The Physiochemical Properties of Pellets Made from the Foliage of Vegetable Crops

Abstract

The increasing demand for renewable energy has driven interest in utilizing agricultural residues for bioenergy applications. This study investigates the pelletization of foliage from six vegetable crops, including tomato, eggplant, summer squash, cucumber corn, and soybean, to assess their potential as bioenergy feedstocks. The physiochemical properties of these biomasses, including particle size and shape, lignin, and elemental composition, were analyzed to determine their impact on pellet density and durability. The results reveal significant variations in pellet quality across different biomasses. Cucumber and summer squash demonstrated the highest pellet densities (1.48–1.51 g/cm³) and superior durability (98.1% and 94.2%, respectively), making them the most promising candidates for pelletization. In contrast, eggplant exhibited the lowest density (1.14 g/cm³) and durability (47.2%), indicating poor pellet quality. The correlation between pellet durability and pellet density was positive and modest at $r=0.647$. The study further highlights the impact of inorganic elements on pellet properties, where the high silica and chlorine content of cucumber, summer squash, tomato, and eggplant reduced energy efficiency and increased ash-related challenges. The resulting color parameters analysis (L*, a*, and b*) shows that the pellets from eggplant, tomato, summer squash, and cucumber foliage are darker than pellets from sawdust, corn stover, and soybean residues.

1. Introduction

The increasing global energy demand, coupled with environmental concerns, has intensified interest in renewable energy sources. Biomass diversification is a critical strategy for ensuring a sustainable and resilient bioeconomy [1]. Over-reliance on a single type of biomass, such as wood, can lead to resource depletion, environmental degradation, and supply chain vulnerabilities [2]. Residues from vegetable crops offer a complementary resource that can reduce pressure on forest resources and diversify feedstock options for bioenergy and biomaterials.

Agricultural waste biomass represents an abundant, underutilized, and valuable renewable resource that can address both energy needs and environmental challenges [3]. Economic benefits arise from converting biowaste into value-added products, creating opportunities for the farmers in rural regions to prosper [3,4]. However, challenges such as feedstock variability, transportation, and storage must be addressed to achieve widespread adoption of biofuel production from biowaste [5].

Biowaste pelletization is a potential solution for dealing with the logistics of biowaste handling. It involves compressing fine biomass particles under heat and pressure, forming compact, high-energy-density pellets [6,7,8]. Pelletized biomass can be used in residential heating, power plants, and industrial processes, replacing traditional fossil fuels [8]. However, the success of pelletization depends on the “pelletability” of the feedstock, a term that encompasses the ease of pellet formation and the quality of the resulting pellets.

The mechanical properties of pellets, including pellet density and durability, are key indicators of their quality. Pelletability is influenced by both the physical and chemical properties of the biomass, with key factors including particle size distribution, moisture content, lignin, and elemental composition [9,10,11]. Smaller particle sizes improve surface contact and inter-particle bonding, enhancing pellet strength, while excessive fineness can lead to die clogging [12]. An optimal moisture level (8–12%) is crucial, as too much moisture reduces pellet durability, whereas insufficient moisture results in brittle pellets [13]. Biomass with irregular particle shapes may result in uneven compression and reduced pellet quality [14]. Additionally, low-ash agricultural residues are preferable for energy applications, as high ash content can reduce combustion efficiency and create operational challenges in combustion systems [15].

Among chemical properties, lignin acts as a natural binder, softening under heat and pressure to improve pellet stability [11,16]. The elemental composition of the biomass, specifically carbon (C), hydrogen (H), and oxygen (O), impacts combustion efficiency, where higher C/O and H/C ratios increase calorific value [17]. The gross calorific value (GCV), representing the total energy released during combustion, is a critical measure for biomass energy potential, varying based on feedstock type, moisture, and elemental composition [18,19,20]. In general, higher carbon and lower moisture levels contribute to a greater GCV, optimizing biomass for bioenergy applications such as combustion, gasification, and pyrolysis [17,21].

