Next Article in Journal
A Novel Framework to Represent Hypoxia in Coastal Systems
Previous Article in Journal
An Assessment of the N Load from Animal Farms in Saline Wetland Catchments in the Ebro Basin, NE Spain
Previous Article in Special Issue
Impact of Management Practices on Soil Organic Carbon Content and Microbial Diversity Under Semi-Arid Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Land
Volume 14
Issue 6
10.3390/land14061171
land-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Sustainable Soil Management: The Dynamic Impact of Combined Use of Crop Rotation and Fertilizers from Agri-Food and Sulfur Hydrocarbon Refining Processes Wastes

by
Angela Maffia
,
Federica Marra
,
Mariateresa Oliva
,
Santo Battaglia
,
Carmelo Mallamaci
and
Adele Muscolo
*
Agriculture Department, Mediterranea University, 89124 Reggio Calabria, Italy
*
Author to whom correspondence should be addressed.
Land 2025, 14(6), 1171; https://doi.org/10.3390/land14061171
Submission received: 28 April 2025 / Revised: 22 May 2025 / Accepted: 27 May 2025 / Published: 29 May 2025
(This article belongs to the Special Issue Soil Ecological Risk Assessment Based on LULC)
Browse Figures
Versions Notes

Abstract

:
Sustainable agriculture increasingly relies on strategies that improve soil fertility while reducing the environmental footprint of chemical inputs. The primary objective of this research was to disentangle the individual and combined effects of crop rotation and fertilization on soil quality. This study aimed to determine whether the effectiveness of fertilization was modified by rotational practices—exploring whether these interactions were additive, antagonistic, or synergistic. This study assessed the impact of two-year open-field crop rotations—broccoli–tomato and broccoli–pepper—combined with organic and mineral fertilization on soil chemical and biological properties. Treatments included sulfur bentonite enriched with orange waste (SBO), horse manure (HM), mineral fertilizer (NPK), and an unfertilized control (CTR). Soil samples were collected after each crop cycle and analyzed for enzymatic activities (fluorescein diacetate hydrolase, dehydrogenase, catalase), microbial biomass carbon (MBC), organic matter, total nitrogen, and macro- and micronutrient content. The results showed that organic amendments, particularly SBO and HM, significantly increased microbial activity, MBC, and nutrient availability compared to NPK and CTR. Organic treatments also led to a reduction in soil pH (−12%) and a more balanced ionic profile, enhancing soil biological fertility across both rotations. By contrast, the NPK treatments favored higher nitrate and chloride concentrations (3.5 and 4.6 mg * g−1 dw, respectively) but did not improve biological indicators. Improvements were more pronounced in the second crop cycle, suggesting the cumulative benefits of organic amendments over time. These findings highlight the potential of combining organic fertilization with crop rotation to enhance soil health and support long-term sustainability in horticultural systems.

1. Introduction

Global food production must increase by 70% to meet the demands of a growing population, projected to reach 9.7 billion by 2050 [1]. This has led to the intensification of agriculture to boost productivity, driven by the widespread use of mineral fertilizers and plant protection products. However, this intensification has also contributed to a rise in soil degradation, threatening soil health. Agriculture plays a crucial role in natural resource management, but its expansion and intensification can negatively impact environmental protection and accelerate the degradation of agricultural lands [2,3]. In response, an ongoing debate has emerged regarding the need for improved fertilizer management and more sustainable soil nutrient use. This highlights the importance of integrating methods and practices that ensure adequate plant nutrition while maintaining long-term soil productivity. Sustainable soil management remains a fundamental challenge in modern agriculture, particularly in the face of growing environmental concerns and the need for efficient resource utilization. To maintain or to improve the fertility and productivity of the agricultural soil, many types of waste can be used, such as organic municipal waste, sewage sludge, waste from agricultural crops, manure from animals, and some types of industrial wastes, as a source of organic matter [4]. In previous works Muscolo et al. [5], Maffia et al. [6], and Panuccio et al. [7] used fertilizers produced from different agro-industrial wastes to improve crop yield and quality, and soil quality. The results evidenced at different extents a positive impact of all the fertilizers produced from wastes on the soil and crops. The integration of agro-industrial waste-derived fertilizers with crop rotation strategies has recently emerged as a promising approach to enhance soil fertility while reducing reliance on synthetic inputs. However, the dynamic interactions between soil amendments and cropping systems require thorough investigation to verify if their combination can be more suitable and productive than their single use, to optimize agronomic practices and ensure long-term sustainability. Crop rotation is a -time-honored agricultural practice known to improve soil health, manage pests and diseases, and enhance crop yields by diversifying the crops grown in succession on the same land [8]. By alternating crops with different nutrient requirements and rooting patterns, crop rotation helps to maintain soil nutrient balance and structure, thereby reducing the need for chemical fertilizers [9]. The utilization of agro-industrial wastes as fertilizers presents an eco-friendly alternative to conventional fertilization methods. Composting and vermicomposting agricultural and industrial wastes can improve both aboveground and belowground ecosystem services, contributing to sustainable agriculture [10]. Sulfur is a macronutrient essential for optimal plant growth and for enhancing resistance to soil-borne fungal and bacterial diseases [11]. In recent years, sulfur has gained renewed importance as a plant nutrient due to its declining availability in the soil. This reduction is attributed to the following: (1) the increased use of mono-ammonium and di-ammonium phosphate fertilizers, which contain less sulfur compared to traditional superphosphate; (2) the decreased atmospheric deposition of sulfur as a result of reduced industrial emissions; and (3) the adoption of higher-yielding crop varieties that extract greater amounts of sulfur from the soil during harvest [12].
Furthermore, sulfur is permitted in organic agriculture worldwide, making the recovery of sulfur from agricultural and industrial wastes an agronomically beneficial and environmentally sustainable strategy [13]. In the Calabria region of Southern Italy, research has shown that the application of sulfur bentonite combined with orange processing wastes—rich in valuable biomolecules such as nutrients and phenolic compounds—can improve soil fertility and promote eco-friendly agricultural practices [14,15,16,17]. Based on previous experiments, this study investigated the combined effects of crop rotation and the innovative fertilizer produced from agro-industrial wastes (sulfur bentonite plus orange waste) on soil quality and fertility. Conducted over two consecutive years, the research employed a rotational system alternating a winter crop (broccoli) with two different summer crops (tomato and pepper). Specifically, Calabrian broccoli, Big Rio tomato, and Topepo pepper were selected, as these are crops cultivated in Calabria with significant economic impact. The experiment was carried out in two distinct plots (1/2 hectare each) within the same area, each plot was further divided into multiple subplots to ensure statistical robustness. One plot featured a broccoli–pepper rotation, while the other employed a broccoli–tomato rotation. The primary objective of this research was to disentangle the individual and combined effects of crop rotation and fertilization on soil quality, with particular attention to the influence of different summer crops grown in rotation with broccoli. The study aimed to determine whether the effectiveness of fertilization was modified by rotational practices—exploring whether these interactions were additive, antagonistic, or synergistic—and whether different rotational crops exerted distinct impacts on soil fertility parameters. Additionally, the research sought to evaluate how the integration of agro-industrial waste-derived fertilizers with diversified cropping systems could contribute to the long-term improvement of soil health and function. By analyzing a range of soil physical and chemical properties under varied crop and fertilization combinations, this study offers critical insights into soil–plant dynamics, informing carbon farming strategies and supporting the transition toward sustainable, resilient, and productive agricultural systems.

2. Materials and Methods

2.1. Fertilizer Production

Sulfur bentonite plus orange waste (called pastazzo) have been produced by SBS Steel Belt Systems srl in tablets of 3/4 mm, as described by Muscolo et al. [18,19]. Sulfur (S) was mixed with bentonite (B) and orange residues (O) coming from the food industry. Elemental S was the principal component of the fertilizer [20]. The fertilizer was tested for pathogens (total coliforms, faecal coliforms, salmonella spp., and Escherichia coli) and heavy metals to avoid a pollutant impact on the soil [21]. The results evidenced an absence of pathogens and heavy metals [20]. The composition of the sulfur bentonite plus orange waste and horse manure fertilizers is reported below, in Table 1.

