The Influence of Vine Rootstock Type on the Energy Potential of Differentiated Material Obtained from Wine Production

Abstract

In the context of growing demand for renewable energy sources and greenhouse gas emission reductions, increasing attention is being paid to the use of agricultural waste as bioenergy feedstock. The energy potential of biomass in the form of vine stems and pomace from the Regent variety of grapes, grafted onto their own roots and various types of rootstocks (125AA, SO₄, 161-49), was assessed, where the control group consisted of ungrafted shrubs growing on their own roots, cultivated in south-eastern Poland. The analyses included the determination of technical and elementary parameters, pollutant emission indicators, and exhaust gas composition parameters. Compared to stems, pomace had a higher calorific value, higher C and H content, and lower dust emissions, while at the same time emitting more CO₂. Stems, on the other hand, showed higher ash content and higher dust emissions, which may limit their energy potential. Among the analysed substrates, pomace from 125AA achieved the highest calorific values at a low moisture content, while biomass from substrate 161-49 was distinguished by the lowest sulphur content and a favourable emission balance. Cluster analysis showed clear grouping of substrates in terms of fuel and emission parameters, indicating the possibility of optimal substrate selection for the production of bioenergy feedstock. The results confirm that the appropriate selection of rootstocks in viticulture can significantly increase the energy value of waste biomass and reduce emissions, supporting the development of local renewable energy systems.

1. Introduction

The global energy sector is currently in crisis due to its excessive dependence on non-renewable energy sources and their significant negative impact on the environment [1]. Considering that the energy sector generates approximately 40% of global greenhouse gas emissions, decisive action is needed to support the energy transition towards systems based on sustainable, low-carbon energy sources [2]. Alongside global population growth, there is a steady increase in energy demand, which poses additional challenges for energy systems in terms of ensuring security of supply [3]. In view of these challenges, the achievement of Sustainable Development Goal 7 (SDG 7), i.e., ensuring universal access to affordable and clean energy, is becoming a matter of fundamental importance [4].

Sustainable development has emerged as a key pillar of modern social progress, forming the basis of development strategies aimed at balancing social needs [5]. In order to successfully transition to more sustainable energy sources, intensive research into alternative, clean energy technologies is essential [6]. In particular, the exploration of various thermochemical biomass conversion techniques offers promising prospects for the development of sustainable energy solutions based on renewable raw materials [3]. In this context, bioenergy emerges as an important element supporting the implementation of SDG 7, potentially playing a key role in ensuring access to clean and affordable energy sources [7]. The identification and assessment of the potential of biomass from crops provide a basis for strategic planning of energy production from agricultural residues, enabling the optimisation of resource use and increasing the efficiency of bioenergy systems [8]. Biomass is a versatile raw material that can be used for ecological and energy purposes, both in its unprocessed form and after advanced mechanical and chemical processes, such as gasification, pyrolysis or fermentation, which enable the production of a wide range of energy products with high utility value [9].

In the world, biomass is mainly used for the production of biofuels and energy through mechanical, thermal and biochemical conversion processes [10].

Agricultural by-products are a significant and readily available resource for bioenergy production. Estimates indicate that their annual biological potential in Europe reaches approximately 950 million tonnes, making them an important element in renewable energy development strategies [11]. The implementation of biomass conversion technologies is limited by the lack of data on the properties of various agricultural residues, which makes it difficult to select appropriate processing technologies [12]. Growing agri-food production increases the need for effective and sustainable management of waste generated during production and processing. Current practices contribute to greenhouse gas emissions and environmental degradation [13].

The perception of agri-food waste as a sustainable biological resource has contributed to the intensification of efforts to quantitatively assess the availability of this waste and its bioenergy potential at national and regional levels, thereby supporting strategic planning for renewable energy sources [14]. Agricultural residues can increase farmers’ income as a source of bioenergy, but their use requires the availability of raw materials, stable supplies and favourable energy policies [8]. Post-harvest residues and animal waste are an underestimated bioenergy resource with great potential, the effective use of which requires research to bridge the gap between laboratory and practice [15].

An additional challenge is the cost of proper management and disposal of biomass residues, which often constitutes a barrier to their effective use [12]. In this context, biomass conversion processes involving thermochemical, biochemical and physicochemical methods offer practical and integrated solutions, enabling both rational waste management and effective use of its energy potential. The perception of a given type of biomass as an effective and cost-effective energy source in the context of energy transition plays a key role in determining its social, political and technological acceptance and implementation in energy systems [16,17]. Effective management of available agricultural waste can contribute to solving a number of socio-economic and environmental problems, while supporting the improvement of the quality of life of rural communities, especially in developing countries, by creating new sources of income, increasing access to energy and reducing environmental degradation [18]. Locally adapted management systems and further research on logistics, seasonality and conversion are key, particularly in the context of the high bioenergy potential of vineyards [19].

Viticulture and wine production, among the oldest and most important agricultural and processing practices in the world, generate significant amounts of by-products, the dominant fraction of which is grape marc. These by-products include seeds, skins and fruit husks [20]. Although well researched in terms of sustainability, the wine industry has a significant impact on the environment through waste, wastewater, pesticides, energy consumption, land pressure and the carbon footprint of transport [21]. The wine industry is characterised by high waste generation, with an estimated 80% of the 75 million tonnes of grapes produced annually going to wine processing [22]. The utilisation of grape pomace through various technological and application approaches is a highly promising area of research and implementation, offering numerous prospects for development [23].

