as the most informative and widely used indicator of microbiological activity. Throughout their life cycle, microorganisms produce carbon dioxide and nitric oxide (I), consume oxygen, and perform nitrogen fixation in an outperformance, among other processes [29,30]. Apart from microbocenosis, plant roots also contribute to soil respiration processes [31,32]. Basal respiration (BR) generally refers to soil respiration that is devoid of roots and determined only by microbial activity. This indicator is widely used to determine the physiological state of microorganisms [33,34]. An increase in the basal respiration rate suggests a favorable condition of the soil microbiome. However, evidence indicates that soil contamination can cause a distinctive increase in the soil respiration rate compared to optimal values [35].
The substrate-induced respiration (SIR) method is now considered the standard approach for the quantification of microbial carbon (Cmic) [36]. This technique involves measuring microbial respiration (CO2 release) for a duration of three to five hours (to prevent microbial multiplication) [37] after the introduction of a readily oxidizable substrate. However, the SIR method exhibits certain limitations. It is not applicable to extremely acidic (pH < 2.5) or highly alkaline (≥8.5) soils [38] due to the dissolving of microbial CO2 in the soil solution [39], leading to its underestimation [40,41].
The microbial metabolic coefficient (qCO2), which represents a specific respiration derived from the ratio of basal respiration to carbon from microbial biomass, is a crucial indicator in ecological monitoring [42]. This coefficient reflects the physiological state of the microbiota. Some papers showed that the qCO2 index is sensitive to any change in land use [43,44,45], and it is applicable to assess the physiological state of microbial communities and the level of disturbance to them. Elevated qCO2 values are characteristic of soils subjected to various anthropogenic interventions, as well as degraded and contaminated soils [46,47,48], including heavy metal pollution [49,50,51,52,53]. Numerous studies indicate that a decrease in the basal respiration rate leads to an increase in the qCO2 Corg−1 ratio [54], which characterizes the utilization of organic carbon (this indicator is higher in disturbed soils).
A key advantage of determining soil respiration parameters and the ecophysiological indices based on them is the ability to assess the response of soil microbial communities to agroecosystem management elements. Several studies suggest the utilization of microbiological indices for the ecological evaluation of land-use systems and analysis of the changes that occur during the transition from one system to another [55,56].
The active transformation of vineyards from traditional to organic management systems [57], as well as the involvement of fallow lands in viticulture, increase the value of the soil biological activity assessment as one of the most important indicators of its condition, including the ampelocenoses of the Northern Black Sea region. In this scenario, the soil microbial respiration, the microbial activity and biomass, and the changes in ecophysiological status may indicate unfavorable processes induced by a combination of agrogenic factors.
The primary objective of this study was to perform a comparative assessment of the functional and ecological state of the vineyard soils cultivated using traditional (including fallow) and organic farming systems in 14 farms in the Northern Black Sea region (Figure 1). This assessment is based on soil agrochemical properties, soil respiration parameters and soil microbiocenosis ecophysiological conditions. The climate of the studied farms is Mediterranean; moderately warm; with moderately hot, dry summers and mild winters with frequent thaws. Monthly precipitation in the autumn–-winter period is significantly higher than the average annual values, while in the spring–summer period, it is much lower. Consequently, precipitation serves as the main limiting environmental factor in the cultivation of field crops, and sustainable yields are unattainable without irrigation. However, agroclimatic and soil conditions in the region are favorable for the growth and development of viticulture and winemaking.

