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Article

Assessing the Impact of No-Tillage Duration on Soil Aggregate Size Distribution, Stability and Aggregate Associated Organic Carbon

by
Kopano Conferance Phefadu
1,* and
Lawrence Munjonji
2
1
Department of Plant Production, Soil Science and Agricultural Engineering, University of Limpopo, P Bag X1106, Polokwane 0727, South Africa
2
Department of Soil Science, Faculty of AgriSciences, Stellenbosch University, P Bag X1, Stellenbosch 7602, South Africa
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(11), 2482; https://doi.org/10.3390/agronomy14112482
Submission received: 29 August 2024 / Revised: 21 October 2024 / Accepted: 22 October 2024 / Published: 24 October 2024
(This article belongs to the Special Issue Soil Organic Matter and Tillage)

Abstract

:
Soil aggregation results from the rearrangement, flocculation and cementation of primary soil particles. Furthermore, the aggregates undergo transformation under no-tillage (NT) overtime. Soil organic carbon (OC) is the major component of soil organic matter and is protected within aggregates and can serve as a proxy for soil structural stability. Organic matter contributes significantly to the formation of soil aggregates and the carbon within them is protected against degradation. This study assessed the impact of tillage systems, soil depth and no-till duration on soil aggregate size distribution, stability and aggregate associated carbon. It was carried out in Thohoyandou (Tshivhilwi and Dzingahe), Vhembe district, Limpopo province, South Africa. The soil samples were collected from NT, conventional tillage (CT) and virgin (VG) fields in the topsoil (0–30 cm) and subsoil (30–60 cm) at each location. The duration of NT for fields in Tshivhilwi and Dzingahe were 8 years (short-term) and >40 years (long-term), respectively. The results showed that macro-aggregates constituted the largest proportion of aggregates, with a percentage contribution of >60% during the short-term and long-term. The mean weight diameter (MWD) varied significantly between NT and VG in the subsoil for the short-term NT. The aggregates were more stable in the short-term NT than long-term NT. Organic carbon in all aggregate fractions between the tillage systems in the topsoil was not significantly affected after more than 40 years. The MWD was higher in the subsoil than topsoil in NT and CT during both periods. Micro-aggregates contained greater OC than other fractions. The study showed that the impact of NT on aggregation, structural stability and the capacity to store carbon vary overtime. It is recommended that the aggregation and/or structural stability of different soil textures under NT with different cropping systems and management practices should be studied periodically.

