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Article

The Effects of Crops Together with Winter Cover Crops on the Content of Soil Water-Stable Aggregates in Organic Farming

1
Chair of Soil Science, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51006 Tartu, Estonia
2
Chair of Animal Breeding and Biotechnology, Institute of Veterinary Medicine and Animal Sciences, Estonian University of Life Science, 51006 Tartu, Estonia
3
Chair of Crop Science and Plant Biology, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51006 Tartu, Estonia
*
Author to whom correspondence should be addressed.
Agriculture 2021, 11(11), 1035; https://doi.org/10.3390/agriculture11111035
Submission received: 9 July 2021 / Revised: 14 October 2021 / Accepted: 17 October 2021 / Published: 22 October 2021
(This article belongs to the Section Agricultural Soils)

Abstract

:
The stability of the soil aggregates is an important soil quality indicator, as it affects the soil’s overall functionality. As the soil aggregates are highly affected by agricultural practices, it is essential to know how crops interact with the aggregation process. Therefore, for obtaining more knowledge, this research was conducted in Estonia in an organic crop rotation field experiment from 2012/2013 through 2015/2016 to study the effects of crops (potato → spring barley undersown with red clover → red clover → winter wheat → pea) under different treatments (TC—control; TW—winter cover crops; TW+MTW with farmyard manure 40 Mg ha−1 per crop rotation). The results showed that in the topsoil (5–10 cm), the soil water-stable aggregate (WSA) content (determined by the wet sieving method) from highest to lowest was following: pea (61.7%), winter wheat (61.6%), spring barley (61.5%), red clover (59.3%), potato (57.1%); whereas in the subsoil (30–35 cm): potato (50.6%), pea (48.5%), red clover (47.9%), spring barley (47.7%), winter wheat (46.4%). Therefore, potato was a noticeable crop, as among the crops, it had the lowest WSA content in the topsoil, while highest in the subsoil. The results shown gave an assumption that the after-effects of some crops (foremost with pea) were noticeable in the soil properties during the following crop. In the topsoil, the differences between crops were significant among crops just for TW and TW+M treatments. In TW, potato was lower than spring barley and winter wheat, but not significantly lower than pea or red clover. In the subsoil, significant differences between crops were observed for TC and TW treatments: in TC, potato was just significantly greater than red clover (but similar to other crops), and in TW, significantly greater than winter wheat. Furthermore, in the topsoil the soil organic carbon (SOC) content was not significantly affected by crops, and the use of winter cover crops generally increased the SOC content while concurrently decreased the WSA content and the soil maximum water holding capacity. This was probably caused by the additional tillage operations which cancelled out the possible benefits for the soil aggregates. As a consequence of the constantly declining SOC content, caused by the weakened soil aggregates, the plant-available P and K contents, especially in the absence of manure applications, decreased as well, probably due to the combination of fixation and removal of plant biomass. Therefore, it is expected that by continuing this trend, the plant growing conditions decline, which in turn will have a negative effect for the aggregate formation and carbon sequestration, which are essential for plant growth.

1. Introduction

The total land area dedicated to organic farming is annually increasing in almost all European Union’s (EU) 27 member states [1]. During the eight-year period from 2012 to 2019, the increase was 45.8%, from 9,457,886 ha to 13,794,106 ha, respectively [1]. In terms of organic area proportion within the utilized agricultural land, Estonia clearly stands out. Based on the data in 2019, its proportion was the second highest of the EU’s 27 member states, 22.3%, of which 19.5% was purely organic and 2.8% was in the transition period. For comparison, based on the data in 2018, the average proportion of the organic area within the utilized agricultural land of the 27 EU countries was 8.0% [1]. This, foremost in Estonia, but also in other EU member states, is most likely caused by multiple factors: (i) the EU policy for subsidizing organic farming, by which conventional agricultural land is converted into organic land [2]; (ii) the increased living standard of consumers, enabling them to afford more expensive agricultural products [3]; (iii) the raised consumer awareness about potentially healthier pesticide-free food [4], and (iv) the increased concerns of environmental aspects [5]. Therefore, if everything remains the same, the organic land area, as well as the popularity of organic products both in Estonia and in other EU member states, is expected to rise even more in the future.
From an agricultural point of view, organic farming is very different from conventional farming due to the absence of mineral fertilizers. Thus, for maintaining soil fertility and quality, in terms of sustaining or improving the soil structure by its content of water-stable aggregates (WSA), fewer resources for soil input are available [6]. The organic agriculture greatly relies on the usage of organic fertilizers, foremost in manure, and by the choice of crops within the crop rotation, as well as on the use of winter cover crops [7]. Having a high content of WSA is important, due to the known fact that they affect the soil’s water storage and movement as well as gas exchange; thereby the soil functionality in general from the plant growth perspective [8].
The vast majority of previous research that focused on the soil aggregation processes has been conducted under conventional farming, and in those studies, the focus was mostly placed on the crop rotation and tillage types [9] and, in a limited form, on the effects of winter cover crops on aggregate stability [10,11]. However, the effects of individual crops within the crop rotation on the aggregate stability, especially in such pedo-climatic conditions which occur in Estonia, have been currently insufficiently studied.
Among crops, potato, due to its high tillage requirements, is known to reduce the WSA content [12,13] as a consequence of enhanced mineralization of the soil organic matter [14] as well as by the mechanical disruption of aggregates. The effects of legumes on the WSA content are not unambiguously understood. Since legumes, in general, mostly have a smaller fibrous root system than cereals and grasses [15]. Thus, their contribution to aggregate binding could, therefore, be lower [16]. However, their nitrogen-fixing ability, in the Baltic pedo-climatic conditions, can increase the soil fertility and thus increase the root biomass production in the subsequent crops, which, in turn, can increase the soil’s organic matter content and, thereby, the WSA content [17]. Additionally, as legumes are known to stimulate the soil microbial activity, they contribute to the abundance of arbuscular mycorrhizal fungi [18], which has positive effects on the soil aggregate stability [16]. Those assumed effects could be even more profound with the use of perennial forage legumes like white clover (Trifolium repens L.) or hybrid alfalfa (Medicago sativa subsp. x varia Martyn), as the soil is undisturbed for a longer period than it is with an annual crop [17]. Both winter and spring cereals, are highly profitable crops and are thus preferred by farmers in the crop rotation, while their effects from a soil structural perspective are not completely clear. The cereal residue management has a substantial impact and can determine the soil organic carbon (SOC) balance [19] and, thus, indirectly influence the WSA content. The winter cereals are also beneficial because they provide soil coverage during the non-growing period and, thus, they act like winter cover crops by protecting the soil from erosion and rain drop forces [20], which may be highly beneficial to the WSA content. However, those effects are highly variable and depend foremost on the soil surface coverage, which is often insufficient [21].
Based on the shortcomings of previous studies, the objective of the current research was to study the effects of crops on the soil aggregate stability and its closely related soil properties in organic farming conditions. Following hypothesizes were formulated: (i) with the manure incorporation the negative effects of potato cultivation on the soil structure can be alleviated to a large extent; (ii) winter cereals are more beneficial for the soil structure than spring cereals, due to their extended period of soil coverage; (iii) the cultivation of legumes, regardless of whether they are annual or perennial, are more beneficial for the soil structure than cereals. Therefore, to test those proposed hypotheses, this study was conducted on a previously established organic field experiment, located in Estonia, which had a five-year crop rotation (pea, potato, spring barley, red clover, winter wheat).

