1. Introduction

2. Materials and Methods

2.3. Soil physical, chemical, and biochemical analysis before and after treatment

Potted soils before treatment were analyzed for physical and chemical properties. Soils were taken in the Grecanica area, specifically in the municipalities of Reggio di Calabria (RC) (soil 1) and Motta San Giovanni (RC) (soil 2). It was used a sandy-loam soil (soil 1) and a sandy-clay soil (soil 2) as stated by FAO soil classification system [30]. Soil texture has been detected by using the hydrometer method [31]. pH was measured in distilled water (soil/solution ratio 1:2.5) with a glass electrode. Electric conductibility (EC) was determined in distilled water by using 1:5 soil/water suspension mechanically shaken at 15 rpm for 1 h and then detected by Hanna instrument conductivity meter. CEC (Cation exchange capacity) was determined with Mehlich methodology [32]. Organic carbon was assessed with dichromate oxidation method [33] and transformed into organic matter multiplying by 1.72; Total nitrogen (TN) was measured with Kjeldahl method [34]. C/N was determined as a carbon/nitrogen ratio. Water soluble phenols were extracted in triplicate as reported by Kaminsky et al. [35]. Gallic acid was used as a standard and the concentration of water-soluble phenolic compounds was expressed as Gallic acid equivalents (μg GAE g^-1 d.s). Microbial biomass carbon (MBC) was determined by using the chloroform fumigation-extraction procedure on fresh soil. [36] Fumigated and unfumigated soil sample extracts were used to detect soluble organic C using the methods of Walkley and Black [33]

Table 1. Physical and chemical properties of soils before fertilization.

Table 1. Physical and chemical properties of soils before fertilization.

	SOIL 1	SOIL 2
Skeleton (%)	45	21
Sandy %	65	50
Clay %	23	27
Loam %	12	23
Textural Class	Sandy-loam	Sandy-Clay-loam
Moisture %	18	32
S.S (%)	82	68
pH (H2O)	8.5	8.3
pH (KCl)	7.8	7.3
EC (μS/cm)	107.3	302
CEC (cmol(+) kg-1)	21.57	27.71
TOC %	1.78	1.98
TN %	0.19	0.2
C/N	9.37	9.9
SOM %	3.07	3.41
WSP (µg GAE g-1 d.s)	56.1	85.62
MBC (μg C g−1 soil)	896	941

Dehydrogenase (DHA) activity was detected with iodonitrotetrazolium chloride according to von Mersi and Shinner method [37]. Catalase activity (CAT) was detected by the method of Kuush et al.[38] measuring the absorbance during the conversion of H₂O₂ to oxygen and water. The decrease in the absorbance was measured at 240 nm, utilizing the extinction coefficient of 39.4 M⁻¹ cm⁻¹. Fluorescein diacetate hydrolase (FDA) activity was determined according to the method of Adam and Duncan [39]. Beta glucosidase activity was tested as reported Valášková et al [40] with few modifications as reported in Muscolo et al. [19]. Soil (1 g fresh weight) was placed into a plastic tube and treated with 4 mL of modified universal buffer (MUB, pH 6). The reaction mixture contains 0.16 mL of 1.2 mM PNPsubstrate (p-nitrophenyl-β-D-glucoside) in 50 mM sodium acetate buffer (pH 5.0) and 0.04 mL of the sample. Reaction mixtures were incubated at 40 °C for 20–120 min. After incubation the reaction was stopped and the yellow color from the p-nitrophenol was developed by the addition of 0.1 mL of 0.5 M sodium carbonate, the p-nitrophenol absorbance was measured on a spectrophotometer at a wavelength of 400 nm and quantified by comparison with a standard curve. Protease activity was detected as reported by Sidari et al. [41]. Two ml of phosphate buffer (0.1 M, pH 7.1) and 0.5 ml of 0.03 M N-a-benzoyl-L arginin amide (BAA) have been added to 1 g of wet soil. The mixture was incubated at 37 °C for 1h and 30 min, then diluted to 10 ml with distilled water. The ammonium concentration was detected with an ammonium selective electrode (CRISON, micro-pH 2002). Urease activity was determined following the method of Kandeler and Gerber [42], with few modifications as reported in Sidari et al. [41]. Five grams of fresh soil were mixed with 2.5 ml of urea (80 mM) and 20 ml 0.1 M borate buffer at pH 10.0. After 2 h in an orbital shaker at 37 °C, 2.5 ml of urea were added to the control. add 30 ml of KCl (2 M) were instead added to both sample and control, shake for 30 min. One ml of the filtered solutions was mixed with 9 ml of distilled water, 5 ml of sodium/salicylate solution, and 2 ml of dichloroisocyanuric acid. Ammonium concentrations were determined at 690 nm by using a calibration curve. The results are reported as µg N-NH₄/g ds/3h. [41].