2.2. Open Field Experiment

Extensive open-field tests were conducted over a total area of 1 hectare to evaluate the effects of fertilizer application and seasonal vegetable crop rotation on soil properties. The experiment took place at Falcone Farm in San Lorenzo (Reggio Calabria). The soil is classified as Sandy–Clay–Loam, with an alkaline pH and a low organic matter content ranging from 0.7% to 1.6%. Before the fertilizer application, the soil in the subplots underwent comprehensive analysis, with the results reported in the Tables as T0. The 1-hectare field was divided into two plots of 0.5 hectares each, which were further subdivided into subplots. Four fertilizer treatments were applied on a nitrogenous base:
  • SBO (476 kg S ha−1)—Sulfur-based amendment
  • CTR (Control)—Unfertilized soil
  • NPK (20/10/10) (476 kg S ha−1)—Chemical fertilizer
  • HM (430 kg ha−1)—Horse manure as an organic amendment
The experiment was arranged in a randomized complete block design and three replicates of each treatment were conducted across three subplots, with six soil samples collected per subplot for each treatment. The experiment was conducted over two consecutive years, and the results represent the average of three independent trials. Throughout the study, irrigation was maintained at 70% of field capacity to support soil vitality. Soil water content was monitored using a direct-read soil pH/moisture meter (R181). The SBO application rate was selected based on the literature data, which suggests pure sulfur application rates ranging from 2200 kg S ha−1 to 3300 kg S ha−1, depending on the soil texture [18,22]. Broccoli was placed in the soil in October and collected in February. After broccoli harvesting, one plot rotated with the Topepo red pepper, and the other one with the tomato Big Rio F1. The tomato and pepper were harvested in July. Soil was collected after the crop harvesting, dried and sieved at 2 mm except for microbial biomass C, and analyzed for their chemical and biological properties, as reported in the soil chemical analysis paragraph.

2.3. Soil Chemical Analysis

The following soil properties were detected. Soil texture with the hydrometer method [23]; electric conductibility (EC) in 1:5 soil/water suspension, after stirring at 15 rpm for 1 h was measured with a Hanna instrument conductivity meter; the pH was determined in soil/solution ratio 1:2.5 with a glass electrode. Organic carbon was detected using the Walkley–Black method [24]. Total nitrogen (TN) was assessed using the Kjeldahl method [25]. C/N was quantified as a carbon/nitrogen ratio. Water soluble phenols were extracted and analyzed as described by Kaminsky and Müller [26], and monomeric and polyphenols were determined by the Box method [27], using tannic acid as the standard. The concentration of water-soluble phenolic compounds was expressed as tannic acid equivalents (μg TAE g−1D.W.). The cation exchange capacity was analyzed using the barium chloride method [28]. Cations and anions were detected using ion chromatography (DIONEX ICS-1100) [29].

2.4. Soil Biological Analysis

The microbial biomass carbon (MBC) was assessed using the chloroform fumigation–extraction procedure [30] on fresh soil. Fumigated and unfumigated soil sample extracts were used to detect the soluble organic C [24]. Fluorescein diacetate hydrolase (FDA) activity was determined according to the method of Adam and Duncan [31]. Dehydrogenase (DHA) activity was assessed using the von Mersi and Schinner method [32]. Catalase activity (CAT) was detected by assessing the absorbance during the transformation of H2O2 to oxygen and water [18]. The decrease in the absorbance was measured at 240 nm, using the extinction coefficient of 39.4 M−1 cm−1. Protease activity was detected as reported in Muscolo et al. [18]. Urease activity was determined as described in Sidari et al. [33]. Ammonium concentrations were determined at 690 nm by using a calibration curve. The results are reported as μg N-NH4 g−1 d−1 3 h−1.

2.5. Statistical Analysis

An analysis of variance was used for all the data sets. One-way ANOVA with Tukey’s honestly significant difference tests for analyzing the effects of fertilizer and crop rotation on each of the parameters measured were used. The ANOVA and t-test were performed using SPSS software, version 29.0. The effects were significant at p ≤ 0.01. To analyze the relationships between the fertilizer, crop rotation, and soil parameters in the two different plots, a principal component analysis (PCA) was used.