2. Materials and Methods

2.1. Field Experiment Description

The study was conducted in the period of 2012/2013 through 2015/2016 on an organic farming experimental field located in Estonia near Tartu (N 58°21′54″, E 26°39′59″). The soil was a Stagnic Luvisol (LV-st-lo) [22] with a sandy loam texture (sand: 56.5%; silt: 34.0%; clay: 9.5%) based on the FAO classification. This type of soil represents ~6% of the total Estonian land area (same as in Europe overall) and ~15% of the Estonian arable land and is mostly located in the southeastern part of Estonia.
Estonia, except the western coast with its islands, is located in a humid continental climate region. The data on air temperature and precipitation were based on the Estonian Environment Agency weather station measurements taken near Tartu in Tõravere (N 58°15′50.27″, E 26°27′41.67″), located 16.5 km away from the field experiment (Table 1). According to the weather station data, there was a high seasonal and annual variability in both the temperature and precipitation. The whole study period (2012/2013 to 2015/2016) compared with the long-term data (1987–2016) was 0.5 °C, or 8.2%, higher in temperature and 15 mm, or 2.2%, higher in precipitation than the average. In 2013, both the overall precipitation (541 mm) and the precipitation in two consecutive months in June (35 mm) and July (59 mm), were the lowest during the study period. This, in addition to relatively high mean temperatures in the summer, especially in June (18.2 °C), indicated a drought period in the summer of 2013.
The organic field experiment (30 m × 120 m) consisted of three side-by-side located fields (10 m × 120 m), each with a different treatment: (i) TC—control without winter cover crops (WCC); (ii) TW—winter cover crops and (iii) TW+M—winter cover crops with the addition of fermented cattle farmyard manure. All those three fields consisted of 20 individual plots, it total 60 plots; each with a size of 10 m × 6 m. Those plots represented one crop within the crop rotation in four replications. The detailed schema of the experiment was depicted in Table 2. The crops in the crop rotation were: (1) pea (Pisum sativum L.), followed by (2) potato (Solanum tuberosum L.), followed by (3) spring barley (Hordeum vulgare L.) undersown with red clover (Trifolium pratense L.), followed by (4) red clover, followed by (5) winter wheat (Triticum aestivum L.). The sowing rates were: (i) pea, 100 seeds m−2; (ii) potato, 5.3 tubers m−2; (iii) barley with red clover undersown, 375 and 280 seeds m−2, respectively; and (iv) winter wheat, 450 seeds m−2. As for the winter cover crops: winter rye (Secale cereale L.) (220 kg ha−1), rapeseed (Brassica napus L. ssp. oleifera var. biennis) (6 kg ha−1) and their mixture (226 kg ha−1) were sown on TW and TW+M in autumn after the harvest of potato, pea and winter wheat, respectively. The manure in TW+M was manually applied in April for potato (20 Mg ha−1), spring barley (with red clover undersown) (10 Mg ha−1) and winter wheat (10 Mg ha−1). By average, the fermented cattle farmyard manure contained following: Ctot 138 g kg−1, Ntot 9.7 g kg−1, Ptot 4.6 g kg−1, Ktot 8.6 g kg−1, Ca 11.7 g kg−1, Mg 3.4 g kg−1 and 44.8% dry matter. Thereupon, manure was plowed with the winter cover crops up to 22 cm into the soil one week before the planting of potato and sowing the spring barley together with red clover.
The pea, winter wheat and spring barley together with red clover were sown with a Kongskilde Combiseed N30 seed driller; depending on the year, at the end of April or at the beginning of May and the winter cereal during late August. The potato was planted with a Juko Ekengards 4100 at the beginning of May. The potato plots were additionally plowed at 25 cm and then harrowed up to 4–5 cm depth before planting. During the growth period, the potato rows were regularly furrowed and hilled. Mechanical weed harrowing was used twice to control weeds in cereals, potato and pea; additionally in potato at a later growth stage, weeds were removed manually. A spring-tine harrow with a working width of 3 m was used for harrowing.
The cereals and peas were harvested between early and mid-August, depending on the maturity and weather conditions, by using a Sampo SR2010 harvester. The red clover yields were harvested for the first time during the end of June and for the second time during the end of August, by a Müthing Mu-H/S 140 flail mower; after the second cut the red clover was plowed into the soil up to 29 cm by using a Kverneland ES80 reversible plow. The potatoes, depending on the weather conditions, were harvested during late August or early September, by using a two-row elevator-type harvester. During the entire experiment, all plant residues (except potato tubers and cereal grains) were returned back to the soil.

2.2. Soil Material

The soil samples were collected during April in all years, one or two weeks before applying manure. Sampling cylinders (average capacity: 88.2026 mL; height: 40 mm; internal diameter: 53 mm) were used to collect undisturbed soil material from the topsoil (5–10 cm) and subsoil (30–35 cm); from both depths four samples were taken. Thus, eight samples per plot were collected. Despite the topsoil being tilled almost annually within the entire depth of 0–30 cm, it was expected that the largest amount of root mass was located at a depth of 5–10 cm and therefore this range was the most relevant for determining the effects of crops.
Each soil-filled cylinder was placed inside a semi-transparent plastic cup and hermetically sealed with a lid. After fieldwork, those cylinders were placed into a cold storage facility (4 °C) to reduce the risk of soil organic matter degradation; to be used later to determine the maximum water holding capacity (Wmax). The soil material for determining the soil water-stable aggregate (WSA) content was collected from the previously mentioned depths at the same time and stored in zipped transparent plastic bags. To conduct the chemical analyses, a soil auger was used to collect material from the topsoil at 0–23 cm depth.

2.3. Physical Measurements

To determine the soil-water stable aggregate stability, loose, air-dried soil material was gently crushed with a mortar and pestle, to reduce the content of large peds, and sifted through a 2 mm sieve, then 4 ± 0.01 g of sieved soil was weighed and added in four replications into the mesh of an Eijkelkamp’s Wet Sieving Apparatus (model: 08.13), which had a 0.25 mm opening. The soil samples, within the sieves, were slowly pre-moistened with a fine plant sprayer and then later slowly immersed into the caps filled with purified water. The device and the procedure were described in more details by Kemper and Rosenau [23], with the exception that instead of the original 0.2% NaOH solution, 0.4% was used, to accelerate the dissolving process of the organic matter. The WSA content calculation process was following:
C H 2 O   = M H 2 O   C A L
C NaOH = M NaOH C 316 L 0.4   g NaOH
WSA % = C NaOH C H 2 O + C NaOH   × 100
where, “ C H 2 O   ” is the weight of dried soil which was dissolved in purified water after three minutes of sieving; “CAL” is the weight of the aluminum cap; “ M H 2 O ” is the combined weight of “ C H 2 O   ” and “CAL”; “CNaOH”is the weight of dried soil which was dissolved by sieving in the 0.4% NaOH solution; “C316L” is the weight of the stainless steel cap; “MNaOH” is the combined weight of “C316L”; “0.4 gNaOH” is the weight of the 0.4% NaOH solution; “WSA%” is the content, in percentages, of the soil-water stable aggregates.
To determine the soil maximum water holding capacity, the soil-filled sampling cylinders were first weighed and then placed in a water bath for 24 h, with the purpose of ensuring complete saturation of the soil pores. Next, those saturated soil-filled sampling cylinders were placed for 10 min on an expanded polystyrene foam (length: 200 mm; width: 80 mm; height: 25 mm) covered with one layer of filter paper, which acted as an absorbent membrane [24]; then weighed, then placed into a drying oven for 24 h at 105.5 °C and thereupon weighed for the final time.

