Physicochemical Properties of Biochar Produced from Grapevine-Pruning Residues of 12 Cultivars

Abstract

The valorization of grapevine pruning residues through pyrolysis provides a sustainable approach to agricultural waste management, producing biochar with agricultural use potential and carbon sink functionality. This study investigated pruning residues from 12 grapevine cultivars to evaluate the cultivar effects on biochar properties. Samples were collected along the Croatian coast from Istria to Dalmatia and included six indigenous cultivars (Malvazija istarska, Pošip, Maraština, Teran, Plavina, and Plavac mali) and six introduced cultivars (Chardonnay, Pinot blanc, Sauvignon blanc, Merlot, Cabernet Sauvignon, and Syrah). For each cultivar, residues were collected from three distinct vineyards with three replicates per vineyard. Pyrolysis was conducted in a muffle furnace at 400 °C. The pruning residues showed acidic pH (4.79–5.45), moderate electrical conductivity (1694–2390 µS cm⁻¹), and ash contents of 2.65–3.49% among all cultivars. Significant differences were observed among cultivars in residue carbon content and ash fraction, which were reflected in the resulting biochar. Biochar yield ranged from 32% to 35%, while pH values were alkaline, ranging from 10.20 to 11.13. Total carbon increased from 43.77 to 45.36% in grapevine-pruning residues to 65.88–71.57% in biochar. FT-IR spectra revealed cultivar-dependent variation in aromatic C=C intensification, while SEM analysis indicated differences in pore abundance and surface area (1.63–4.13 m² g⁻¹) between cultivars. These results demonstrate that carbon-dense cultivars produced biochars with greater structural stability, indicating enhanced resistance to decomposition. Spectroscopic and microscopic analyses consistently showed increased aromatic condensation, reduced aliphatic functionality, and greater porosity following pyrolysis. These cultivar-dependent differences highlight pruning residues as a chemically heterogeneous but predictable feedstock, with biochar properties primarily governed by the intrinsic characteristics of the source material.

1. Introduction

The valorization of agricultural waste, particularly the conversion of biomass into new materials and products, has gained considerable attention in recent years. European environmental strategies emphasize the transition towards a circular economy, with a focus on waste recycling and the development of value-added, soil-improving materials [1]. In this context, grapevine-pruning residues are a promising source of biomass. According to the International Organization of Vine and Wine (OIV) [2], in 2020, the global vineyard area was estimated at 7.3 million hectares, with 3.3 million hectares located in the European Union (EU). In Croatia, vineyards occupy approximately 19,000 hectares [3]. As reported by Guerrero et al. [4], grapevine pruning produces approximately 2–5 tons of residues per hectare during each growing season.

Typically, grapevine-pruning residues are either shredded and incorporated into the soil or burned in the field [5]. However, both disposal methods can negatively affect the environment and viticultural productivity. When mulched and left, these residues in the vineyard may serve as a substrate for Botrytis cinerea spore development [6], thereby increasing the risk of infection in subsequent grape production. Conversely, open-field burning contributes to greenhouse gas emissions [7] and increases rural fire hazards relative to more controlled valorization practices [8].

Moreover, the chemical composition of grapevine canes, including pruning residues, can vary significantly among cultivars [7], and the quantity of biomass produced can depend on cultivar-specific growth characteristics [9]. Ampelographic characterization enables the identification of grapevine cultivars based on morphological features of leaves, shoots, and berries [10]. In addition, cultivars also differ in disease susceptibility [11] and flavanol composition [12], further underscoring the genetic and phenotypic diversity that influences both plant performance and residue quality [13]. These cultivar-dependent traits also affect the chemical composition and structural attributes of vine residues, thereby determining feedstock quality for pyrolysis. Consequently, variation in parameters such as lignin content, tissue density, and secondary metabolites can lead to measurable differences in biochar yield and physicochemical properties [13]. Such variability among cultivars not only affects vineyard productivity but also determines the potential of pruning residues for subsequent utilization pathways. In light of these concerns, alternative and sustainable valorization strategies are needed. One promising approach is pyrolysis, a thermochemical process that converts organic residues into biochar—a carbon-rich material with potential for long-term carbon sequestration [14] and soil amendment applications [15]. For example, Prelac et al. [16] demonstrated that biochar derived from grapevine pruning could act as an efficient adsorbent for polyphenolic compounds, indicating additional valorization routes. Moreover, Nunes et al. [17] described the broader review of vineyard pruning waste valorization emphasizes pyrolysis as a viable circular-economy process for the wine industry, capable of converting high-lignin residues into stable carbon products suitable for soil amendment and carbon storage.

During pyrolysis, feedstocks undergo substantial physical and chemical transformations [18]. Some pyrolysis methods, such as flame curtain pyrolysis, are widespread due to their environmentally friendly characteristics and operational simplicity [19], but do not provide controlled conditions, such as those provided by reactors or muffle furnaces. The physical and chemical properties of the resulting biochar are influenced by pyrolysis conditions, including temperature and oxygen availability, as well as by the nature of the feedstock [20]. A wide range of biomass types, including agricultural residues, food industry by-products, forestry waste, and sewage sludge, have been explored as potential biochar feedstocks [21,22,23]. Among these, lignocellulosic biomass has proven especially advantageous due to its structural stability and high carbon content, which enhance both biochar yield and quality.

Biomass with a high lignocellulosic content is desirable, as lignin carbonization contributes to higher biochar yields [24,25]. Lignin is a major structural component of grapevine canes, accounting for approximately 20% of their dry weight [26]. The high carbon content of grapevine-pruning residues makes them particularly suitable for producing biochar with agronomic value [17,27,28]. Unlike labile organic matter that decomposes readily and contributes to soil CO₂ emissions [5], biochar is rich in stable organic carbon and is less susceptible to mineralization [6]. Due to this carbon stability, biomass residues such as grapevine pruning waste are increasingly recognized as valuable feedstocks for sustainable reuse [29].

The pyrolysis temperature strongly affects the physicochemical properties of the resulting biochar; for example, low-temperature biochars tend to have lower pH and greater potential for improving soil fertility [30,31]. Conversely, biochar produced at higher temperatures typically has higher pH values, greater internal surface area, and enhanced water retention. Specifically, increasing the pyrolysis temperature from 400 to 800 °C has been shown to increase the water holding capacity from 12.9 to 27.6 g water g⁻¹ dry for various biomass types, including tree leaves and sawdust [32]. In general, biochar is characterized by its alkaline nature, extensive pore network, and large specific surface area, all of which contribute to improved soil structure, moisture-holding capacity, and long-term soil productivity [33,34]. Beyond enhancing soil fertility, these physicochemical characteristics also facilitate carbon sequestration, pollutant immobilization, and overall improvements in soil health, highlighting biochar’s multifunctional role in sustainable environmental management.

In this study, grapevine-pruning residues from 12 different grapevine cultivars were characterized and used for biochar production. Despite increasing interest in producing biochar from agricultural residues, a clear research gap remains regarding how varietal differences in grapevine biomass influence the physicochemical properties of the resulting biochar. Previous studies have generally treated grapevine pruning as a uniform feedstock, overlooking the substantial anatomical and chemical variability that exists among cultivars. This lack of attention to cultivar-dependent variability represents a critical knowledge gap, as such differences may significantly affect biochar quality and its potential agronomic value [35,36,37].