1. Introduction

Soil aggregation is a complex process occurring due to the interaction between physical, chemical and biological properties [1]. It is the rearrangement, flocculation and cementation of primary soil particles [2]. Furthermore, it is mainly determined by agents such as organic carbon (OC), clay content and biota [3]. Tillage, cropping systems, irrigation and fertilization, among others, also have an impact on soil aggregation. It was stated that management practices such as no-tillage, crop diversification or rotation and crop residue retention contribute to soil organic carbon increases [4]. Soil structure (i.e., aggregates) and organic matter are dynamic soil properties that are very sensitive to soil and crop management practices [5]. Generally, no-tillage increases aggregate stability and soil organic matter content [6].
No-tillage can contribute immensely to sustainable agriculture by enhancing the soil’s capacity to build resistance against mechanical destruction, which may over time lead to erosion, compaction, reduced porosity, poor permeability, etc. [7]. Long-term, no-tillage can improve aggregation and its stability as well as organic carbon storage capacity better than short-term no-tillage [8]. Furthermore, no-tillage performs better than conventional tillage on the maintenance of soil structure and carbon storage [8]. Conventional tillage destroys soil aggregates, and this may lead to the loss of carbon due to the hastened oxidation of organic matter [9]. Consequently, this results in poor soil structure and high carbon loss to the atmosphere. On the other hand, no-tillage promotes aggregation due to less mechanical disturbance of the soil, which may also enhance carbon storage within the aggregates. It was reported that no-tillage increased the aggregate associated carbon of silty loam soil more than conventional tillage practices. Furthermore, long-term no-tillage in a temperate climatic zone can increase aggregate stability due to reduced disturbance and the retention of crop residues on the soil surface, as compared to conventional tillage [10]. A significant improvement in aggregate size distribution and stability after seven years of continuous no-tillage was also reported [11].
Long-term no-tillage has been found to have a positive effect on the accumulation of organic carbon and aggregation, especially at the 0–10 cm soil depth, compared to conventional tillage [12] and this may also extend to the lower soil depths. The adoption of no-tillage results in increased aggregate stability along the soil profile compared to conventional tillage [13]. This was shown by the increase in the mean weight diameter (MWD) at a 0–10 cm soil depth for durations of <10, 10–20 and >20 years, but the increase in the entire profile was only recorded for durations of more than 20 years. Different soils respond differently to the type of tillage management practices over time; furthermore, their effectiveness and/or suitability depend on factors such as soil type, among others [3,14]. Hence, it was necessary to assess how aggregate size distribution, the MWD and the aggregate associated OC of clayey soil were affected by the duration of no-tillage systems.
Soil organic matter contains approximately 55% organic carbon and 45% of other essential elements [5]. Furthermore, organic carbon is the main component of soil organic matter and can serve as a proxy for soil structural stability [15]. Soil organic carbon is the type of carbon that is stored in the organic matter [8]. It is added to the soil through crop residue decomposition, microbes and root exudates. Organic matter contributes significantly to formation soil aggregates and the carbon within them is protected against degradation [16]. Soil organic carbon acts as a binding agent in aggregate formation [17]. Furthermore, the amount of carbon may vary in different aggregate size fractions. The high accumulation of soil organic carbon in the micro-aggregates results in the effective formation of macro-aggregates under no-tillage [18,19]. In addition, primary soil particles (<20 μm) join together into micro-aggregates (20–250 μm), which are then bound to form macro-aggregates (>250 μm) [20]. On the other hand, the disintegration of macro-aggregates forms smaller aggregates (20–250 μm) that are much more stable [21]. This may also lead to the loss of some of the soil organic carbon.
This study aimed to assess the impact of tillage systems, soil depth and no-till duration on soil aggregate size distribution, stability and aggregate associated carbon. The following research questions were asked: (i) What impact does the tillage system have on the distribution of aggregates, their stability and aggregate associated carbon? (ii) Does the duration of no-till practice have an influence on soil aggregate size distribution, stability and aggregate associated carbon? (iii) Does aggregate stability and aggregate associated carbon vary with depths, as influenced by tillage system and no-till duration?

2. Materials and Methods

2.1. Site Description

The study was conducted in Thohoyandou (Tshivhilwi and Dzingahe), Vhembe district, Limpopo province, South Africa. Tshivhilwi is located at 22°50′54″ S, 30°38′38″ E and 512 m altitude. The no-tillage (NT) field at this study site was 6 ha; maize was planted all year round in rotation with legumes and vegetables under irrigation. In the conventional tillage (CT), field maize was the only crop cultivated under dryland. Dzingahe was located at 22°55′32″ S, 30°31′00″ E and 662 m altitude. The NT field at this study site was 2 ha; maize and ground nuts were the main crops intercropped under dryland. In the CT field, maize was the only crop also cultivated under dryland. The virgin (VG) fields at both study sites were never cultivated; however, they were communal rangelands for livestock grazing. The NT fields in Tshivhilwi and Dzingahe were 8 years (short-term) and >40 years (long-term) old, respectively. The number of years was estimated to be about 50 years for conventional tillage fields. An average annual rainfall of 762 mm, minimum temperature of 15 °C and maximum temperature of 28 °C was recorded for both study sites. Furthermore, the study sites were characterized by a clayey soil texture.

2.2. Soil Sampling

Soil sampling was carried out from the NT, CT and VG fields in Tshivhilwi and Dzingahe. The VG field was used as a control for the study at each location. Five sampling points were selected randomly over an area = 1000 m2 of each field per location, with a view to the soil variability. Five soil pits (1 m × 1 m × 0.7 m) were dug on the selected sampling points in each field per location and demarcated to two sampling depths of 0–30 cm (topsoil) and 30–60 cm (subsoil). The samples were allowed to dry at room temperature before analyses. A total of thirty soil samples (15 topsoil and 15 subsoil) were collected per location.