In the context of the growing need to use agricultural by-products as renewable energy sources, waste generated in the wine production process is becoming particularly important. Grape pomace and stems, which are produced in significant quantities as a result of fruit pressing and processing, are potentially valuable bioenergy raw materials. One of the factors that may influence their energy properties is the type of rootstock on which the vines were grown. The analysis assessed the energy potential of biomass obtained from the stems and pomace of Regent grapes, taking into account the rootstock used (125AA, 161-49, SO₄) and their own roots.

2. Materials and Methods

Research was conducted in 2024 at the NOBILIS vineyard (50°39′ N; 21°34′ E) in the Sandomierz Uplands in south-eastern Poland. The research material consisted of Regent grapevines planted in spring 2010 at a spacing of 2.0 × 1.0 m (5000 plants ha⁻¹) on loess soil. The plants were trained as a single Guyot cane with a trunk height of 40 cm, a single arm about 0.9 m long and 1 double spur (Figure 1).

The experiment evaluated the energy value of biomass in the form of stalks and pomace depending on the type of rootstock used for growing grapevines. The vines of the tested variety were grown on three types of rootstocks, 125AA, SO₄ and 161-49, with ungrafted vines growing on their own roots as controls (Figure 2). A total of 25 kg of grapes was harvested from each combination. The grapes were harvested manually when they reached optimal ripeness, between 23.5 and 24.5 °Brix. The bunches were divided into stalks and berries. The stems were dried at a controlled temperature, while the berries were crushed by hand and the juice was separated using a Lancman 55 hydropress (fabricant Lancman, Čeplje, Slovenia).

This study began by placing the plant material in a room with a constant temperature and humidity, where it was dried naturally in air-drying conditions at 20 °C and 55–60% humidity for a period of two weeks. The material for laboratory analysis was first ground (to a thickness of 0.5 mm) using a Retsch SM 100 mill (Retsch GmbH, Haan, Germany, 2022) with a power of 1.5 kW. For the purposes of this study, 100 g of material was obtained in 2 min, which consumed 0.045 kWh. The methodology for measuring energy parameters is presented in

Table 1. Fuel characterisation analysis.

Parameter	Method	Equipment
Energetic Properties
Higher heating value (HHV; MJ·kg−1)	EN-ISO 1928:2020 [23]	isoperibolic calorimeter LECO AC 600 (Devon, UK)
Lower heating value (LHV; MJ·kg−1)
Proximate Analysis
Ash (A; %)	EN-ISO 18122:2022 [24]	thermogravimetric analyser LECO TGA 701 (Devon, UK)
Volatile matter (V; %)	EN-ISO 18123:2023 [25]
Moisture (MC; %)	EN-ISO 18134:2023 [26]
Fixed carbon (FC; %)	FC = 100 − V − A − M [27]
Ultimate Analysis
Carbon (C; %)	EN-ISO 16948:2015 [28]	elemental analyser LECO CHNS 628 (Devon, UK)
Hydrogen (H;%)
Nitrogen (N; %)
Sulphur (S; %)	EN-ISO 16994:2016 [29]
Oxygen (O; %)	O = 100 – A – H – C – S − N [30]

,

Table 2. Emission factors (emission factors calculated according to the study in [31]).

Parameter	Method and Equipment
Carbon monoxide emission factor (Ec) of chemically pure coal (CO; kg·Mg−1)	$CO={\displaystyle \frac{28}{12}}·E_c$$·(C/\mathrm{CO})$, CO—carbon monoxide emission factor (kg·kg−1), ${\displaystyle \frac{28}{12}}$— molar mass ratio of carbon monoxide and carbon, EC—emission factor of chemically pure coal (kg∙kg−1), C/CO—part of the carbon emitted as CO (for biomass 0.06).
Carbon dioxide emission factor (CO2; kg·Mg−1)	${CO}_2={\displaystyle \frac{44}{12}}·\left(E_c-{\displaystyle \frac{12}{28}}·CO-{\displaystyle \frac{12}{16}}·E_{{CH}_4}-{\displaystyle \frac{26.4}{31.4}}·E_{NMVOC}\right),$ ${\mathrm{CO}}_2—\mathrm{carbon} \mathrm{dioxide} \mathrm{emission} \mathrm{factor} (\mathrm{kg}·{\mathrm{kg}}^{-1}), {\displaystyle \frac{44}{12}}$$—\mathrm{molar} \mathrm{mass} \mathrm{ratio} \mathrm{of} \mathrm{carbon} \mathrm{dioxide} \mathrm{and} \mathrm{pure} \mathrm{coal}, {\displaystyle \frac{12}{28}}$$—\mathrm{molar} \mathrm{mass} \mathrm{ratio} \mathrm{of} \mathrm{carbon} \mathrm{dioxide} \mathrm{and} \mathrm{carbon} \mathrm{monoxide}, {\displaystyle \frac{12}{16}}$—molar mass ratio of carbon and methane, ECH4—methane emission factor, ENMVOC—emission index of non-methane VOCs (for biomass 0.009).
Sulphur dioxide emission factor (SO2; kg·Mg−1)	${SO}_2={\displaystyle \frac{2S}{100}}·\left(1-r\right),$ SO2—sulphur dioxide emission factor (kg∙kg−1), 2—molar mass ratio of SO2 and sulphur, S—sulphur content in fuel (%), r—coefficient determining the part of total sulphur retained in the ash.
Emission factor calculated from (NOX; kg·Mg−1)	${NO}_x={\displaystyle \frac{46}{14}}·E_c·N/C·\left(N_{{NO}_x}/N\right)$, NOx—NOx emission factor (kg∙kg−1), ${\displaystyle \frac{46}{14}}$—molar mass ratio of nitrogen dioxide to nitrogen. The molar mass of nitrogen dioxide is considered due to the fact that nitrogen oxide in the air oxidizes very quickly into nitrogen dioxide. N/C—nitrogen to carbon ratio in biomass, NOx/N—part of nitrogen emitted as NOx (for biomass 0.122).