2. Materials and Methods

Soil samples were collected using a soil auger at depths of 0–10 cm and 10–20 cm. The most typical areas in terms of landscape conditions were chosen as soil sampling sites. The so-called “envelope” method was used to obtain a generalized picture of soil property distribution for each farm. This method involves taking five samples from a 5 m by 5 m plot (at the corners of the plot and in the middle of the plot). A sample of 0.5 kg weight was taken from each point. The five individual samples were then combined, mixed and one combined sample weighing 1.0 kg was retained from the total mass. All operations were carried out separately for samples with depths of 0–10 and 10–20 cm. Mixed samples were collected from 5 sites for each farm, and those mixed samples was mixed according to the abovementioned procedure and analyzed. Soils on all farms were identified as Haplic KASTANOZEMS/Haplic CALCISOLS according to WRB.
Soil preparations included milling, removing plant roots, stones and other inclusions. Water pH was analyzed potentiometrically with a glass electrode using a SevenCompact pH meter S220 (Greifensee, Switzerland, Mettler Toledo). The organic matter content was measured by the photometric method using a strong oxidizing agent (K2Cr2O7) in the presence of H2SO4 (Walkley and Black method [58]) with a Leki UV2107 (Helsinki, Finland, MEDIORA OY) spectrophotometer at a wavelength of 600 nm. Mobile sulfur content was determined using a 0.15 percent CaCl2 solution [59]. The mobile phosphorus and potassium content in soils was determined by an ammonium carbonate extraction, according to the Machigin method (with pH = 9.0 and 1:20 soil/solution ratio) [60]. After extraction, potassium content was determined using flame emission photometry. Phosphorus was determined by a spectrophotometer after color development with ammonium molybdate and SnCl2. All analyses were performed in triplicate.
The determination of basal respiration (BR) was carried out in accordance with CEN EN ISO 16072-2011 Soil Quality Laboratory methods for the determination of microbial soil respiration [61]. Soil was moistened with distillated water of 0.2 mL and incubated for 24 h at 22 ± 0.5 °C. After incubation, the carbon dioxide content in 3 mL of the air probe extracted by a syringe was measured using a Chromatec-Crystal 5000.1 (Yoshkar-Ola, Russia, Chromatec) gas chromatograph. The BR rate was expressed in C-CO2 μg−1 soil per hour, with a repeatability of five times.
Substrate-induced respiration (SIR) was determined in a similar manner, but the soil was moistened with an aqueous glucose solution (10 mg glucose g−1 soil) instead of distilled water and incubated for 3.5 h at 22 ± 0.5 °C. The SIR rate was expressed in µg CO2 g−1 soil per hour, with a five-fold repeatability.
Soil microbial biomass carbon (Cmic) was calculated by converting the SIR rate using the formula [29]:
SIR (µg CO2 g−1 h−1) × 40.04 + 0.37
The specific respiration of microbial biomass (qCO2) was calculated as the ratio of the basal respiration rate to microbial biomass carbon and expressed in µg CO2 C mg−1 Cmic h−1:
qCO2 = BR/Cmic
The particle size distribution was determined using the areometric method [62].
The data were statistically processed using the R language. The “FactoMiner” package was used for Principal Component Analysis (PCA) [63] and “FactoExtra” package for visualization [64,65]. All variables except Ni, Cu, Cd, Cr and Corg were normally distributed according to the Shapiro–Wilk test (p < 0.05). Hence, a non-parametric statistics test for a group comparison was used (Kruskal–Wallis).

3. Results

3.1. Agrochemical Properties of Soils under Vineyards

The pH values of the aqueous extracts in farms soils of the studied ranged from 7.2 to 8.4 (Table 1), corresponding to a neutral-to-moderately alkaline environment, which is ideal for grape crops. In most cases, soil pH values increased with depth, likely due to the carbonate nature of bedrock.
Although soil types and subtypes are similar and the geographical location of the farms is comparable, the organic content in the upper parts of the soil profile ranged widely from 1.48% to 4.34%. The highest average values were found in fallow soils, 3.37% and 3.33%, which were closely followed by farms with traditional land-use systems, 3.33% and 3.01%. The lowest average organic carbon content was a property of organic farms, at 2.58% and 2.54% in the 0–10 cm and 10–20 cm horizons, respectively. As the depth increased, there was a general trend of decreasing organic matter content, although exceptions were observed in farms No 1, No 5, and No 8. The granulometric analysis revealed that the soils of the studied farms possess a light clayey texture.
The mobile phosphorus content in the soils of the studied farms ranged considerably, from 3.8 to 138.3 mg P2O5 kg−1 of soil (Figure 2C), which classifies them into different supply categories: very low for farm No 14; low for farms No 3, 4, and 9; medium for farms No 2, 7, 10, and 11; high for farms No 5, 6, and 12; very high for farm No 8; and extremely high for farms No 1 and 13 in the top soil layer (0–10 cm). In nine of the studied farms, the mobile phosphorus content in the soil at a depth of 10–20 cm decreased by 1.6–7.4 times compared to the 0–10 cm horizon. Meanwhile, in five farms, the differences between the horizons were not significant.
Unlike mobile phosphorus, the available potassium content in the soils of the farms corresponded to an increased, high, and very high supply state and ranged from 359 to 1109 mg K2O kg−1 soil in the 0–10 cm horizon. Concurrently, the available potassium content in the upper horizon of soils from organic farms and fallow lands varied within a narrow range and was characterized by elevated–high and high–very high supply states, respectively. In contrast, in the soils of traditional farms, the variation in the considered indicator was significant and corresponded to the supply state level from elevated in farm No 14 to very high in farm No 12.
Contrary to the available phosphorus content, the available potassium content correlated with the land management system used in the farm and was significantly higher (p = 0.0007) in organic farms compared to conventional and fallow systems (Figure 2A).
The mean mobile sulfur content in the soils of organic farms was 1.8–3.4 and 2.9–3.7 times higher compared to the soils of traditional farms and fallow lands, in upper and lower studied horizons, respectively (Figure 2B).