Table 2. Soil enzymatic activities before fertilization. Dehydrogenase (DHA, µg INTF g^-1 d.s h^-1). Catalase activity (CAT. O₂/3min/g d.s). Fluorescein diacetate hydrolase (FDA, µg fluorescein g ^-1 d.s). Urease (URE, N-NH₄/g ds/3h). ß-glucosidase (ßGLU, µg para-nitrophenol (p-NP) g/h). Protease (PRO µg Tyrosine *g d.s *2h).

Table 2. Soil enzymatic activities before fertilization. Dehydrogenase (DHA, µg INTF g^-1 d.s h^-1). Catalase activity (CAT. O₂/3min/g d.s). Fluorescein diacetate hydrolase (FDA, µg fluorescein g ^-1 d.s). Urease (URE, N-NH₄/g ds/3h). ß-glucosidase (ßGLU, µg para-nitrophenol (p-NP) g/h). Protease (PRO µg Tyrosine *g d.s *2h).

	SOIL 1	SOIL 2
DHA	1.31	2.83
CAT	1.54	3.85
FDA	8.93	15.10
ß-GLU	514	348
PRO	167	157
URE	312	289

2.4. Environmental impact: Carbon and Water footprint.

The study was carried in Grecanica Area, specifically in Motta San Giovanni, province of Reggio Calabria. The main features of the studied system were collected through visits to farm, direct interview with farmers using a specific collection sheet. The farm carried out the treatments by subdividing 4 experimental plots, carrying out the treatments described in section 2. The farm grew tomatoes of the Big Rio F1 variety, with a planting density of 3 plants/m2, with a sprinkler irrigation system. Pesticide, insecticide and acaricide treatments were the same for all experimental plots, as were soil tillage and harvesting. The only difference between the experimental plots was the fertilization. The farms inputs and outputs used in the analyzed systems are reported in Table 3.

2.4.1. Carbon Footprint

The Life Cycle Assessment approach, according the ISO 14040:2006 [43]. was used to estimate environmental impacts with a focus on Global Warming (GWP 100a) for the Carbon Footprint.

LCA methodology contains four stages: goal and scope definition, life cycle inventory life cycle impact assessment and interpretation. [44] The system boundaries, as shown in Figure 1, starts with planting of tomato plants and ends with harvesting, that following the PCR 2010:07 “Arable and vegetative crops”, corresponds to CORE processes, that are the farming phases: transports of plants, acceptance of plants, planting, harvest. In accordance with the PCR, [45] this study does not include: manufacturing of buildings and capital goods other than agricultural machinery, business travel of personnel, travel to and from work by personnel, research and development activities.

Furthermore, due to the lack of data, the analysis did not consider: input transport (fertilizers and pesticides) from the place of production to the field. All the inputs used in the agricultural phase (fertilizers, pesticides, fuels, various materials utilized during the harvesting) were considered. Primary data were collected in situ during the 2021-2022 agricultural year, from May to October, using a data collection sheet on a farm that carried out the experimentation in collaboration in the open field located in Motta San Giovanni (RC). All inputs are reported in Table 3. Direct emissions from fuel and lubricant were taken from SimaPro’s LCI database.

Table 3. Farm inputs and outputs used in the analyzed systems.

Table 3. Farm inputs and outputs used in the analyzed systems.