The innovation of this study lies in its systematic evaluation of 12 grapevine cultivars spanning different origins and berry colors to determine how inherent varietal characteristics shape both biomass properties and the resulting biochar. Therefore, the objective of this study was to assess the variation in both the biomass characteristics and the resulting biochar properties among 12 grapevine cultivars. Furthermore, the work aimed to evaluate whether biochar produced from diverse cultivars maintains consistent properties suitable for agricultural use in sustainable viticultural systems. To clearly address the above research gap, this study specifically focuses on two targeted scientific questions. (i) How do cultivar-specific biomass traits (such as chemical composition and structural attributes) influence the physicochemical properties of the resulting biochar? (ii) Do biochars derived from different grapevine cultivars exhibit sufficiently consistent characteristics to support their application in soil improvement within sustainable viticulture?

2. Materials and Methods

2.1. Sample Collection and Preparation

Grapevine-pruning residues were collected at the beginning of February 2020 during winter dormancy. Samples were obtained along the Croatian coastal region, spanning from the northernmost area of Istria to the southernmost area of Dalmatia. The study included 12 cultivars of Vitis vinifera L., as listed in

Table 1. List of the researched grapevine cultivars.

Cultivar	Acronym
Malvazija	MI
Pošip	PO
Maraština	MA
Teran	TE
Plavina	PL
Plavac mali	PM
Chardonnay	CH
Pinot blanc	PB
Sauvignon blanc	SB
Merlot	ME
Cabernet sauvignon	CS
Syrah	SY

. Six of these were indigenous Croatian cultivars (Malvazija istarska, Pošip, Maraština, Teran, Plavina, and Plavac mali), while the remaining six were introduced cultivars (Chardonnay, Pinot blanc, Sauvignon blanc, Merlot, Cabernet sauvignon, and Syrah). For each cultivar, pruning residues were collected from three distinct vineyards, with three replicates from each vineyard. The amount of pruning residues for one replicate was collected from three fully developed grapevines, resulting in a total of 27 sampled fully developed vines per cultivar.

The collected residues were cut into pieces approximately 3 cm in length, pre-dried in a forced-air oven at 105 °C for 24 h, and stored at room temperature in a dark and dry environment until further analysis. Grapevine-pruning residues collected for biochar production were left to air-dry for 7 days.

2.2. Characterization of Grapevine-Pruning Residues

All samples were ground using a centrifugal mill (ZM200, Retsch GmbH, Haan, Germany). Ash content was determined using a muffle furnace (Nabertherm L9/11/B410, Nabertherm GmbH, Lilienthal, Germany). One gram of ground sample was combusted in ceramic crucibles using the following temperature program: heating from room temperature to 105 °C over 20 min, followed by ramping to 750 °C over 5 h. Ash content was calculated as:

$$Ash\left(\%\right)={\displaystyle \frac{mAsh}{mSample}}$$

(1)

Ash (%) represents the mass content of ash, expressed as a percentage (%), and mAsh is the mass of produced ash, expressed in g, while mSample is the mass of the sample (grape-vine-pruning residues), expressed in grams.

Pruning residues pH was measured by mixing 5 mL of the sample with 25 mL of deionized water (1:5 v/v). The suspension was stirred, and the pH was recorded using a pH meter (inoLab Multi 9310 IDS, Xylem Inc., Washington, WA, USA). Electrical conductivity (EC) was assessed by mixing 1 g of sample with 25 mL of deionized water (1:25 m/v), rotating for 1 h, and measuring EC using a conductivity meter (FiveGo F3, Mettler Toledo AG, Columbus, OH, USA).

Total carbon (TC) was quantified using a total organic carbon analyzer with a solid sample module (TOC-L with SSM-500A, Shimadzu Corporation, Kyoto, Japan). Approximately 50 mg of pre-dried and ground sample was used for each measurement. Total nitrogen (N) was measured by the Kjeldahl method [33]. One gram of sample was digested with 12 mL of concentrated H₂SO₄ and two KJTabs™ at 420 °C for 1 h using a UDK 149 Nitrogen Analyzer (VELP Scientifica, Usmate, Italy). After cooling, samples were distilled with 30 mL H₃BO₄ and 50 mL NaOH, and titrated using 0.1 N HCl.

Macro- and microelements (P, K, Mg, Ca, S, Cu, Na, Si, Zn) were determined using ICP-OES with both axial and radial viewing (ICPE-9820, Shimadzu, Japan) after microwave digestion (Ethos UP, Milestone Srl, Milan, Italy). For each sample, 250 mg of ground material was digested with 6 mL HNO₃ and 2 mL H₂O₂. The digestion program included a 25 min ramp to 200 °C and a 15 min hold. After cooling, the samples were diluted to 25 mL with ultrapure water. Method accuracy was evaluated using four certified reference materials from the WEPAL dried plant material program (WEPAL, Wageningen, The Netherlands). Operating parameters were as follows: 1.15 kW of RF power, 12 L min⁻¹ of plasma flow rate, 0.5 L min⁻¹ of auxiliary gas flow rate, and 0.5 L min⁻¹ of nebulizer flow rate. Sample solutions were introduced into the plasma using a concentric nebulizer and a cyclonic-type spray chamber. Argon (99.999% pure, Linde Gases, Ananindeua, Brazil) was used to purge the optics and to form the plasma.

The surface morphology was examined using scanning electron microscopy (SEM) with a field emission gun (Quanta 250 FEG-SEM, FEI Company, Hillsboro, OR, USA). Fourier-transform infrared spectroscopy (FT-IR) analysis was conducted using pellets made from ground sample and KBr (1:150 mass ratio) pressed with a hydraulic press (Specac^® Atlas 15T, SPECAC Inc., Fort Washington, PA, USA). Spectra were collected in the 400–4000 cm⁻¹ range with a 4 cm⁻¹ resolution using a FT-IR spectrometer (IRTracer-100, Shimadzu, Japan). Spectra were normalized at maximum intensity.

2.3. Biochar Characterization

Biochar was produced from the pruning residues using a muffle furnace (Nabertherm L9/11/B410, Nabertherm GmbH, Germany) under oxygen-limited conditions. Three replicates of air-dried grapevine-pruning residues per location (a total of 27 replicates per cultivar) were placed in ceramic crucibles with lids and heated at a rate of 10 °C per minute to a final temperature of 400 °C, which was maintained for 1 h. The temperature of 400 °C was selected based on our previous research [35], where biochars produced from grapevine-pruning residues at 400 °C had the highest biochar yield, the highest pH value, and the highest SSA value. The produced biochar yield was calculated according to the following Equation (2).

$$Yield\left(\%\right)={\displaystyle \frac{mBC}{mPR}}\times 100$$

(2)

Yield (%) represents the mass yield of biochar, mBCis the mass (kg) of biochar, and mPR is the mass (kg) of pruning residues.