3.2. Parameters of Soil Respiration in the Ampelocenoses of the Southern Part of Crimea

A non-parametric median comparison between BR and land-use systems, using the Kruskal–Wallis criterion (p = 0.01), revealed a tendency for lower BR in traditional farms practicing chemical plant protection systems compared to organic farms. Cultivated soils exhibit intermediate values of BR (Figure 2E, Table 2).
The value of substrate-induced respiration (SIR), which characterizes the potential activity of the soil microbial community, showed a wide variation in the upper 10 cm layer of soil in organic and conventional farms, ranging from 6.27 to 22.65 and from 2.11 to 6.27 µL CO2 g−1 soil h−1, respectively (Table 2). In fallow soils, this value was low and varied within a narrow range of 1.98 to 3.10 µL CO2 g−1 soil h−1. A significant difference according to the Kruskal–Wallis criterion was observed between SIR in the soils of organic farms and those of farms with traditional land use and fallow soils (Figure 2D).
The highest microbial biomass carbon content in the 0–10 cm horizon was found in organic farms, averaging 545.8 µg C g−1, compared to 161.1 µg C g−1 in farms with conventional land use (Table 2)
An estimation of the right number of axes to interpret suggests restricting the analysis to the description of the first three axes (Figure 3). These axes present an amount of inertia greater than those obtained by the 0.95 quantile of random distributions (66.8% against 51.5%) and more than all other PCs altogether. This observation suggests that only these axes are carrying real information. Consequently, the description will stand to these axes.
The first two dimensions of the analysis express 48.12% of the total dataset variance; this means that 48.12% of the individual (or variable) cloud total variability is explained by the plane. This is an intermediate percentage, and the first plane represents a part of the data variability. This value is greater than the reference value that equals 30.39%; the variability explained by this plane is thus significant (the reference value is the 0.95 quantile of the inertia percentage distribution obtained by simulating 924,214 data tables of equivalent size based on a normal distribution).
The histogram in the top part of Figure 3A–C quantifies the contribution of soil properties and respiration indices in the first three axes and provides a threshold for the contribution of higher variables. It is important to note that variable grouping into principal components can be logically interpreted. Thus, the first principal component consists mainly of variables related to microbial biomass (Cmic/Corg, SIR, BR, Corg) and soil and ecosystem properties directly affecting it (Age, pH (H2O)). The second main component is determined mainly by the content of heavy metals in the soil (Cr, Pb, Ni, Cd, Zn) and the third one by the granulometric composition of the soil and the biogenic elements (clay, silt, sand, Zn, S).
The distribution of principal component scores for three land-use systems on the first two principal component axes are shown in Figure 3E. The score diagram shows that the first principal component axis can distinguish soils sampled in farms with traditional land use from fallow lands and organics farms. Since age and pH (H2O) contributed more to the first principal component axis and were negatively correlated (Figure 3D), while Cmic/Corg, SIR, BR contribute less and were positively correlated, organic farms could be distinguished from traditional farms by a lower pH, younger vines and a higher SIR, BR and Cmic/Corg ratio in soils.