	CTR	A	B	C
Fertilizers (kg ha-1)
NPK		170
Horse Manure			430
Sulfur Bentonite + Orange waste				476
Chemicals (kg ha-1)
Primor 50	0.75	0.75	0.75	0.75
Daramun	4	4	4	4
Human labour (h ha-1)	45	46	48	46
Machinery (h ha-1)	5	10	12	10
Diesel (kg ha-1)	10	13	15	13
Water (m3 ha-1)	750	750	750	750
Electricity (kWh kg-1)	0.13	0.14	0.15	0.15
Production (t ha-1)	47	57.5	58	58.4

The impact assessment was performed using SimaPro 9.02, with the problem oriented LCA method developed by the Institute of Environmental Sciences of the University of Leiden [46]. It was used the method CML-IA Baseline V3.06/ EU25 +3, 2000. The following impact categories were considered according to the selected method: abiotic depletion (AD); abiotic depletion (fossil fuels) (AD fossil fuels); global warming potential (GWP) or climate change; photochemical oxidation (PO); ozone layer depletion (ODP); human toxicity (HT); freshwater aquatic ecotoxicity (FWE); marine aquatic ecotoxicity (MAE); terrestrial ecotoxicity (TE); air acidification (AA) and eutrophication (EU).

2.4.2. Water Footprint

For this study WF was performed as established by Hoekstra et al. 2011 [47] in “The Water Footprint assessment manual” that defining the guidelines for the water footprint. The peculiarity of this methodology is the division of the water footprint into 3 components: blue, green, and grey. The total water footprint is given by the sum of them according to the formula below:

WF_total: WF_green + WF_Blue + WF_grey.

Particularly, for the WFP blue and green is required the calculation of the crop water requirement (CWR, m³ ha^-1), following the formulas below:

WF_green= CWU_green/crop yield

WF_blue= CWU_blue/crop yield

The green and blue components of CWU (m³ ha^-1) were calculation by accumulation of daily evapotranspiration (ET mm/day) over the whole growing season:

$$\mathrm{C}\mathrm{W}\mathrm{U}\mathrm{g}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{n}=10\mathrm{x}{\sum }_{d=1}^{d=harvesting}ETgreen$$

$$\mathrm{C}\mathrm{W}\mathrm{U}\mathrm{b}\mathrm{l}\mathrm{u}\mathrm{e}=10\mathrm{x}{\sum }_{d=1}^{d=harvesting}ETblue$$

ET_green represents green water evapotranspiration and ET _blue instead blue water evapotranspiration [47]. The summation is done over the period from the day of planting (day 1) to the day of harvest. The green and blue water evapotranspiration has been estimated by using the CROPWAT model developed by the Food and Agriculture Organization of the United Nations [48] which is based on the method described by Allen et al. [49].

The CROPWAT model offers two different options to calculate evapotranspiration: the ‘crop water requirement option’ (assuming optimal conditions) and the ‘irrigation schedule option’ (including the possibility to specify actual irrigation supply in time [50] and for this study we use the first option. According to Pellegrini et al., [51]:

• ETgreen was calculated as the minimum of Crop WaterRequirement (CWR, mm year⁻¹) and effective precipitation (Peff, mm year⁻¹).
• ETblue was estimated from Irrigation Requirement (IR) rates as the minimum betweenIR (m3 year−1) and the irrigation volume (Ieff, m3 ha−1 year−1). [51].
• IR was calculated as a constant value for the analyzed systems according to the following equation: IR = max (0; CWR-Peff)

In the CROPWAT 8.0 software, after entering the input data related to climate data of Reggio Calabria in the year 2021-2022, crop Kc, rainfall and soil characteristics we obtained the CWR needed to calculate the green and blue water footprint, as shown in Table 4.

Following Hoekstra et al. 2011 [47], the grey component of Water Footprint was calculated as:

WF product, grey = [(α X AR)/(C _max − C _nat)]/Y

where:

• AR is the chemical application rate to the field per hectare (kg ha⁻¹);
• α is the leaching-run-off fraction;
• c_max is the maximum acceptable concentration for the pollutant considered (kg m⁻³);
• c_nat is the natural concentration for the pollutant considered (kg m⁻³);
• Y is the crop yield (tons ha⁻¹).

For the grey component of WF only nitrogen fertilizers have been considered, according to Hoekstra et al., 2011, [47] because Nitrogen represents an important source of pollution in Europe as can be seen from the Nitrates Directive 1990. [51]. From Legislative Decree 152/2006 the acceptable limit value for nitrogen was found to be 15 mg/l and a leaching factor (𝛼) 0.1 was considered for all cultivation systems.