and

Table 3. Exhaust gas composition (exhaust gas composition was calculated according to [32,33]).

Parameter	Method and Equipment
Theoretical oxygen demand $(V_{O_2}$; Nm3·kg−1)	$V_{O_2}={\displaystyle \frac{22.41}{100}}·\left({\displaystyle \frac{C}{12}}+{\displaystyle \frac{H}{4}}+{\displaystyle \frac{S-O}{32}}\right)$, where C—biomass carbon content (%), H—biomass hydrogen content (%), S—biomass sulphur content (%), O—biomass oxygen content (%).
The stoichiometric volume of dry air required to burn 1 kg of biomass (Voa; Nm3·kg−1)	$V_{O_a}={\displaystyle \frac{V_{O_2}}{0.21}},$ since the oxygen content in the air is 21%, which participates in the combustion process in the boiler, this is the stoichiometric volume of dry air required to burn 1 kg of biomass.
Carbon dioxide content of the combustion products $(V_{{CO}_2}$; Nm3·kg−1)	$V_{{CO}_2}={\displaystyle \frac{22.41}{12}}$$· {\displaystyle \frac{C}{100}},$
Content of sulphur dioxide $(V_{{SO}_2}$; Nm3·kg−1)	$V_{{SO}_2}={\displaystyle \frac{22.41}{32}}$$· {\displaystyle \frac{S}{100}}$,
Water vapor content of the exhaust gas $(V_{H_{2}O}$; Nm3·kg−1)	$V_{H_{2}O}^H={\displaystyle \frac{22.41}{100}}·\left({\displaystyle \frac{H}{2}}+{\displaystyle \frac{M}{18}}\right)$, $\mathrm{which} \mathrm{is} \mathrm{the} \mathrm{component} \mathrm{of} \mathrm{water} \mathrm{vapor} \mathrm{volume} \mathrm{from} \mathrm{the} \mathrm{hydrogen} \mathrm{combustion} \mathrm{process} (V_{H_{2}O}^H;$${\mathrm{Nm}}^3{\mathrm{H}}_2\mathrm{O}·{\mathrm{kg}}^{-1}\mathrm{fuel}) V_{H_{2}O}^a=1.61·x·V_{oa}$ and the volume of moisture contained in the combustion air $(V_{H_{2}O}^a$$; {\mathrm{Nm}}^3{\mathrm{H}}_2\mathrm{O}·{\mathrm{kg}}^{-1}\mathrm{fuel}) V_{H_{2}O}$$= V_{H_{2}O}^H$$+V_{H_{2}O}^a$; M—fuel moisture content (%), x—air absolute humidity (kg H2O·kg−1 dry air).
The theoretical nitrogen content in the exhaust gas $(V_{N2}$; Nm3 kg−1)	$V_{N2}={\displaystyle \frac{22.41}{28}}·{\displaystyle \frac{N}{100}}+0.79·V_{oa}$, considering that the nitrogen in the exhaust comes from the fuel composition and the combustion air, and the nitrogen content in the air is 79%.
The total stoichiometric volume of dry exhaust gas ${(V}_{gu};$Nm3 kg−1)	$V_{gu}=V_{C{O}_2}+V_{S{O}_2}+V_{N_2}$
The total volume of exhaust gases $(V_{ga}$; Nm3·kg−1)	$V_{ga}=V_{gu}+V_{H_{2}O}$ Assuming that biomass combustion is carried out under stoichiometric conditions, i.e., using the minimum amount of air required for combustion (λ = 1), a minimum exhaust gas volume will be obtained.

.

The experiment was designed as a randomised block design consisting of four combinations with five replicates. The replicates consisted of plots, each containing three plants. After completion of the experiment, the results were statistically analysed using one-way analysis of variance (ANOVA), comparisons between varieties within each plant material separately and comparisons of plant material for each variety separately. Statistical inference was performed at a significance level of p < 0.05. In addition, the results were presented in graphical form. Multivariate data analysis techniques were used, including cluster analysis and principal component analysis. The results of the cluster analysis were presented using a dendrogram to show the yield and quality of wine waste and the calorific value of stems and pomace. The relationships between the components of grapevine biomass, independent of plant material, were determined separately for each variety. All analyses were performed using STATISTICA 13 software (StatSoft, Inc.; TIBCO Software; Palo Alto, CA, USA; 2015).

3. Results and Discussion

Table 4. Technical and elemental analysis of different rootstocks of the Regent grapevine variety (A), different types of plant material (B) and the interaction of both factors (A*B) (dry matter).