4. Discussion

The active application of soil microbiological indices is recommended for the ecological evaluation of land-use systems and the analysis of changes in soil ecological quality during the transition from one system to another [55,56]. The advantage of determining soil respiration parameters and the ecophysiological indices calculated based on them lies in the possibility of an integrated comparative assessment of the soil microbiota’s response to agroecosystem management mechanisms.
The microbial metabolic coefficient (qCO2) is referred to as an index of microbial stress. This index is sensitive to any change in land use [30,44] and its value can be used to quantify the ecophysiological condition of the microbial community. The studies did not show significant differences in the microbial metabolic coefficient index in conventional and organic farm soils, although there was a trend towards lower qCO2 in the upper horizon of organic farm soils compared to conventional farm soils. In contrast, the qCO2 values in fallow soils were significantly (p = 0.025) higher (Figure 2F).
It is well-established that the carbon fraction of microbial biomass constitutes 1 to 5% of soil organic carbon [66], and the higher it is, the more organic carbon is available. Consequently, research on soil microbial activity often utilizes the calculation of the Cmic/Corg ratio as an indicator of favorable conditions for the functioning of the soil microbial community and as a characteristic of the “quality” of its organic matter [30].
In our study, the Cmic/Corg ratio in the 0–10 cm horizon was highest in the soils of organic farms, averaging 2.23%, while in the soils of traditional farms and fallow fields, this ratio decreased by 4 and 8 times, respectively (Table 2). In the 10–20 cm horizon, the Cmic/Corg ratio was also lower in fallow soils and soils of traditional vineyards compared to organic ones. This indicates that under the conditions of organic land use in vineyards, more favorable conditions for fixing carbon in the composition of microbial biomass are created in the soil, resulting in an increase in its proportion in the soil’s organic matter.
In contrast to the Cmic/Corg index, the qCO2/Corg ratio was typically higher in disturbed soils. Based on the calculations performed, the highest value of the qCO2/Corg index was observed in the 0–10 cm horizon of fallow soils, averaging 109.6 µg CO2 C mg−1 Cmic h−1/g Corg g−1 soil, which was 1.7 and 2 times higher than in the soils of traditional and organic vineyards, respectively. In the 10–20 cm horizon, the differences between farms in this indicator were less pronounced.
The microbial respiration coefficient (QR), i.e., the ratio of BR values to SIR values, is considered an integral index to assess the state of the soil and its microbial pool. A QR value between 0.1 and 0.2 is thought to indicate a favorable condition of the soil microbial community [66]. In our study, the highest QR average value in the upper 10 cm layer was detected in fallow soils (0.15). A significantly lower QR value was observed in traditional farm soils (0.08), and the lowest in organic soils (0.05).
Low QR values in operating farms, particularly organic ones, are indicative of a lack of nutrients in the soil, which correlates with the previously presented results of the content of mineral nutrients.
Comparable data are reported by Probst et al. [12], where the microbial biomass carbon content was highest in the soil of organic farms, ranging from 320 to 1000 µg C g−1 soil.
Sustainable grape cultivation is influenced by a myriad of abiotic and biotic factors [67], including the utilization of highly productive and adaptive varieties [68], a range of agrotechnological techniques that allow for the product quality management during yield formation [69], and the duration of various types of land use [70]. The cumulative impact of local, natural and agrotechnological factors is encapsulated by the term “terroir”, which determines the uniqueness and quality of wine. However, there are objective limitations to obtaining high-quality products, which are associated with climatic changes on one hand, and a series of environmental risks specific to ampelocenoses on the other hand, such as a continuous long-term cultivation in a single area, a reduction in species and soil biodiversity, the development of erosion processes on trans-eluvial landscape elements, and perennial high pesticide loads.
All the negative phenomena in viticulture are reflected in the ecological state of the soil, primarily in its biological properties. Unlike humus content, which is a more stable indicator primarily dependent on several properties and genetic features of the soil, the state of the soil microbial community is considered an important indicator of the initial manifestation of negative influences on the soil and the degree of its disturbance.