2.3. Aggregate Size Distribution and Stability Determination

The aggregate size distribution was determined by placing a 100 g dry subsample on a stack of sieves (4, 2, 0.212 and 0.05 mm) (Clear edge Filtration S.a. (Pty) Ltd., Johannesburg, South Africa). Aggregates were separated by vibrations with a sieve shaker for 5 min. Each aggregate size fraction was weighed except for aggregates greater than 4 mm, which were discarded. The aggregates were categorized in terms of diameter, as shown in Table 1. The mean weight diameter (MWD) was then calculated [22]:
M W D = i = 1 n x i w i
  • MWD = mean weight diameter
  • xi = mean diameter of each size fraction (mm)
  • wi = proportion of total sample weight (g)
  • n = number of size fractions

2.4. Aggregate Associated Organic Carbon (OC) Analysis

The organic carbon in each aggregate size fraction was analyzed using the Walkley and Black wet oxidation method [23]. Oxidizable OC in the soil was oxidized by potassium dichromate (0.167 mol L−1) solution mixed with a concentrated sulfuric acid. The dichromate that was reduced during the reaction with the soil is proportional to the oxidizable OC present in the aggregates. The OC was estimated by measuring the remaining unreduced dichromate by back-titration with ferrous ammonium sulfate using o-phenanthroline-ferrous indicator.

2.5. Soil Bulk Density, Clay, Silt and Sand Percentage Determination

Stainless steel cylindrical core samplers (Eijkelkamp GeoPoint Soil Solutions, Sassenheim, The Netherlands) with a volume of 100 cm3 were used to collect bulk density (BD) samples from the topsoil and subsoil. The BD was calculated by using the oven-dried soil mass in g and the volume of the core in cm3, as BD = mass/volume [24]. Soil texture was determined by soil particle size distribution analysis using the hydrometer method. The proportions of the soil particles (clay, silt and sand) in percentages were calculated to determine the texture class(es) from the soil texture triangle [25].

2.6. Data Analysis

The collected data were subjected to an analysis of variance (ANOVA) and a multivariate analysis of variance (MANOVA) at a 95% confidence interval (p ≤ 0.05) to compare the parameters measured in the NT, CT and VG fields at each location, using IBM SPSS statistics 29.0. Aggregate size fractions, mean weight diameter (MWD) and aggregate associated organic carbon between the topsoil and subsoil in each tillage system and the duration (8 years and 40 years) of NT were computed with MANOVA. The relationship between the parameters was analyzed with the Pearson correlation coefficient (r).