	Name	HHV	LHV	MC	A	V	FC
Variety (A)	125AA	16.97 ± 0.96 b	15.83 ± 0.94 b	6.02 ± 0.03 ab	9.31 ± 1.42 b	66.47 ± 1.11 a	18.20 ± 0.53 b
	161-49	16.87 ± 0.96 c	15.70 ± 0.96 c	6.36 ± 0.19 ab	7.52 ± 0.54 d	66.46 ± 1.74 a	19.66 ± 1.11 a
	SO4	17.19 ± 1.82 a	16.07 ± 1.82 a	5.13 ± 1.63 b	10.60 ± 1.52 a	64.05 ± 0.19 c	20.22 ± 3.14 a
	Control	16.60 ± 0.44 d	15.43 ± 0.42 d	6.68 ± 0.26 a	8.07 ± 1.49 c	65.66 ± 1.58 b	19.59 ± 0.43 a
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001
Material (B)	Stem	15.95 ± 0.27 b	14.81 ± 0.26 b	6.41 ± 0.24 b	9.99 ± 1.55 a	64.68 ± 0.69 b	18.93 ± 1.48 b
	Pomace	17.86 ± 0.69 a	16.70 ± 0.72 a	5.69 ± 0.28 a	7.76 ± 1.04 b	66.65 ± 1.61 a	19.90 ± 1.94 a
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001
A*B	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001

Explanations: HHV = high heating value, LHV = lower heating value, MC = moisture, A = ash content, V = volatile matter content, FC = fixed carbon. Significant difference means that different letters in the column indicate significant differences at α = 0.05.

presents the results of technical and elemental analysis of different rootstocks of the Regent grapevine variety (A) and two types of plant material (B), together with an assessment of the statistical significance of differences between rootstocks and between materials as well as their interaction (A*B). The analysis showed that the grapevine rootstock had a significant effect on all the parameters studied, and the type of plant material significantly differentiated all the traits. A significant interaction effect between the rootstock and the type of material was found for all the parameters analysed (Table 4).

Among the substrates, SO₄ had the highest calorific values: HHV (17.19 MJ·kg⁻¹) and LHV (16.07 MJ·kg⁻¹). The lowest HHV was recorded in the Control substrate (16.60 MJ·kg⁻¹), which also had the lowest LHV (15.43 MJ·kg⁻¹). The ash content (A) was highest in SO₄ (10.60%) and lowest in 161-49 (7.52%). The highest volatility (V) was found in substrate 161-49 (66.46%), while the lowest was found in SO₄ (65.04%). The highest fixed fraction (FC) was recorded in substrate SO₄ (20.22%), and the lowest in 125AA (18.20%).

The type of plant material significantly differentiated all analysed parameters. Pomace was characterised by higher values of HHV (17.86 MJ·kg⁻¹) and LHV (16.70 MJ·kg⁻¹), higher carbon (47.38%) and hydrogen (6.79%) content, and higher volatility (66.65%) and solid fraction (19.90%) compared to stalks. In turn, stalks showed higher ash content (9.68%) (Table 4).

The following table shows the emission factors of selected pollutants and the elemental ratios for different rootstocks of the Regent grapevine variety and two types of plant material, together with an assessment of the statistical significance of the differences between rootstocks and materials and their interaction. The analysis showed that the vine rootstock had a significant effect on all the emission parameters studied. The type of plant material significantly differentiated all the characteristics. A significant interaction effect between the rootstock and the type of material was also observed for all the parameters analysed (

Table 5. Analysis of the elemental composition of stems and pomace depending on the type of rootstock.

	Name	C	H	N	S	O	H/C	N/C	O/C
	Unit	%
Variety (A)	125AA	45.67 ± 1.91 b	6.80 ± 0.42 a	1.57 ± 0.16 a	0.07 ± 0.02 a	36.59 ± 1.15 b	1.49 ± 0.03 b	0.03 ± 0.00 a	0.60 ± 0.04 b
	161-49	45.55 ± 1.6 bc	6.83 ± 0.38 a	1.46 ± 0.25 b	0.07 ± 0.01 a	38.58 ± 1.74 a	1.50 ± 0.03 b	0.03 ± 0.00 b	0.64 ± 0.05 a
	SO4	46.16 ± 3.13 a	6.58 ± 0.18 b	1.28 ± 0.10 d	0.07 ± 0.02 a	35.31 ± 1.78 c	1.52 ± 0.07 a	0.03 ± 0.00 c	0.64 ± 0.02 a
	Control	45.17 ± 1.09 c	6.86 ± 0.46 a	1.36 ± 0.09 c	0.06 ± 0.01 a	38.48 ± 0.31 a	1.43 ± 0.06 c	0.03 ± 0.00 d	0.58 ± 0.07 c
	p-value	0.0001	0.0001	0.0001	0.1841	0.0001	0.0001	0.0001	0.0001
Material (B)	Stem	43.90 ± 0.46 b	6.44 ± 0.06 b	1.36 ± 0.09 b	0.05 ± 0.01 b	38.26 ± 1.32 a	1.47 ± 0.01 b	0.03 ± 0.00 a	0.65 ± 0.02 a
	Pomace	47.38 ± 1.13 a	7.09 ± 0.22 a	1.47 ± 0.24 a	0.08 ± 0.01 a	36.22 ± 1.88 b	1.50 ± 0.08 a	0.03 ± 0.01 a	0.57 ± 0.04 b
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001
A*B	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.00

Explanations: C—carbon content, H—hydrogen content, N—nitrogen content, S—sulphur content, O—oxygen content, H/C—ratio of hydrogen to carbon, N/C—ratio of nitrogen to carbon, O/C—ratio of oxygen to carbon. Significant difference means that different letters in the column indicate significant differences at α = 0.05.