3. Results

After the first cycle of the broccoli–tomato crop rotation, notable changes were observed in the soil chemical properties. The water content increased across all treatments compared to both the baseline control (initial soil conditions) and the unfertilized soil (Table 2). The soil pH decreased significantly only in the presence of SBO. Among the treatments, the SBO uniquely increased the concentration of water-soluble phenols (WSP), whereas the NPK was the only treatment that led to a significant reduction in WSP. Organic carbon (OC), total nitrogen (TN), cation exchange capacity (CEC), and microbial biomass carbon (MBC) increased across all treatments, including the unfertilized control (Table 2). Enzymatic activities, including fluorescein diacetate hydrolysis (FDA) and dehydrogenase (DHA), increased in the HM and SBO treatments relative to both controls. However, catalase (CAT) activity decreased with the SBO application (Figure 1). No significant differences were found in the lithium content. By contrast, potassium and magnesium levels rose compared to the control, while the calcium content declined in the soil treated with HM and SBO. Nitrate concentrations peaked with the NPK treatment, whereas sulfate concentrations were highest in the soil treated with SBO (Figure 2).
In the second cycle of the broccoli–tomato rotation, electrical conductivity (EC) increased compared to the initial conditions (T0), especially in the soil treated with SBO and NPK. The pH again decreased with the SBO application (Table 3), while WSP increased in all treatments, most markedly in the unfertilized soil. FDA and DHA activities, along with OC, TN, and MBC, increased in the HM and SBO treatments relative to controls. Conversely, the CAT activity declined (Figure 3).
When comparing the first and second crop cycles, soil properties, anions, and cations changed within each treatment. To integrate these multidimensional changes, a principal component analysis (PCA) was conducted using all chemical, biochemical, and ionic parameters measured across both crop cycles under the broccoli–tomato rotation. The biplot (Figure 4) shows the spatial distribution of treatments and variables along the first two principal components, which together explained 59.03% of the total variance (F1: 39.49%; F2: 19.54%). Samples from the second cycle (T02, CTR2, SBO2, HM2, NPK2) generally shifted toward the positive side of F1, closely associated with improved biological and fertility indicators, including MBC, DHA, FDA, EC, TN, and CEC. By contrast, untreated or initial-cycle samples, like T02 and CTR1, were positioned on the negative side of F1, in proximity to variables such as Cl−, Br−, NO2−, and Na+, suggesting lower microbial activity and potential ionic accumulation. This multivariate visualization supports the observed trend of progressive soil improvement under organic treatments across successive crop cycles, distinguishing them from the mineral or unfertilized plots both chemically and biologically.
In the first broccoli–pepper crop rotation cycle, the SBO treatment led to a decrease in the soil pH and an increase in EC, WSP, FDA, OC, OM, and MBC, especially when compared to the NPK treatment and the two controls. The water content increased across all treatments compared to T0 and the control (Table 4).
FDA activity, representing the overall microbial hydrolytic potential, was highest in the SBO-treated soil, followed closely by HM, while the lowest values were observed in the CTR and NPK treatments. DHA activity followed a similar pattern, peaking under the SBO treatment, indicative of enhanced microbial respiration and metabolic activity. By contrast, CAT activity, which reflects oxidative stress regulation, remained relatively low across all treatments, with only slight variations among them. The T0 and NPK treatments showed slightly higher CAT values compared to the organic amendments (Figure 5). The cation analysis revealed higher concentrations of K+ and Mg2+ in the HM and SBO treatments, indicating improved nutrient availability from organic sources. Ca2+ was most abundant in the NPK and CTR treatments, while Na+ levels were elevated in the T0 and mineral-fertilized soil (Figure 6a). Regarding anions, NO3− and Cl− peaked under NPK, confirming the influence of synthetic fertilization. SO42− and PO43− were notably higher in the SBO-treated plots, reflecting sulfur and phosphorus contributions from the amendment (Figure 6b). Overall, organic treatments enriched the soil with key macroelements while minimizing salt accumulation. This trend continued in the second cycle: The pH decreased in the HM and SBO treatments, while EC, OC, OM, TN, CEC, and MBC increased compared to both T0 and control (Table 5).
Enzymatic activities measured after the second cycle of the broccoli–pepper rotation (Figure 7) showed an overall increase compared to the first cycle. FDA activity remained highest in the HM and SBO treatments, indicating sustained microbial hydrolytic capacity, followed by the T0 and NPK treatments. DHA levels were also elevated under the SBO and HM treatments, confirming enhanced microbial respiration. CAT activity remained consistently low across all treatments, with minor differences; slightly higher values were recorded in the T0 and CTR treatments suggesting limited oxidative stress variation among the treatments. Overall, the enzymatic profiles in the second cycle mirrored those of the first, with a general trend of increased microbial functional activity in organically amended soil. In the second cycle of the broccoli–pepper rotation, Ca2+ remained highest in the NPK-treated soil, while K+ and Mg2+ increased under the HM and SBO treatments, indicating enhanced nutrient input from organic amendments, while Na+ persisted at higher levels in T0, and NH4+ stayed low across all treatments. Among anions, Cl− and NO3− peaked in the NPK treatment, reflecting continued mineral fertilization. SO42− and PO43− were elevated in the SBO and HM treatments, supporting the influence of sulfur- and phosphorus-rich amendments. Minor ions, such as NO2− and Br−, remained low, with slight increases in the mineral treatments. Overall, organic inputs improved nutrient availability, while the NPK treatment favored ion accumulation (Figure 8).
To integrate the multivariate effects of treatments over time, a principal component analysis (PCA) was conducted using chemical, biochemical, and ionic soil parameters measured across both crop cycles under the broccoli–pepper rotation. The biplot (Figure 9) illustrates the distribution of treatments and active variables along the first two principal components, which together explained 62.80% of the total variance (F1: 41.38%; F2: 21.43%). Samples from the second cycle (T02, CTR2, SBO2, HM2, NPK2) displayed a clear separation from first-cycle samples, with SBO2 and HM2 positioned on the far right of F1, closely associated with MBC, OM, DHA, SO42−, and CEC, indicating enhanced microbial and nutrient status under organic management. First-cycle treatments, such as SBO1 and HM1, were also positively associated with fertility-related variables like EC, TN, and WC. Conversely, T02 and CTR1/CTR2 were located on the negative side of F1, clustering with Cl−, NO2−, Na+, and Mg2+, suggesting lower biological activity and possible ionic accumulation. NPK1 and NPK2 were grouped along the upper right quadrant, aligning with NO3−, NH4+, and CAT, reflecting a mineral nitrogen-driven soil profile. This PCA confirms the distinct and progressive enrichment of soil biological and chemical properties under organic amendments, while distinguishing the mineral- and non-treated plots along contrasting multivariate trajectories.
To assess whether the combined effects of fertilization and crop rotation influenced soil functioning, a correlation matrix was computed using all chemical and biochemical variables measured across both crop cycles (Table 6). This analysis revealed several significant relationships that clarify how different management strategies shape soil fertility dynamics. The correlation matrix highlights strong positive relationships among organic matter (OM), organic carbon (OC), total nitrogen (TN), cation exchange capacity (CEC), and microbial biomass carbon (MBC), indicating enhanced fertility with organic inputs. Enzymatic activities (FDA, DHA) correlate positively with MBC and negatively with pH and catalase (CAT), suggesting increased microbial activity under acidified conditions. Electrical conductivity (EC) and water content (WC) also show positive associations with key fertility indicators.
Three-way ANOVA (Table 7) revealed that fertilization had a significant effect on all soil chemical and biological variables (p < 0.001). Several parameters, including MBC, CAT, DHA, FDA, and OM, also exhibited significant two- and three-way interactions.
Main effects of the year were significant for most variables, especially for microbial and enzymatic indicators such as FDA and WC. By contrast, the rotation alone had limited effects, but its interaction with other factors (notably Year × Rotation) was significant for selected variables including OC, TN, and WC.