2.4. Chemical Analysis

The total nitrogen (Ntot) content was determined with the Kjeldahl method [25]. The ammonium lactate (AL) method [26] was used to measure the contents of plant-available: (i) phosphorous (PA), (ii) potassium (KA), (iii) calcium (CaA) and (iv) magnesium (MgA). The total carbon content was measured by Dumas combustion method using a VarioMax CNS analyzer (ELEMENTAR, Germany). Considering that the average soil pHKCl was 6.0, and therefore carbonates were absent, it was assumed that the soil total carbon content was equivalent to that of the soil organic carbon (SOC) content.

2.5. Data Analysis

The normality of variables was prior checked to ensure that the preconditions have been fulfilled for the analysis of variance. Multi-factorial analysis of variance (ANOVA) was used to determine the statistical significance of the soil’s physical properties (WSA content and Wmax) individually from both depths (topsoil: 0–5 cm; subsoil: 30–35 cm), between the crops, winter cover crop management systems, yearly differences and their interactions. The same analysis was used in all soil’s chemical properties (SOC, Ntot, PA, KA, MgA, CaA and C:N), but only from the topsoil (0–23 cm). As due to soil disturbances caused by plowing those properties were expected to be homogeneous within the entire plow layer. Additionally, in all ANOVA tests the plots were considered as random factors. The Tukey’s HSD (honest significant difference) was used as a post-hoc test. The correlations between the WSA content and other physical-chemical properties were calculated in a pair-wise configuration. The data analyses were performed by using Dell Statistica version 13.2 (2016); in all tests, results were considered significant if p < 0.05.

3. Results

3.1. The Effects of Crops, Treatments, Yearly Differences and Depths on the Soil Water-Stable Aggregate Content

The results of the ANOVA showed that in both depths the interactions between the crops and all factors, for the WSA content, as well as Wmax, were statistically significant (Table 3). Furthermore, the interactions between crops and treatments, as well as crops and the yearly differences, for the WSA content and Wmax in were also significant in both depths. The crops were significant for the WSA content and Wmax in both depths; however, it was remarkable, that in the subsoil the effects of crops for the WSA content and Wmax, despite being significant, were still considerably weaker (p = 0.012 and p = 0.037, respectively) than in the topsoil (both p < 0.001). The treatments were significant in both depths for the WSA content; however, for the Wmax, those treatments were significant only in the topsoil. The yearly differences were significant for the WSA content and Wmax in both depths.
The averaged WSA content in the topsoil was 24.9% higher than in the subsoil; with a few exceptions the WSA content in the topsoil was always higher than in the subsoil (Table 4). When all years and treatments were averaged, in the topsoil among all crops, potato had the lowest (57.1%) WSA content (significantly in TW and TW+M), while, at the same time in the subsoil, it had the highest (50.5%) WSA content (significantly in TC and TW) among crops. Additionally, in the topsoil, the WSA content in potato treatments steadily decreased from TC to TW+M, which was generally the opposite with other crops. In the subsoil, the WSA content in potato was also highest in TC (this time significantly); however, the lowest WSA content was found in TW. This occurred even though both treatments differed significantly from the control. In the subsoil, all crops had the lowest WSA content in TW, whereas in the topsoil, only pea had the lowest WSA content in TW. Furthermore, pea was a notable crop in the topsoil; as compared with others, it was relatively unaffected by treatments and, at the same time, had the highest WSA content (61.7%), followed closely by winter wheat (61.6%) and spring barley (61.5%). In the subsoil, pea (48.6%) had the second highest WSA content as well, and the difference between spring barley (47.7%) and winter wheat (46.4%) increased. In general, if treatments from all years and depths were averaged, pea (55.2%) had the highest, while potato (53.8%) and red clover (53.6%) had the lowest WSA content; thus, the differences were not large. With the interactions between the WSA content and yearly differences, the patterns were not clearly recognizable. However, the period of 2014/2015 was noticeable, as in most cases, the WSA content in crops was much lower than in other years; this was especially drastic in TW. In the topsoil among all crops, except potato, the usage of farmyard manure contributed to an increase of the WSA content; whereas in TC there was a decline in all most crops except pea. Furthermore, regardless of depths, most significant differences among crops occurred in TW and TW+M treatments.

3.2. The Effects of Crops, Treatments, Yearly Differences and Depths on the Soil Maximum Water Holding Capacity

In the topsoil the lowest Wmax values among the crops occurred under spring barley, which, in most treatments, were statistically significant; in the subsoil however, this did not occur (Table 5). The study also revealed that in the topsoil the Wmax values with red clover and winter wheat steadily increased from TC to TW+M. In the subsoil, however, this same pattern occurred only with spring barley. The Wmax shared a similar sharp decline in 2014/2015 as with the WSA content, because those soil properties were positively correlated by each other (in the topsoil: r = +0.25; p < 0.001; N = 240 and in the subsoil: r = +0.57; p < 0.001; N = 240). However, during the study period, the Wmax, compared to the WSA content, had a much steeper decline, which was even noticeable in the manure applied TW+M treatment.

3.3. The Effects of Crops, Treatments and Yearly Differences on the Soil Organic Carbon Content

Based on the ANOVA results, the crops had no significant effect (p = 0.380) on the SOC content, but the treatments and yearly differences had (p = 0.048 and p = 0.004, respectively) (Table 6). During the study period a declining trend in the SOC content was noted among all crops; if all treatments were averaged, the SOC content declined 7%, from 1.64% to 1.53%; however, the decline was most severe in TC by 11.4%, from 1.61% to 1.53% and least severe with TW+M by 4.1%, from 1.67% to 1.60%. Despite the crops having no statistically significant effects on the SOC content, it was still noticed during the study period that the decline of the SOC content was highest under potato by average 15.1%, from 1.68% to 1.46%, and in TC even 26.2%, from 1.72% to 1.36%. It was also noticeable that the lowest decline occurred under winter wheat.

3.4. The Effects of Crops, Treatments and Yearly Differences on the Plant-Available Phosphorus and Potassium

According to the ANOVA results, there was a significant (p < 0.001) interaction between the crops and the yearly variation for the KA content (Table 6). Furthermore, individually, the crops, treatments and yearly variation too had significant (p = 0.003, p = 0.012 and p < 0.001, respectively) effects for the KA content. However, the PA content was significantly (p < 0.001) affected only by the yearly differences. During the study period the PA content steadily decreased among all crops (Table 7). Pea was the only crop that showed significant differences between treatments one out of the years (2015/2016). The KA content among crops during the study period was the lowest under potato (108.8 mg/kg), which was 9.5% lower than under red clover (119.1 mg/kg), which had the second lowest KA content. However, the KA content between spring barley (122.5 mg/kg), pea (123.5 mg/kg) and winter wheat (126.8 mg/kg) was very similar. Regardless of the crops, the KA content during the entire study period decreased; still, compared with the PA content, the decline was less severe and fluctuated more between the years.