).

The SO₄ substrate was distinguished by the highest carbon content (46.16%), while the lowest value of this parameter was found in Control (45.17%). The highest hydrogen content was obtained in the Control substrate (6.86%), and the lowest in SO₄ (6.58%). The highest nitrogen content was recorded in 125AA (1.57%), while the lowest was in SO₄ (1.28%). In terms of sulphur (S) content, the differences between the substrates were not statistically significant; the values ranged from 0.06% (Control) to 0.07% (for the other substrates). The highest oxygen (O) content was found in substrate 161-49 (38.58%), and the lowest in SO₄ (35.31%) (Table 5).

Among the substrates, the highest emissions of CO (56.87 kg·Mg⁻¹), SO₂ (0.13 kg·Mg⁻¹) and dust (13.39 kg·Mg⁻¹) were recorded in Control, which also showed the lowest O/C ratio (0.58%). The highest NOₓ emissions were found in the 125AA pad (5.52 kg·Mg⁻¹), while the lowest were found in Control (4.52 kg·Mg⁻¹). The lowest CO and CO₂ emission values were observed in SO₄ (55.65 and 1362.64 kg·Mg⁻¹), which also had the highest H/C (1.52%) and O/C (0.64%) ratios. The 161-49 substrate showed the lowest SO₂ emissions (0.09 kg·Mg⁻¹) and dust emissions (9.50 kg·Mg⁻¹), with the lowest H/C ratio (1.50%).

The type of plant material significantly differentiated all analysed parameters. Pomace was characterised by higher CO emissions (58.37 vs. 54.08 kg·Mg⁻¹), NOₓ (5.18 vs. 4.81 kg·Mg⁻¹), CO₂ (1429.30 vs. 1324.30 kg·Mg^{− 1}), SO₂ (0.15 vs. 0.11 kg·Mg⁻¹) and solid fraction (N/C 0.04 vs. 0.03%), with a lower O/C ratio (0.57 vs. 0.65%) compared to stalks (

Table 6. Emission indicators of selected pollutants (CO, CO₂, SO₂, NOₓ, dust) for different Regent grapevine rootstocks (A) and types of plant material (B) and interactions between both factors (A*B).

Name		CO	NOx	CO2	SO2	Dust
Unit		kg Mg−1
Variety (A)	125AA	56.27 ± 2.36 b	5.52 ± 0.58 a	1377.87 ± 57.76 b	± 0.14 ± 0.03 a	11.76 ± 1.79 b
	161-49	56.11 ± 1.97 bc	5.14 ± 0.89 b	1374.05 ± 48.19 bc	0.14 ± 0.03 a	9.50 ± 0.68 d
	SO4	55.65 ± 1.34 c	4.82 ± 0.31 c	1362.64 ± 32.75 c	0.11 ± 0.02 a	10.19 ± 1.88 c
	Control	56.87 ± 3.86 a	4.52 ± 0.35 d	1392.64 ± 94.41 a	± 0.13 ± 0.04 a	13.39 ± 1.92 a
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001
Material (B)	Shank	54.08 ± 0.57 b	4.81 ± 0.33 b	1324.30 ± 14.01 b	0.11 ± 0.03 b	12.61 ± 1.96 a
	Pomace	58.37 ± 1.39 a	5.18 ± 0.86 a	1429.30 ± 33.95 a	0.15 ± 0.01 a	9.80 ± 1.32 b
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001
A*B	p-value	0.0001	0.0001	0.0001	0.0001	0.0001

Explanation: CO—carbon monoxide emission; CO₂—carbon dioxide emission; SO₂—sulphur dioxide emission; NOₓ—nitrogen oxide emission; Dust—particulate matter emission. Significant differences are indicated by different letters within columns; significance level was set at α = 0.05.

).

Another aspect analysed was the composition of exhaust gases, which plays an important role in assessing the energy suitability of biomass, as presented in

Table 7. Exhaust gas composition for different rootstocks of the Regent grapevine variety (A) and types of plant material (B), and interactions between both factors (A*B).