A practical use of vegetable crop residues after a fruit harvest is converting them into bioenergy to supply heat for greenhouse operations. Pelletized biomass from vegetable crop residues can serve as a renewable energy source for greenhouse heating systems, contributing to circular energy practices by converting post-harvest waste into usable thermal energy. The latest research by Jadischke and Lubitz (2025) analyzed various potential options to deal with biowaste from vegetable production [4]. Recent advancements have highlighted the promising role of biomass-based heating systems in enhancing greenhouse sustainability, particularly through the valorization of agricultural residues. Faidallah et al. (2022) [22] demonstrated a biomass heating system using crop residues like okra and cotton stalks to maintain optimal thermal and humidity conditions in winter greenhouses. Their system not only increased productivity, yielding up to 27.6% more fresh weight in summer squash, but also integrated carbon sequestration via biochar, highlighting a dual function of energy production and soil enrichment [22]. Similarly, Huang et al. (2020) implemented a buried gas–soil heat exchanger fueled by biomass combustion, which effectively elevated greenhouse air and soil temperatures by over 5 °C and 8 °C, respectively, while maintaining economic feasibility for rural deployment [23].

Building on these practical outcomes, Perron (2023) evaluated a biomass polygeneration system in Québec, Canada, showing that coupling greenhouses with constant-output gasification units and thermal storage could recover nearly 50% of waste heat annually [24]. This approach significantly reduced the heating system’s required nominal power, reinforcing the potential for closed-loop energy systems. Complementing these efforts, Reinoso Moreno et al. (2019) optimized the processing of greenhouse crop residues in Spain, enhancing their fuel quality via drying, contamination reduction, and blending with almond shells [25]. This enabled their effective use in biomass boilers while simultaneously utilizing captured CO₂ for greenhouse enrichment, demonstrating a complete circular model for energy and carbon reuse [25].

Together, these works present a compelling body of evidence that vegetable plant residues can be transformed into valuable energy inputs when appropriate processing methods are applied. Although none of the studies focused specifically on pelletization, several addressed essential pre-treatment steps such as drying, ash reduction, and contamination removal, foundational to densification technologies. The present study builds on this foundation by exploring pelletization as a viable route to transforming greenhouse waste into high-quality, renewable fuel, thereby contributing to a more circular and sustainable greenhouse production system by enhancing the handling and storage properties of the greenhouse residues.

Despite significant progress in the study of the processibility and pelletization of various biomasses, data are not available on the pelletization of vegetable crop foliage, in particular cucumber, eggplant, summer squash, and tomato. Earlier research by Gholami B. et al. (2024) investigated the net specific grinding energy and physiochemical properties of ground biomass from corn, soybean, tomato, cucumber, eggplant, and summer squash [26]. Their results showed that samples like sawdust and corn stover with a high C/O ratio contained higher lignin content and required more energy for grinding. The lignin content varied from 5.6% for summer squash to 29.2% for sawdust. Similarly, the sawdust and summer squash exhibited the highest (77.3 kWh/t) and lowest (5.1 kWh/t) net specific grinding energy, respectively [26].

2. Objectives

This research aims to investigate the pelletization of the foliage of six different vegetable crops, including tomato, eggplant, cucumber, summer squash, corn, and soybean. It evaluates the density and durability of pellets produced from the foliage of these crops. It also investigates the influence of biomass properties, including particle morphology and physiochemical characteristics, on pellet formation and quality, using a single manual pellet press under controlled conditions to minimize equipment-related variability. Additionally, the study aims to assess the energy potential of the pelletized biomass by analyzing GCV and ash-related properties, thereby evaluating the suitability of these materials as renewable solid fuels for thermal energy applications. By evaluating key properties such as pellet density and durability, the study seeks to identify the most promising biomasses for bioenergy and biomaterial applications, supporting resource diversification and sustainable agricultural practices by valorizing biomass streams that have not previously been considered for pelletization at this level of detail.

3. Material and Methods

3.1. Sample Preparation

The seedlings of the horticultural crops, eggplant and tomato, were initially grown in a greenhouse for six weeks before being transplanted to the field. The cucumber and summer squash were directly seeded in the field. The agricultural crops, corn and soybean, was cultivated at the Lods Agronomy Research Centre. The cultivation of tomato, eggplant, cucumber, and summer squash was conducted at the horticultural centre, MacDonald Campus, McGill University, Canada. A sawdust sample of lodgepole pine and white spruce with a 50/50 split was supplied by Premium Pellet Co., Vanderhoof, BC, Canada, as a benchmark material for comparison. The foliage samples had 5–10% (wet basis) moisture content upon arrival. Samples were ground using a knife mill (Model SM100, Retsch Inc., Newtown, PA, USA) with a screen with 4 mm square perforations. After grinding, all samples were kept in air-tight bags to avoid moisture uptake.