3. Results

3.1. Effect of different fertilizers on soils quality

The chemical properties of soil 1, assessed six months after the treatments, exhibited significant variations. Notably, there were no significant changes in soil texture. However, in the soils treated with Sulfur Bentonite (SB), notable reductions were observed in both pH in water and KCl levels. Simultaneously, there was an increase in electrical conductivity (EC), suggesting the potential for an enhanced mineralization process with ion release. Additionally, the organic matter content, C/N ratio, cation exchange capacity (CEC), and microbial biomass all experienced increases. (Table 5)

Conversely, in the soils treated with SB, the phenol content and catalase activity decreased compared to all other treatments, while other enzyme activities increased. A strong positive and significant correlation was observed between Microbial Biomass Carbon (MBC), organic matter, pH in KCl, C/N ratio, Water Soluble Phenol (WSP), FDA hydrolysis, Dehydrogenase (DHA) activity, Protease activity, and Urease activity. However, no correlation was found between MBC and beta-glucosidase, and MBC exhibited an inverse correlation with Catalase activity. (Table 6)

Six months after the treatments, the chemical properties of soil 2 exhibited notable variations among the different treatment groups. However, in the soils treated with SB (Sulfur Bentonite), the reductions in both pH (measured in water) and KCl levels were particularly significant, surpassing the changes observed in soil 1. In contrast, Electrical Conductivity (EC), Cation Exchange Capacity (CEC), Organic Matter (OM), C/N ratio, Water-Soluble Phenols (WSP), and Microbial Biomass Carbon (MBC) all followed a similar increasing trend as seen in soil 1. (Table 5)

When examining the biochemical data, akin to the findings in soil 1, the SB-treated soil in soil 2 exhibited elevated levels of DHA (Dehydrogenase), FDA (Fluorescein Diacetate), and Beta-glucosidase activities, surpassing the other treatments, as previously observed. However, in the case of Protease and Urease activities, they displayed increases compared to the control and NPK treatments, aligning with soil 1. (Table 6) Notably, they were found to be on par with the HM (Horse Manure) treatment, marking a departure from the results observed in soil 1.

Furthermore, Catalase activity once again registered its lowest values in the SB-treated soil, confirming the consistent pattern observed in soil 1.

Table 5. Physical and chemical properties of soil 1 and soil 2 six months after treatments with the different fertilizers: CTR= Control unfertilized soil; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue. Values are the mean of three replicates (n=12).

Table 5. Physical and chemical properties of soil 1 and soil 2 six months after treatments with the different fertilizers: CTR= Control unfertilized soil; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue. Values are the mean of three replicates (n=12).

	CTR	A	B	C	CTR	A	B	C
	Soil 1				Soil 2
Skeleton (%)	45a	45a	45a	45a	21a	21a	21a	21a
Sandy %	65a	65a	65a	65a	50a	50a	50a	50 a
Clay %	23a	23a	23a	23a	27a	27a	27a	27a
Loam %	12a	12a	12a	12a	23a	23a	23a	23a
Textural Class	Sandy-loam	Sandy-loam	Sandy-loam	Sandy-loam	Sandy-Clay-loam	Sandy-Clay-loam	Sandy-Clay-loam	Sandy-Clay-loam
pH (H2O)	8.3a	8.76a	8.0b	7.82b	8.2a	8.43a	7.89ab	7.2b
pH (KCl)	7.70a	7.85a	7.75a	7.58b	7.2a	7.1ab	7.4a	6.98b
EC (μS/cm)	106b	123ab	132a	142a	298a	291ab	267b	326a
CEC	20.65b	22.87b	23.65ab	28.56a	26.61b	24.23b	26.45b	31.56a
TOC %	1.67b	1.45b	2.02a	2.03a	1.51b	1.25b	1.98a	2.12a
TN %	0.14a	0.17a	0.16a	0.12ab	0.12b	0.21a	0.19a	0.15b
C/N	11.93b	8.53c	12.63b	16.92a	12.58a	5.95c	10.42b	14.13a
SOM %	2.88b	2.50b	3.48a	3.50a	2.60ab	2.16b	3.41a	3.65a
WSP (µg GAE*g-1 d.s)	55.68a	55.23a	52.45b	51.53b	82.67b	79.81b	91.76a	97.23a
MBC μg C g−1 soil	901b	876b	926a	976a	945b	965b	1023ab	1198a

Different letters in the same row indicate significant differences (Turkey’s test p ≤0.05).