3. Results

3.1. Aggregate Size Distribution and Mechanical Stability

At Tshivhilwi, where no-tillage was practiced for 8 years (short term), it was observed that NT had almost three times (30.45%) more larger aggregates (>2 mm) compared to in CT (11.75%) and twice those of VG (16.98%) in the 0–30 cm soil depth (Figure 1A). However, NT had a significantly lower percentage of micro-aggregates compared to CT (p = 0.027) but did not differ with the VG in the same depth. No significant differences were observed between the tillage systems for aggregates ranging between 0.212 and 2 mm. Macro-aggregates (0.212–2 mm) constituted the largest proportion of aggregates, with a percentage contribution of >60% (Figure 1A,B).
At Dzingahe, where no-tillage was practiced for over 40 years (long-term), micro-aggregates showed a significant difference between NT and CT (p = 0.044) and CT and VG (p = 0.044) in the topsoil (Figure 2A). Large macro-aggregates (>2 mm) were not different but were at least 2% higher in NT (18.67%) than in CT (16.23%) in the 0–30 cm soil depth. A similar trend in the percentage of macro-aggregates (0.212–2 mm) was also found in the topsoil in NT (62.72%) and CT (59.11%). However, micro-aggregates at the same depth were 5% higher in CT (23.19%) than NT (17.31%) and almost two times higher than VG (12.70%). In the subsoil, large macro-aggregates in CT (23.95%) were 3% more than NT (20.28%), whereas macro-aggregates were just over 1% higher in NT (62.21%) than CT (60.33%). On the other hand, there was only a 1% non-significant difference in micro-aggregates between NT (15.82%) and CT (14.82%) (Figure 2B). Macro-aggregates constituted the largest proportion of aggregates, with a percentage contribution of >60% (Figure 2A,B), which is similar to what was found for the short-term duration.
The mean weight diameter (MWD) only showed a significant difference between NT and VG (p = 0.027) in the subsoil after 8 years of NT (Figure 3). Even though no differences were observed in the topsoil, it was relatively higher in NT, with a value of 1.25 mm compared to CT (1.06 mm) and VG (1.22 mm). In the subsoil, a similar trend was also observed, where the MWD was higher in NT compared to the other tillage systems. After more than 40 years of no-till practice, the mean weight diameter (MWD) was non-significant between all tillage systems, except between CT and VG (p = 0.007) in the topsoil (Figure 3). It was higher in VG (1.18 mm) than in NT (1.11 mm) and CT (1.17 mm) in the topsoil and subsoil. The MWD was also higher in VG (1.18 mm) than CT (1.17 mm) and NT (1.11 mm) in the subsoil.
The aggregate size distribution and MWD were also compared between short-term (8 years) and long-term (>40 years) for the NT-only situation. Large macro-aggregates and micro-aggregates in the topsoil were significantly (p = 0.006 and p = 0.001, respectively) affected by the duration of NT. Large macro-aggregates in the subsoil also showed a significant difference (p = 0.026). The percentage of micro-aggregates in the topsoil was almost 4 times greater in long-term NT (17.31%) than short-term NT (4.57%), whereas in the subsoil it was almost 3 times greater in long-term NT (15.82%) than short-term NT (6.27%). The MWD in both soil depths was higher during the short-term NT (1.25 and 1.31 mm) than long-term NT (1.09 and 1.00 mm).
The aggregate size distribution and MWD in both soil depths were compared for each tillage system. Overall, soil depth did not significantly affect the aggregate size distribution and MWD in each tillage system during the short-term and long-term. However, the large macro-aggregates (p = 0.024) and MWD (p = 0.034) differed significantly with CT in the long term. The subsoil indicated a more stable structural stability than topsoil in NT and CT. The soils in all tillage systems had a clay percentage above 30%, with no significant difference in the short-term and long-term; however, this value was higher in the subsoil than the topsoil. Furthermore, the bulk density showed that the soils at both depths were not compacted (mostly below 1.5 g/cm3) (Table 2).

3.2. Aggregate Associated Organic Carbon (OC)

There was no significant difference in organic carbon in all aggregate size fractions between the tillage systems for both soil depths during the short term (Figure 4A,B). However, macro-aggregates and micro-aggregates had relatively more OC in the NT scenario (1.30% and 1.58%, respectively) in the topsoil. In the subsoil, NT also showed relatively higher OC in all the aggregate size fractions. The OC under NT in the large macro-aggregates, macro-aggregates and micro-aggregates was 0.70%, 0.92% and 0.98%, compared to 0.60%, 0.53% and 0.72% in CT and 0.57%, 0.65% and 0.71% in VG, respectively.
Organic carbon in all aggregate fractions between the tillage systems in the topsoil was not significantly affected after more than 40 years (long term) (Figure 5A). Even though no significant differences were observed in the topsoil, large macro-aggregates and macro-aggregates in NT showed higher OC values (1.80% and 1.93%) than CT (1.58% and 1.80%) and VG (1.34% and 1.44%), while micro-aggregates in CT (2.28%) had more OC than NT (1.92%) and VG (1.80%) at the 30–60 cm soil depth. Organic carbon in both large macro-aggregates and macro-aggregates was significantly higher in CT compared to VG in the subsoil (Figure 5B).
The OC in large macro-aggregates and macro-aggregates was significantly affected by the duration of NT at both soil depths. All aggregate fractions contained more OC in the long term (>40 years) NT than short term (8 years) NT. It ranged from 0.72% to 1.93% in the long-term and 0.70 to 1.58% in the short-term. Overall, the results showed that the OC in all these aggregate size fractions was not significantly affected by soil depth. The aggregate associated OC was however larger in the topsoil than the subsoil.