The ash content of the ground samples was measured in four replications following the method described by Sluiter et al. (2008) [27]. It was determined as the percentage of residue remaining after dry oxidation at 550–600 °C in a furnace. The GCV was also measured in four replicates using an oxygen bomb calorimeter (Parr Model 6100, Parr Instrument Company, Moline, IL, USA) in accordance with ISO 18125:2017 [28], providing key data on energy content to evaluate the feasibility of each biomass type as a solid fuel. The extractives of ground material were measured on a dry basis using a Soxhlet unit [29]. The lignin content of the ground material was analyzed for insoluble (Klason) lignin contents [30]. All extractive and lignin measurements were repeated four times. The elemental analysis of the ground samples was measured via FISONS—EA 1108 (Thermo Fisher Scientific, Waltham, MA, USA) Elemental Analyzer in four replicates. The inorganic constituents of the biomass were analyzed using X-ray Fluorescence (XRF) spectroscopy, equipped with a thin-window Ag anode X-ray tube (Model Epsilon 1, Malvern PANalytical, Malvern, UK). Prior to analysis, the biomass samples were combusted in a muffle furnace at over 550–600 °C for 4 h, and the resulting ash residues were used for elemental determination. This process ensures that the measured values represent the inorganic mineral fraction of the biomass. Spectrum acquisition and evaluation were conducted using PANalytical software, capable of detecting and quantifying up to 70 elements. To ensure measurement reliability, each ash sample was analyzed in triplicate, and average values were reported.

The True Density (TD) of the biomass was measured using a gas pycnometer (Quantachrome Instruments, Boyton Beach, FL, USA; Model MVP-D160-E) with five replications to achieve reproducibility of the results. The Bulk Density (BD) of the ground biomass was determined by the mass of the biomass in a container with inner dimensions of 100 × 100 × 100 mm. The particle size distribution was measured by sieving in accordance with the ANSI/ASAE standard S319.4 [31] using a Ro-Tap shaker (Tyler Industrial Products, Cleveland, OH, USA) in four replications. The shape factors of the particles were determined through image processing using the open-source software ImageJ (Version 1.53 K, National Institutes of Health, Bethesda, MD, USA) on over 1000 random particles to obtain width (W), length (L), area (A), and perimeter (P). The aspect ratio and equivalent particle diameter of the biomass particles were calculated using classical geometric Equations (1) and (2) [32,33,34].

$$AR={\displaystyle \frac{W}{L}}$$

(1)

$$D_{eq}=\sqrt{{\displaystyle \frac{4A}{\pi }}}$$

(2)

where AR is the aspect ratio (dimensionless), W is the maximum width, and L is the maximum length of each particle. Also, A is the projected two-dimensional area of the particle yielding an equivalent diameter ($D_{eq}$) in units of length.

3.2. Pelletization

The pelletization procedure of biomass was done according to Yu et al., 2021 [35]. To understand the effect of the physiochemical properties of the biomasses on pelletization, all process control parameters, including die size, pressure, die temperature, and retention time, were set constantly to their optimum value based on the literature review. The moisture content of samples was adjusted to 12% (±0.5) by spraying water on the samples. Following the moisture adjustment, a lab mixer was used to condition the biomass for 60 min, ensuring homogeneous moisture distribution. A cylinder die unit with a 6.35 mm internal diameter and 90 mm length was filled with the ground sample. The die was heated to 120 °C using a heating element controlled by a temperature controller. The material was compressed using a plunger with a diameter slightly less than the diameter of the die (Figure 1). The maximum applied pressure was 10 kN. After 5 min of retention time, the pellet was pushed out of the die. Approximately 0.6–0.7 g of biomass was used for each pellet. Ten pellets were made from each sample and, after cooling down, were stored in sealed glass bottles for further analysis.

3.3. Pellet Density

The mass, length, and diameter of each pellet were measured immediately after extrusion using a digital caliper with two decimal places to calculate the pellet density (PDe) by dividing pellet mass by pellet volume.

3.4. Pellet Durability

The pellet durability (PDu) was measured by using a single-pellet durability analyzer designed and built in-house [36]. The device consisted of a small, square box, 60 × 60 × 60 mm, with a removable lid (Figure 2). The box was attached to the arm of a laboratory shaker (Burrell Scientific Wrist Action—Model 75 Shaker, Burrell Scientific, Zelienople, PA, USA). The process involves weighing a pellet, placing the single pellet along with a metal pellet of 6 mm diameter and 12 mm length in the cavity, covering the box with its lid, securing the top, and shaking the box for 10 min. Upon completion of the shaking, all its contents are sieved through a 3.15 mm screen to separate the broken particles that were generated during the shaking process. The single-pellet durability is calculated by Equation (3).

$$Du\left(\%\right)={\displaystyle \frac{m_a}{m_b}}\times 100$$

(3)

where m_a is the mass of pellets retained on top of the sieve and m_b is the original mass of the pellets before shaking.