Ash content, EC, TC, and N content of biochar were determined using the same methods as described in Section 2.2. For pH measurement, 5 mL of air-dried biochar was mixed with 25 mL of 0.01 M CaCl₂ (1:5 v/v), rotated for 1 h, and measured following DIN ISO 10390. Calcium chloride was used instead of water because biochar analysis guidelines suggest that it could be a standardized approach to minimize the confounding effects of water-soluble inorganic and organic carbon, which are present in biochar and influence pH measurement in water.

Elemental composition (P, K, Mg, Ca, S, Cu, Na, Si, and Zn) was assessed by ICP-OES after microwave digestion. A quantity of 200 mg of ground biochar was digested with 6 mL HNO₃, 2 mL H₂O₂, and 0.4 mL HF. The digestion program was different from the one used for grapevine-pruning residues, and according to the manufacturer’s instructions, it consisted of a 35 min ramp to 190 °C with a 20 min hold. After cooling, 5 mL of H₃BO₃ was added, and a second digestion was carried out using the same temperature program. Digested samples were then diluted to 25 mL with ultrapure water. Operating parameters of the ICP-OES were the same as reported in Section 2.2.

The surface morphology of biochar was analyzed using scanning electron microscope combined with a field emission gun (Quanta 250 FEG-SEM, FEI Company, Hillsboro, OR, USA). The specific surface area (SSA) was determined using the Brunauer–Emmett–Teller (BET) method. Nitrogen gas adsorption was measured at −196 °C using a Gemini 2380 Surface Area Analyzer (Micromeritics, Norcross, GA, USA). Samples were degassed at 200 °C for 4 h under vacuum (10⁻³ mbar) and the Langmuir isotherm was applied. FT-IR spectra of biochar samples were recorded following the same protocol used for grapevine-pruning residues (Section 2.2).

2.4. Statistical Analysis

Statistical analyses were performed using Statistica 12 software (Tibco, Inc., Palo Alto, CA, USA). All experiments included three biological replicates per cultivar, with each replicate collected from different geographic plots to ensure independence. The influence of grapevine cultivar on the properties of pruning residues and the resulting biochars was evaluated using one-way analysis of variance (ANOVA). Prior to ANOVA, data were checked for normality and homogeneity of variance. When ANOVA indicated significant differences (p < 0.05), Tukey’s LSD (Least Significant Difference) test was applied for pairwise comparisons between cultivars at a 95% confidence level. Additionally, Pearson correlation analyses were conducted to evaluate relationships between selected chemical and physical parameters of grapevine-pruning residues and the corresponding biochar samples. All results are presented as mean ± standard deviation, and statistically significant differences identified by the LSD test are indicated in the tables using superscript letters. To further explore the relationships among grapevine cultivars and the key factors driving biochar variability, Principal Component Analysis (PCA) was performed on the dataset of physicochemical parameters of both pruning residues and derived biochars. PCA was conducted using OriginPro 9.64 (Northampton, MA, USA, OriginLab Corporation). Variables were standardized prior to analysis to ensure comparability. A correlation Heatmap was performed by using the Seaborn library (version 0.13.2) in Python (version 3.10) to provide a more intuitive visualization of the relationships between feedstock characteristics and biochar properties.

3. Results

3.1. Characterization of Grapevine-Pruning Residues

The pH values (

Table 2. Chemical characteristics of grapevine-pruning residues.

Cultivar	pH	EC (µS/cm)	Ash (%)
MI	5.45 ± 0.11 a	2390 ± 20.8 a	3.49 ± 0.09 a
PO	5.08 ± 0.08 bcd	1982 ± 20.8 ab	2.76 ± 0.09 ab
MA	4.79 ± 0.02 d	1975 ± 109.1 ab	3.02 ± 0.21 ab
TE	5.27 ± 0.11 ab	2055.6 ± 47.5 ab	2.87 ± 0.09 ab
PL	4.86 ± 0.04 cd	2076.6 ± 21.8 ab	2.98 ± 0.12 ab
PM	5.09 ± 0.06 bcd	2016.3 ± 115.8 ab	2.65 ± 0.33 b
CH	5.08 ± 0.08 bcd	1848 ± 58 ab	2.78 ± 0.15 ab
PB	5.06 ± 0.08 bcd	1778 ± 124 b	2.65 ± 0.16 b
SB	5.01 ± 0.09 bcd	1814 ± 235.8 b	2.59 ± 0.19 b
ME	4.93 ± 0.02 cd	1906 ± 47.2 ab	2.82 ± 0.11 ab
CS	5.16 ± 0.03 abc	1694 ± 127 b	2.77 ± 0.10 ab
SY	5.16 ± 0.05 abc	1839 ± 66.3 b	2.61 ± 0.22 b
Mean	5.07 ± 0.02	1947 ± 39	2.83 ± 0.05
p value	***	***	*

Results are presented as mean values ± standard error. Data were analyzed according to one-way ANOVA by following Tukey’s post hoc test. The different letters indicate statistically significant differences between the treatments. * and *** indicate statistically significant differences at p < 0.05 and 0.001. MI–Malvazija istarska, PO–Pošip, MA–Maraština, TE–Teran, PL–Plavina, PM–Plavac mali, CH–Chardonnay, PB–Pinot blanc, SB–Sauvignon blanc, ME–Merlot, CS–Cabernet sauvignon, and SY–Syrah.

) of grapevine-pruning residues were significantly different between all studied cultivars (p < 0.001) and were in the range from 4.79 to 5.45. The highest pH value was detected in cultivar MI, followed by TE, CS, and SY, while MA had the lowest pH value. The EC values (Table 2) of grapevine-pruning residues were also significantly different between all studied cultivars (p < 0.001) and were in the range from 1694 µS/cm to 2390 µS/cm. MI also had the highest EC value, followed by PO, TE, PM, and ME, while other cultivars showed comparable lower EC values. Likewise, ash content values (Table 2) were significantly different for all studied cultivars (p < 0.001) ranging from 2.65% to 3.49%. Ash content was highest in cultivar MI, while it was lowest in cultivars PM, PB, SB, and SY.

The content of the most abundant elements (TC, P, K, Mg, Ca, and S) in grape-vine-pruning residues was significantly different between the studied cultivars (

Table 3. Elemental composition of grapevine-pruning residues.