Our investigations of the soil microbiota respiratory activity in ampelocenoses revealed substantial differences in the ecophysiological status of the soil microbiome in vineyards, depending on the land-use system. It has been suggested that the activity of soil microbiocenoses is more dependent on the total pool of organic carbon [71]. According to our findings, the organic carbon content in soils of organic farms was, on average, 0.7% and 0.8% lower than in the soils of traditional farms and fallow lands, respectively. However, the most favorable conditions for soil microbiota functioning were observed in organic farming, as evidenced by higher substrate-induced respiration and microbial biomass carbon (2.8 times higher than in traditional farms), the Cmic/Corg ratio (4.1 times higher than in traditional farms), and the lowest qCO2 value among all investigated soils (1.5 µg CO2 C mg−1 Cmic h−1).
Similar observations were reported by Probst et al. (2008), who examined the effects of conventional and organic grape-growing technologies on microbial biomass and ecophysiological indices in the vicinity of Colmar, northeastern France [12]. The researchers found the highest microbial biomass content and the lowest qCO2 value in the soil of organic farms, with soil microbial activity positively correlated with the duration of organic land-use practices.
Organic farms soils were characterized by high mobile sulfur provision (18.3 mg kg−1 vs. 8.0 mg kg−1 in conventional farms), which is likely due to the use of sulfur-containing preparations approved for plant protection in organic farming. Based on the classification of soils by mobile sulfur content given by Aristarkhov [72], this parameter in soils of traditional farms and fallow lands was low (less than 6.0 mg kg−1) (Figure 2B). However, it has been suggested that the increase in available sulfur in the soil of ampelocenoses enhances the availability of nitrogen to plants and the assimilation of these elements, which may collectively result in a decrease in the accumulation of phenolic compounds in grapes and a deterioration in the quality of the wine material obtained from them [69].
According to Kovalevskaya et al. [71], the conversion of arable to fallow soils led to the accumulation of organic matter in the upper soil horizons, which in turn contributed to the increased respiratory activity of soils and increased microbial carbon stocks. Our findings demonstrated that the Corg content in fallow soils was indeed higher than in conventional and organic farm soils, but this did not lead to improved microbial activity indicators. Conversely, the active and potentially active (responding to readily available substrate) portion of the microbial pool, as determined by the substrate-induced respiration index, was less pronounced in fallow soils than in the soils of active vineyards. Furthermore, fallow soils exhibited the highest qCO2 value, reaching 5.57 µg CO2 C mg−1 Cmic h−1, although the value of this indicator in stable ecosystem soil is ≤2–4 µg CO2 C mg−1 Cmic h−1 [73]. This indicates a low efficiency of microorganisms’ utilization of organic compounds to maintain their life activity, as well as a high rate of microbial biomass die-off. The latter is confirmed by the low Cmic, averaging 96 µg C g−1 soil, which is 5.7 and 1.7 times lower than in the soils of organic and conventional farms, respectively. A certain imbalance in the functioning of soil microbiota in this category of soils is also indicated by the maximum value of the indicator qCO2/Corg.
The soils of farms with traditional viticulture technologies showed inferior soil respiration indicators compared to the soils of organic farms. However, the microbiological activity and stability of the soil microbiome in these traditional farms were higher than in fallow soils. This could be influenced by the time factor, since the age of vineyards in organic and traditional farms in our study ranged from 5 to 20 years, which is relatively short for ampelocenoses. Meanwhile, fallow soils were previously used for about 40–60 years in the agricultural turnover with the application of traditional agricultural technologies and chemical plant protection systems—the effects of which could have influenced the current functioning of their microbiome.
A common problem for all studied soils was low mobile phosphorous content. Phosphorus is a vital nutrient for grapevines as it supports normal root system development and function, promotes the formation of large inflorescences, and stimulates the ripening of berries, as approximately 45% of the grapevine’s active root system lies within a depth of 30 cm and about 70% within 45 cm [74]; phosphorus availability across all horizons is crucial.