	Name	Vo(O2)	Voa	VCO2	VSO2	VH2O	VN2	Voga	Vogu
	Unit	Nm3·kg−1
Variety (A)	125AA	0.98 ± 0.07 ab	4.66 ± 0.32 ab	0.85 ± 0.04 b	0.00 ± 0.00 a	0.84 ± 0.05 b	4.93 ± 0.38 a	7.37 ± 0.51 a	5.79 ± 0.42 a
	161-49	0.96 ± 0.06 bc	4.59 ± 0.3 bc	0.85 ± 0.03 bc	0.00 ± 0.00 a	0.84 ± 0.04 ab	4.79 ± 0.44 b	7.22 ± 0.56 b	5.64 ± 0.47 b
	SO4	0.96 ± 0.05 c	4.57 ± 0.22 c	0.84 ± 0.02 c	0.00 ± 0.00 a	0.85 ± 0.06 a	4.70 ± 0.11 b	7.13 ± 0.22 b	5.54 ± 0.13 b
	Control	0.98 ± 0.08 a	4.69 ± 0.38 a	0.86 ± 0.06 a	0.00 ± 0.00 a	0.80 ± 0.00 c	4.73 ± 0.23 b	7.15 ± 0.35 b	5.59 ± 0.28 b
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001
Material (B)	Stem	0.91 ± 0.01 b	4.35 ± 0.05 b	0.82 ± 0.01 b	0.00 ± 0.00 b	0.80 ± 0.01 b	4.53 ± 0.10 b	6.85 ± 0.11 b	5.35 ± 0.1 b
	Pulp	1.03 ± 0.02 a	4.90 ± 0.11 a	0.88 ± 0.02 a	0.00 ± 0.00 a	0.87 ± 0.04 a	5.05 ± 0.21	7.59 ± 0.22 a	5.93 ± 0.21 a
	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001
A*B	p-value	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001	0.0001

Explanations: V_O2 = the theoretical oxygen demand, Vo_a = the stoichiometric volume of dry air required to burn 1 kg of biomass, V_CO2 = the carbon dioxide content, V_SO2 = the content of sulphur dioxide, V_H2O = the water vapour content in the exhaust gas, V_N2 = the theoretical nitrogen content in the exhaust gas, V_gu = the total stoichiometric volume of dry exhaust gas, V_ga = the total volume of exhaust gases. Significant difference means that different letters in the column indicate significant differences at α = 0.05.

.

Among the analysed pads, the highest VO₂ value was achieved by the Control pad (0.98 Nm³·kg⁻¹), while the lowest was achieved by the SO₄ pad (0.96 Nm³·kg⁻¹). In terms of VOa, the highest result was recorded for the 125AA pad (4.66 Nm³·kg⁻¹), and the lowest for the SO₄ pad (4.57 Nm³·kg⁻¹). The highest VCO₂ value was recorded for the Control pad (0.86 Nm³·kg⁻¹), and the lowest for SO₄ (0.84 Nm³·kg⁻¹). For VH₂O, the highest level was found in Control (0.86 Nm³·kg⁻¹), and the lowest in 125AA (0.83 Nm³·kg⁻¹). The highest VN₂ was recorded for Control (4.73 Nm³·kg⁻¹), and the lowest for 161-49 (4.79 Nm³·kg⁻¹). In terms of V_oga, the Control pad had the highest value (7.15 Nm³·kg⁻¹), while the lowest was recorded in 161-49 (7.22 Nm³·kg⁻¹). V_oga was highest in Control (5.59 Nm³·kg⁻¹) and lowest in 161-49 (5.64 Nm³·kg⁻¹).

The type of plant material significantly differentiated all analysed parameters—pomace was characterised by higher values of VO₂, VOa, VCO₂, VH₂O, VN₂, V_oga and V_ogu compared to stalks (Table 7).

A comparison of the obtained test results for pomace with data from the literature on grapevines indicates similar HHVs and LHVs. Similar energy values can be obtained from pomace as for Miscanthus. The carbon content for all tested cases is similar to that of Vitis vinifera, but lower than for Miscanthus. The hydrogen content in the tested samples was higher than for Miscanthus, although similar to Vitis vinifera in other studies. The sulphur content was recorded at a similar level. In contrast, the ash content was similar to that of Miscanthus, but in the other cases the levels were quite high and similar to those of agrobiomass. Lower oxygen content was found in all cases.

A significant interaction between the substrate and the type of material was also found for all analysed characteristics except sulphur, which means that the influence of the substrate on these parameters varied depending on the type of plant material. The observed differences indicate that the SO₄ rootstock had more favourable energy properties, while pomace, compared to stalks, had higher calorific values and carbon content, which may be important in assessing their energy potential (

Table 8. Comparison of literature data on fuel characteristics, emission factors and exhaust gas composition.

	Name	Unit	Vitis vinifera (Sabor) [34]	Vitis vinifera (Ave) [34]	[20]	Pruning Vine [35]
energy parameters	HHV	MJ·kg−1	17.3	17.4	18.072
	LHV		-	-		18.19
	A	%	7.2	6.8	9.6	2.6
	V		-	-	79
	FC		-	-	11.4
	C		44.2	42.6	47.09	44.62
	H		6.1	6.1	6.3	5.77
	N		1	0.9	0.1	0.7
	S		0.07	0.09	0.1	0.05
	O		43	41.9	46.42
emission factors			Pinus radiata [36]	Eucalyptus globulus [36]	Jackfruit peels [30]	Jackfruit seeds [30]	Wheat straw [31]
	CO	kg Mg−1	63.52	61.75	50.28	51.46	50.57
	NOx		5.63	4.52	4.66	8.71	1.83
	CO2		1527.79	1484.34	1203.47	1232.43	1238.24
	SO2		0.72	0.46	0.07	0.11	0.14
	Dust		3.69	5.2	-	-	10.56
amounts of air and of dry flue gases			Pure white grape pomace [37]	Pure red grape pomace [37]	Meadow hay [38]	Timothy grass [38]
	Voga	Nm3 kg−1	5.95	6.22	4.14	4.42
	Vogu		4.58	4.79	4.03	4.29

).