Cultivar	TC	N	P	K	Mg	Ca	S	Cu	Na	Si	Zn
	%	%	g/kg	g/kg	g/kg	g/kg	g/kg	mg/kg	mg/kg	mg/kg	mg/kg
MI	44.37 ± 0.16 bcd	0.57 ± 0.07	0.56 ± 0.03 ab	8.62 ± 0.69 ab	0.91 ± 0.05 abcd	6.48 ± 0.44 a	0.28 ± 0.01 abc	3.53 ± 0.45 ab	64.35 ± 6.97 a	17.23 ± 4.84 ab	6.93 ± 0.91 ab
PO	44.63 ± 0.16 abc	0.71 ± 0.06	0.62 ± 0.03 ab	7.07 ± 0.51 ab	1.14 ± 0.10 ab	6.60 ± 0.86 a	0.30 ± 0.02 ab	3.25 ± 0.49 b	60.84 ± 6.95 a	13.45 ± 3.02 ab	5.97 ± 0.95 ab
MA	43.77 ± 0.21 c	0.65 ± 0.05	0.61 ± 0.01 ab	7.25 ± 0.60 ab	1.15 ± 0.07 a	7.60 ± 0.39 a	0.30 ± 0.01 ab	4.05 ± 0.61 ab	126.32 ± 18.62 a	24.65 ± 5.43 ab	6.69 ± 0.70 ab
TE	44.89 ± 0.15 abc	0.67 ± 0.07	0.53 ± 0.06 ab	7.87 ± 0.55 ab	0.72 ± 0.06 de	6.07 ± 0.55 ab	0.26 ± 0.01 bc	2.29 ± 0.19 b	60.72 ± 3.75 a	16.68 ± 7.85 ab	5.56 ± 1.31 ab
PL	44.51 ± 0.22 abcd	0.60 ± 0.03	0.57 ± 0.03 ab	9.33 ± 0.33 a	0.65 ± 0.07 de	6.12 ± 0.32 ab	0.27 ± 0.01 abc	3.72 ± 0.64 ab	141.68 ± 28.51 a	22.47 ± 5.28 ab	7.22 ± 1.58 ab
PM	45.36 ± 0.17 a	0.52 ± 0.03	0.46 ± 0.03 b	7.10 ± 0.40 ab	1.02 ± 0.04 abc	4.05 ± 0.20 b	0.25 ± 0.01 bc	2.01 ± 0.12 b	64.71 ± 6.55 a	4.72 ± 0.54 b	4.50 ± 0.44 b
CH	44.57 ± 0.13 abcd	0.56 ± 0.04	0.48 ± 0.05 ab	6.22 ± 0.60 b	0.82 ± 0.04 cde	5.83 ± 0.65 ab	0.25 ± 0.02 bc	2.89 ± 0.38 b	147.58 ± 45.41 a	15.32 ± 4.45 ab	8.56 ± 1.23 ab
PB	45.02 ± 0.23 ab	0.59 ± 0.03	0.50 ± 0.03 ab	7.76 ± 0.55 ab	0.60 ± 0.07 e	6.37 ± 0.34 a	0.27 ± 0.01 abc	3.29 ± 0.50 ab	61.02 ± 2.48 a	31.27 ± 15.17 ab	5.22 ± 1.16 ab
SB	44.27 ± 0.16 bcd	0.53 ± 0.04	0.49 ± 0.05 ab	6.60 ± 0.80 b	0.86 ± 0.04 bcde	5.46 ± 0.54 ab	0.25 ± 0.02 bc	2.38 ± 0.26 b	105.45 ± 27.39 a	13.14 ± 3.74 ab	9.31 ± 1.23 ab
ME	44.02 ± 0.08 cd	0.69 ± 0.05	0.66 ± 0.04 a	7.53 ± 0.34 ab	0.72 ± 0.05 de	7.47 ± 0.37 a	0.32 ± 0.01 a	3.42 ± 0.33 ab	98.18 ± 23.24 a	12.81 ± 3.00 ab	7.19 ± 1.34 ab
CS	44.60 ± 0.22 abcd	0.50 ± 0.03	0.50 ± 0.05 ab	6.92 ± 0.53 ab	0.78 ± 0.06 cde	5.77 ± 0.53 ab	0.24 ± 0.01 c	2.38 ± 0.18 b	88.46 ± 13.81 a	12.39 ± 2.31 ab	6.36 ± 1.00 ab
SY	44.71 ± 0.18 abc	0.65 ± 0.06	0.59 ± 0.03 ab	6.64 ± 0.33 b	1.13 ± 0.06 ab	5.87 ± 0.28 ab	0.28 ± 0.00 abc	5.61 ± 1.05 a	151.13 ± 37.67 a	42.68 ± 11.43 a	10.03 ± 0.80 a
Mean	44.55 ± 0.06	0.60 ± 0.20	0.55 ± 0.11	7.41 ± 0.16	0.87 ± 0.02	6.14 ± 0.15	0.27 ± 0.00	3.24 ± 0.43	97.54 ± 18.45	18.90 ± 5.59	6.96 ± 1.05
p value	***	n.s.	**	***	***	***	***	***	n.s.	*	*

Results are presented as mean values ± standard error. Data were analyzed according to one-way ANOVA by following Tukey’s post hoc test. The different letters indicate statistically significant differences between the treatments. *, **, and *** indicate statistically significant differences at p < 0.05, 0.01, and 0.001, and n.s. represents non-significant differences. MI–Malvazija istarska, PO–Pošip, MA–Maraština, TE–Teran, PL–Plavina, PM–Plavac mali, CH–Chardonnay, PB–Pinot blanc, SB–Sauvignon blanc, ME–Merlot, CS–Cabernet sauvignon, and SY–Syrah.

), except for nitrogen content (Table 3). Significant differences were observed for TC, K, Mg, Ca and S (p < 0.001), as well as for P (p < 0.01). The TC content of grapevine-pruning residues was in the range from 43.77% to 45.36%. The highest TC content was detected in MI cultivar residues, while the lowest TC content was reported in cultivar MA residues. Other cultivars showed similar and comparable TC content to MI. The N content of grapevine-pruning residues was in the range from 0.50% to 0.71%. The highest N content was found in cultivar PO, and the lowest was detected in cultivar PM. Other cultivars showed similar and comparable results to cultivars PO and PM. The P content of grapevine-pruning residues was in the range from 0.46 g/kg to 0.66 g/kg. The highest P content was found in cultivar ME, while the lowest content was detected in cultivar PM. Other researched cultivars were comparable to ME and PM. The K content for grapevine-pruning residues was in the range from 6.22 g/kg to 9.33 g/kg. The highest K content was detected in cultivar PL, while the lowest content was detected in cultivars CH, SB, and SY. The Mg content of grapevine-pruning residues was in the range from 0.60 g/kg to 1.15 g/kg. Cultivar MA had the highest Mg content followed by PO, SY, PM, and MI, while cultivar PB had the lowest Mg content followed by SB, CH, CS, ME, TE, and PL. The Ca content of grapevine-pruning residues was in the range from 4.05 g/kg to 7.60 g/kg. The highest Ca content was detected in the cultivars MA, ME, PO, MI, and PB, while cultivar PM had the lowest Ca content. The S content of grapevine-pruning residues was in the range from 0.24 g/kg to 0.32 g/kg. The highest S content was found in cultivar Merlot, followed by MA and PO, while the lowest content was detected in cultivar CS, followed by SB, CH, PM, and PL.

All microelement (Cu, Si, Zn) contents (Table 3) of grapevine-pruning residues were significantly different between cultivars, except for Na content. The Cu content of grapevine-pruning residues was in the range from 2.01 mg/kg to 5.61 mg/kg. The highest Cu content was detected in cultivar SY, while the lowest content was detected in cultivars PO, CH, SB, CS, TE, and PM. The Cu contents of other cultivars were comparable. The Si content of grapevine-pruning residues was in the range from 4.72 mg/kg to 46.68 mg/kg. The highest Si content was found in cultivar SY, while the lowest content was detected in cultivar PM. The Si content of all other cultivars were comparable to the cultivars SY and PM. The Zn content of grapevine-pruning residues was in the range from 4.50 mg/kg to 10.3 mg/kg. The highest Zn content was found in cultivar SY, while the lowest content was detected in cultivar PM. The Zn contents of all other cultivars were comparable to the cultivars SY and PM. The Na content of grapevine-pruning residues was in the range from 60.84 mg/kg to 151.13 mg/kg. The highest Na content was found in cultivar SY, while the other cultivars were comparable to SY.