3.5. Color Measurement

The color parameters of the pellets were measured using a Konica Minolta CM-5 spectrophotometer (Konica Minolta, Tokyo, Japan) that operates in reflectance mode. The instrument was calibrated with a standard white calibration plate before each measurement to ensure accuracy. The color of the samples was evaluated based on the CIE Lab (CIELAB) color space, where L* represents the lightness (0 = black, 100 = white), a* denotes the red–green axis (positive values indicate red, negative values indicate green), and b* corresponds to the yellow–blue axis (positive values indicate yellow, negative values indicate blue) [37]. Each sample was measured in five replications to account for variability, and the average values of L*, a*, and b* were recorded for further analysis. The measurements were conducted under standard D65 illumination with a 10° observer angle, following industry-standard procedures for color evaluation. The color parameters were combined to form a color change index $∆E$ for each biomass using Equation (4) [37]. ${∆E}_i$ quantify the color variation between the ground biomass and the corresponding pellet, indicating the extent of thermal and mechanical transformation during the single-pellet production process.

$${∆E}_i=\sqrt{{\left(a_i-a_0\right)}^2+{\left(b_i-b_0\right)}^2+{\left(L_i-L_0\right)}^2}$$

(4)

where subscript i denotes the biomass color index and subscript 0 denotes the pellet color index.

4. Results and Discussion

4.1. Pellet Characterization

The pelletized forms of various biomasses using the manual pellet press are shown in Figure 3. The picture shows variations in the visual appearance of the pellets. These differences imply that biomass composition may be responsible for the visual appearance of each pellet. This section discusses the implications of these findings, analyzing the relationship between biomass characteristics and pellet durability.

4.2. Color Index Parameters

The results of the mean comparison analysis of the color index of the pellets are summarized in

Table 1. The mean comparison analysis of color index of various pellets made from crops foliage.

Pellets	Color Parameters (-)
	L*	a*	b*	${∆\mathit{E}}_{\mathit{i}}$
Sawdust	61.71 e	5.93 f	22.13 e	13.1 a
Soybean	52.92 d	4.48 e	18.82 d	13.1 a
Corn stover	49.69 c	4.51 e	18.23 d	12.5 b
Eggplant	40.67 b	2.44 c	15.36 c	18.7 c
Tomato vine	40.94 b	0.35 a	16.15 c	20.4 d
Summer squash	36.28 a	0.83 b	14.18 b	18.0 c
Cucumber	36.55 a	3.01 d	10.41 a	20.2 d
Pr > F (Model)	<0.0001	<0.0001	<0.0001	<0.0001
Significant	Yes	Yes	Yes	Yes

Note: Values followed by different letters (a to f) within a column show significant differences in each parameter among various samples (p < 0.05) based on a least-squares means comparisons using Tukey’s HSD test.

. The color parameters (L*, a*, b*, ${∆E}_i$) of different pellet samples showed significant variation (p < 0.0001) based on the least-squares mean comparison method. Sawdust pellets exhibited the highest lightness (L* = 61.71), strongest red component (a* = 5.93), and most yellow hue (b* = 22.13), making them the brightest and most yellowish among all samples. In contrast, the cucumber (L* = 36.55) and summer squash (L* = 36.28) pellets had the lowest lightness values, indicating that they were the darkest. The a* values revealed that tomato vine (a* = 0.35) and summer squash (a* = 0.83) pellets had the lowest red intensity, suggesting a greener appearance, while sawdust had the most reddish hue. Similarly, b* values indicated that cucumber (b* = 10.41) had the least yellow component, appearing more bluish, whereas sawdust exhibited the strongest yellow coloration.

The ${∆E}_i$ values, which show color change during pelletization, varied significantly among biomass samples, with tomato vine (20.4) and cucumber (20.2) exhibiting the highest color changes, followed by eggplant (18.7) and summer squash (18.0). Sawdust (13.1) and soybean (13.1) had moderate color changes, while corn stover (12.5) showed the least color variation.