4. Discussion

Scientific studies have investigated the individual and combined effects of crop rotation and organic amendments on soil health and crop productivity illuminating that both practices offer significant benefits, with their effectiveness varying in respect to specific agricultural contexts and objectives. Crop rotation has been shown to enhance soil microbial biomass and diversity. A global synthesis revealed that crop rotation increased soil microbial biomass carbon (MBC) by 13.43% and microbial biomass nitrogen (MBN) by 15.84%, compared to continuous monoculture systems [34]. Additionally, Shannon’s diversity index, a measure of microbial diversity, was significantly elevated by 7.68% under crop rotation practices [35]. These improvements were attributed to the varied root exudates and organic matter inputs from different crops, which create a more hospitable environment for diverse microbial communities [36]. These findings can also explain the increase in organic matter in the plots amended with the inorganic fertilizer NPK. The application of organic amendments instead directly added organic matter to the soil, thereby enhancing the soil organic carbon (SOC) stocks. Research carried on in UK arable systems, comparing diversified crop rotations and organic amendments have confirmed our results, evidencing significant SOC accumulation in the upper layer of the soil (0–30 cm) amended with organic fertilizers [37]. The increase in soil organic carbon (SOC) has been consistently associated with enhanced soil physical and chemical properties, including improved aggregate stability, increased water-holding capacity, and greater nutrient retention and availability. Furthermore, the application of organic amendments significantly stimulated soil biological activity, as evidenced by elevated enzymatic activities, such as dehydrogenase and FDA. These enzymatic processes are key indicators of microbial functioning and nutrient turnover, thereby playing a pivotal role in sustaining nutrient cycling and promoting long-term soil health and fertility [38]. Our results demonstrated that fertilization exerts a more dominant influence on soil fertility and ecosystem functioning than crop rotation alone. Specifically, the control plots subjected to crop rotation without fertilization exhibited significantly lower levels of soil organic matter, microbial biomass carbon (MBC), and enzymatic activities, indicating that the absence of nutrient input limits biological and biochemical soil functions. This trend was further supported by observations in the plots treated with mineral fertilizers (NPK), which also showed reduced concentrations of organic matter, MBC, and enzymatic activity compared to the organically amended plots. These findings highlighted the limited capacity of crop rotation by itself to sustain soil biological quality in the absence of external nutrient inputs. A principal component analysis (PCA) further reinforced this conclusion by revealing a strong positive correlation between dehydrogenase activity, MBC, and organic matter with the HM and SBO treatments, underscoring the central role of fertilization in enhancing microbial-driven soil processes. While both crop rotation and organic fertilization independently contributed to the improved soil health, they contribute to varying extents. Organic fertilization, particularly with biologically enriched amendments, tends to have a more immediate and pronounced effect on microbial activity, soil organic carbon (SOC) accumulation, and nutrient availability. By contrast, crop rotation—especially when incorporating diverse species or extended ley periods—contributes more gradually by enhancing root diversity, soil structure, and long-term nutrient cycling. For example, integrating multi-year grass–clover leys within crop rotations, combined with compost fertilization, has been shown to significantly increase SOC levels compared to either practice alone [39]. This combination leverages both the continuous input of organic residue and the structural and functional benefits of diverse cropping, ultimately leading to improved soil fertility, biological activity, and agroecosystem resilience. The changes observed in the soil properties across two crop rotation cycles (broccoli–tomato and broccoli–pepper) highlighted the interactive effects of both crop identity and fertilization strategies. While the crop species (tomato vs. pepper) significantly influenced microbial and nutrient dynamics, the type of fertilizer applied played a central role in modulating soil health indicators, such as pH, enzymatic activity, organic matter, and nutrient availability [40]. These findings reinforce the complexity of plant–soil–microbe–fertilizer interactions in agroecosystems, and their importance in shaping sustainable soil management practices [41]. The fertilizer type had a marked influence on the direction and magnitude of soil property changes. Notably, SBO and HM were more effective than NPK or the unfertilized control in enhancing microbial activity, organic carbon levels, and nutrient cycling. Organic fertilizers, such as SBO and HM, significantly reduced the soil pH, particularly with SBO, and with the effect being more pronounced in the broccoli–pepper system in the second cycle of both rotations. This acidification is likely due to the sulfur added with SBO that is well known to decrease the pH. Souri and Sayadi [42] demonstrated the efficiency of sulfur bentonite granules in decreasing the soil pH and improving the uptake of nutrient elements by the crop cultivated in calcareous soil. Additionally, the decrease in the soil pH in the presence of HM and mostly of SBO can be ascribed also to the oxidation of organic compounds, nitrification of ammonium, and excretion of organic acids by roots due to an increase in microorganisms enhanced by the high carbon input from organic amendments and by sulfur, as already demonstrated by other authors [43]. The mild acidification of the NPK fertilization is consistent with its targeted nutrient supply and minimal organic content. The increase in EC, most prominent under NPK, followed by SBO, reflected the accumulation of soluble ions released during the mineralization of organic matter (in SBO) or supplied directly via inorganic salts (in NPK). There is a difference in the soil electric conductivity also between tomato and pepper in rotation with broccoli, which may be due to the different absorption capacity and amount of soil ions between the two varieties. Although higher EC can indicate improved nutrient availability, it may also signal potential risks of salinity build up by fertilizer application [44].
All fertilization treatments, including the unfertilized control, even if at a different extent, led to an increase in the soil organic carbon (OC) and total nitrogen (TN), suggesting a cumulative contribution from plant residues and microbial biomass. However, the greatest increases were recorded under SBO and HM, due to their direct organic inputs and their role in stimulating microbial carbon use efficiency and residue incorporation [45]. By contrast, NPK showed a limited capacity to build the SOC, confirming the well-established notion that inorganic fertilization alone lacks the capacity to sustain long-term improvements in soil organic matter [46]. Interestingly, while SBO initially increased TN, a decline was observed in the second cycle of broccoli–pepper, likely due to the combination of rapid nitrogen mineralization and high uptake by pepper plants. This points to a potential mismatch between nitrogen release and crop demand, emphasizing the need for synchronized fertilization strategies. CEC increased under all treatments except for NPK, with the most significant enhancement seen in the SBO- and HM-treated soil. This is attributable to the high humified material supported by high value of C/N which contribute to greater ion retention and buffering capacity [44]. The decline in exchangeable calcium, sodium, and magnesium, particularly under organic treatments, may result from enhanced leaching or competitive uptake by plants and microorganisms. Organic amendments significantly promoted enzymatic activities (FDA and DHA), confirming their role in stimulating microbial metabolism through increased substrate availability [47]. The application of SBO, in particular, elevated water-soluble phenols (WSP), which serve as carbon-rich energy sources for microbes and can enhance the degradation of complex organic matter [48].
However, catalase (CAT) activity declined under SBO, suggesting a possible oxidative stress response or a shift in microbial community composition, possibly away from catalase-producing taxa [47]. While a decrease in catalase activity is often associated with oxidative stress and microbial imbalance, in certain contexts it may also reflect a stabilization or maturation of the soil microbial community. For example, in soil where organic matter inputs are reduced and overall microbial respiration rates decline, the generation of reactive oxygen species (ROS), like hydrogen peroxide, may also decrease. As a result, the microbial demand for antioxidant enzymes, such as catalase, diminishes, leading to lower catalase activity. In this case, the decline could indicate a lower oxidative burden in the soil environment, potentially associated with more stable redox conditions or a shift toward microbial communities that maintain equilibrium with reduced enzymatic antioxidant requirements. The contrasting effects of SBO—increasing overall microbial activity while reducing CAT—highlight the complex, compound-specific impacts of organic fertilizers on microbial ecology. The NPK application led to increased nitrate and ammonium concentrations, indicating high immediate nutrient availability. However, its effect on microbial activity, organic carbon, and CEC was limited, aligning with the findings that inorganic fertilization often supports short-term productivity but fails to improve the long-term soil health [49]. The reduction in WSP under the NPK treatment further underscores its limited support for microbial substrate pools. While the type of fertilizer shaped the baseline soil changes, the subsequent crop species modulated the degree and direction of those changes through rhizosphere-driven mechanisms. For instance, pepper, particularly under SBO, intensified the decline in TN and pH, and amplified enzymatic activities, compared to tomato. This suggests that pepper’s rhizosphere environment is more dynamic, with higher exudate-driven microbial turnover, possibly due to greater dependence on AMF symbioses and root-induced nutrient solubilization [50]. The synergistic effect of organic amendments with pepper roots likely accelerated nutrient cycling processes, explaining the elevated nitrate and sulfate concentrations. Conversely, tomato’s effects appeared more moderate and buffered, promoting a more stable microbial environment, with less dramatic shifts in nitrogen and pH.
The strong and consistent effect of fertilization across all variables supports the central role of nutrient input in determining soil fertility status. However, the significant interaction effects—especially those involving year and crop rotation—highlight that fertilization outcomes are not static, but depend on the temporal and biological context.
Microbial and enzymatic indicators, such as MBC, CAT, DHA, and FDA, were especially sensitive to interactions, suggesting that microbial dynamics are modulated by both management practices and the crops involved. The effect of rotation was more evident in the interaction terms than as a main factor, which suggests that crop sequence influences soil processes indirectly, by modifying the plant–microbe interactions over time.
These results emphasize the need to consider fertilization strategies in combination with crop rotation and seasonal dynamics to optimize soil health and biological functioning in diversified cropping systems. In the current context of high fossil fuel prices, the use of crop rotation combined with sulfur bentonite organo-mineral fertilizer (SBO) offers a more sustainable alternative to synthetic fertilizers such as NPK. With conventional fertilizers priced at €616/ton for nitrogen, €525/ton for phosphate, and €534/ton for potassium, SBO, priced at only €230/ton [7], provides a cost-effective and environmentally friendly option, particularly when considering its additional value in land restoration. This integrated approach supports both soil health and long-term economic viability for farmers.

5. Conclusions

The outcomes of this study demonstrate that both fertilization strategy and crop identity play pivotal roles in shaping soil chemical and biochemical properties across successive rotation cycles. Organic amendments, such as SBO and HM, significantly enhanced microbial activity, soil organic matter content, and cation exchange capacity. However, these benefits were accompanied by increased acidification and accelerated nutrient turnover—particularly when applied in conjunction with pepper cultivation, a biologically active crop. By contrast, the NPK fertilization promoted short-term nutrient availability but did not contribute substantially to long-term indicators of soil health.
These findings underscore the importance of considering the interaction between fertilizer type and crop species in the design of crop rotation systems. Organic inputs, when strategically paired with microbial-stimulating crops, like pepper, may optimize soil microbial functioning and nutrient cycling. However, this approach also presents challenges, such as the need for careful monitoring of soil pH, nitrogen availability and synchronization, and the potential buildup of salinity.
Looking forward, the key challenge will be to refine and implement fertilization regimes that are not only crop-specific but responsive to site conditions and long-term sustainability goals. Future research should focus on developing dynamic nutrient management frameworks that integrate organic and inorganic inputs, account for microbial functional diversity, and mitigate the risks associated with acidification and nutrient imbalance. Moreover, there is a pressing need to evaluate these systems under varying climatic and soil conditions to ensure their adaptability and resilience.
In summary, our findings indicate that, under the specific pedoclimatic conditions of this study, organic fertilization can independently enhance soil ecosystem functioning, regardless of the crop rotation scheme. This suggests that neither crop rotation nor organic amendment alone can be universally regarded as superior; rather, their effectiveness is highly context-dependent. A synergistic strategy that combines tailored organic inputs with carefully planned crop rotations appears to be the most effective approach for improving soil health, strengthening agroecosystem resilience, and advancing sustainable agricultural productivity.