Table 6. Enzymatic activities of Soil 1 and Soil 2 six months after treatments with the different fertilizers. CTR= Control. soil without fertilizer; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue. Dehydrogenase (DHA, µg INTF g^-1 d.s h^-1), Catalase activity (CAT. O₂/3min/g d.s), Fluorescein diacetate hydrolase (FDA, µg fluorescein g ^-1 d.s), Urease (URE, N-NH₄/g ds/3h), ß-glucosidase (ßGLU, µg para-nitrophenol (p-NP) g/h), Protease (PRO µg Tyrosine *g d.s *2h). The date are the mean of three replicates (n=12).

Table 6. Enzymatic activities of Soil 1 and Soil 2 six months after treatments with the different fertilizers. CTR= Control. soil without fertilizer; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue. Dehydrogenase (DHA, µg INTF g^-1 d.s h^-1), Catalase activity (CAT. O₂/3min/g d.s), Fluorescein diacetate hydrolase (FDA, µg fluorescein g ^-1 d.s), Urease (URE, N-NH₄/g ds/3h), ß-glucosidase (ßGLU, µg para-nitrophenol (p-NP) g/h), Protease (PRO µg Tyrosine *g d.s *2h). The date are the mean of three replicates (n=12).

	CTR	A	B	C	CTR	A	B	C
	Soil 1				Soil 2
DHA	1.29b	1.34b	1.59ab	2.01a	2.69b	3.1ab	3.5a	3.8a
FDA	8.56b	8.51b	9.01a	9.34a	14.5b	15.51b	17.01a	19.14a
CAT	1.34a	1.51a	1.01b	0.96b	2.84a	2.51a	2.41a	1.96b
ßGLU	510a	546a	555a	557a	355b	365b	372ab	401a
PRO	165b	157b	167b	212a	145b	157b	177a	201a
URE	298b	312ab	351b	365b	258b	297a	281a	279a

Different letters in the same row indicate significant differences (Turkey’s test p ≤0.05).

Table 7. Correlation matrix (Pearson (n)) of physical, chemical and biochemical properties of soil 1 six months after treatments.

Table 7. Correlation matrix (Pearson (n)) of physical, chemical and biochemical properties of soil 1 six months after treatments.