The observed color changes in the biomasses post-pelletization are primarily due to the thermal degradation of hemicellulose and cellulose, leading to browning, and the softening and oxidation of lignin, resulting in darker shades. Studies have shown that hemicellulose decomposes at lower temperatures compared to cellulose and lignin, contributing to early stage browning during thermal treatment [38,39]. Additionally, the oxidation of lignin has been associated with the development of brownish hues in wood residues [38,39]. These findings, which are consistent with the visual appearance of the pellets, highlight the significant impact of different biomass compositions on pellet color, which can influence their aesthetic and commercial properties in applications such as biofuel production.

4.3. Inorganic Elements

The XRF analysis was conducted on the residual ash of the pellets after combustion at 550–600 °C to trace the presence of inorganic elements. This analysis provides valuable insights into the differences in the physicochemical properties of the biomass and helps to better understand the visual appearance and composition of the resulting pellets. The summarized results of the XRF analysis are presented in

Table 2. Inorganic elemental composition (ppm) of various ground biomasses based on XRF and their correlation with the color parameters of the pellets.

Inorganic Elements	Ground Foliage Samples							Correlations With
	Corn	Soybean	Tomato	Eggplant	Cucumber	Summer Squash	Sawdust	L*	a*	b*
Si	9237 d	3861 c	806 ab	1138 b	17,526 e	18,116 e	230 a	−0.424	−0.357	−0.602
P	1233 b	1279 b	2799 d	2383 c	5255 e	5430 f	928 a	−0.743	−0.744	−0.821
S	422 b	372 b	5709 e	1771 c	1785 c	2208 d	51 a	−0.592	−0.857	−0.435
Cl	2999 e	303 b	3102 f	2156 d	2087 c	10,850 g	70 a	−0.610	−0.659	−0.815
K	11,065 b	12,386 c	15,188 d	23,542 f	24,190 g	16,948 e	569 a	−0.894	−0.618	−0.748
Ca	3930 b	11,263 c	38,473 f	23,095 d	32,636 e	56,363 g	1395 a	−0.811	−0.921	−0.874
Fe	346 cd	428 d	148 ab	246 bc	2146 f	1957 e	71 a	−0.497	−0.447	−0.654
Cu	31 e	34 f	22 d	15 a	20 c	17 b	30 e	0.861	0.694	0.787
Zn	5 a	7 b	40 f	24 c	36 e	30 d	5 a	−0.804	−0.912	−0.688
Mn	23 a	22 a	40 b	19 a	64 c	70 d	68 cd	0.052	−0.173	−0.145
Ti	37 d	65 e	18 b	28 c	311 g	222 f	8 a	−0.454	−0.397	−0.574

Note I: Values followed by different letters (a to g) within a row show significant differences for each element among various samples (p < 0.05) based on least-squares means comparisons using Tukey’s HSD test. Note II: Values in bold show significant correlation by Pearson method at p = 0.05.

.

The XRF analysis reveals that summer squash, cucumber, tomato vine, and eggplant contain high concentrations of inorganic elements such as Si, P, Cl, K, Ca, and Fe. The variability in inorganic elements among biomass samples significantly influences ash content and energy content, affecting their combustion performance [40,41]. High silica (Si) content, observed in summer squash (18,116 ppm) and cucumber (17,526 ppm), contributes to higher ash formation, leading to increased slagging and fouling in boilers [42]. Similarly, high chlorine (Cl) levels, particularly in summer squash (10,850 ppm) and tomato vine (3102 ppm), accelerate ash corrosion and slag buildup, reducing combustion efficiency [42]. Sulfur (S), present in higher amounts in tomato vine (5709 ppm) and summer squash (2208 ppm), also increases ash formation and potential SO₂ emissions, which can affect air quality and boiler lifespan [43,44]. While zinc (Zn) and copper (Cu) are found in lower concentrations, they still contribute to chemical reactions within the ash, influencing its composition and reactivity.

This high inorganic mineral content in summer squash, cucumber, tomato vine, and eggplant correlates with their higher ash content and lower GCV, making them less suitable for combustion due to increased slagging and fouling risks. While silicon does not directly cause soot formation, its presence—especially in high concentrations with elements like potassium and calcium—promotes the formation of low-melting-point ash compounds that contribute to slagging and fouling in exhaust systems. These deposits can restrict airflow and indirectly facilitate conditions conducive to soot buildup. These findings are consistent with previous research, reinforcing the idea that biomasses with high ash content tend to have lower energy efficiency [15,45,46]. However, their rich inorganic composition makes them promising candidates for alternative applications, such as absorbents in filtration or environmental remediation [47,48,49,50].