Author Contributions

Conceptualization, A.M. (Adele Muscolo); methodology, F.M.; software, A.M. (Angela Maffia); validation, A.M. (Angela Maffia); S.B., F.M., M.O., and C.M.; investigation, S.B.; resources, A.M. (Adele Muscolo); data curation, A.M. (Angela Maffia); writing—original draft preparation, A.M. (Adele Muscolo); writing—review and editing, A.M. (Angela Maffia) and A.M. (Adele Muscolo); visualization, S.B.; supervision, A.M (Adele Muscolo); project administration, A.M. (Adele Muscolo); funding acquisition, A.M. (Adele Muscolo). All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the project LIFE20 ENV/IT/000229—LIFE RecOrgFert PLUS, and funded by the LIFE Programme of the European Commission.

Data Availability Statement

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

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cole, M.B.; Augustin, M.A.; Robertson, M.J.; Manners, J.M. The Science of Food Security. Npj Sci. Food 2018, 2, 14. [Google Scholar] [CrossRef] [PubMed]
  2. Techen, A.-K.; Helming, K. Pressures on Soil Functions from Soil Management in Germany. A Foresight Review. Agron. Sustain. Dev. 2017, 37, 64. [Google Scholar] [CrossRef]
  3. Virto, I.; Imaz, M.; Fernández-Ugalde, O.; Gartzia-Bengoetxea, N.; Enrique, A.; Bescansa, P. Soil Degradation and Soil Quality in Western Europe: Current Situation and Future Perspectives. Sustainability 2014, 7, 313–365. [Google Scholar] [CrossRef]
  4. Chew, K.W.; Chia, S.R.; Yen, H.-W.; Nomanbhay, S.; Ho, Y.-C.; Show, P.L. Transformation of Biomass Waste into Sustainable Organic Fertilizers. Sustainability 2019, 11, 2266. [Google Scholar] [CrossRef]
  5. Muscolo, A.; Mauriello, F.; Marra, F.; Calabrò, P.S.; Russo, M.; Ciriminna, R.; Pagliaro, M. AnchoisFert: A New Organic Fertilizer from Fish Processing Waste for Sustainable Agriculture. Glob. Chall. 2022, 6. [Google Scholar] [CrossRef]
  6. Maffia, A.; Marra, F.; Celano, G.; Oliva, M.; Mallamaci, C.; Hussain, M.I.; Muscolo, A. Exploring the Potential and Obstacles of Agro-Industrial Waste-Based Fertilizers. Land 2024, 13, 1166. [Google Scholar] [CrossRef]
  7. Panuccio, M.R.; Marra, F.; Maffia, A.; Mallamaci, C.; Muscolo, A. Recycling of Agricultural (Orange and Olive) Bio-Wastes into Ecofriendly Fertilizers for Improving Soil and Garlic Quality. Resour. Conserv. Recycl. Adv. 2022, 15, 200083. [Google Scholar] [CrossRef]
  8. Rodale Institute. Regenerative Organic Agriculture and Climate Change a Down- to-Earth Solution to Global Warming. 2014. Available online: https://rodaleinstitute.org/wp-content/uploads/rodale-white-paper.pdf (accessed on 2 March 2025).
  9. Liu, C.; Plaza-Bonilla, D.; Coulter, J.A.; Kutcher, H.R.; Beckie, H.J.; Wang, L.; Floc’h, J.-B.; Hamel, C.; Siddique, K.H.M.; Li, L.; et al. Diversifying Crop Rotations Enhances Agroecosystem Services and Resilience. Adv. Agron. 2022, 173, 299–335. [Google Scholar] [CrossRef]
  10. Pradhan, G.; Meena, R.S.; Kumar, S.; Lal, R. Utilizing Industrial Wastes as Compost in Wheat-Rice Production to Improve the above and below-Ground Ecosystem Services. Agric. Ecosyst. Environ. 2023, 358, 108704. [Google Scholar] [CrossRef]
  11. Rai, A.; Singh, A.K.; Mishra, R.; Shahi, B.; Rai, V.K.; Kumari, N.; Kumar, V.; Gangwar, A.; Sharma, R.B.; Rajput, J.; et al. Sulphur in Soils and Plants: An Overview. Int. Res. J. Pure Appl. Chem. 2020, 21, 66–70. [Google Scholar] [CrossRef]
  12. Lisowska, A.; Filipek-Mazur, B.; Kalisz, A.; Gorczyca, O.; Kowalczyk, A. Changes in Soil Sulfate Sulfur Content as an Effect of Fertilizer Granules Containing Elemental Sulfur, Halloysite and Phosphate Rock. Agronomy 2023, 13, 1410. [Google Scholar] [CrossRef]
  13. Sayara, T.; Basheer-Salimia, R.; Hawamde, F.; Sánchez, A. Recycling of Organic Wastes through Composting: Process Performance and Compost Application in Agriculture. Agronomy 2020, 10, 1838. [Google Scholar] [CrossRef]
  14. Maffia, A.; Scotti, R.; Wood, T.; Muscolo, A.; Lepore, A.; Acocella, E.; Celano, G. Transforming Agricultural and Sulfur Waste into Fertilizer: Assessing the Short-Term Effects on Microbial Biodiversity via a Metagenomic Approach. Life 2024, 14, 1633. [Google Scholar] [CrossRef] [PubMed]
  15. Maffia, A.; Marra, F.; Canino, F.; Oliva, M.; Mallamaci, C.; Celano, G.; Muscolo, A. Comparative Study of Fertilizers in Tomato-Grown Soils: Soil Quality, Sustainability, and Carbon/Water Footprints. Soil Syst. 2023, 7, 109. [Google Scholar] [CrossRef]
  16. Russo, M.; Di Sanzo, R.; Marra, F.; Carabetta, S.; Maffia, A.; Mallamaci, C.; Muscolo, A. Waste-Derived Fertilizer Acts as Biostimulant, Boosting Tomato Quality and Aroma. Agronomy 2023, 13, 2854. [Google Scholar] [CrossRef]
  17. Marra, F.; Maffia, A.; Canino, F.; Greco, C.; Mallamaci, C.; Adele, M. Effects of fertilizer produced from agro-industrial wastes on the quality of two different soils. Arch. Agron. Soil Sci. 2023, 69, 3600–3618. [Google Scholar] [CrossRef]
  18. Muscolo, A.; Mallamaci, C.; Settineri, G.; Calamara, G. Increasing soil and crop productivity by using agricultural wastes pelletized with elemental sulfur and bentonite. Agron. J. 2017, 109, 1900–1910. [Google Scholar] [CrossRef]
  19. Muscolo, A.; Papalia, T.; Settineri, G.; Romeo, F.; Mallamaci, C. Three different methods for turning olive pomace in resource: Benefits of the end products for agricultural purpose. Sci. Total Environ. 2019, 662, 1–7. [Google Scholar] [CrossRef]
  20. Muscolo, A.; Romeo, F.; Marra, F.; Mallamaci, C. Transforming agricultural, municipal and industrial pollutant wastes into fertilizers for a sustainable healthy food production. J. Environ. Manag. 2021, 17, 113771. [Google Scholar] [CrossRef]
  21. Ben Said, I.; Muscolo, A.; Mezghani, I.; Chaieb, M. Reclaimed municipal wastewater for forage production. Water Sci. Technol. 2017, 75, 1784–1793. [Google Scholar]
  22. Severson, R.C.; Shacklette, H.T. Essential Elements and Soil Amendments for Plants: Sources and Use for Agriculture, 1017; US Government Printing Office: Washington, DC, USA, 1988.
  23. Bouyoucos, G.J. Hydrometer Method Improved for Making Particle Size Analyses of Soils1. Agron. J. 1962, 54, 464–465. [Google Scholar] [CrossRef]
  24. Walkley, A.; Black, I.A. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 1934, 37, 29–38. [Google Scholar] [CrossRef]
  25. Kjeldahl, J. Neue Methode zur Bestimmung des Stickstoff in organishen Kopern. Anal. Chem. 1883, 22, 354–358. [Google Scholar]