from\ to	pH (H2O)	pH (KCl)	EC	CEC	TOC %	TN %	C/N	SOM %	WSP	MBC	DHA	FDA	CAT	ßGLU	PRO	URE
pH (H2O)	1	0.853	-0.581	-0.638	-0.974	0.724	-0.938	-0.974	0.845	-0.931	-0.806	-0.902	0.972	-0.344	-0.768	-0.792
pH (KCl)	0.853	1	-0.398	-0.649	-0.718	0.978	-0.965	-0.718	0.618	-0.904	-0.770	-0.771	0.735	-0.075	-0.902	-0.560
EC	-0.581	-0.398	1	0.923	0.666	-0.278	0.600	0.666	-0.922	0.738	0.891	0.865	-0.719	0.944	0.700	0.952
CEC	-0.638	-0.649	0.923	1	0.635	-0.586	0.768	0.635	-0.871	0.858	0.970	0.897	-0.698	0.761	0.905	0.884
TOC %	-0.974	-0.718	0.666	0.635	1	-0.556	0.857	1.000	-0.902	0.884	0.795	0.911	-0.996	0.488	0.679	0.862
TN %	0.724	0.978	-0.278	-0.586	-0.556	1	-0.894	-0.556	0.468	-0.814	-0.682	-0.647	0.578	0.055	-0.875	-0.411
C/N	-0.938	-0.965	0.600	0.768	0.857	-0.894	1	0.857	-0.802	0.983	0.888	0.909	-0.877	0.311	0.932	0.755
SOM %	-0.974	-0.718	0.666	0.635	1.000	-0.556	0.857	1	-0.902	0.884	0.795	0.911	-0.996	0.488	0.679	0.862
WSP	0.845	0.618	-0.922	-0.871	-0.902	0.468	-0.802	-0.902	1	-0.894	-0.935	-0.977	0.932	-0.791	-0.771	-0.996
MBC	-0.931	-0.904	0.738	0.858	0.884	-0.814	0.983	0.884	-0.894	1	0.954	0.969	-0.913	0.482	0.943	0.860
DHA	-0.806	-0.770	0.891	0.970	0.795	-0.682	0.888	0.795	-0.935	0.954	1	0.974	-0.843	0.691	0.940	0.928
FDA	-0.902	-0.771	0.865	0.897	0.911	-0.647	0.909	0.911	-0.977	0.969	0.974	1	-0.942	0.672	0.880	0.960
CAT	0.972	0.735	-0.719	-0.698	-0.996	0.578	-0.877	-0.996	0.932	-0.913	-0.843	-0.942	1	-0.537	-0.728	-0.896
ßGLU	-0.344	-0.075	0.944	0.761	0.488	0.055	0.311	0.488	-0.791	0.482	0.691	0.672	-0.537	1	0.428	0.843
PRO	-0.768	-0.902	0.700	0.905	0.679	-0.875	0.932	0.679	-0.771	0.943	0.940	0.880	-0.728	0.428	1	0.749
URE	-0.792	-0.560	0.952	0.884	0.862	-0.411	0.755	0.862	-0.996	0.860	0.928	0.960	-0.896	0.843	0.749	1

Table 8. Correlation matrix (Pearson (n)) of physical, chemical, and biochemical properties of soil 2 six months after treatment.

Table 8. Correlation matrix (Pearson (n)) of physical, chemical, and biochemical properties of soil 2 six months after treatment.

	pH (H2O)	pH (KCl)	EC	CEC	TOC %	TN %	C/N	SOM %	WSP	MBC	DHA	FDA	CAT	ßGLU	PRO	URE
pH (H2O)	1	0,360	-0,583	-0,966	-0,914	0,314	-0,765	-0,914	-0,961	-0,964	-0,824	-0,922	0,849	-0,923	-0,919	0,127
pH (KCl)	0,360	1	-0,924	-0,491	0,048	0,191	-0,173	0,048	-0,111	-0,514	-0,207	-0,349	0,472	-0,524	-0,315	-0,168
EC	-0,583	-0,924	1	0,737	0,216	-0,506	0,536	0,216	0,337	0,645	0,254	0,445	-0,495	0,606	0,415	-0,163
CEC	-0,966	-0,491	0,737	1	0,816	-0,511	0,853	0,816	0,867	0,918	0,666	0,814	-0,745	0,856	0,805	-0,286
TOC %	-0,914	0,048	0,216	0,816	1	-0,228	0,726	1,000	0,984	0,814	0,807	0,846	-0,718	0,769	0,858	-0,182
TN %	0,314	0,191	-0,506	-0,511	-0,228	1	-0,832	-0,228	-0,176	-0,131	0,278	0,075	-0,189	0,001	0,084	0,934
C/N	-0,765	-0,173	0,536	0,853	0,726	-0,832	1	0,726	0,693	0,592	0,285	0,458	-0,314	0,476	0,455	-0,735
SOM %	-0,914	0,048	0,216	0,816	1,000	-0,228	0,726	1	0,984	0,814	0,807	0,846	-0,718	0,769	0,858	-0,182
WSP	-0,961	-0,111	0,337	0,867	0,984	-0,176	0,693	0,984	1	0,903	0,878	0,925	-0,826	0,871	0,932	-0,073
MBC	-0,964	-0,514	0,645	0,918	0,814	-0,131	0,592	0,814	0,903	1	0,887	0,968	-0,948	0,991	0,961	0,109
DHA	-0,824	-0,207	0,254	0,666	0,807	0,278	0,285	0,807	0,878	0,887	1	0,974	-0,960	0,922	0,979	0,413
FDA	-0,922	-0,349	0,445	0,814	0,846	0,075	0,458	0,846	0,925	0,968	0,974	1	-0,978	0,980	0,999	0,261
CAT	0,849	0,472	-0,495	-0,745	-0,718	-0,189	-0,314	-0,718	-0,826	-0,948	-0,960	-0,978	1	-0,982	-0,973	-0,413
ßGLU	-0,923	-0,524	0,606	0,856	0,769	0,001	0,476	0,769	0,871	0,991	0,922	0,980	-0,982	1	0,973	0,245
PRO	-0,919	-0,315	0,415	0,805	0,858	0,084	0,455	0,858	0,932	0,961	0,979	0,999	-0,973	0,973	1	0,259
URE	0,127	-0,168	-0,163	-0,286	-0,182	0,934	-0,735	-0,182	-0,073	0,109	0,413	0,261	-0,413	0,245	0,259	1