4. Discussion

The reason why the topsoil potato had the lowest WSA content among all crops was most likely caused by the high number of tillage operations [27], which were further intensified by the use of WCC [11]. However, the reasons why in the subsoil potato had the highest WSA content, especially in the control treatment, were not completely clear. The first possible explanation could be the lasting after-effects of pea in the subsoil, as at the same soil layer pea had the second highest WSA content. The other possible explanation could be the relocation of dissolved organic matter from the topsoil into the subsoil [28], which could contribute to improvements in the soil structure. The reason why the WSA content among crops, except in potato, was higher in the topsoil than in the subsoil can be primarily associated with the decline of the SOC content by depth [17], as in the present study a positive correlation (r = +0.27; p < 0.001; N = 240) between the SOC content and the WSA content occurred (Table 8).
Furthermore, as the subsoil was located below the plow layer, it was unaffected by direct soil disturbances caused by the tillage, which further increased the contrasts between those soil layers. The high variability of the WSA content over the years was nothing novel, especially on such sandy-textured soils [13,29]. In the current study, those annual variations, besides the coarse soil texture, were most likely caused by the combination of the wetting-drying and freezing-thawing cycles [30], as well as by differences in plant growth, especially in the root development [31], and in the tillage [32]. The reason why, in all crops in the subsoil, the lowest WSA content occurred with the WCC treatments could be due to the disruption of the soil structure during the WCC growth process, either by the additional tillage or by compaction. Still, these consequences were considerably mitigated by the manure application, as the addition of organic matter most likely resulted in an increase in the SOC content. On the other hand, the use of WCC could be directly beneficial for the WSA content, as according to Shepherd et al. [33], the soil surface coverage, by at least 70%, greatly reduces the aggregate disrupting rain drop energy; as well as indirectly as a consequence by the increased SOC content [34]. However, the results of the present study suggest that despite the positive effects of the WCC on increasing the SOC content, the additionally required soil tillage operations cancelled out the possible benefits for the WSA content; such findings were similar to those of Sánchez de Cima et al. [11]. The most rational explanation why, in the topsoil under red clover and winter wheat, the WSA content and Wmax still increased from the control to the manure-applied WCC treatment despite the lack of dedicated WCC (as those crops already provided soil coverage during the winter) could be due to the after-effects of the previous crop(s), by which, especially by the manure application, the SOC content was increased. It was not fully understood why the crops in 2014/2015, especially with the WCC treatment, had the lowest WSA content and Wmax. Based on the obtained data, it could be suggested that this was most likely associated with compaction during the WCC sowing process, which were carried out in all years in August, and particularly since August of 2014 had the highest precipitation with 126 mm, which compared to the study period average of 89 mm, was 42% higher, the increased soil moisture content most likely made the soil more susceptible to compaction [35]. Nevertheless, the late harvesting, mostly caused by late rainfalls, could be an obstructive factor in the future for the growth of WCC as well as for the winter cereals, as with elevated soil moisture content, the soil structure is more susceptible to compaction during the sowing process [36]. Still, as mentioned already earlier, the present soil had precondition which favored large yearly fluctuations in the WSA content.
The limited effects of crops on the SOC content, could be the consequences of the crop rotation, by which the effects of individual crops were evened out. Thus, it could be suggested that more than one growth season is needed to see significant differences between the individual crops and the SOC content. The reason why the SOC content mostly declined during the study period was presumably due to the tillage operations, which, especially under potato, enhanced the mineralization of soil organic matter by disrupting the soil macro-aggregates. The decline could be also caused by insufficient carbon sequestration in the form of organic material input [37]. Although, the WCC treatments, especially with manure application, remarkably helped to lessen the decline, because manure not only enhances the soil directly with SOC, but also enhances the plant biomass production by fertilization [38].
The significant positive correlation (r = +0.61; p < 0.001; N = 480) between the WSA content and Wmax clearly indicated the importance of a stable soil structure on its water retention capacity. Even though, in Estonia, the annual precipitation exceeds the evaporation rate, drought periods with various lengths during the growing season still occasionally occur. Therefore, maintaining a high WSA content can help to reduce the volatility of plant yields caused by water deficit during the growing season [39], and it could also help to reduce the leaching of soil nutrients during the wet periods as well. The reason why in the topsoil that the significant lowest Wmax occurred in spring barley was most likely due to the after-effects of previously grown potato; therefore, it can be concluded that the destructive effects of potato tillage on the soil water retention lasted longer than on the WSA content. Compared to the WSA content, the greater decline of the Wmax during the study period could be an indication that the Wmax was more sensitive to the SOC decrease than the WSA content. Limited support for this assumption was found in the correlations where the Wmax and the SOC content (r = +0.33; p < 0.001; N = 240) were slightly more correlated than the WSA content and the SOC content (r = +0.27; p < 0.001; N = 240).
The positive correlations of the PA and KA content between the WSA and SOC content (Table 8) can be explained in multiple ways. At first, as both those soil nutrient are essential for plant growth, they helped to increase the biomass production and enhanced the root system [17], by which a greater degree of root exudes were released, which acted as transient and temporary binding agents for the aggregates [16]. The second reason can be explained by the complex dynamics and interactions between the soil nutrients, SOC and WSA content [40,41]. For instance, a large amount of the PA is stored in the inter-aggregated soil organic matter [41,42]. Thus, a disruption of those aggregates will cause mineralization in the organic matter and this, in turn, increases the sorption of phosphorous to silt and clay particles, through which, as a consequence, the soil PA decreased [41]. While the soil clay content was small, the silt content still contributed to 1/3 of the soil’s mineral particles and, thus, its impact on phosphorous, as well as on potassium fixation must not be underestimated [42]. As the phosphorous leaching is negligible, the main reason for the decline was the fixation thru sorption, through which the total pool of phosphorous still remained unchanged [43] and as well as by the removal of plant biomass in the form of plant yields. Despite the above-mentioned positive correlation between the contents of KA and WSA, the effects of potassium on the soil aggregates are still controversial, although lately, the vast majority of researchers still favor that potassium does have positive effects on the aggregation [44]. However, in the present study, the positive correlation could be related to the low clay content (9.5%) of the soil, as potassium has been found to affect the inter-particle bonds in clays by dispersing clay particles [45]. Thus, in the present context, the benefits of potassium by the increased biomass production and thus in the carbon sequestration [17], as between the KA and SOC content, a significant correlation occurred (r = +0.44; p < 0.001; N = 240), which likely outweighed the dispersing effects of clay particles. Compared to the other crops, the lowest KA content, found under potato, was due to the known fact that this crop has a high potassium requirement [46], and therefore, a great amount of KA was removed from the soil along with the potato tubers [46]. The second-lowest KA content, which occurred under with red clover, could also be associated with the highest dry mass yields (data not presented) among the crops, by which large quantities of potassium were removed; however, the difference in this case was that the harvested biomass yields were returned and left on the plots to decompose, through which the potassium was slowly released back into the soil. In this case, some of the released potassium will still eventually be leached out of the soil [47]. The fluctuation in the KA content over the years could be explained by the complex potassium fixating-releasing processes in this feldspar-rich soil parent material. When compared to the PA content, the less severe decline in the KA content could be related to the soil enrichment by atmospheric precipitation. According to the data from the Estonian Environment Research Center near Tartu during 2012–2016, the mean soil enrichment by K+ with precipitation was ~2.6 kg ha−1 yr−1 ± 0.8 SE. While in general, according to the Estonian soil nutrient gradation classification for this soil texture, based on the Mehlich 3 method, the average PA content was considered as high, and the KA content was considered as medium, because they ranged between 81–120 mg/kg and 100–200 mg/kg, respectively [48]. However, in a longer time period, the depletion of those plant-available nutrients could be detrimental to the WSA content and impede the overall soil functionality.
As for the potential limitations of this study, which might affected the results and the interpretation of the conclusion(s), following points have to be highlighted: (1) the absence of a comparison study under conventional farming conditions; (2) the lack of different manure application rates for comparison; (3) the soil clay content was low—with a higher clay content the soil aggregation processes might differed; (4) the duration of the study was relatively short.