When comparing the literature data with the obtained research results, it can be seen that in terms of CO emission indicators, the analysed biomass does not show significant deviations. The obtained results are comparable to the emission indicators for agrobiomass. In the case of CO₂ emissions, they are within the average range, and it can be seen that, compared to Pinus radiata, the average emission rates are approximately 135 kg·Mg⁻¹ lower. In terms of NO_x, comparable emission factors were obtained for Pinus radiata, Eucalyptus globulus and Jackfruit peels, while much lower values were obtained for Jackfruit seeds and the values were approx. 1.5 kg·Mg⁻¹ lower than for wheat straw. SO₂ and dust emission rates were similar to those for typical agrobiomass, e.g., wheat straw.

A significant interaction between the substrate and the type of plant material was also found for all the characteristics studied, indicating that the influence of the substrate on these parameters varied depending on the type of material. The observed differences confirm that Control was characterised by the highest emissions of most pollutants, while substrate SO₄ showed the lowest CO and CO₂ emissions, and pomace generally had higher emission rates compared to stalks (Table 8).

An analysis of the literature data with research results on the volume of exhaust gases generated indicates that the tested material, regardless of whether it is stalks or pomace, shows a higher theoretical amount of air and theoretical amount of dry flue gases in relation to pure red and white grape pomace, as well as biomass in the form of grasses. Compared to grape pomace_, the differences are in the ranges of 1.3–1.6 Nm³ kg⁻¹ (V_oga) and 1.1–1.3 Nm³ kg⁻¹ (V_ogu), and compared to grasses, the amounts are significantly higher.

A significant interaction effect between the substrate and the type of material was also found for all the characteristics studied, which means that the influence of the substrate on these parameters varied depending on the plant material (Table 8).

Table 9. Canonical correlation analysis examining the relationship between stalks and pomace regardless of the variety tested.

		Pedicel
		HHV	LHV	C	M	O%	A	V	FC	CO	H/C	O/C	CO2	Dust	VCO2
Residues	HHV	−0.81	−0.82	−0.54	0.85	−0.29	0.42	−0.78	−0.21	−0.54	0.62	−0.14	−0.54	0.42	−0.54
	LHV	−0.81	−0.82	−0.54	0.85	−0.30	0.43	−0.78	−0.21	−0.54	0.62	−0.15	−0.54	0.43	−0.54
	C	−0.81	−0.81	−0.49	0.88	−0.40	0.49	−0.76	−0.28	−0.49	0.58	−0.27	−0.49	0.49	−0.49
	H	0.91	0.91	0.74	−0.68	0.47	−0.63	0.68	0.45	0.74	−0.73	0.27	0.74	−0.63	0.74
	N	0.66	0.62	0.70	0.19	0.80	−0.88	−0.03	0.91	0.70	−0.49	0.64	0.70	−0.88 *	0.70
	S	0.41	0.38	0.31	0.43	0.60	−0.59	−0.45	0.76	0.31	−0.40	0.56	0.31	−0.59	0.31
	M	0.90	0.90	0.67	−0.72	0.49	−0.62	0.68	0.44	0.67	−0.70	0.31	0.67	−0.62	0.67
	O	0.69	0.70	0.44	−0.79	0.37	−0.45	0.78	0.23	0.44	−0.47	0.26	0.44	−0.45	0.44
	A	−0.72	−0.71	−0.58	0.68	−0.53	0.62	−0.72	−0.42	−0.58	0.50	−0.39	−0.58	0.62	−0.58
	V	0.87	0.85	0.78	−0.35	0.77	−0.88	0.50	0.75	0.78	−0.59	0.58	0.78	−0.88	0.78
	FC	−0.93	−0.92	−0.78	0.40	−0.68	0.81	−0.48	−0.69	−0.78	0.68	−0.48	−0.78	0.81	−0.78
	CO	−0.81	−0.81	−0.49	0.78	−0.40	0.49	−0.76	−0.28	−0.49	0.58	−0.27	−0.49	0.49	−0.49
	NOx	0.66	0.62	0.70	0.19	0.80	−0.88	−0.03	0.91	0.70	−0.49	0.64	0.70	−0.88 *	0.70
	H/C	0.88	0.88	0.64	−0.75	0.44	−0.57	0.74	0.37	0.64	−0.67	0.27	0.64	−0.57	0.64
	N/C	0.73	0.69	0.73	0.10	0.82	−0.91	0.06	0.90	0.73	−0.53	0.66	0.73	−0.91 *	0.73
	O/C	0.72	0.73	0.45	−0.80	0.37	−0.45	0.79	0.23	0.45	−0.50	0.25	0.45	−0.45	0.45
	CO2	−0.81	−0.81	−0.49	0.78	−0.40	0.49	−0.76	−0.28	−0.49	0.58	−0.27	−0.49	0.49	−0.49
	SO2	0.41	0.38	0.31	0.43	0.60	−0.59	−0.45	0.76	0.31	−0.40	0.56	0.31	−0.59	0.31
	Dust	−0.72	−0.71	−0.58	0.68	−0.53	0.62	−0.72	−0.42	−0.58	0.50	−0.39	−0.58	0.62	−0.58
	VoO2	−0.63	−0.64	−0.30	0.78	−0.32	0.36	−0.77	−0.14	−0.30	0.40	−0.25	−0.30	0.36	−0.30
	Voa	−0.63	−0.64	−0.30	0.78	−0.32	0.36	−0.77	−0.14	−0.30	0.40	−0.25	−0.30	0.36	−0.30
	VCO2	−0.81	−0.81	−0.49	0.78	−0.40	0.49	−0.76	−0.28	−0.49	0.58	−0.27	−0.49	0.49	−0.49
	VSO2	0.41	0.38	0.31	0.43	0.60	−0.59	−0.45	0.76	0.31	−0.40	0.56	0.31	−0.59	0.31
	V’H2O	0.91	0.91	0.72	−0.70	0.48	−0.63	0.68	0.45	0.72	−0.72	0.29	0.72	−0.63	0.72
	VoH2O	0.92	0.91	0.86	−0.51	0.50	−0.69	0.49	0.57	0.86	−0.80	0.26	0.86	−0.69	0.86
	VN2	0.34	0.30	0.53	0.51	0.61	−0.67	−0.35	0.79	0.53	−0.28	0.50	0.53	−0.67	0.53
	Voga	0.36	0.32	0.55	0.49	0.59	−0.67	−0.34	0.78	0.55	−0.31	0.47	0.55	−0.67	0.55
	Vogu	0.26	0.22	0.47	0.58	0.56	−0.61	−0.42	0.74	0.47	−0.22	0.46	0.47	−0.61	0.47