Regarding energy content, biomasses with higher Si and Cl levels, such as summer squash, corn stover, and tomato vine, generally exhibit lower GCV due to increased non-combustible residues. In contrast, biomasses with lower inorganic content, such as sawdust (230 ppm Si, 70 ppm Cl), retain higher energy content, as they generate less ash and experience fewer slagging and corrosion issues during combustion, making them more suitable for combustion and energy production [51]. According to iso 17225-6 standards [52], controlling Si, Cl, and S levels is crucial to optimizing fuel quality, ensuring efficient energy production and minimizing operational challenges in combustion systems.

4.4. Effect of Inorganic Elements of Biomass on Pellet Color Index

The results of the correlation test of the inorganic elements in the biomasses with the color index of the pellets are also presented in Table 2. The color parameters L*, a*, and b* of pellets are significantly influenced by the inorganic elemental composition of the biomasses, particularly Ca, S, P, Cl, K, Cu, and Zn, as measured by XRF. The correlation analysis indicates that higher concentrations of these elements generally reduce L*, a*, and b*, making the pellets appear darker, greener, and less yellow [53,54]. Calcium (Ca), potassium (K), and zinc (Zn) exhibit strong negative correlations with L*, suggesting that higher concentrations of these minerals increase light absorption and reduce reflectance, leading to a darker biomass appearance [53]. This finding is visually supported by the color variations observed in cucumber, summer squash, and eggplant pellets, confirming the relationship between the measured properties and their physical appearance.

Similarly, sulfur (S), calcium (Ca), and zinc (Zn) exhibit negative correlations with a*, meaning their presence shifts the biomass color toward greener shades, likely due to their involvement in chemical reactions that affect pigmentation [55]. The green color of the tomato vine pellets can be attributed to the presence of sulfur, calcium, and zinc.

Calcium (Ca), phosphorus (P), and chlorine (Cl) also negatively correlate with b*, meaning that increased concentrations of these elements make the biomass appear less yellow (more bluish). In contrast, copper (Cu) shows a positive correlation with L*, indicating that higher Cu content may contribute to a brighter biomass appearance, potentially due to its interaction with organic components. This relationship highlights the importance of elemental composition in influencing the visual characteristics of the biomass, which could have implications for quality assessment and processing in biomass applications.

Elements like Si, Fe, Mn, and Ti had minimal influence on the color parameters (L*, a*, b*) of the pellets, as indicated by their weak correlations. Silicon (Si), despite its high presence in some biomasses such as cucumber (17,526 ppm) and summer squash (18,116 ppm), did not significantly alter pellet color, likely due to its inorganic nature. Iron (Fe), although associated with pigmentation in some materials, was present in relatively low amounts and showed only weak effects. Manganese (Mn) and titanium (Ti) also had negligible impacts, as their concentrations were low and their correlations with color parameters were minimal. These findings suggest that Si, Fe, Mn, and Ti do not contribute significantly to pellet color changes, whereas elements such as P, S, Cl, K, Ca, Zn, and Cu play a more dominant role in influencing color variations during thermal processing.

While pellet color does not directly affect combustion heat, it reflects thermal and chemical changes in the biomass during pelletization and is significantly correlated with compositional variables such as inorganic mineral content and ash formation potential. This makes it a valuable indicator for quality monitoring and process diagnostics.

4.5. Pellet Density and Pellet Durability

Pellet density is a crucial factor affecting the storage efficiency and energy content of biomass pellets [56]. The analysis of single-pellet density and durability across different biomass sources reveals notable trends and potential applications, highlighting significant differences in their properties (

Table 3. Pellet density, durability, and the major compositional properties of the tested biomass dried foliage.