FT–IR spectroscopic analysis was conducted on pruning residue samples from twelve different grapevine cultivars (Figure 1). The spectra were recorded in the range of 4000 to 400 cm⁻¹, and characteristic absorption bands were observed, indicating the presence of functional groups typical for plant lignocellulosic materials.

All samples exhibited a broad absorption band around 3400 cm⁻¹, corresponding to O–H stretching vibrations associated with water, alcohols, and phenols. This band was most prominent in the cultivars Maraština, Malvazija istarska, and Plavina. In addition, a distinct peak near 2920 cm⁻¹, related to C–H stretching in aliphatic structures, was present in all cultivars and especially pronounced in Chardonnay, Pinot Blanc, and Sauvignon Blanc. The region around 1700 cm⁻¹ revealed C=O stretching vibrations, typically attributed to carboxylic acids, esters, and aldehydes. These signals were observed in all samples, with the highest intensities detected in Chardonnay, Pinot Blanc, and Malvazija Istarska.

Furthermore, the spectral region between 1600 and 1500 cm⁻¹ showed aromatic C=C vibrations mainly derived from lignin, clearly expressed in Syrah, Plavac mali, and Cabernet Sauvignon. The fingerprint region, spanning from 1250 to 1000 cm⁻¹, contained bands corresponding to C–O, C–OH, and C–O–C vibrations, indicative of cellulose and hemicellulose structures. These signals were found in all samples, with particularly strong expression in Chardonnay, Maraština, and Merlot.

3.2. Characterization of Biochar Samples

The pH values of biochar samples produced from the grapevine-pruning residues were significantly different between all studied cultivars (p < 0.001). The range of pH values (

Table 4. Chemical characteristics of biochar samples.

Cultivar	pH	EC (µS/cm)	Ash (%)	Yield (%)
MI	10.57 ± 0.27 ab	655.3 ± 183.7	8.35 ± 0.24 a	33.37 ± 0.25 ab
PO	10.20 ± 0.28 b	820.6 ± 25.6	7.21 ± 0.12 b	33.53 ± 0.74 ab
MA	10.42 ± 0.11 ab	600 ± 13.5	8.34 ± 0.35 a	34.55 ± 0.15 ab
TE	10.65 ± 0.17 ab	684 ± 165.1	7.51 ± 0.17 ab	35.04 ± 0.81 a
PL	10.96 ± 0.16 ab	829 ± 67.4	7.62 ± 0.06 ab	34.03 ± 0.46 ab
PM	11.13 ± 0.18 a	980.3 ± 34.3	7.67 ± 0.21 ab	35.03 ± 0.47 a
CH	10.89 ± 0.09 ab	713.6 ± 70.3	7.22 ± 0.12 ab	34.32 ± 0.32 ab
PB	10.70 ± 0.14 ab	575 ± 67.4	6.79 ± 0.31 b	35.21 ± 0.36 a
SB	10.63 ± 0.09 ab	1067 ± 123.3	6.76 ± 0.52 b	32.65 ± 0.17 b
ME	11.03 ± 0.14 a	774 ± 53.9	7.42 ± 0.08 ab	34.95 ± 0.14 a
CS	10.78 ± 0.06 ab	775 ± 76.2	7.06 ± 0.08 b	33.71 ± 0.23 ab
SY	10.54 ± 0.18 ab	780.3 ± 129.4	6.92 ± 0.15 b	32.87 ± 0.27 b
Mean	10.70 ± 0.05	770 ± 33.2	7.40 ± 0.08	34.10 ± 0.14
p value	***	n.s.	***	***

Results are presented as mean values ± standard error. Data were analyzed according to one-way ANOVA by following Tukey’s post hoc test. The different letters indicate statistically significant differences between the treatments. *** indicate statistically significant differences at p < 0.001, and n.s. represents non-significant differences. MI–Malvazija istarska, PO–Pošip, MA–Maraština, TE–Teran, PL–Plavina, PM–Plavac mali, CH–Chardonnay, PB–Pinot blanc, SB–Sauvignon blanc, ME–Merlot, CS–Cabernet sauvignon, and SY–Syrah.

) of biochar samples was from 10.2 to 11.13. Biochar produced from cultivars PM and ME had the highest pH value, while the lowest was reported in biochar produced from PO residues. All other cultivars, MI, MA, TE, PL, CH, PB, SB, CS, and SY were comparable to PM, ME, and PO cultivars. The EC values (Table 4) of biochar samples were not significantly different. The range of EC values was from 575 µS/cm to 1067 µS/cm. The ash content values (Table 4) for biochar samples were significantly different among the studied cultivars (p < 0.001) and were in the range of 6.76% to 8.35%. The highest ash content was noted in biochars from MI and MA residues, while PO, PB, SB, CS, and SY had the lowest ash content.

Biochar yields (Table 4) obtained from residues of the studied grapevine cultivars were significantly different between all cultivars (p < 0.001). The range of obtained biochar yield was from 32.87% to 35.04%. The highest biochar yield was detected in cultivars PM, TE, PB, and ME, while the lowest biochar yield was reported for cultivars SB and SY. All other cultivars, MI, PO, MA, PL, CH, and CS, were comparable to PM, TE, PB, ME, SB, and SY cultivars.

The most abundant elements (TC, N, P, K, Mg, Ca, and S) in biochar samples (

Table 5. Elemental composition of biochar samples.

Cultvar	TC	N	P	K	Mg	Ca	S	Cu	Na	Si	Zn
	%	%	g/kg	g/kg	g/kr	g/kg	g/kg	mg/g	mg/g	mg/g	mg/g
MI	71.57 ± 0.66 a	0.96 ± 0.05 abc	3.27 ± 0.18 ab	21.71 ± 1.78 a	2.17 ± 0.06 bcd	22.42 ± 1.87 a	1.68 ± 0.27 a	38.22 ± 8.40 a	74.80 ± 16.27 b	467.49 ± 119.22 c	22.46 ± 0.91 c
PO	66.43 ± 1.32 de	1.06 ± 0.03 ab	2.52 ± 0.11 cde	19.27 ± 1.68 ab	2.26 ± 0.21 bcd	16.60 ± 0.69 bcd	1.22 ± 0.04 bc	4.14 ± 1.15 b	423.61 ± 100.27 ab	979.99 ± 52.02 ab	31.55 ± 3.56 abc
MA	65.88 ± 0.54 e	0.88 ± 0.12 abc	2.57 ± 0.09 bcde	16.72 ± 1.98 ab	2.79 ± 0.20 ab	21.31 ± 1.25 ab	1.62 ± 0.06 ab	9.08 ± 2.07 b	412.02 ± 73.72 ab	853.96 ± 81.42 abc	39.69 ± 5.87 abc
TE	70.90 ± 0.83 ab	0.88 ± 0.07 abc	3.62 ± 0.17 a	17.28 ± 1.31 ab	3.18 ± 0.37 a	14.28 ± 0.61 c	1.11 ± 0.06 c	5.58 ± 0.77 b	208.88 ± 20.73 ab	989.79 ± 49.01 ab	23.64 ± 2.65 bc
PL	67.32 ± 0.62 cde	0.89 ± 0.13 abc	3.05 ± 0.34 abc	19.42 ± 1.14 ab	1.61 ± 0.12 d	18.50 ± 1.13 abcd	1.37 ± 0.05 abc	12.46 ± 3.86 b	455.31 ± 88.03 ab	769.07 ± 22.97 bc	24.94 ± 3.55 bc
PM	70.40 ± 0.48 abc	0.62 ± 0.04 c	2.49 ± 0.06 cde	16.38 ± 0.25 ab	2.28 ± 0.11 bcd	15.74 ± 1.30 cd	1.07 ± 0.02 c	5.42 ± 1.12 b	550.29 ± 104.33 ab	666.00 ± 37.06 bc	23.82 ± 2.12 bc
CH	69.28 ± 0.58 abcde	0.74 ± 0.10 bc	2.65 ± 0.12 bcde	16.48 ± 0.95 ab	1.85 ± 0.09 d	20.68 ± 1.07 abc	1.28 ± 0.06 abc	6.01 ± 1.00 b	585.11 ± 182.93 a	1216.08 ± 122.34 a	37.68 ± 7.27 abc
PB	69.55 ± 0.79 abcd	0.94 ± 0.06 abc	2.20 ± 0.06 e	14.29 ± 1.35 b	2.09 ± 0.19 bcd	17.56 ± 0.95 abcd	1.04 ± 0.04 c	18.94 ± 4.65 b	214.97 ± 28.71 ab	1258.16 ± 39.68 a	28.55 ± 2.30 bc
SB	68.88 ± 0.75 abcde	0.89 ± 0.06 abc	2.25 ± 0.22 de	17.07 ± 1.62 ab	2.01 ± 0.11 bcd	14.56 ± 1.23 c	1.33 ± 0.06 abc	4.09 ± 0.94 b	381.08 ± 113.94 ab	692.88 ± 48.50 bc	45.57 ± 6.34 ab
ME	66.88 ± 0.66 de	1.16 ± 0.08 a	2.96 ± 0.08 abcd	19.42 ± 0.88 ab	1.66 ± 0.09 d	22.32 ± 0.73 a	1.61 ± 0.06 ab	5.98 ± 0.61 b	296.25 ± 81.42 ab	1276.81 ± 228.52 a	51.89 ± 8.26 a
CS	68.03 ± 0.34 bcde	0.94 ± 0.05 abc	2.21 ± 0.13 e	18.38 ± 1.11 ab	1.96 ± 0.07 cd	19.40 ± 0.84 abcd	1.36 ± 0.04 abc	4.53 ± 0.65 b	353.48 ± 73.41 ab	871.59 ± 51.42 abc	34.10 ± 3.40 abc
SY	66.65 ± 0.60 de	1.16 ± 0.05 a	2.49 ± 0.08 cde	19.64 ± 1.34 ab	2.75 ± 0.17 abc	17.41 ± 0.68 abcd	1.34 ± 0.02 abc	12.05 ± 2.96 b	602.84 ± 193.08 a	991.47 ± 48.39 ab	35.70 ± 4.62 abc
Mean	68.48 ± 0.26	0.92 ± 0.03	2.69 ± 0.05	18.09 ± 0.41	2.22 ± 0.06	18.99 ± 0.39	1.33 ± 0.03	10.54 ± 2.35	379.89 ± 89.74	919.44 ± 75.05	33.30 ± 4.24
p value	***	***	***	*	***	***	***	***	*	***	***

Results are presented as mean values ± standard error. Data were analyzed according to one-way ANOVA by following Tukey’s post hoc test. The different letters indicate statistically significant differences between the treatments. * and *** indicate statistically significant differences at p < 0.05 and 0.001. MI–Malvazija istarska, PO–Pošip, MA–Maraština, TE–Teran, PL–Plavina, PM–Plavac mali, CH–Chardonnay, PB–Pinot blanc, SB–Sauvignon blanc, ME–Merlot, CS–Cabernet sauvignon, and SY–Syrah.

) obtained from grapevine-pruning residues were significantly different between all cultivars. Significant differences were observed for TC, N, P, Mg, Ca, and S (p < 0.001) and for K (p < 0.05). The TC content of biochar samples was in the range from 65.88% to 71.57%. The highest TC content was noted in biochar produced from cultivar MI residues, followed by cultivars TE, PM, CH, PB, and SB, while MA had the lowest TC content. The N content of biochar samples was in the range from 0.62% to 1.16%. The highest N content was found in biochar obtained from cultivars SY and ME, while the lowest was reported in biochar produced from PM residues. Cultivars PO, MI, MA, TE, PL, PB, SB, and CS were comparable to ME and SY cultivars. Furthermore, cultivars MI, MA, TE, PL, CH, PB, SB, and CS were comparable to the PM cultivar. The P content of biochar samples was in the range from 2.20 g/kg to 3.62 g/kg. The highest P content was reported in the cultivar TE followed by cultivars MI, PL, and ME. The lowest P content was detected in cultivars CS and PB, followed by SB, SY, P, PM, MA, and CH cultivars. The K content of biochar samples was in the range from 14.29 g/kg to 21.71 g/kg. The highest K content was found in the MI cultivar, while the lowest content was detected in the cultivar PB. The K contents of other cultivars were comparable to cultivars MI and PB. The Mg content of biochar samples was in the range from 1.85 g/kg to 3.18 g/kg. The highest Mg content was found in cultivar TE, followed by cultivars MA and SY. The lowest Mg content was detected in cultivars ME, CH, and PL. The Ca content of biochar samples was in the range from 14.28 g/kg to 22.42 g/kg. The highest Ca content was found in biochar from cultivars MI and ME, followed by MA, CH, CS, PL, PB, and SY cultivars. The lowest Ca content was detected in SB and TE cultivars, followed by PO and PM cultivars. The S content of biochar samples was in the range from 1.04 g/kg to 1.68 g/kg. The highest S content was found in biochar from MI cultivar. Cultivars MA, ME, PL, CS, SY, SB, and CH were comparable to the MI cultivar. The lowest S content was detected in cultivars TE, PM, and PB. Cultivars PO, PL, CH, SB, CS, and SY were comparable to cultivars TE, PM, and PB.

All studied microelement (Cu, Na, Si, Zn) contents of biochar samples (Table 5) obtained from the grapevine-pruning residues were significantly different between cultivars. Significant differences were observed for Cu, Si, and Zn (p < 0.001) and for Na (p < 0.05). The Cu content of biochar samples was in the range from 4.09 mg/kg to 38.22 mg/kg. The highest value of Cu content was detected in biochar from MI cultivar, while the lowest content was detected in cultivar SB, followed by PB, PL, SY, MA, CH, ME, TE, PM, CS, PO, and SB. The Na content of biochar samples was in the range from 74.80 mg/kg to 602.84 mg/kg. The highest Na content was reported in cultivars SY and CH, while the lowest was detected in MI cultivar. Other cultivars were comparable to cultivars SY, CH, and MI. The Si content of biochar samples was in the range from 467.49 mg/kg to 1276.81 mg/kg. The highest Si content was found in biochar from cultivars M, PB, and CH. Cultivars SY, TE, PO, MA, and CS were comparable to cultivars M, PB, and CH. The lowest Si content was detected in the MI cultivar. Cultivars SB, PM, PL, MA, and CS were comparable to the MI cultivar. The Zn content for biochar samples was in the range from 22.46 mg/kg to 51.89 mg/kg. The highest Zn content was found in biochar from the ME cultivar. Cultivars SB, PO, MA, CH, CS, and SY were comparable to the ME cultivar. The lowest Zn content was detected in the cultivar MI. Cultivars PB, PL, PM, TE, PO, MA, CH, CS, and SY were comparable to the MI cultivar.