presents all energy parameters obtained from the combustion of stalks and pomace, which showed significant correlations between each other. A single asterisk denotes very strong positive and negative correlations at the level of 0.8. It was shown that with an increase in HHV and LHV in stalks, the levels of HHV, LHV, C, FC, CO, CO₂ and CO₂ in pomace decrease. Positive correlations were observed with an increase in HHV and LHV in stems, strongly positively correlating with H, M, V, VC and V_H2O. With an increase in Weco, Weco2 and Vco2 strongly positively correlate with VO_H2O, which decreases in pomace with an increase in the H/C level in stems. The M content in the stems positively correlates with HHV, LHV and C. With an increase in A in the stems, the levels of N, V, Wnox and N/C in the pomace decrease, while the opposite relationship was observed in the case of FC. With an increase in O in the stems, the levels of N, NO_x and N/C in the pomace increase. A positive correlation was observed between FC in the stems and N, NO_x and N/C in the pomace. In the case of the dust level in the stems, negative correlations were observed with N, V, NO_x and N/C, and an inverse relationship with FC.

The dendrogram presented (Figure 3a) allowed us to determine the similarity of rootstock types in terms of biomass size and energy parameter levels. Based on the results obtained, three distinct clusters were identified, the first consisting of rootstock 125AA and Control shrubs, followed by 161-49 and the significantly different rootstock SO₄. Figure 3b shows a dendrogram that determines the similarities of rootstock types in terms of biomass size and energy parameters in the evaluated pomace. Based on the results obtained, three distinct clusters were identified, as in Figure 3a. The first consists of rootstocks 125AA and 161-49, followed by Control shrubs and the significantly different rootstock SO₄, where the same relationship was observed as for the pedicels shown in Figure 3a.

4. Conclusions

The research showed that both the type of substrate and the type of biomass had a statistically significant impact on physicochemical properties, combustion parameters and pollutant emissions. Among the analysed substrates, SO₄ had the highest calorific value (HHV = 17.19 MJ∙kg⁻¹; LHV = 16.07 MJ∙kg⁻¹), which indicates that it had the highest energy potential, while the Control substrate achieved the lowest values (HHV = 16.60 MJ∙kg⁻¹; LHV = 15.43 MJ∙kg⁻¹). The 125AA substrate was distinguished by the highest nitrogen content (1.57%) and the highest content of volatile substances (V = 66.47%), while 161-49 was characterised by the highest oxygen content (38.58%) and the lowest ash content (7.52%). These differences confirm that the choice of rootstock can significantly modify the energy properties of grapevine biomass.

The type of biomass was a factor that differentiated the tested parameters more strongly than the type of rootstock alone. Grape pomace showed a significantly higher calorific value (HHV = 17.86 MJ∙kg⁻¹; LHV = 16.70 MJ∙kg⁻¹), higher carbon (47.38%) and hydrogen (7.09%) content, and lower ash content (7.76%) compared to stems, which had lower energy values (HHV = 15.95 MJ∙kg⁻¹; LHV = 14.81 MJ∙kg⁻¹) and higher ash content (9.99%). In the emission analysis, pomace generated less dust (9.80 vs. 12.61 kg∙Mg⁻¹), but significantly more CO (58.37 vs. 54.08 kg∙Mg⁻¹), CO₂ (1429.30 vs. 1324.30 kg∙Mg⁻¹) and NOₓ (5.18 vs. 4.81 kg∙Mg⁻¹).

In summary, the results obtained indicate that grape marc is a more promising energy source than grape stalks due to its higher calorific value, more favourable elemental composition and lower dust emissions. Among the analysed substrates, SO₄ stands out in particular, as it offers the highest energy potential, while the Control substrate has the least favourable combustion and emission parameters. These relationships clearly confirm that wine waste can be a valuable source of renewable energy, while also pointing to the important role of both the type of biomass and the substrate used in shaping its energy properties.