  26. Kaminsky, R.; Müller, W.H. A recommendation against the use of alkaline soil extractions in the study of allelopathy. Plant Soil 1978, 49, 641–645. [Google Scholar] [CrossRef]
  27. Box, J.D. Investigation of the Folin–Ciocalteau reagent for the determination of polyphenolic substances in natural waters. Water Res. 1983, 17, 511–525. [Google Scholar] [CrossRef]
  28. Hendershot, W.H.; Duquette, M. A Simple Barium Chloride Method for Determining Cation Exchange Capacity and Exchangeable Cations. Soil Sci. Soc. Am. J. 1986, 50, 605–608. [Google Scholar] [CrossRef]
  29. Maffia, A.; Marra, F.; Canino, F.; Battaglia, S.; Mallamaci, C.; Oliva, M.; Muscolo, A. Humic Substances from Waste-Based Fertilizers for Improved Soil Fertility. Agronomy 2024, 14, 2657. [Google Scholar] [CrossRef]
  30. Vance, E.D.; Brookes, P.C.; Jenkinson, D.S. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 1987, 19, 703–707. [Google Scholar] [CrossRef]
  31. Adam, G.; Duncan, H. Development of a sensitive and rapid method for the measurement of total microbial activity using fluorescein diacetate (FDA) in a range of soils. Soil Biol. Biochem. 2001, 33, 943–951. [Google Scholar] [CrossRef]
  32. Von Mersi, W.; Schinner, F. An improved and accurate method for determining the dehydrogenase activity of soils with iodonitrotetrazolium chloride. Biol. Fertil. Soils 1991, 11, 216–220. [Google Scholar] [CrossRef]
  33. Sidari, M.; Santonoceto, C.; Anastasi, U.; Preiti, G.; Muscolo, A. Variations in four genotypes of lentil under NaCl-salinity stress. Am. J. Agron. Biol. Sci. 2008, 3, 410–416. [Google Scholar] [CrossRef]
  34. Liu, Q.; Zhao, Y.; Li, T.; Chen, L.; Chen, Y.; Sui, P. Changes in Soil Microbial Biomass, Diversity, and Activity with Crop Rotation in Cropping Systems: A Global Synthesis. Appl. Soil Ecol. 2023, 186, 104815. [Google Scholar] [CrossRef]
  35. Venter, Z.S.; Jacobs, K.; Hawkins, H.-J. The impact of crop rotation on soil microbial diversity: A meta-analysis. Pedobiologia 2016, 59, 215–223. [Google Scholar] [CrossRef]
  36. Wang, L.; Zhao, Y.; Al-Kaisi, M.; Yang, J.; Chen, Y.; Sui, P. Effects of seven diversified crop rotations on selected soil health indicators and wheat productivity. Agronomy 2020, 10, 235. [Google Scholar] [CrossRef]
  37. Zani, C.F.; Manning, D.A.C.; Abbott, G.D.; Taylor, J.A.; Cooper, J.; Lopez-Capel, E. Diversified Crop Rotations and Organic Amendments as Strategies for Increasing Soil Carbon Storage and Stabilisation in UK Arable Systems. Front. Environ. Sci. 2023, 11, 1113026. [Google Scholar] [CrossRef]
  38. Zhou, J.; Xu, H.; Zhang, M.; Feng, R.; Xiao, H.; Xue, C. Impact of Organic Amendments on Black Wheat Yield, Grain Quality, and Soil Biochemical Properties. Agronomy 2025, 15, 961. [Google Scholar] [CrossRef]
  39. Loaiza Puerta, V.; Pujol Pereira, E.I.; Wittwer, R.; van der Heijden, M.; Six, J. Improvement of Soil Structure through Organic Crop Management, Conservation Tillage and Grass-Clover Ley. Soil Tillage Res. 2018, 180, 1–9. [Google Scholar] [CrossRef]
  40. Chen, Q.; Song, Y.; An, Y.; Lu, Y.; Zhong, G. Soil Microorganisms: Their Role in Enhancing Crop Nutrition and Health. Diversity 2024, 16, 734. [Google Scholar] [CrossRef]
  41. Howe, J.A.; McDonald, M.D.; Burke, J.; Robertson, I.; Coker, H.; Gentry, T.J.; Lewis, K.L. Influence of Fertilizer and Manure Inputs on Soil Health: A Review. Soil Secur. 2024, 16, 100155. [Google Scholar] [CrossRef]
  42. Souri, B.; Sayadi, Z. Efficiency of Sulfur-Bentonite Granules to Improve Uptake of Nutrient Elements by the Crop Plant Cultivated in Calcareous Soil. Commun. Soil Sci. Plant Anal. 2021, 52, 2414–2430. [Google Scholar] [CrossRef]
  43. Huang, Y.; Kang, R.; Mulder, J.; Zhang, T.; Duan, L. Nitrogen Saturation, Soil Acidification, and Ecological Effects in a Subtropical Pine Forest on Acid Soil in Southwest China. J. Geophys. Res. Biogeosci. 2015, 120, 2457–2472. [Google Scholar] [CrossRef]
  44. Tejada, M.; Garcia, C.; Gonzalez, J.L.; Hernandez, M.T. Use of Organic Amendment as a Strategy for Saline Soil Remediation: Influence on the Physical, Chemical and Biological Properties of Soil. Soil Biol. Biochem. 2006, 38, 1413–1421. [Google Scholar] [CrossRef]
  45. Lal, R. Soil Carbon Sequestration to Mitigate Climate Change. Geoderma 2004, 123, 1–22. [Google Scholar] [CrossRef]
  46. Titirmare, N.S.; Ranshur, N.J.; Patil, A.H.; Patil, S.R.; Margal, P.B. Effect of Inorganic Fertilizers and Organic Manures on Physical Properties of Soil: A Review. Int. J. Plant Soil Sci. 2023, 35, 1015–1023. [Google Scholar] [CrossRef]
  47. Gao, Y.; Sun, S.; Xing, F.; Mu, X.; Bai, Y. Nitrogen Addition Interacted with Salinity-Alkalinity to Modify Plant Diversity, Microbial PLFAs and Soil Coupled Elements: A 5-Year Experiment. Appl. Soil Ecol. 2019, 137, 78–86. [Google Scholar] [CrossRef]
  48. Badri, D.V.; Vivanco, J.M. Regulation and Function of Root Exudates. Plant Cell Environ. 2009, 32, 666–681. [Google Scholar] [CrossRef]
  49. Maeder, P.; Fliessbach, A.; Dubois, D.; Gunst, L.; Fried, P.; Niggli, U. Soil Fertility and Biodiversity in Organic Farming. Science 2002, 296, 1694–1697. [Google Scholar] [CrossRef]
  50. Philippot, L.; Raaijmakers, J.M.; Lemanceau, P.; van der Putten, W.H. Going Back to the Roots: The Microbial Ecology of the Rhizosphere. Nat. Rev. Microbiol. 2013, 11, 789–799. [Google Scholar] [CrossRef]
Land 14 01171 g001
Figure 1. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the second cycle of broccoli–tomato crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Figure 1. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the second cycle of broccoli–tomato crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Land 14 01171 g001
Land 14 01171 g002
Figure 2. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–tomato crop rotation. The first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Figure 2. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–tomato crop rotation. The first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Land 14 01171 g002
Land 14 01171 g003
Figure 3. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the second cycle of the broccoli–tomato crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Figure 3. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the second cycle of the broccoli–tomato crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Land 14 01171 g003
Land 14 01171 g004