The results of the specific surface area analysis of biochar samples (Figure 2) produced from grapevine-pruning residues were significantly different between cultivars. The specific surface area for biochar samples was in the range from 1.63 m² g⁻¹ to 4.13 m² g⁻¹. Biochar produced from cultivar MA residues had the highest specific surface area, followed by SB, PO, and SY. Biochar produced from cultivars PB and TE had the lowest specific surface area.

The scanning electron microscope (SEM) pictures of grapevine-pruning residues and produced biochar are shown in Figure 3 and Figure 4. Pictures at high magnification showed a clear difference between the used feedstock and the produced biochar. The grapevine pruning residues display an ordered structure of fibers like in Figure 3A–C, and on Figure 4A–C, it can be seen that most of the biochar morphology had changed. The biochar samples had higher numbers of pores due to exposure to the process of pyrolysis.

FT–IR spectroscopic analysis was carried out on biochar samples obtained through pyrolysis of grapevine-pruning residues from twelve different grapevine cultivars (Figure 5). The spectra were recorded in the range of 4000 to 400 cm⁻¹, and the observed absorption bands revealed the presence of functional groups characteristic of thermally processed lignocellulosic materials.

A broad absorption band was observed around 3400 cm⁻¹ in all samples, which is attributed to O–H stretching vibrations, likely originating from phenolic or carboxylic groups and/or residual moisture. The presence of C–H stretching vibrations was noted around 2920 cm⁻¹, indicating partial degradation of aliphatic structures during pyrolysis. Furthermore, a band near 1700 cm⁻¹ corresponds to C=O stretching vibrations typical of carboxylic acids and ketones. This signal was present in nearly all cultivars, with particularly strong expression in Chardonnay, Merlot, and Syrah.

The region between 1600 and 1500 cm⁻¹ showed aromatic C=C vibrations, indicating the presence of stable aromatic structures that are remnants of lignin. These bands were especially prominent in Teran, Plavac mali, and Syrah. In the range from 1250 to 1000 cm⁻¹, absorption bands corresponding to C–O, C–OH, and C–O–C bonds were recorded. These vibrations are characteristic of residual cellulose, hemicellulose, and phenolic compounds, and were detected in all analyzed samples. Additionally, deformation vibrations of aromatic rings were observed in the spectral region below 800 cm⁻¹, further supporting the presence of condensed aromatic systems in the biochar matrix.

3.3. Correlation Analysis

The correlation matrices revealed clear differences in physicochemical relationships between pruning residues and biochar (Figure 6). In pruning residues, strong positive correlations occurred among Ca, S, P, and Mg, and ash content was positively associated with Ca, S, and Cu. pH showed weak negative correlations with most nutrients. In biochar, pyrolysis resulted in stronger associations among pH, EC, and TC, along with notable positive correlations between Ca and S and between K and P. Nitrogen and magnesium displayed weak or negative correlations with other elements. Overall, the two materials exhibited distinct correlation structures reflecting their contrasting chemical compositions.

In pruning residues, the PCA shows that variation along PC1 is mainly driven by differences in nutrient composition, with elements such as S, Ca, K, N, and P contributing positively, while Na, Zn, Mg, and Si contribute negatively. PC2 reflects changes associated with pH, EC, and total carbon, indicating variability in chemical reactivity and carbon content. The sample distribution suggests moderate variability across pruning residues. In contrast, biochar shows a PC1 strongly influenced by major nutrients such as K, Ca, and S on the positive axis, with Zn and Na contributing in the opposite direction. PC2 again reflects pH, EC, and TC influences, but with tighter sample clustering, indicating greater chemical uniformity. Overall, biochar exhibits clearer nutrient-driven separation and less variability than pruning residues (Figure 7).

4. Discussion

The results indicate significant variability in the chemical composition of grapevine pruning residues, consequently highlighting the substantial influence of the cultivar on the physicochemical profile of the produced biochar. As noted by Čabalová et al. [38], cultivar is a critical factor influencing the composition and valorization potential of grapevine biomass. The variability observed in pH, ash, nitrogen, and carbon content (Table 2 and Table 3) is consistent with previous findings on grapevine residues [35,39,40,41,42]. The observed differences in pH, ash, nitrogen, and carbon content arise from genotype-specific traits such as nutrient allocation, secondary metabolism, wood maturity, and particularly the proportions of lignin, cellulose, and hemicellulose, all of which strongly influence thermal decomposition behavior and subsequent biochar properties. In addition, these results emphasize that the observed differences are not merely descriptive but reflect underlying physiological and structural traits of the cultivars, which govern residue quality and biochar characteristics.

The pruning residues exhibited acidic pH (4.79–5.45), moderate electrical conductivity (1694–2390 µS cm⁻¹), and ash contents of 2.65–3.49% (Table 2) among all cultivars, reflecting their lignocellulosic nature. The acidity is linked to cultivar-specific differences in hemicellulose acetylation and lignin-bound organic acids [42]. Upon pyrolysis, cellulose and hemicellulose degrade rapidly, releasing volatile organic acids, whereas lignin decomposes more slowly and contributes to the formation of thermally stable aromatic structures [43]. This differential degradation explains that cultivars with higher lignin content produce more carbon-dense, alkaline biochars. This mechanistic perspective contributes to the formation of alkaline biochar (pH 10.2–11.13; Table 4), confirming the conversion of acidic feedstock into a basic material through the concentration of alkali metals (K, Ca, and Mg) and the formation of carbonates and oxides [44]. However, all biochars exhibited strong alkalinity (pH > 10), contrasting with the acidic residues. This alkalinity, coupled with EC values of 575–1067 µS cm⁻¹, indicates the presence of soluble mineral salts beneficial for neutralizing acidic soils. As Zaidun et al. [45] and Mosharrof [46] observed, biochar application can raise soil pH by 5–10%, improving nutrient uptake and microbial activity. The positive correlation between residue EC and biochar EC, ash, and nutrient content further demonstrates that intrinsic feedstock composition drives biochar nutrient retention.

The biochar yield (32–35%) among all cultivars aligns with reports of 30–40% for woody feedstocks at ~400 °C [25]. Variation among cultivars suggests that differences in lignocellulosic structure and mineral content directly affect pyrolysis efficiency and yield. Residues with higher EC and ash content, such as MI and PO, produced biochars with higher EC and mineral concentration, indicating a positive linkage between feedstock ionic strength and biochar nutrient retention. Such interdependence implies that the selection of nutrient-rich residues enhances the agronomic potential of biochar.