3.3. The Correlation Between the Measured Soil Parameters

The MWD in both soil depths in the short-term showed a negative relationship with macro-aggregates (r = −0.23 and r = −0.53) and micro-aggregates (r = −0.94 ** and r = −0.86 **), but it was significant and strongly positive with large macro-aggregates (r = 0.97 ** and r = 0.94 **). A weak positive correlation between clay content and the MWD (r = 0.33) in the topsoil, and a very weak negative correlation (r = −0.14) in the subsoil, were identified. The correlation between bulk density and the MWD was negative (r = −0.43 and r = −0.35) at both soil depths. The aggregate OC of all fractions at both soil depths correlated positively with the MWD except for the large macro-aggregates in the topsoil (Table 3).
In the long-term tillage (>40 years) (Table 4), the MWD at both soil depths correlated positively with large macro-aggregates (r = 0.83 ** and r = 0.91 **) and macro-aggregates (r = 0.34 and r = 0.16), and negatively with micro-aggregates (r = −0.92 ** and r = −0.94 **). Bulk density also correlated positively with the MWD (r = 0.46 and r = 0.32) at both soil depths. Clay content in the topsoil showed a very weak positive correlation with the MWD (r = 0.08); however, in the subsoil it was positive (r = 0.39). The aggregate OC of all fractions at both soil depths correlated negatively with the MWD, which differs with the results for the short-term.

4. Discussion

The results showed a high percentage of macro-aggregates at both soil depths and for all tillage systems. They accounted for a higher percentage than other aggregate size fractions, which was similar to what was found by Six et al. and Zhao et al. [19,26]. However, there were noticeable differences in aggregate size distribution between the tillage systems. The conspicuous dominance of macro-aggregate fractions in all tillage systems and depths could be due to the high clay content of the soil. Clay particles act as cementing agents during aggregation and soils that have a high proportion of clay tend to form relatively larger aggregates [17,20]. Conventional tillage (CT) had a higher percentage of micro-aggregates than NT in the topsoil in both the short- and long-term. However, in the subsoil, micro-aggregates were higher in CT in the short-term and in NT during the long-term. This could be attributed to the intensity and duration of these tillage systems at both study sites. Conventional tillage has a destructive tendency towards soil structural stability, which mostly mechanically pulverizes aggregates in the soil, whereas NT is known to promote aggregation. The duration of either tillage system contributes largely to the resultant aggregate size distribution as the changes occur over time. Furthermore, the level of the impact of the tillage systems on aggregate size distribution and stability could have been modified by additional management practices such as fertilization, irrigation, crop rotation, mono-cropping, inter-cropping and residue management. Hence, even after 40 years, NT did not show a significant difference in the MWD for CT, which could, to some extent, have been affected by these management practices. In the study conducted by Zhou and others [27], it was clear that cropping systems affected the soil aggregate stability and organic carbon storage. These cropping systems contribute to the amount of organic matter added to the soil as crop residues after harvest; therefore, the organic carbon content is stored in the soil, while tillage systems influence the amount that is retained. Soils under NT have shown more organic carbon storage than those under CT.
The overall stability of the aggregates of the soils in all tillage systems, as shown by the MWD, was moderate [28]. The stability of individual aggregate fractions contributes to the overall structural stability of the soil. The soil aggregates were more stable in NT, except in the long-term, where there were more stable aggregates observed in CT in the subsoil, and this concurs with the findings of Mondal and Chakraborty [13]. A greater MWD was reported in the topsoil in NT than in CT, which is in accordance with what was found in this study [11,18]. The higher aggregate stability in NT could be attributed to the less soil disturbance that mostly helps preserve the structure as compared to CT. The key factors on the effect of tillage on aggregate stability is the frequency, intensity and period of the tillage [12,13]. This was indicated by the differences in the number of years and cropping systems under NT. The strong significant positive and negative correlation of the MWD with large macro-aggregates and micro-aggregates, respectively, showed that the soil structural stability was dependent more on the distribution of these aggregate size fractions than the duration. However, it must be noted that the MWD was marginally higher in the short-term than in the long-term. The relationship between bulk density and the MWD between the tillage periods was not consistent. It was negative for 8 years and positive after more than 40 years. Irrespective of this contrasting relationship, the low bulk densities generally showed that the soils were not compacted and hence the MWD was moderate. Clay percentage showed a positive relationship with the MWD, except in the short-term in the subsoil where it was negative. Moreover, the higher clay content in the subsoil may have influenced it having a higher MWD than the topsoil. Zeng et al. [28] also found a significant increase in the MWD with clay content. Oliveira et al. and Zeng et al. reported conflicting results, where the MWD decreased with depth in the NT scenario [12,28]. The low bulk density and high clay content supported the fractionation and moderate stability of the aggregates. Aggregate stability contributes significantly to the sustainability of the soil and crop production [29] by maintaining good soil structure, optimum fertility and regulating soil air and water movement and storage.
Organic matter and clay content are among the binding agents that contribute to the formation of soil aggregates [2,30]. However, the activities in NT and CT manipulated the aggregation process, where, in some parts, there were signs (i.e., surface crust) of destroyed aggregates. However, some aggregates of different sizes were still intact and stable. Micro-aggregates across the tillage systems had the highest organic carbon compared to other aggregate size fractions at both soil depths except in the short term where macro-aggregates had a greater organic carbon in CT. Boix-Fayos et al. and Yudina and Kuzyakov indicated that micro-aggregates protect most of the carbon in the soil, which supports the findings of this study [21,31]. The findings are, however, contradictory to the findings of Zhou et al. [27], who discovered small macro-aggregates (0.25–2 mm) to be the fraction with higher soil organic carbon. The OC content of micro-aggregates in both soil depths showed a contrasting trend between the tillage periods, where, in the short-term, it was highest in NT, while in the long-term, it was highest in CT. However, NT showed itself to be better than CT for aggregate associated organic carbon in the topsoil, which could have been due to the lesser mechanical alteration of the soil aggregates. Breaking macro-aggregates into micro-aggregates increases the surface area for organic carbon microbial oxidation [32]. Therefore, this will possibly lead to rapid OC loss. The impact of these tillage systems on the aggregates contribute to the amount of organic carbon stored and/or lost in the soil. Moreover, the duration of NT did not influence the OC storage across the aggregate fractions. However, the OC values in all aggregate fractions during long-term NT were negligibly higher than in short-term NT. The amount of OC in the soil influences the cation exchange capacity, which is important for nutrient retention for optimum crop growth, but this can also be altered by the clay percentage [33,34]. In addition, increased OC enhances the soil microbial biomass, diversity and activity, and therefore boosts the mineralization and availability of essential plant nutrients.

5. Conclusions

The soil under the short-term (8 years) NT scenario had more structural stability than for long-term (>40 years) NT, as revealed by the MWD. However, the MWD was higher in the subsoil than in the topsoil in NT and CT during both periods. This showed that the subsoil had more structural stability than the topsoil, regardless of the duration. Macro-aggregates constituted the highest percentage compared to other fractions. The percentage of large macro-aggregates and micro-aggregates was inconsistently and relatively lower than macro-aggregates across the tillage systems in the short-term and long-term. Micro-aggregates contained a greater OC, which indicated that they have the capacity to store and protect more carbon than other fractions. All aggregate fractions contained more OC in the topsoil than in the subsoil. In addition, all aggregate fractions had a higher OC during long-term NT than short-term NT. This corroborates the potential of NT to increase and protect the carbon in the soil over time. In addition to the impact of tillage practices over time, the cropping systems and other management practices such as irrigation may to some extent influence soil structural stability. Further research is recommended to investigate the effect of NT duration on aggregate size distribution, stability and capacity to store carbon in different soil textures and relate this to crop yield(s). The changes in aggregate stability and carbon storage should be monitored periodically for NT scenarios with different cropping systems and management practices such as residue management and irrigation. The combination of these management practices can contribute towards sustainable crop production.