Figure 4. Principal component analysis (PCA) of chemical, biochemical, and ionic soil parameters under the broccoli–tomato crop rotation. The biplot represents soil samples collected after the first cycle (T01, CTR1, NPK1, HM1, SBO1) and the second cycle (T02, CTR2, NPK2, HM2, SBO2).
Figure 4. Principal component analysis (PCA) of chemical, biochemical, and ionic soil parameters under the broccoli–tomato crop rotation. The biplot represents soil samples collected after the first cycle (T01, CTR1, NPK1, HM1, SBO1) and the second cycle (T02, CTR2, NPK2, HM2, SBO2).
Land 14 01171 g004
Land 14 01171 g005
Figure 5. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the first cycle of the broccoli–pepper crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Figure 5. Fluorescein diacetate hydrolase (FDA, µg FDA/g d.s.), dehydrogenase (DHA, µg TTF/h/g d.s.), and catalase, (CAT, O2/3 min/g d.s.) detected in soil after the first cycle of the broccoli–pepper crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Land 14 01171 g005
Land 14 01171 g006
Figure 6. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–pepper crop rotation. The first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Figure 6. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–pepper crop rotation. The first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Land 14 01171 g006
Land 14 01171 g007
Figure 7. Fluorescein diacetate hydrolase (FDA. µg FDA/g d.s.), dehydrogenase (DHA. µg TTF/h/g d.s.), and catalase. (CAT. O2/3 min/g d.s.) detected in soil after the second cycle of the broccoli–pepper crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Figure 7. Fluorescein diacetate hydrolase (FDA. µg FDA/g d.s.), dehydrogenase (DHA. µg TTF/h/g d.s.), and catalase. (CAT. O2/3 min/g d.s.) detected in soil after the second cycle of the broccoli–pepper crop rotation. The data refers to the open field experiments carried on from October 2022 to July 2023. Soil samples were collected after the tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Land 14 01171 g007
Land 14 01171 g008
Figure 8. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–pepper crop rotation. The second crop rotation cycle, from October 2023 to July 2024, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Figure 8. Cations (a) and anions (b) (mg * g−1 dw) in soil under the broccoli–pepper crop rotation. The second crop rotation cycle, from October 2023 to July 2024, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). Different letters indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05). n.s. = not significant (p > 0.05).
Land 14 01171 g008
Land 14 01171 g009
Figure 9. Principal component analysis (PCA) of chemical, biochemical, and ionic soil parameters under the broccoli–pepper crop rotation. The biplot represents soil samples collected after the first cycle (T01, CTR1, NPK1, HM1, SBO1) and the second cycle (T02, CTR2, NPK2, HM2, SBO2).
Figure 9. Principal component analysis (PCA) of chemical, biochemical, and ionic soil parameters under the broccoli–pepper crop rotation. The biplot represents soil samples collected after the first cycle (T01, CTR1, NPK1, HM1, SBO1) and the second cycle (T02, CTR2, NPK2, HM2, SBO2).
Land 14 01171 g009
Table 1. Chemical characteristic of sulfur bentonite plus orange waste and horse manure fertilizers. Data are the mean of three replications ± standard deviation. Different letters in the same row indicate, significant differences among the treatments (* Tukey’s test, p ≤ 0.05).
Table 1. Chemical characteristic of sulfur bentonite plus orange waste and horse manure fertilizers. Data are the mean of three replications ± standard deviation. Different letters in the same row indicate, significant differences among the treatments (* Tukey’s test, p ≤ 0.05).
Chemical PropertiesHMSBO
pH7.0 a* ± 0.16.8 a ± 0.2
EC (mS/cm)12 a ± 1.11.3 b ± 0.9
Moisture (%)86.7 a ± 3.2nd ± 2.9
OC (%)22.6 a ± 1.96.3 b ± 2.5
TN (%)3.0 a ± 0.60.9 b ± 0.3
C/N7.3 a ± 1.99.3 a ± 1.7
Na+ (mg g−1 dw)1.8 a ± 0.50.12 b ± 0.2
NH4+ (mg g−1 dw)0.24 a ± 0.030.09 b ± 0.04
K+ (mg g−1 dw)3.2 a ± 2.31.32 b ± 2.6
Mg2+ (mg g−1 dw)1.9 a ± 0.41.41 b ± 0.7
Ca2+ (mg g−1 dw)2.3 a ± 0.71.1 b ± 1.0
Cl− (mg g−1 dw)3.8 a ± 0.50.11 b ± 0.6
PO43− (g g−1 dw)2.8 a ± 0.40.3 b ± 0.3
Table 2. Chemical and biological properties of soil after the first crop cycle of the broccoli–tomato rotation (October 2022–July 2023), with samples collected after tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Table 2. Chemical and biological properties of soil after the first crop cycle of the broccoli–tomato rotation (October 2022–July 2023), with samples collected after tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
WC (%)pHECWSPOCOM TNC/NCECMBC
T07.8 ± 0.2 b8.16 ± 0.1 a100 ± 6 e23.3 ± 3 b0.73 ± 0.03 d1.25 ± 0.1 d0.09 ± 0.01 b8.1 ± 0.2 b13.4 ± 0.1 b433 ± 8 e
CTR8 ± 0.2 b8.24 ± 0.2 a171 ± 9 d23.2 ± 2 b1.40 ± 0.02 c2.40 ± 0.3 c0.10 ± 0.02 b14.0 ± 0.2 a15.2 ± 0.1 b476 ± 10 d
HM13 ± 0.2 a8.19 ± 0.2 a232 ± 10 a22.4 ± 3 b1.70 ± 0.04 b2.92 ± 0.1 b0.15 ± 0.01 a11.3 ± 0.1 a17.1 ± 0.2 a752 ± 12 b
SBO16 ± 0.2 a7.99 ± 0.1 a207 ± 8 b28.8 ± 2 a1.98 ± 0.1 a3.40 ± 0.2 a0.14 ± 0.02 a14.1 ± 0. 2 a17.0 ± 0.2 a788 ± 11 a
NPK16 ± 0.2 a8.38 ± 0.2 a195 ± 9 b19.5 ± 3 b1.67 ± 0.07 b2.87 ± 0.2 b0.18 ± 0.02 a9.2 ± 0.01 b16.5 ± 0.02 a611 ± 13 c
Table 3. Chemical and biological properties of soil after the second crop cycle of the broccoli–tomato rotation (October 2022–July 2023), with samples collected after tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Table 3. Chemical and biological properties of soil after the second crop cycle of the broccoli–tomato rotation (October 2022–July 2023), with samples collected after tomato harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
WC (%)pHECWSPOCTNC/NOM CECMBC
T07.85 ± 0.2 c8.16 ± 0.2 a100 ± 7 d23.3 ± 2 c0.73 ± 0.05 d0.09 ± 0.001 b8.1 ± 1 d1.25 ± 0.05 d13.4 ± 0.5 c433 ± 15 d
CTR11.0 ± 0.1 b8.21 ± 0.1 a217 ± 9 c45.1 ± 6 a1.62 ± 0.1 c0.08 ± 0.002 b20.2 ± 3 a2.40 ± 0.1 c15.7 ± 0.7 a498 ± 14 d
HM14.0 ± 0.7 a7.89 ± 0.2 ab220 ± 8 c30.2 ± 4 b2.14 ± 0.2 ab0.19 ± 0.001 a11.2 ± 1 c3.68 ± 0.2 a16.3 ± 0.5 a952 ± 15 b
SBO14.0 ± 0.6 a7.50 ± 0.2 b310 ± 11 b27.9 ± 3 b2.30 ± 0.2 a0.17 ± 0.001 a13.5 ± 2 b3.95 ± 0.3 a15.0 ± 1 a988 ± 10 a
NPK11.0 ± 0.8 b8.29 ± 0.3 a370 ± 9 a25.0 ± 2 c1.95 ± 0.1 b0.17 ± 0.002 a11.4 ± 1 c3.35 ± 0.2 b14.4 ± 0.4 b0761 ± 11 c