5. Conclusions

According to the primarily formulated hypothesizes, by the obtained results of this study: (i) the effects of potato were controversial, as in the topsoil (5–10 cm), among crops, it had the lowest WSA content and Wmax; while in the subsoil (30–35 cm) it had both the highest WSA content and Wmax. Furthermore, it was disproved that manure had any noticeable positive effects for the soil structure on potato; (ii) it was disproved that winter cereals were more beneficial for the soil structure than spring barley, as both had a similar WSA content and Wmax; (iii) from legumes, it was confirmed that pea, if averaged from both depths, had the highest WSA content, while the effects of red clover for the WSA content were considered average; still, the differences of pea and red clover compared to the other crops were not significant.
In overall, the differences between the crops were not substantially large, and the obtained results gave the assumption that some of the crops had lasting after-effects to the soil structure-related properties in the following crops. The effects of the WCC were controversial; on the one hand, they did slightly increase the SOC content, but on the other hand, due to the additional tillage operations, they had a destructive effect on the WSA content and Wmax. However, if farmyard manure was added, the WCC consequences on the WSA content were largely eliminated. Besides the negative nutrient balance, the decline in the PA and KA contents was also the consequence of the declining SOC content, which, inside the soil aggregates, acted as storage for the plant-available nutrients. Therefore, by continuing this trend, especially in the absence of manure applications, the decline in plant biomass yields is obvious. This in turn decreases the stability of soil aggregates and the carbon sequestration, as both are significantly interconnected by each other. Still, as the aggregation process is complex; based on the limitations of this study, more diverse studies for deeper knowledge of those processes in different aspects are needed.

Author Contributions

Conceptualization, M.A., T.K., A.S. and E.R.; methodology, M.A., A.S., E.R. and T.K.; software, E.R.; validation, A.S. and E.R.; formal analysis, M.A.; investigation, M.A. and E.R.; resources, E.R.; data curation, M.A. and T.K.; writing—original draft preparation, M.A.; writing—review and editing, A.S., T.K. and E.R.; visualization, M.A. and T.K.; supervision, E.R., T.K. and A.S.; project administration, M.A. and E.R.; funding acquisition, E.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the Horizon 2020 project iSQAPER (project number 635750) and by the ERA-NET Core organic project FertilCrop (project number 8-2/T15015PKTK).