Author Contributions

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

Funding

This work was supported by the National Research Foundation—Thuthuka [grant number 129567].

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Acknowledgments

We would like to acknowledge the Department of Plant Production, Soil Science and Agricultural Engineering at the University of Limpopo; the Risk and Vulnerability Science Centre at the University of Limpopo; the Department of Research Administration and Development at the University of Limpopo and the farmers in Tshivhilwi and Dzjngahe.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. A comparison of aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG in the short-term—ST (8 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
Figure 1. A comparison of aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG in the short-term—ST (8 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
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Figure 2. A comparison of aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG in the long-term—LT (>40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
Figure 2. A comparison of aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG in the long-term—LT (>40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
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Figure 3. A comparison of the mean weight diameter (MWD) in the topsoil (0–30 cm) and subsoil (30–60 cm) between NT, CT and VG in the short-term—ST (8 years) and long-term—LT (>40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
Figure 3. A comparison of the mean weight diameter (MWD) in the topsoil (0–30 cm) and subsoil (30–60 cm) between NT, CT and VG in the short-term—ST (8 years) and long-term—LT (>40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
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Figure 4. A comparison of organic carbon (OC) in different aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG fields in the short-term—ST (8 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
Figure 4. A comparison of organic carbon (OC) in different aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) between NT, CT and VG fields in the short-term—ST (8 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
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Figure 5. A comparison of organic carbon (OC) in different aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) soil depths between NT, CT and VG fields in the long-term—LT (after >40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance test at p > 0.05.
Figure 5. A comparison of organic carbon (OC) in different aggregate size fractions in the topsoil (0–30 cm) (A) and subsoil (30–60 cm) (B) soil depths between NT, CT and VG fields in the long-term—LT (after >40 years). The standard deviation error bars represent the spread of the data relative to the mean. Bars with the same letters, within the same class of aggregates, do not differ from each other by the analysis of variance test at p > 0.05.
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Table 1. Aggregate size categories based on diameter.
Table 1. Aggregate size categories based on diameter.
Category Diameter (mm)
Large macro-aggregates>2 mm
Macro-aggregates0.212–2 mm
Micro-aggregates0.05–0.212 mm
Table 2. Soil bulk density (BD), clay, silt and sand percentages in the topsoil (0–30 cm) and subsoil (30–60 cm) in NT, CT and VG in the short-term (8 years) and long-term (>40 years).
Table 2. Soil bulk density (BD), clay, silt and sand percentages in the topsoil (0–30 cm) and subsoil (30–60 cm) in NT, CT and VG in the short-term (8 years) and long-term (>40 years).
Tillage SystemShort-TermLong-Term
BD
(g/cm3)
Clay
(%)
Silt
(%)
Sand
(%)
BD
(g/cm3)
Clay
(%)
Silt
(%)
Sand
(%)
0–30 cm
NT1.32 a37.60 a18.40 a44.00 a1.19 a36.53 a26.53 a36.93 a
CT1.37 a30.53 a23.47 a46.00 a1.22 a34.27 a35.07 a30.67 a
VG1.38 a34.67 a22.67 a42.67 a1.32 b32.00 a32.00 a36.00 a
30–60 cm
NT1.23 a41.47 ab13.20 a45.33 a1.20 a41.07 a30.80 a28.13 a
CT1.57 b34.93 a19.07 a46.00 a1.26 a48.93 a28.40 a22.67 a