5. Conclusions

Studies of comprehensive soil health metrics in the conditions of the Northern Black Sea region have shown significant variations due to used viticulture systems and the land-use management history. At the same time, the most significant differentiation was observed for the parameters of the soil microbiota functioning. The respiration of microorganisms in farms practicing organic land use significantly exceeds similar indicators in farms with a traditional system and in fallows.
An assessment of the available soil nutrient content showed a relatively low state of labile phosphorus and potassium form supply for most farms. The high content of mobile sulfur in the soil of organic farms can reduce the quality of the obtained wine materials. There were no excesses in the content of metal elements in any of the studied farms, as well as reliable differences in their distribution in the soil.
The influence of viticulture systems primarily affects soil microbiota and, to a lesser extent, soil macro and micro elements’ supply states.

Author Contributions

Conceptualization, I.V. and A.N.; methodology, I.V. and I.A.; software, A.Y.; validation, V.G., D.M. and A.Y.; formal analysis, V.G. and D.M.; investigation, V.G. and I.A.; resources, I.V.; data curation, V.G. and A.Y.; writing—original draft preparation, I.A. and V.G.; writing—review and editing, I.V. and A.Y.; visualization, V.G.; supervision, I.V.; project administration, I.A.; funding acquisition, I.V. All authors have read and agreed to the published version of the manuscript.