Properties	Ground Foliage Samples							Correlations With
	Corn	Soybean	Tomato	Eggplant	Cucumber	Summer Squash	Sawdust	Pellet Density (g/cm3)	Pellet Durability (%)
Pellet Density (g/cm3)	1.19 b	1.24 c	1.32 d	1.14 a	1.48 e	1.51 f	1.22 c	1	0.647
Pellet Durability (%)	92.3 d	77.2 b	97.0 ef	47.2 a	98.1 f	94.2 de	87.2 c	0.647	1
Extractive (%, db)	5.67 c	1.49 a	4.79 b	4.36 b	1.82 a	1.70 a	2.17 a	−0.508	−0.135
Lignin (%, db)	18.53 f	15.42 d	16.20 e	12.36 c	9.38 b	5.61 a	29.17 g	−0.621	−0.011
GCV (MJ/kg, db)	17.2 cd	17.5 d	14.8 b	16.7 c	14.3 b	13.6 a	21.0 e	−0.707	−0.275
Ash (%)	5.5 b	6.8 c	18.3 e	14.5 d	25.3 f	33.6 g	0.3 a	0.833	0.253
C/O ratio (-)	0.953 b	0.964 b	0.795 d	0.836 c	0.640 e	0.455 f	1.158 a	−0.805	−0.237
TD (g/cm3)	1.239 e	1.398 d	1.424 b	1.242 e	1.412 c	1.489 a	1.395 d	0.783	0.582
BD (kg/m3)	107.7 a	200.2 d	259.9 e	196.4 c	259.5 e	289.0 f	186.9 b	0.790	0.265
D50 (mm)	0.71 b	0.67 c	0.61 d	0.69 b	0.65 c	0.59 e	0.85 a	−0.559	−0.190
AR (-)	0.32 a	0.37 a	0.39 a	0.45 a	0.32 a	0.40 a	0.33 a	−0.018	−0.150
Deq (mm)	1.92 ab	1.90 ab	1.25 a	1.22 a	1.87 ab	2.09 ab	2.60 a	−0.113	−0.186

Note I: Values followed by different letters (a to g) within a row show significant differences in each parameter among various samples at (p < 0.05) based on least-squares means comparisons using Tukey’s HSD test. Note II: Values in bold show significant correlation by the Pearson method at p = 0.05.

). Pellet densities range from 1.14 g/cm³ (eggplant) to 1.51 g/cm³ (summer squash), and durability values range from 47.2% (eggplant) to 98.1% (cucumber). Cucumber and summer squash stand out as the best biomass candidates for pelletization, exhibiting both high density (1.48 g/cm³ and 1.51 g/cm³, respectively) and strong durability (98.1% and 94.2%). Conversely, eggplant proves to be the weakest option, with the lowest density (1.14 g/cm³) and the lowest durability (47.2%), indicating poor pellet quality. Mean comparison analysis of the parameters shows that eggplant and summer squash are significantly distinct in their density and durability values. A notable trend is observed where pellets with higher density, such as cucumber and summer squash, tend to have greater pellet durability, while eggplant, which has the lowest density, also exhibits the weakest durability [16,57]. While the eggplant biomass exhibited poor pellet characteristics under standardized conditions, its performance may be significantly improved through the optimization of pelletization parameters, a direction recommended for future studies.

The analysis of various biomass sources reveals that the C/O ratio, true density, and bulk density have the most significant impact on pellet density. A strong correlation ($r=-0.805$) was observed between the C/O ratio and pellet density, indicating that biomasses with higher carbon-to-oxygen ratios or higher lignin content, such as sawdust and corn stover, exhibit lower pellet densities. This could be attributed to a higher lignin content in these biomasses, which reduces their compaction efficiency. Interestingly, this finding contradicts other researchers’ results, as several researchers have claimed that lignin acts as a natural binder and can enhance pellet quality [11,16]. While lignin contributes to pellet strength, its effect on compaction efficiency is not straightforward. The elastic nature of certain biomass materials, influenced by their lignin content and other structural components, can affect their behavior during densification, potentially impacting compaction efficiency [16].

On the other hand, true density ($r=0.783$) and bulk density ($r=0.790$) were positively correlated with pellet density, showing that denser raw biomasses such as summer squash, tomato vine, and cucumber tend to form denser pellets [58,59]. This trend confirms that higher-density biomass materials allow for better compaction and reduced void spaces, improving pellet quality.

While certain factors significantly influence pellet density, some parameters exhibit moderate correlations, indicating a minor effect on pellet compaction performance. Lignin ($r=-0.621$) and extractives ($r=-0.508$) show moderate correlations, suggesting that higher concentrations of these components slightly reduce pellet density. This could be due to lignin’s elasticity and extractives interfering with biomass compaction, limiting density increase [60]. It is true that lignin acts as a natural adhesive in biomass, enhancing pellet durability by binding particles together. However, its impact on pellet density is inconsistent. Some studies report that while lignin improves durability, it does not significantly affect bulk density [61]. Additionally, D50 (median particle size) displayed a correlation ($r=-0.559$) with pellet density, reinforcing that smaller biomass particles enhance densification by improving packing efficiency and reducing void spaces [12,62]. Although these factors contribute to variations in pellet density, they do not have as strong of an impact as true density, bulk density, and the C/O ratio.