Acknowledgments

The authors express their great gratitude to the Chair of Crop Science and Plant Biology for maintaining the field experiment as well as everyone else involved in this.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. The average air temperature and sum of precipitation, during the years of study and compared with long-term (30-year) averages.
Table 1. The average air temperature and sum of precipitation, during the years of study and compared with long-term (30-year) averages.
Temperature (°C):
Quarter201220132014201520162012–20161987–2016
Q1−5.0−5.8−1.80.3−3.0−3.1−3.1
Q210.412.411.010.312.111.210.9
Q315.415.516.315.415.715.715.3
Q40.74.41.93.71.12.41.4
Average5.46.76.97.56.56.66.1
Precipitation (mm):
Quarter201220132014201520162012–20161987–2016
Q11398585109155115120
Q2205144240206279215173
Q3230161224183205200213
Q4198151153124150155165
Total772541701622789685671
Notes: Q1—January, February, March; Q2—April, May, June; Q3—July, August, September; Q4—October, November, December.
Table 2. The schema of the field experiment, which reflects the cropping sequence in spring of 2015 and 2016.
Table 2. The schema of the field experiment, which reflects the cropping sequence in spring of 2015 and 2016.
2016 Spring
TC TW TW+M
IV20 potato40 potato + WW60 potato + WW + M20
19 s. barley39 s. barley59 s. barley + M10
18 red clover38 red clover58 red clover
17 w. wheat37 w. wheat + WWR57 w. wheat + WWR + M10
16 pea36 pea + WR56 pea + WR
III15 potato35 potato + WW55 potato + WW + M20
14 s. barley34 s. barley54 s. barley + M10
13 red clover33 red clover53 red clover
12 w. wheat32 w. wheat + WWR52 w. wheat + WWR + M10
11 pea31 pea + WR51 pea + WR
II10 potato30 potato + WW50 potato + WW + M20
9   s. barley29 s. barley49 s. barley + M10
8   red clover28 red clover48 red clover
7   w. wheat27 w. wheat + WWR47 w. wheat + WWR + M10
6   pea26 pea + WR46 pea + WR
I5   potato25 potato + WW45 potato + WW + M20
4   s. barley24 s. barley44 s. barley + M10
3   red clover23 red clover43 red clover
2   w. wheat22 w. wheat + WWR42 w. wheat + WWR + M10
1   pea21 pea + WR41 pea + WR
2015 Spring
TCTWTW+M
IV20 pea40 pea + WR60 pea + WR
19 potato39 potato + WW59 potato + WW + M20
18 s. barley38 s. barley58 s. barley + M10
17 red clover37 red clover57 red clover
16 w. wheat36 w. wheat + WWR56 w. wheat + WWR + M10
III15 pea35 pea + WR55 pea + WR
14 potato34 potato + WW54 potato + WW + M20
13 s. barley33 s. barley53 s. barley + M10
12 red clover32 red clover52 red clover
11 w. wheat31 w. wheat + WWR51 w. wheat + WWR + M10
II10 pea30 pea + WR50 pea + WR
9   potato29 potato + WW49 potato + WW + M20
8   s. barley28 s. barley48 s. barley + M10
7   red clover27 red clover47 red clover
6   w. wheat26 w. wheat + WWR46 w. wheat + WWR + M10
I5   pea25 pea + WR45 pea + WR
4   potato24 potato + WW44 potato + WW + M20
3   s. barley23 s. barley43 s. barley + M10
2   red clover22 red clover42 red clover
1   w. wheat21 w. wheat + WWR41 w. wheat + WWR + M10
Notes: TC—control treatment without winter cover crops; TW—treatment with winter cover crops; TW+M—treatment with winter cover crops and with additional fermented cattle farmyard manure application. Roman numbers, in left of the table, indicate the replication number. Superscripted numbers indicate the plot numbers. Winter cover crops: WW—winter rye; WR—rapeseed WWR—mixture of winter rye and rapeseed. Farmyard manure application rates: M10—10 Mg ha−1; M20—20 Mg ha−1.
Table 3. Results of the full-factorial analysis of variance from the topsoil (5–10 cm) and subsoil (30–35 cm) between the crops, winter cover crop management systems, yearly differences and their combined interactions of which effects were tested on the soil water-stable aggregate (WSA) content and soil maximum water holding capacity (Wmax).
Table 3. Results of the full-factorial analysis of variance from the topsoil (5–10 cm) and subsoil (30–35 cm) between the crops, winter cover crop management systems, yearly differences and their combined interactions of which effects were tested on the soil water-stable aggregate (WSA) content and soil maximum water holding capacity (Wmax).
Topsoil (5–10 cm)Subsoil (30–35 cm)
WSAWmaxWSAWmax
CF4.900 = 17.60
p < 0.001
F4.900 = 14.32
p < 0.001
F4.900 = 3.23
p = 0.012
F4.900 = 2.57
p = 0.037
TF2.900 = 5.23
p = 0.006
F2.900 = 1.89
p = 0.152
F2.900 = 54.22
p < 0.001
F2.900 = 28.77
p < 0.001
YF3.900 = 44.98
p < 0.001
F3.900 = 81.34
p < 0.001
F3.900 = 22.32
p < 0.001
F3.900 = 58.16
p < 0.001
C × TF8.900 = 3.58
p < 0.001
F8.900 = 3.90
p < 0.001
F8.900 = 1.95
p = 0.049
F8.900 = 3.11
p = 0.002
C × YF12.900 = 8.77
p < 0.001
F12.900 = 4.35
p < 0.001
F12.900 = 4.63
p < 0.001
F12.900 = 3.53
p < 0.001
T × YF6.900 = 52.30
p < 0.001
F6.900 = 8.06
p < 0.001
F6.900 = 24.81
p < 0.001
F6.900 = 23.19
p < 0.001
C × T × YF24.900 = 3.66
p < 0.001
F24.900 = 2.48
p < 0.001
F24.900 = 3.33
p < 0.001
F24.900 = 2.06
p = 0.002
Factors: C—crops; T—winter cover crop management systems; Y—yearly differences. Soil Parameters: WSA—the content of soil water-stable aggregates; Wmax—soil maximum water holding capacity.
Table 4. The average content of soil water-stable aggregates (%) with the standard error (SE) of mean in the topsoil (5–10 cm) and subsoil (30–35 cm) by crops, winter cover crop management systems and years.
Table 4. The average content of soil water-stable aggregates (%) with the standard error (SE) of mean in the topsoil (5–10 cm) and subsoil (30–35 cm) by crops, winter cover crop management systems and years.
YearTopsoil (5–10 cm)Soil water-stable aggregate (WSA) content (%)
PeaPotatos. BarleyCloverw. Wheat
TC2015/201660.7 ± 1.1 Ba49.2 ± 2.4 Aa52.0 ± 1.4 Aa49.4 ± 2.7 Aa51.7 ± 2.1 Aa
2014/201558.4 ± 0.957.4 ± 1.8 b53.8 ± 1.4 a55.7 ± 1.6 ab57.0 ± 0.8 ab
2013/201464.4 ± 0.9 b64.5 ± 1.9 b66.8 ± 2.6 b62.2 ± 1.5 b67.1 ± 1.2 b
2012/201362.0 ± 1.2 a63.3 ± 1.463.8 ± 1.3 a62.7 ± 1.163.5 ± 1.3 b
Average61.4 ± 0.658.6 ± 1.259.1 ± 1.2a57.5 ± 1.159.9 ± 1.0
TW2015/201669.0 ± 1.9 BCb56.7 ± 1.3 Ab63.3 ± 1.3 Bb64.0 ± 1.9 Bb70.8 ± 1.7 Cb
2014/201560.0 ± 1.6 C46.9 ± 0.8 Aa53.8 ± 1.5 Ba52.9 ± 1.5 Ba54.7 ± 1.1 Ba