VG1.39 c44.00 b14.27 a41.73 a1.44 b42.67 a27.33 a30.00 a
Averages followed by the same letters, in the same column, do not differ from each other by the analysis of variance (LSD) test at p > 0.05.
Table 3. Pearson correlation heatmap between aggregate fractions, MWD and aggregate associated carbon in topsoil and subsoil for short-term. The color of each cell represents the strength and direction of the correlation between two variables, with darker colors indicating stronger correlations (close to = 1/−1) and lighter colors indicating weaker correlations (close to 0).
Table 3. Pearson correlation heatmap between aggregate fractions, MWD and aggregate associated carbon in topsoil and subsoil for short-term. The color of each cell represents the strength and direction of the correlation between two variables, with darker colors indicating stronger correlations (close to = 1/−1) and lighter colors indicating weaker correlations (close to 0).
F1-TF2-TF3-TMWD-TF1-SF2-SF3-SMWD-SF1OC-TF2OC-TF3OC-TF1OC-SF2OC-SF3OC-S
F1-T1
F2-T−0.451
F3-T−0.86−0.021
MWD-T0.97−0.23−0.941
F1-S0.70−0.48−0.420.651
F2-S−0.690.480.50−0.63−0.781
F3-S−0.290.120.12−0.29−0.650.041
MWD-S0.59−0.40−0.310.550.94−0.53−0.861
F1OC-T−0.270.640.07−0.120.000.22−0.320.121
F2OC-T0.090.49−0.230.230.34−0.03−0.570.450.911
F3OC-T0.310.48−0.570.470.270.02−0.530.380.580.741
F1OC-S0.20−0.13−0.040.180.120.23−0.440.290.390.420.281
F2OC-S0.46−0.14−0.400.470.57−0.18−0.730.670.370.630.640.511
F3OC-S0.51−0.42−0.280.450.68−0.34−0.690.740.200.460.400.540.941
F1 = large macro-aggregates, F2 = macro-aggregates, F3 = micro-aggregates, MWD = mean weight diameter, OC = organic carbon, T = topsoil, S = subsoil.
Table 4. Pearson correlation heatmap between aggregate fractions, MWD and aggregate associated carbon in topsoil and subsoil for long-term. The color of each cell represents the strength and direction of the correlation between two variables, with darker colors indicating stronger correlations (close to = 1/−1) and lighter colors indicating weaker correlations (close to 0).
Table 4. Pearson correlation heatmap between aggregate fractions, MWD and aggregate associated carbon in topsoil and subsoil for long-term. The color of each cell represents the strength and direction of the correlation between two variables, with darker colors indicating stronger correlations (close to = 1/−1) and lighter colors indicating weaker correlations (close to 0).
F1-TF2-TF3-TMWD-TF1-SF2-SF3-SMWD-SF1OC-TF2OC-TF3OC-TF1OC-SF2OC-SF3OC-S
F1-T1
F2-T−0.241
F3-T−0.54−0.691
MWD-T0.830.34−0.921
F1-S−0.620.390.13−0.381
F2-S0.330.38−0.560.53−0.261
F3-S0.31−0.640.32−0.07−0.72−0.481
MWD-S−0.500.55−0.10−0.170.910.16−0.941
F1OC-T−0.07−0.370.38−0.28−0.03−0.220.18−0.121
F2OC-T−0.34−0.210.45−0.460.23−0.410.080.060.871
F3OC-T−0.48−0.040.41−0.490.67−0.31−0.380.550.480.741
F1OC-S−0.36−0.690.87−0.74−0.09−0.510.48−0.300.530.540.401
F2OC-S−0.45−0.400.69−0.660.08−0.450.26−0.100.570.780.700.831
F3OC-S−0.13−0.220.3−0.250.09−0.330.16−0.050.350.590.660.580.821
F1 = large macro-aggregates, F2 = macro-aggregates, F3 = micro-aggregates, MWD = mean weight diameter, OC = organic carbon, T = topsoil, S = subsoil.
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Phefadu, K.C.; Munjonji, L. Assessing the Impact of No-Tillage Duration on Soil Aggregate Size Distribution, Stability and Aggregate Associated Organic Carbon. Agronomy 2024, 14, 2482. https://doi.org/10.3390/agronomy14112482

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Phefadu KC, Munjonji L. Assessing the Impact of No-Tillage Duration on Soil Aggregate Size Distribution, Stability and Aggregate Associated Organic Carbon. Agronomy. 2024; 14(11):2482. https://doi.org/10.3390/agronomy14112482

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Phefadu, Kopano Conferance, and Lawrence Munjonji. 2024. "Assessing the Impact of No-Tillage Duration on Soil Aggregate Size Distribution, Stability and Aggregate Associated Organic Carbon" Agronomy 14, no. 11: 2482. https://doi.org/10.3390/agronomy14112482

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