Funding

The research was financed by the Ministry of Science and Higher Education of Russian Federation: 075-15-2021-1030.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Soilsystems 07 00073 g001
Figure 1. Location of soil sampling points in the southern part of the Crimea peninsula. Colored dots represent investigated farms with different type of landuse.
Figure 1. Location of soil sampling points in the southern part of the Crimea peninsula. Colored dots represent investigated farms with different type of landuse.
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Soilsystems 07 00073 g002
Figure 2. Potassium content (mg kg −1 soil) (A), mobile sulfur (mg kg−1 soil) (B), phosphorus oxide (mg kg−1 soil) (C), SIR (μL CO2 C g−1 soil h−1) (D), BR (μg CO2 C g−1 soil h−1) (E), qCO2 (μg CO2 C mg−1 Cmic h−1) (F) compared between different land-use types in the upper and lower horizons of the Crimean ampelocenoses soils according to the Kruskal–Wallis criterion.
Figure 2. Potassium content (mg kg −1 soil) (A), mobile sulfur (mg kg−1 soil) (B), phosphorus oxide (mg kg−1 soil) (C), SIR (μL CO2 C g−1 soil h−1) (D), BR (μg CO2 C g−1 soil h−1) (E), qCO2 (μg CO2 C mg−1 Cmic h−1) (F) compared between different land-use types in the upper and lower horizons of the Crimean ampelocenoses soils according to the Kruskal–Wallis criterion.
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Soilsystems 07 00073 g003
Figure 3. The Principal Component Analysis (PCA) of studied farms soil properties and functional parameters performed with “Fallow”, “Traditional” and “Organic” faming systems as factors. The variable contribution to principal components shown for PC1 (A), PC2 (B) and PC (C). The variable factor map (D). The variables in black are considered as active whereas those in blue are illustrative. The labeled variables shown are the best on the plane. The individual factor map (E). Different colored ellipses indicate significant differences between groups (Wilks test, p < 0.001). Red dashed line corresponds to the expected variable contribution value if the contribution were uniform.
Figure 3. The Principal Component Analysis (PCA) of studied farms soil properties and functional parameters performed with “Fallow”, “Traditional” and “Organic” faming systems as factors. The variable contribution to principal components shown for PC1 (A), PC2 (B) and PC (C). The variable factor map (D). The variables in black are considered as active whereas those in blue are illustrative. The labeled variables shown are the best on the plane. The individual factor map (E). Different colored ellipses indicate significant differences between groups (Wilks test, p < 0.001). Red dashed line corresponds to the expected variable contribution value if the contribution were uniform.
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Table 1. pH value, content of organic carbon (Corg), mobile phosphorus (P2O5), exchangeable potassium (K2O) and mobile sulfur (S) in soils of Crimean ampelocenoses with different land-use systems.
Table 1. pH value, content of organic carbon (Corg), mobile phosphorus (P2O5), exchangeable potassium (K2O) and mobile sulfur (S) in soils of Crimean ampelocenoses with different land-use systems.
Farm
Number		Depth, cmLand-Use
System		pH (H2O)SandClaySiltCorgP2O5K2OS
pH Unit%%%%mg kg−1mg kg−1mg kg−1
10–10Organic7.52015651.4884.852128.1
10–207.82.4748.855116.3
20–107.94028323.5321.357529.2
10–207.82.483.8016817.1
30–106.53530352.2814.642810.7
10–206.72.218.104339.40
40–107.93520452.7814.347813.7
10–207.92.481.9432812.3
50–107.2205753.4843.852110.6
10–207.33.8446.95147.60
60–107.24035251.9331.435937.8
10–207.41.7435.241026.3
70–10Fallow8.34025353.3129.05116.40
10–208.43.0917.94085.70
80–108.23530353.6450.04753.60
10–208.23.8319.04853.10
90–108.34535203.1710.75567.80
10–208.33.084.703746.40
100–10Traditional7.93530353.5321.357539.2
10–207.93.4117.64754.70
110–107.93025453.4920.95783.60
10–208.13.2811.55473.40
120–108.13525404.3449.211092.10
10–208.24.1360.711522.10
130–107.54020402.041387095.70
10–207.61.9657.47294.20
140–108.12010703.245.203737.80
10–208.23.196.104317.40
Table 2. Soil respiration indices (basal (BR, μg CO2 C g−1 soil h−1) and substrate-induced respiration (SIR, μL CO2 g−1 soil h−1)), microbial biomass carbon content (Cmic, μg C g−1 soil h−1), Cmic/Corg ratio (%), qCO2/Corg microbial metabolic coefficient and microbial respiration ratio (QR) in soils of Crimean ampelocenoses.
Table 2. Soil respiration indices (basal (BR, μg CO2 C g−1 soil h−1) and substrate-induced respiration (SIR, μL CO2 g−1 soil h−1)), microbial biomass carbon content (Cmic, μg C g−1 soil h−1), Cmic/Corg ratio (%), qCO2/Corg microbial metabolic coefficient and microbial respiration ratio (QR) in soils of Crimean ampelocenoses.
Farm NumberDepth, cmLand-Use SystemBRSIRCmicqCO2Cmic/CorgqCO2/CorgQR
10–10Organic0.599.053631.632.451100.07
10–200.678.573441.941.3978.50.08
20–100.486.272511.900.7153.80.08
10–200.248.473400.691.3727.80.03
30–100.7422.79070.823.9836.00.05
10–200.5321.48560.613.8727.60.02
40–100.7415.66241.202.2443.20.05
10–200.202.1386.02.160.3587.10.09
50–101.5019.97971.902.2954.60.08
10–200.927.202883.210.7583.60.13
60–100.258.303330.731.7337.80.03
10–200.509.003591.412.0681.00.06
70–10Fallow0.452.03825.570.261680.22
10–200.113.191280.840.4127.20.03
80–100.213.101251.700.3446.70.07
10–200.064.461790.330.478.600.01
90–100.291.9880.03.610.251140.15
10–200.312.501003.140.321020.12
100–10Traditional0.486.272511.900.7153.80.08
10–200.103.871550.630.4518.50.03
110–100.303.521412.150.4061.60.09
10–200.187.523020.580.9217.70.02
120–100.212.1185.02.440.1956.20.10
10–200.133.041221.110.3026.90.04
130–100.545.892362.311.161130.09
10–200.094.851940.450.9923.00.02
140–100.112.2892.01.230.2838.00.05
10–200.332.1386.04.010.271260.15
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Gabechaya, V.; Andreeva, I.; Morev, D.; Yaroslavtsev, A.; Neaman, A.; Vasenev, I. Exploring the Influence of Diverse Viticultural Systems on Soil Health Metrics in the Northern Black Sea Region. Soil Syst. 2023, 7, 73. https://doi.org/10.3390/soilsystems7030073

AMA Style

Gabechaya V, Andreeva I, Morev D, Yaroslavtsev A, Neaman A, Vasenev I. Exploring the Influence of Diverse Viticultural Systems on Soil Health Metrics in the Northern Black Sea Region. Soil Systems. 2023; 7(3):73. https://doi.org/10.3390/soilsystems7030073

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Gabechaya, Valeria, Irina Andreeva, Dmitriy Morev, Alexis Yaroslavtsev, Alexander Neaman, and Ivan Vasenev. 2023. "Exploring the Influence of Diverse Viticultural Systems on Soil Health Metrics in the Northern Black Sea Region" Soil Systems 7, no. 3: 73. https://doi.org/10.3390/soilsystems7030073

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