2013/201451.7 ± 4.3 Aa61.3 ± 2.2 Bb65.5 ± 1.6 Bb61.4 ± 1.0 Bb63.6 ± 1.2 Bb
2012/201361.4 ± 1.1 Aa63.1 ± 1.6 A69.6 ± 1.3 Bb60.1 ± 1.4 A58.6 ± 1.8 Aa
Average60.5 ± 1.5AB57.0 ± 1.1A63.0 ± 1.0Bb59.6 ± 0.9AB61.9 ± 1.0B
TW+M2015/201672.2 ± 1.5 Bb56.8 ± 2.0 Ab65.8 ± 1.5 Bb68.2 ± 1.9 Bb68.6 ± 1.6 Bb
2014/201560.2 ± 1.5 B49.7 ± 2.5 Aa63.8 ± 2.4 Bb59.6 ± 2.2 Bb61.3 ± 1.8 Bb
2013/201453.6 ± 1.4 a52.5 ± 1.1 a55.9 ± 1.8 a56.2 ± 1.1 a53.9 ± 1.4 a
2012/201367.3 ± 1.6 Bb63.4 ± 1.5 AB63.5 ± 1.3 ABa58.9 ± 1.7 A68.1 ± 1.1 Bb
Average63.3 ± 1.1B55.6 ± 1.1A62.3 ± 1.0Bab60.7 ± 1.0B63.0 ± 1.0B
YearSubsoil (30–35 cm)
PeaPotatos. BarleyCloverw. Wheat
TC2015/201646.6 ± 1.150.3 ± 3.0 b52.0 ± 2.9 b45.7 ± 3.9 ab57.4 ± 3.5 b
2014/201549.1 ± 2.8 ABb57.3 ± 1.8 Bb41.9 ± 3.0 Ab45.9 ± 4.7 ABb43.2 ± 2.2 Ab
2013/201454.1 ± 2.852.6 ± 3.055.2 ± 4.150.1 ± 3.3 ab47.7 ± 3.8 ab
2012/201359.1 ± 2.1 b63.9 ± 2.7 b54.3 ± 4.355.5 ± 3.058.1 ± 2.4
Average52.2 ± 1.1ABb56.0 ± 1.5Bb50.9 ± 1.9ABb49.3 ± 1.9Aab51.6 ± 1.7ABb
TW2015/201652.9 ± 3.4 B52.2 ± 2.0 Bb50.2 ± 1.6 ABb56.4 ± 2.1 Bb42.5 ± 2.2 Aa
2014/201529.3 ± 3.4 a36.2 ± 3.1 a31.9 ± 1.8 a28.7 ± 1.5 a27.7 ± 1.9 a
2013/201452.4 ± 3.1 B42.9 ± 3.1 AB33.3 ± 3.1 A38.8 ± 3.7 Aa37.1 ± 3.7 Aa
2012/201342.5 ± 3.4 a52.0 ± 1.9 a48.8 ± 4.751.5 ± 5.145.3 ± 5.5
Average44.3 ± 2.0ABa45.8 ± 1.6Ba41.0 ± 1.8ABa43.8 ± 2.1ABa38.2 ± 2.0Aa
TW+M2015/201645.3 ± 2.342.0 ± 2.2 a40.6 ± 1.4 a41.3 ± 3.2 a42.3 ± 2.6 a
2014/201561.1 ± 1.4 Bc60.2 ± 1.1 Bb48.4 ± 3.0 Ab53.9 ± 2.3 ABb48.8 ± 1.9 Ab
2013/201451.8 ± 2.8 B36.7 ± 2.5 A54.6 ± 4.2 B54.8 ± 3.3 Bb53.7 ± 1.5 Bb
2012/201339.1 ± 3.3 Aa61.2 ± 4.1 Bab60.9 ± 2.1 B52.7 ± 2.6 B52.4 ± 2.5 B
Average49.3 ± 1.6ab50.0 ± 1.9a51.1 ± 1.7b50.7 ± 1.6b49.3 ± 1.2b
Notes: TC—control treatment without winter cover crops; TW—treatment with winter cover crops; TW+M—treatment with winter cover crops and with additional fermented cattle farmyard manure application. Means (± SE) with different upper case letters (A, B, C) within a row are significantly different (Tukey’s HSD test; p < 0.05) between crops. Means (± SE) with different lower case letters (a, b, c) within columns are significantly different (Tukey’s HSD test; p < 0.05) between winter cover crop management treatments.
Table 5. The average soil maximum water holding capacity (weight %) with the standard error (SE) of mean in the topsoil (5–10 cm) and subsoil (30–35 cm) by crops, winter cover crop management system and years.
Table 5. The average soil maximum water holding capacity (weight %) with the standard error (SE) of mean in the topsoil (5–10 cm) and subsoil (30–35 cm) by crops, winter cover crop management system and years.
YearTopsoil (5–10 cm)Soil maximum water holding capacity (weight %) (Wmax)
PeaPotatos. BarleyCloverw. Wheat
TC2015/201626.5 ± 0.4 BC26.0 ± 0.5 ABC24.2 ± 0.5 Aa25.3 ± 0.3 ABa27.8 ± 0.7 C
2014/201530.0 ± 1.1 Bb30.2 ± 1.7 Bb23.8 ± 0.5 A28.4 ± 0.8 B26.7 ± 0.8 ABab
2013/201433.4 ± 0.9 Bb31.3 ± 0.7 AB29.1 ± 1.1 A30.1 ± 0.9 ABa28.8 ± 0.7 A
2012/201326.2 ± 0.5 Aa27.0 ± 0.6 AB29.0 ± 0.6 B28.1 ± 0.9 AB26.6 ± 0.7 AB
Average29.0 ± 0.5B28.6 ± 0.6Bb26.5 ± 0.5A28.0 ± 0.4ABa27.5 ± 0.4AB
TW2015/201628.0 ± 0.526.0 ± 1.326.8 ± 0.9 b28.2 ± 0.8 b28.3 ± 0.4
2014/201524.5 ± 0.4 Aa23.6 ± 0.7 Aa23.8 ± 0.7 A28.0 ± 0.9 B25.4 ± 0.8 ABa
2013/201429.5 ± 1.1 a30.3 ± 0.730.4 ± 0.932.1 ± 0.5 ab31.6 ± 0.9
2012/201329.9 ± 0.8 Bb27.6 ± 1.0 AB28.8 ± 0.5 AB30.2 ± 1.1 B26.4 ± 0.6 A
Average28.0 ± 0.5AB26.9 ± 0.6Aa27.5 ± 0.5A29.6± 0.5Bb27.9 ± 0.5AB
TW+M2015/201627.6 ± 0.9 AB26.4 ± 0.5 AB25.1 ± 0.7 Aab26.4 ± 0.7 ABab28.2 ± 0.8 B
2014/201525.8 ± 0.6 ABa27.5 ± 0.7 BCb23.8 ± 0.8 A29.6 ± 0.8 C28.3 ± 0.8 BCb
2013/201431.2 ± 1.3 ABab29.7 ± 0.8 A29.7 ± 0.7 A33.6 ± 0.8 Bb29.1 ± 1.0 A
2012/201330.0 ± 0.7 ABb28.8 ± 0.6 AB27.4 ± 0.5 A30.6 ± 1.1 B28.7 ± 0.9 AB
Average28.6 ± 0.5BC28.1 ± 0.4ABab26.5 ± 0.4A30.0 ± 0.5Cb28.6 ± 0.4BC
YearSubsoil (30–35 cm)
PeaPotatos. BarleyCloverw. Wheat
TC2015/201620.8 ± 1.321.8 ± 0.821.5 ± 0.8 ab19.9 ± 0.7 a21.6 ± 1.0
2014/201519.3 ± 0.4 ABa21.7 ± 0.6 B18.8 ± 0.9 A20.9 ± 1.0 ABb20.3 ± 0.5 ABb
2013/201423.0 ± 1.6 b24.2 ± 0.7 b24.1 ± 0.7 ab20.9 ± 0.7 b22.0 ± 0.9 b
2012/201324.2 ± 0.8 AB26.5 ± 1.0 Ba22.5 ± 1.1 A23.6 ± 1.0 AB22.4 ± 0.4 A
Average21.8 ± 0.6ABab23.5 ± 0.4Bb21.7 ± 0.5AB21.3 ± 0.5Aa21.6 ± 0.4Ab
TW2015/201620.3 ± 0.5 A21.6 ± 0.7 AB23.8 ± 0.8 ABb23.8 ± 0.6 ABb21.3 ± 0.6 AB
2014/201517.7 ± 0.4 a19.5 ± 1.217.7 ± 0.618.1 ± 0.4 a17.0 ± 0.2 a
2013/201418.9 ± 0.6 ABa17.2 ± 1.0 Aa21.4 ± 1.2 Ba17.1 ± 0.5 Aa17.0 ± 0.5 Aa
2012/201324.2 ± 1.422.7 ± 0.8 b24.0 ± 0.823.4 ± 1.123.8 ± 1.1
Average20.3 ± 0.5a20.2 ± 0.5a21.7 ± 0.520.6 ± 0.5a19.8 ± 0.5a
TW+M2015/201619.4 ± 0.520.9 ± 0.619.5 ± 0.4 a20.5 ± 0.6 a20.7 ± 0.6
2014/201522.9 ± 0.7 BCb21.9 ± 0.4 BC19.2 ± 0.4 A23.0 ± 0.6 Cb20.8 ± 0.5 ABb
2013/201423.8 ± 0.8 b22.9 ± 1.4 b25.2 ± 0.5 b25.2 ± 0.8 c22.1 ± 0.5 b
2012/201322.2 ± 0.7 A23.3 ± 0.7 ABb25.8 ± 1.2 B22.9 ± 0.7 AB24.5 ± 0.7 AB
Average22.1 ± 0.4b22.3 ± 0.4b22.4 ± 0.522.9 ± 0.4b22.0 ± 0.3b
Notes: TC—control treatment without winter cover crops; TW—treatment with winter cover crops; TW+M—treatment with winter cover crops and with additional fermented cattle farmyard manure application. Means (± SE) with different upper case letters (A, B, C) within a row are significantly different (Tukey’s HSD test; p < 0.05) between crops. Means (± SE) with different lower case letters (a, b, c) within columns are significantly different (Tukey’s HSD test; p < 0.05) between winter cover crop management treatments.
Table 6. Results of the full-factorial analysis of variance between the crops, winter cover crop management systems, yearly differences and their combined interactions of which effects were tested on different soil chemical properties.
Table 6. Results of the full-factorial analysis of variance between the crops, winter cover crop management systems, yearly differences and their combined interactions of which effects were tested on different soil chemical properties.
SOCNtotPAKAMgACaA
CF4.180 = 1.06
p = 0.380
F4.180 = 0.92
p = 0.452
F4.180 = 0.219
p = 0.928
F4.180 = 4.186