The total carbon (TC) in pruning residues (Table 3, 43.77–45.36%) increased to 65.88–71.57% in biochar (Table 5) among all cultivars, confirming carbon enrichment due to the preferential volatilization of cellulose and hemicellulose and the relative concentration of lignin-derived aromatic carbon structures formed during pyrolysis [47]. The nitrogen content also increased slightly (0.62–1.16%), likely reflecting the partial retention of nitrogen in heterocyclic and pyridinic forms [30]. This enrichment enhances the biochar’s potential as a slow-release nitrogen source [25]. Interestingly, the positive correlation between total carbon in residues and biochar carbon (r > 0.60) supports the role of lignin and cellulose proportions in determining the carbonization efficiency, as cultivars richer in lignin typically yield more aromatic and carbon-dense biochars, as observed by Sun et al. [48]. Conversely, the trade-off between TC and mineral concentration suggests that carbonization efficiency reduces the mineral mass fraction, thereby affecting nutrient density. Moreover, these findings indicate that cultivar-specific compositional traits, especially differences in lignin, cellulose, and mineral content, mechanistically govern the observed variation in biochar yield, stability, alkalinity, and nutrient retention.

The concentrations of micro- and macro-elements (Table 3 and Table 5) increased significantly post-pyrolysis, consistent with mineral concentration effects as volatile compounds are released [17]. However, differences among cultivars in elemental distribution suggest that physiological factors and mineral speciation within the plant influence final biochar composition more than total feedstock mineral content. Similar results have been reported by Grafmüller et al. [49], who noted that mineral distribution in biomass and its reactivity during pyrolysis determine the final composition of biochar more than absolute feedstock content alone.

FT–IR spectra (Figure 5) revealed that dehydration and decarboxylation reactions during pyrolysis led to the disappearance of O–H (3400 cm⁻¹) and C–H (2920 cm⁻¹) bands, while aromatic C=C bands (1600–1500 cm⁻¹) intensified, indicating increased aromatic condensation and carbon stability. These chemical transformations reflect cultivar-dependent differences in lignin and cellulose content, which influence the formation of functional groups and adsorption capacity. The persistence of minor bands at 1250–1000 cm⁻¹ (C–O and C–O–C) suggests residual functional groups contributing to adsorption capacity [50,51]. These transformations reflect progressive structural aromatization typical of thermochemical conversion of lignocellulosic biomass [52], while SEM micrographs (Figure 1) confirmed significant morphological changes, transitioning from an organized fibrous residue structure to porous, irregular carbon matrices. Such increased porosity (specific surface area = 1.63–4.13 m² g⁻¹; Figure 2) enhances nutrient retention and adsorption potential [53,54]. This increased porosity, influenced by the initial fiber and lignin structure of each cultivar, enhances nutrient retention, adsorption potential, and water-holding capacity. However, increased porosity and surface area provide more physical space and chemical sites for nutrient ions to attach, be trapped, or interact with the biochar surface. This leads to better nutrient retention, reduced leaching, and higher adsorption potential, ultimately improving water-holding capacity. These results agree with Lehmann and Joseph [55], who linked high surface reactivity to improved cation exchange capacity and soil fertility enhancement.

Pruning residues showed strong co-occurrence of Ca, S, P, and Mg because these macronutrients are structurally integrated in plant tissues and frequently accumulate together in cell walls and vascular components [56]. The positive correlation of ash with mineral elements reflects the concentration of inorganic constituents as organic matter combusts or thermally decomposes [55]. Pyrolysis modifies these relationships by volatilizing labile organics and light elements, particularly nitrogen- and magnesium-bearing compounds resulting in reduced covariance of these elements in biochar [57]. Concurrently, the loss of volatiles concentrates non-volatile minerals, strengthening associations such as Ca–S and K–P and increasing biochar alkalinity, EC, and carbon stability [58] (Figure 6). These shifts are reflected in the PCA: pruning residues exhibit wide dispersion along nutrient-rich vs. nutrient-poor gradients and a pH/EC/TC axis, demonstrating natural heterogeneity; in contrast, biochar forms tighter clusters because pyrolysis homogenizes chemical structure and amplifies mineral-driven variability (Figure 7). Collectively, the heatmap and PCA indicate that feedstock chemistry governs initial nutrient interactions, while pyrolysis selectively removes, concentrates, and stabilizes components, producing a more uniform, mineral-dominated biochar whose nutrient profile remains partly predictable from the original residues.

The results based on the measurements of parameters such as pH, EC, ash, carbon, nitrogen, and mineral content highlight that the chemical composition of grapevine residues strongly influences biochar quality. Although biochars produced in this research fall within the expected range for woody feedstocks, the observed moderate differences do have potential practical implications. Biochars with higher pH and higher ash or mineral content may be beneficial when applied to acidic soils, where they can increase soil pH, improve nutrient availability, and reduce aluminum toxicity [59,60]. On the other hand, biochars with slightly lower pH or lower ash content may be more appropriate for neutral soils, where excessive alkalinity may not be desirable [61]. Grapevine-pruning residues from cultivars with higher mineral content yield nutrient-rich, alkaline biochars, while lignin-rich cultivars produce more carbon-dense, stable biochars for carbon sequestration, highlighting the functional implications of varietal differences. These dual functions, nutrient supply and carbon stabilization, make grapevine-derived biochar a promising tool for sustainable viticulture and circular bioeconomy models [62,63,64].

5. Conclusions

This study demonstrated a significant influence of grapevine cultivar on the chemical composition of pruning residues and, consequently, the physicochemical quality of derived biochar. Variations in pH, EC, ash, and elemental composition among cultivars affected biochar yield and chemical composition. Residues with higher mineral content, such as Malvazija Istarska and Plavac mali, produced biochar with elevated alkalinity and nutrient concentrations. Conversely, carbon-dense cultivars yielded biochar with greater aromaticity and structural stability, indicating higher potential for long-term carbon sequestration. Spectroscopic and microscopic analyses confirmed significant chemical and structural transformations during pyrolysis, including increased aromatic condensation, reduced aliphatic functionality, and enhanced porosity, all of which improve stability, adsorption, and cation-exchange potential. Correlation analysis further indicated that certain elemental and physicochemical traits (e.g., total C, N, ash, Ca, K) are partially conserved from feedstock to biochar, suggesting that residue chemistry can serve as a predictor of biochar performance. The results are based on laboratory-scale analyses; therefore, cultivar-dependent differences in biochar properties are validated, whereas implications for soil performance, nutrient availability, and carbon sequestration remain potential, rather than experimentally confirmed. Key limitations include the absence of soil and plant-based experiments and evaluation under a single pyrolysis condition. Future work should focus on (i) soil incubation and field trials to validate biochar functionality, (ii) plant response and toxicity assessments, (iii) evaluation across different soil types, and (iv) techno-economic and life-cycle analyses to support large-scale application. By aligning feedstock selection with desired functionality (e.g., biochar with higher pH values to be applied on acid soils, or biochar containing significant amounts of some nutrients applied according to crop needs or on nutrient-poor soils), grapevine-derived biochar has the potential to support sustainable viticulture, soil restoration, and circular bio-economy strategies.