Pellet durability, a key indicator of pellet strength and resistance to mechanical degradation, is positively correlated with true density (r = 0.582), confirming that biomasses with higher intrinsic density, such as cucumber and summer squash, tend to produce more durable pellets [16,57]. However, the weak correlations among C/O ratio ($r=-0.237$), lignin ($r=-0.011$), and extractives ($r=-0.135$) with pellet durability indicate that these compositional properties do not significantly contribute to durability differences among samples. Instead, durability may be more influenced by processing conditions such as force, temperature, retention time, moisture content, and binder additions rather than inherent biomass characteristics.

The correlation analysis of pellet durability presents some ambiguities. Interestingly, several parameters, including aspect ratio (AR) and equivalent diameter (D_eq), did not show significant correlations with either pellet density or durability. The weak correlation of AR ($r=-0.018$) and D_eq ($r=-0.113$) with pellet density, as well as their negligible effect on durability, suggests that particle shape plays a minimal role in determining pellet characteristics. This finding contrasts with some studies that suggest elongated particles may hinder compaction efficiency; however, in this case, biomass composition and particle size appear to have a greater influence than particle shape [34,63]. The weak relationships observed in these parameters highlight the complexity of pellet formation, that multiple interacting factors beyond simple compositional analysis influence pellet quality.

In summary, the C/O ratio, true density, and bulk density play the most significant roles in determining pellet density, while lignin, extractives, and D50 particle size have a moderate impact. Pellet durability is primarily associated with true density, but other factors, such as processing conditions, likely play a dominant role. Meanwhile, particle shape parameters, such as aspect ratio and equivalent diameter, exhibit no significant influence on pellet density or durability, suggesting that biomass composition and processing techniques are more critical in optimizing pellet quality.

5. Conclusions

This study explored the pelletization performance of six vegetable crops’ foliage, emphasizing the influence of the physiochemical properties of the biomass on pellet density and durability through a controlled pelletization process. The findings provide valuable insights into optimizing biomass selection for bioenergy applications, supporting sustainable agricultural waste valorization and diversification of feedstock resources.

The findings are summarized as follows:

• As confirmed in our findings, denser raw biomass samples generally yield denser pellets, consistent with prior studies. However, this trend is quantitatively validated here for previously uncharacterized greenhouse crop residues.
• We found that under standardized pelletization conditions, factors such as particle shape and elemental composition had minimal correlation with pellet durability, suggesting that processing conditions may play a stronger role—especially for high-moisture, low-lignin foliage materials.
• Pellet density and pellet durability exhibited a positive correlation (0.647), indicating that higher-density biomass materials generally produced more durable pellets, whereas lower-density biomasses resulted in weaker pellet structures.
• Higher concentrations of inorganic elements in the biomass samples, such as summer squash, cucumber, tomato vine, and eggplant, but particularly silica, chlorine, and sulfur, led to increased ash formation and reduced gross calorific value, negatively impacting the combustion efficiency of the biomass pellets.
• The color parameters were strongly correlated with physicochemical properties, reinforcing that the color index can serve as an indicator of pellet quality, energy content, and combustion characteristics. Inorganic elements such as calcium (Ca), phosphorus (P), and potassium (K) exhibited strong negative correlations with brightness L*, indicating that higher mineral content leads to darker pellets. Also, higher lignin, GCV, and C/O ratio levels in sawdust samples were associated with higher L* values (brighter pellets), while higher ash content (cucumber and summer squash) led to lower L* values (darker pellets).

The findings of this study demonstrate that pellets made from vegetable foliage—particularly cucumber, tomato, and summer squash—possess modest calorific value and acceptable mechanical integrity, positioning them as promising alternative solid biofuels. Despite challenges related to ash content, these residues represent an underutilized biomass resource suitable for localized, small-scale thermal energy applications, such as greenhouse boiler systems and on-site heating solutions. Given that greenhouse operations in Canada alone generate thousands of tonnes of foliage waste annually, with an average gross calorific value of approximately 14 MJ/kg, the utilization of this biomass could substantially reduce dependence on fossil fuels in greenhouse heating systems.