Figure 2. PCA of physical and chemical properties of soil 1 (a) and soil 2 (b) six months after treatments with the different fertilizers with CTR=Control, soil without fertilizer; A=nitrogen:phosphorous:potassium; B=horse manure; C=sulfur bentonite+orange residue.

Figure 2. PCA of physical and chemical properties of soil 1 (a) and soil 2 (b) six months after treatments with the different fertilizers with CTR=Control, soil without fertilizer; A=nitrogen:phosphorous:potassium; B=horse manure; C=sulfur bentonite+orange residue.

Figure 3. PCA of enzymatic activities of soil 1 (a) and soil 2 (b) six months after treatments with the different fertilizers CTR=Control, soil without fertilizer; A=nitrogen:phosphorous:potassium; B=horse manure; C=sulfur bentonite+orange residue .

Figure 3. PCA of enzymatic activities of soil 1 (a) and soil 2 (b) six months after treatments with the different fertilizers CTR=Control, soil without fertilizer; A=nitrogen:phosphorous:potassium; B=horse manure; C=sulfur bentonite+orange residue .

3.2. Environmental impact

3.2.1. Carbon Footprint

The environmental analysis results, with a functional unit of 1 hectare and one ton of tomatoes considered for all impact categories for, can be found in Table 9 and Table 10. For Global Warming Potential (GWP 100a), Figure 4 reveals that among the four analyzed systems, System A has the highest impact at 26.04 kg CO2 eq/ton. This is followed by System B at 23.21 kg CO2 eq/ton and System CTR at 23.05 kg CO2 eq/ton. Notably, System C, which utilized Sulphur fertilizer bentonite, stands out as the most sustainable with an impact value of 22.77 kg CO2 eq/ton.

When breaking down by individual phases as seen in Figure 5, soil tillage emerges as the most impactful phase. This is followed by fertilization, registering an impact of 4.2 kg CO2 eq/ton when applied. The organic fertilization using horse manure (System B) has an impact of 4.5 kg CO2 eq/ton. Meanwhile, synthetic fertilization with NPK (System A) showcases the highest emissions among the systems, with values hitting 7.2 kg CO2 eq/ton.

3.2.2. Water Footrpint

The results of the water footprint (WF) are presented by breaking it down into its components (green, blue and grey) and then as total water consumption. Table 11 gives the data on yields, green evapotranspiration (Et green), blue evapo-transpiration (Et blue), direct and indirect fraction of water used for the different systems analysed, with the WF expressed in m3 per tonne of tomato yield. Since all systems are located in Reggio Calabria (RC) and share identical climatic conditions, green and blue evapotranspiration remains consistent across all systems and differences in productivity result mainly from different fertilisation approaches.

Figure 6. Total Water Footprint (m3/ton) broken down by its components (green, blue, grey) in the different cultivation systems. CTR= Control, soil without fertilizer; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue Values are expressed in m3 per tons of tomato.

Figure 6. Total Water Footprint (m3/ton) broken down by its components (green, blue, grey) in the different cultivation systems. CTR= Control, soil without fertilizer; A= nitrogen:phosphorous:potassium; B= horse manure; C=sulfur bentonite + orange residue Values are expressed in m3 per tons of tomato.

The system with the lowest water footprint is related to the use of sulphur-based bentonite fertilisers (A), which resulted in higher productivity. On the other hand, the control system (CTR) has the highest water footprint due to its lower production.

4. Discussion

5. Conclusions

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