p = 0.003
F4.180 = 0.445
p = 0.776
F4.180 = 0.23
p = 0.920
TF2.180 = 3.09
p = 0.048
F2.180 = 2.80
p = 0.063
F2.180 = 0.333
p = 0.717
F2.180 = 4.575
p = 0.012
F2.180 = 6.633
p = 0.002
F2.180 = 3.31
p = 0.039
YF3.180 = 4.61
p = 0.004
F3.180 = 98.72
p < 0.001
F3.180 = 17.819
p < 0.001
F3.180 = 14.287
p < 0.001
F3.180 = 103.859
p < 0.001
F3.180 = 12.97
p < 0.001
C × TF8.180 = 0.35
p = 0.943
F8.180 = 0.41
p = 0.916
F8.180 = 0.280
p = 0.972
F8.180 = 0.268
p = 0.975
F8.180 = 0.149
p = 0.997
F8.180 = 0.21
p = 0.989
C × YF12.180 = 0.92
p = 0.524
F12.180 = 0.94
p = 0.504
F12.180 = 0.671
p = 0.778
F12.180 = 3.056
p < 0.001
F12.180 = 0.572
p = 0.862
F12.180 = 0.26
p = 0.994
T × YF6.180 = 0.48
p = 0.822
F6.180 = 1.10
p = 0.363
F6.180 = 1.279
p = 0.269
F6.180 = 0.780
p = 0.587
F6.180 = 0.144
p = 0.990
F6.180 = 1.66
p = 0.133
C × T × YF24.180 = 0.48
p = 0.981
F24.180 = 0.60
p = 0.932
F24.180 = 0.628
p = 0.910
F24.180 = 1.052
p = 0.404
F24.180 = 0.606
p = 0.926
F24.180 = 0.49
p = 0.978
Factors: C—crops; T—winter cover crop management systems; Y –yearly differences. Soil parameters: SOC—soil organic carbon content; Ntot—total nitrogen; PA—plant-available phosphorous; KA—plant-available potassium; MgA— plant-available magnesium; CaA— plant-available calcium. Significant results (p < 0.05) are marked in bold.
Table 7. The average plant-available phosphorous (PA) and potassium (KA) content (mg/kg) and their standard error (SE) of mean within the topsoil by crops, winter cover crop management systems and years.
Table 7. The average plant-available phosphorous (PA) and potassium (KA) content (mg/kg) and their standard error (SE) of mean within the topsoil by crops, winter cover crop management systems and years.
YearPA (mg/kg)
PeaPotatos. BarleyCloverw. Wheat
TC2015/201689.3 ± 4.8 a89.9 ± 7.688.8 ± 5.498.8 ± 10.399.3 ± 10.4
2014/201594.9 ± 16.2104.7 ± 16.6109.9 ± 16.2105.5 ± 12.7109.0 ± 17.0
2013/2014117.2 ± 12.2112.0 ± 16.5107.9 ± 9.1104.6 ± 9.7116.9 ± 14.8
2012/2013143.8 ± 10.9141.5 ± 8.6131.2 ± 10.1134.1 ± 10.2143.3 ± 12.3
Average111.3 ± 7.6112.0 ± 7.6109.5 ± 6.2110.7 ± 6.0117.1 ± 7.5
TW2015/2016109.9 ± 13.7 ab90.7 ± 10.192.7 ± 12.199.5 ± 17.296.5 ± 8.4
2014/2015102.8 ± 13.0112.6 ± 15.0102.4 ± 13.3106.4 ± 9.9112.4 ± 11.5
2013/2014106.0 ± 12.5124.3 ± 13.6120.5 ± 12.3118.7 ± 12.5109.0 ± 12.4
2012/2013126.6 ± 16.3130.4 ± 14.9137.4 ± 16.8121.5 ± 18.3126.0 ± 19.3
Average111.3 ± 6.7114.5 ± 7.2113.3 ± 7.6111.5 ± 7.0111.0 ± 6.6
TW+M2015/2016126.1 ± 5.4 b102.2 ± 3.9105.1 ± 5.5103.5 ± 8.3103.7 ± 7.2
2014/2015107.7 ± 12.4107.6 ± 14.796.7 ± 10.6103.4 ± 10.1129.6 ± 12.9
2013/2014118.6 ± 12.7109.4 ± 8.9103.4 ± 5.5137.0 ± 11.7120.2 ± 10.8
2012/2014111.6 ± 9.8113.7 ± 7.1151.3 ± 12.0123.2 ± 11.7124.9 ± 13.3
Average116.0 ± 5.0108.2 ± 4.4114.1 ± 6.9116.8 ± 6.0119.6 ± 5.7
YearKA (mg/kg)
PeaPotatos. BarleyCloverw. Wheat
TC2015/2016111.7 ± 6.494.0 ± 8.193.1 ± 6.2121.2 ± 16.2122.5 ± 9.9
2014/2015102.9 ± 7.497.7 ± 8.9114.0 ± 14.3120.8 ± 4.1126.0 ± 16.0
2013/2014112.9 ± 9.1102.3 ± 15.6117.0 ± 10.6109.2 ± 9.7113.2 ± 8.7
2012/2013143.3 ± 16.9133.3 ± 10.9135.8 ± 6.1125.6 ± 4.2136.2 ± 2.4
Average117.7 ± 6.2106.8 ± 6.4115.0 ± 5.9119.2 ± 4.7124.5 ± 5.1
TW2015/2016130.3 ± 11.791.8 ± 11.192.1 ± 7.996.8 ± 9.4110.8 ± 7.2
2014/2015127.3 ± 13.8111.8 ± 6.8121.9 ± 10.9124.5 ± 8.6138.3 ± 15.4
2013/2014106.5 ± 9.5102.7 ± 9.7109.8 ± 8.1118.0 ± 16.5105.5 ± 12.7
2012/2014121.6 ± 19.4117.5 ± 16.6164.6 ± 34.7123.5 ± 23.7129.0 ± 21.8
Average121.4 ± 6.7106.0 ± 5.8122.1 ± 11.0115.7 ± 7.6120.9 ± 7.6
TW+M2015/2016140.9 B ± 3.2114.4 A ± 5.9108.9 A ± 5.8102.6 A ± 5.7118.3 AB ± 7.4
2014/2015127.4 AB ± 8.3113.2 A ± 7.4104.4 A ± 7.3117.5 AB ± 8.2153.4 B ± 12.1
2013/2014131.9 ± 9.9105.8 ± 4.2116.3 ± 7.9138.3 ± 14.7128.0 ± 9.3
2012/2013125.2 A ± 5.2121.3 A ± 5.1192.2 B ± 7.7131.6 A ± 5.4139.9 A ± 9.3
Average131.3B ± 3.6113.7A ± 2.9130.5B ± 9.8122.5AB ± 5.5134.9B ± 5.5
Notes: TC—control treatment without winter cover crops; TW—treatment with winter cover crops; TW+M—treatment with winter cover crops and with additional fermented cattle farmyard manure application. Means (± SE) with different upper case letters (A, B, C) within a row are significantly different (Tukey’s HSD test; p < 0.05) between crops. Means (± SE) with different lower case letters (a, b, c) within columns are significantly different (Tukey’s HSD test; p < 0.05) between winter cover crop management treatments.
Table 8. Pearson’s correlations between aggregate stability soil chemical properties.
Table 8. Pearson’s correlations between aggregate stability soil chemical properties.
WSASOCNtotPAKAMgACaA
WSAn/an/an/an/an/an/an/a
SOC+0.27 ●●●n/an/an/an/an/an/a
Ntot+0.02+0.48 ●●●n/an/an/an/an/a
PA+0.24 ●●●+0.54 ●●●+0.34 ●●●n/an/an/an/a
KA+0.19 ●●+0.44 ●●●+0.40 ●●●+0.77 ●●●n/an/an/a
MgA+0.03+0.23 ●●●+0.54 ●●●+0.61 ●●●+0.61 ●●●n/an/a
CaA–0.03+0.32 ●●●+0.37 ●●●+0.67 ●●●+0.54 ●●●+0.61 ●●●n/a
Notes: WSA—the content of soil water-stable aggregates; SOC—soil organic carbon content; Ntot—total nitrogen; PA—plant-available phosphorous; KA—plant-available potassium; MgA—plant-available magnesium; CaA—plant-available calcium; n/a—not applicable. Number of data points: 240. Significant results are marked with: ●●p < 0.01; ●●●p < 0.001.
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Are, M.; Kaart, T.; Selge, A.; Reintam, E. The Effects of Crops Together with Winter Cover Crops on the Content of Soil Water-Stable Aggregates in Organic Farming. Agriculture 2021, 11, 1035. https://doi.org/10.3390/agriculture11111035

AMA Style

Are M, Kaart T, Selge A, Reintam E. The Effects of Crops Together with Winter Cover Crops on the Content of Soil Water-Stable Aggregates in Organic Farming. Agriculture. 2021; 11(11):1035. https://doi.org/10.3390/agriculture11111035

Chicago/Turabian Style

Are, Mihkel, Tanel Kaart, Are Selge, and Endla Reintam. 2021. "The Effects of Crops Together with Winter Cover Crops on the Content of Soil Water-Stable Aggregates in Organic Farming" Agriculture 11, no. 11: 1035. https://doi.org/10.3390/agriculture11111035

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