Table 4. Chemical analysis of soil under the broccoli–pepper crop rotation. The first cycle refers to the first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Table 4. Chemical analysis of soil under the broccoli–pepper crop rotation. The first cycle refers to the first crop rotation cycle, from October 2022 to July 2023, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
WC (%)pHECWSPOCTNC/NOM CECMBC
T07.85 ± 0.2 c8.16 ± 0.3 a100 ± 2.1 c23.34 ± 0.6 b0.73 ± 0.5 c0.09 ± 0.5 b8.1 ± 0.6 c1.25 ± 0.1 c13.4 ± 0.4 b433 ± 4.6 c
CTR9.3 ± 2.1 b8.16 ± 0.5 a188 ± 4.1 b30.96 ± 0.7 a1.48 ± 0.4 b0.08 ± 0.1 b18.5 ± 0.3 a2.54 ± 0.7 b14.1 ± 0.5 b499 ± 3.4 c
HM16.5 ± 1.2 a8.14 ± 0.7 a233 ± 2.3 ba26.85 ± 0.5 b1.93 ± 0.1 b0.18 ± 0.1 a10.7 ± 0.5 b3.31 ± 0.2 a18.2 ± 0.5 a852 ± 4.4 b
SBO16.5 ± 3.1 a7.94 ± 0.9 a275 ± 2.1 a24.34 ± 2.1 b2.16 ± 0.1 a0.17 ± 0.2 a12.7 ± 0.4 ab3.71 ± 0.1 a16.9 ± 0.7 a988 ± 5.6 a
NPK16.00 ± 3.4 a8.38 ± 0.1 a295 ± 3.4 a19.55 ± 1.4 c1.67 ± 0.3 b0.18 ± 0.1 a9.2 ± 0.6 c2.87 ± 0.2 b15.6 ± 0.8 b735 ± 5.5 b
Table 5. Chemical analysis of soil under the broccoli–pepper crop rotation. The second cycle refers to the second crop rotation cycle, from October 2023 to July 2024, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
Table 5. Chemical analysis of soil under the broccoli–pepper crop rotation. The second cycle refers to the second crop rotation cycle, from October 2023 to July 2024, with soil samples collected after the pepper harvest. The treatments include T0 (initial soil), CTR (unfertilized control), HM (horse manure), SBO (sulfur bentonite plus orange waste), and NPK (mineral fertilizer). The measured variables include water content (WC, %), pH, electrical conductivity (EC, µS cm−1), water-soluble phenols (WSP, µg TAE g−1 dry soil), organic carbon (OC, %), organic matter (OM, %), total nitrogen (TN, %), carbon-to-nitrogen ratio (C/N), cation exchange capacity (CEC, cmol+ kg−1), and microbial biomass carbon (MBC, µg C g−1). Values are expressed as a mean ± standard deviation. Different letters within the same column indicate statistically significant differences among the treatments according to Tukey’s test (p < 0.05).
WC (%)pHECWSPOCTNC/NOMCECMBC
T07.85 ± 0.1 c8.16 ± 0.1 a100 ± 1.5 b23.34 ± 1.5 b0.73 ± 0.1 c0.09 ± 0.2 a8.1 ± 0.7 c1.25 ± 0.1 c13.4 ± 1.2 b433 ± 2.5 c
CTR10 0 ± 0.2 b8.25 ± 0.2 a192 ± 2.5 ab37.5 ± 0.5 a1.54 ± 0.1 b0.10 ± 0.3 a15.4 ± 0.8 a2.65 ± 0.3 b13.9 ± 1.3 b501 ± 2.7 c
HM13.5 ± 0.2 b7.97 ± 0.4 a223 ± 2.7 a25.50 ± 1.7 b1.93 ± 0.2 b0.16 ± 0.3 a12.1 ± 1.1 b3.31 ± 0.3 a15.2 ± 1.6 a879 ± 3.5 a
SBO13.0 ± 0.3 b7.81 ± 0.4 a249 ± 3.5 a32.50 ± 1.2 a2.10 ± 0.2 a0.13 ± 0.3 a16.2 ± 1.2 a3.61 ± 0.4 a15.81 ± 1.2 a955 ± 4.7 a
NPK16.00 ± 0.3 a8.38 ± 0.7 a264 ± 2.3 a19.55 ± 1.4 c1.67 ± 0.3 b0.18 ± 0.2 a9.2 ± 1.2 bc2.87 ± 0.1 b15.6 ± 1.2 a755 ± 5.6 b
Table 6. Correlation matrix (Pearson (n − 1) among soil chemical, biochemical, and ionic variables measured across both crop rotation cycles and all fertilization treatments. Values in bold are different from 0 with a significance level, alpha = 0.005.
Table 6. Correlation matrix (Pearson (n − 1) among soil chemical, biochemical, and ionic variables measured across both crop rotation cycles and all fertilization treatments. Values in bold are different from 0 with a significance level, alpha = 0.005.
VariablesWCpHECWSPFDACATDHAOCTNC/NOMCECMBC
WC1−0.3130.4460.0420.1440.0490.2420.7730.7600.1410.7790.8000.718
pH−0.3131−0.242−0.199−0.7300.615−0.901−0.506−0.326−0.132−0.522−0.064−0.715
EC0.446−0.24210.2250.209−0.106−0.0200.8200.6380.3340.8100.2690.704
WSP0.042−0.1990.2251−0.2740.1460.0800.275−0.2650.8420.1590.1160.062
FDA0.144−0.7300.209−0.2741−0.9010.7810.2660.399−0.3840.345−0.0990.642
CAT0.0490.615−0.1060.146−0.9011−0.632−0.056−0.1800.394−0.1200.394−0.416
DHA0.242−0.901−0.0200.0800.781−0.63210.2670.183−0.0350.2910.0970.573
OC0.773−0.5060.8200.2750.266−0.0560.26710.7670.4260.9920.6400.892
TN0.760−0.3260.638−0.2650.399−0.1800.1830.7671−0.2250.8210.4900.839
C/N0.141−0.1320.3340.842−0.3840.394−0.0350.426−0.22510.3200.3610.089
OM0.779−0.5220.8100.1590.345−0.1200.2910.9920.8210.32010.6250.922
CEC0.800−0.0640.2690.116−0.0990.3940.0970.6400.4900.3610.62510.481
MBC0.718−0.7150.7040.0620.642−0.4160.5730.8920.8390.0890.9220.4811
Table 7. The p-values from three-way ANOVA testing the effects of fertilization, crop rotation, and year on soil chemical and biological variables. Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001, n.s. = not significant (p > 0.05).
Table 7. The p-values from three-way ANOVA testing the effects of fertilization, crop rotation, and year on soil chemical and biological variables. Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001, n.s. = not significant (p > 0.05).
VariableFertilizerFertilizer × RotationFertilizer × YearFertilizer × Year × RotationRotationYearYear × Rotation
C/N************n.s******
CAT******************n.s
CEC****************n.s
DHA******************
EC***n.s******n.s******
FDA************n.s***n.s
MBC*******************
OC*******n.s******
OM***********n.s******
TN***n.s******n.sn.s***
WC*********************
WSP*********************
pH***n.s*n.sn.s***n.s
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Maffia, A.; Marra, F.; Oliva, M.; Battaglia, S.; Mallamaci, C.; Muscolo, A. Sustainable Soil Management: The Dynamic Impact of Combined Use of Crop Rotation and Fertilizers from Agri-Food and Sulfur Hydrocarbon Refining Processes Wastes. Land 2025, 14, 1171. https://doi.org/10.3390/land14061171

AMA Style

Maffia A, Marra F, Oliva M, Battaglia S, Mallamaci C, Muscolo A. Sustainable Soil Management: The Dynamic Impact of Combined Use of Crop Rotation and Fertilizers from Agri-Food and Sulfur Hydrocarbon Refining Processes Wastes. Land. 2025; 14(6):1171. https://doi.org/10.3390/land14061171

Chicago/Turabian Style

Maffia, Angela, Federica Marra, Mariateresa Oliva, Santo Battaglia, Carmelo Mallamaci, and Adele Muscolo. 2025. "Sustainable Soil Management: The Dynamic Impact of Combined Use of Crop Rotation and Fertilizers from Agri-Food and Sulfur Hydrocarbon Refining Processes Wastes" Land 14, no. 6: 1171. https://doi.org/10.3390/land14061171

APA Style

Maffia, A., Marra, F., Oliva, M., Battaglia, S., Mallamaci, C., & Muscolo, A. (2025). Sustainable Soil Management: The Dynamic Impact of Combined Use of Crop Rotation and Fertilizers from Agri-Food and Sulfur Hydrocarbon Refining Processes Wastes. Land, 14(6), 1171. https://doi.org/10.3390/land14061171

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop