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Energies 18 (9): 2284 (2025)
Gholami Banadkoki, Omid
Sokhansanj, Shahab
Lau, Anthony
Agricultural residues serve as a vast yet underutilized biomass resource with significant potential for bioenergy and biomaterial applications. Converting these residues into densified biomass pellets enhances energy density, handling efficiency, and transportability, offering a sustainable alternative to conventional feedstocks. While extensive research has focused on woody biomass, studies on the pelletization of vegetable crop foliage remain limited. This study examines the pelletability of foliage from corn, soybean, tomato, eggplant, cucumber, and summer squash, assessing their physical properties, bulk durability, bulk density, and energy consumption during pelletization. Results demonstrated that variation in biomass composition significantly influences pellet quality, with lignin content improving durability and ash content affecting moisture uptake and combustion properties. Cucumber had the highest pellet density (691.2 kg/m³) and durability (97.9%), making it suitable for long-term storage and transport. Sawdust exhibited the lowest moisture absorption (16–18% db), which is attributed to its highest lignin content. Pelletization energy requirements varied significantly, with cucumber (21.8 kWh/t) and summer squash (18.7 kWh/t) requiring the lowest energy input, whereas soybean (49.6 kWh/t) and sawdust (47.3 kWh/t) exhibited the highest energy demands due to greater resistance to densification. A predictive model was developed to correlate single pellet density and durability with bulk pellet properties—yielding high predictive accuracy, with R² = 0.936 for bulk density (BDe) and R² = 0.861 for bulk durability (BDu)—thereby facilitating process optimization for large-scale pellet production. This study demonstrated that foliage residues from greenhouse crops, such as cucumber and summer squash, can be effectively pelletized with low energy input and high physical integrity. These outcomes suggest that such underutilized agricultural residues hold promise as a densified intermediate feedstock, supporting future applications in bioenergy systems and advancing circular resource use in controlled-environment agriculture.
Academic Editors: Carmen OtiliaRusaˇnescu and Nicoleta UngureanuReceived: 24 March 2025Revised: 18 April 2025Accepted: 25 April 2025Published: 29 April 2025Citation: Gholami Banadkoki, O.;Sokhansanj, S.; Lau, A. Analysis of thePelletability of Vegetable Crop FoliageUsing a Commercial Flat Die PelletMill. Energies 2025, 18, 2284. https://doi.org/10.3390/en18092284Copyright: © 2025 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license(https://creativecommons.org/licenses/by/4.0/).ArticleAnalysis of the Pelletability of Vegetable Crop Foliage Usinga Commercial Flat Die Pellet MillOmid Gholami Banadkoki 1,2,* , Shahab Sokhansanj 1,2,3 and Anthony Lau 1,21 Biomass and Bioenergy Research Group (BBRG), University of British Columbia, Vancouver, BC V6T 1Z3,Canada; shahab.sokhansanj@ubc.ca (S.S.)2 Chemical and Biological Engineering Department, Faculty of Applied Science, University of British Columbia,Vancouver, BC V6T 1Z3, Canada3 Department of Chemical and Biological Engineering, University of Saskatchewan,Saskatoon, SK S7N 5A9, Canada* Correspondence: omid1370@mail.ubc.caAbstract: Agricultural residues serve as a vast yet underutilized biomass resource withsignificant potential for bioenergy and biomaterial applications. Converting these residuesinto densified biomass pellets enhances energy density, handling efficiency, and trans-portability, offering a sustainable alternative to conventional feedstocks. While extensiveresearch has focused on woody biomass, studies on the pelletization of vegetable cropfoliage remain limited. This study examines the pelletability of foliage from corn, soybean,tomato, eggplant, cucumber, and summer squash, assessing their physical properties, bulkdurability, bulk density, and energy consumption during pelletization. Results demon-strated that variation in biomass composition significantly influences pellet quality, withlignin content improving durability and ash content affecting moisture uptake and com-bustion properties. Cucumber had the highest pellet density (691.2 kg/m3) and durability(97.9%), making it suitable for long-term storage and transport. Sawdust exhibited thelowest moisture absorption (16–18% db), which is attributed to its highest lignin con-tent. Pelletization energy requirements varied significantly, with cucumber (21.8 kWh/t)and summer squash (18.7 kWh/t) requiring the lowest energy input, whereas soybean(49.6 kWh/t) and sawdust (47.3 kWh/t) exhibited the highest energy demands due togreater resistance to densification. A predictive model was developed to correlate singlepellet density and durability with bulk pellet properties—yielding high predictive accuracy,with R2 = 0.936 for bulk density (BDe) and R2 = 0.861 for bulk durability (BDu)—therebyfacilitating process optimization for large-scale pellet production. This study demonstratedthat foliage residues from greenhouse crops, such as cucumber and summer squash, can beeffectively pelletized with low energy input and high physical integrity. These outcomessuggest that such underutilized agricultural residues hold promise as a densified inter-mediate feedstock, supporting future applications in bioenergy systems and advancingcircular resource use in controlled-environment agriculture.Keywords: agricultural biomass; batch pellet production; bulk durability; pelletability;physiochemical properties; scale up1. IntroductionBiomass utilization for energy production has gained significant traction in recentdecades as a sustainable alternative to fossil fuels. With the increasing demand for re-newable energy sources, agricultural residues are being explored as potential feedstocksEnergies 2025, 18, 2284 https://doi.org/10.3390/en18092284Energies 2025, 18, 2284 2 of 22for pelletization due to their abundance and lower cost compared to traditional woodybiomass. Agricultural residues such as corn, soybean, and tomato often go unutilized,leading to environmental concerns such as air pollution from open-field burning [1] andmethane emissions from decomposition [2]. Pelletization transforms these residues intoa high-density, energy-efficient form suitable for combustion and bioenergy applications,contributing to waste valorization and a circular bioeconomy [3–5].Pelletization is a widely adopted technique that enhances the physical propertiesof biomass by increasing its density, improving its transportability, and optimizing itscombustion characteristics [6–8]. This process involves compressing biomass under heatand pressure to produce uniform cylindrical pellets with improved energy content andmechanical properties. Key factors influencing pelletization include moisture content,particle size, chemical composition, and process parameters, such as die pressure andretention time [9–11]. While extensive studies have been conducted on woody biomasspelletization [12–15], limited research exists on the properties of agricultural residues andtheir behavior during the densification process on a large scale.The majority of biomass pelletization research has focused on single-pellet exper-iments, which provide insights into fundamental densification mechanisms. However,batch-scale studies are essential for bridging the gap between laboratory research andindustrial applications. Batch processes introduce additional variables such as feed ratefluctuations [16], power consumption, and operational efficiency, which significantly im-pact pellet quality and energy requirements. Understanding these parameters is crucial foroptimizing large-scale pellet production and ensuring consistency in pellet characteristics.Several factors influence the quality of pellets produced in batch-scale processes. Themoisture content of the biomass plays a critical role, as an optimal moisture level (typically8–12%) enhances bonding and reduces friction in the pellet mill [17–19]. Additionally, thechemical composition of biomass, particularly its lignin, cellulose, and hemicellulose con-tent, affects pellet durability and combustion efficiency. Lignin, a natural binder, enhancespellet mechanical strength when exposed to heat [11,15], while excessive ash content canlower combustion efficiency and increase emissions [20].Particle size and shape also have a significant impact on pelletization efficiency andfinal pellet quality. Smaller particles provide a greater surface area for bonding, improvingpellet density and mechanical strength [21,22]. However, excessive fines can lead to dieclogging and increased energy consumption during pelletization. Studies have shownthat an optimal aspect ratio and circularity contribute to improved pellet integrity anddurability [21,23].Energy efficiency is a critical consideration in large-scale pellet production. Pellet millsrequire substantial energy input for compression, and understanding energy consumptionpatterns is essential for process optimization. The net energy required for pelletization isdetermined by measuring the total energy input during pellet production and subtractingthe no-load energy consumption of the mill [24]. By analyzing the specific energy consump-tion per ton of pellets produced, researchers can develop strategies to enhance processefficiency and reduce operational costs.Over-reliance on a single biomass feedstock, such as wood, poses sustainability risksand supply chain challenges [25,26]. Diversifying biomass sources to include agricul-tural residues promotes environmental conservation, enhances feedstock availability, andsupports rural economies [19,27]. By investigating the pelletization potential of variousvegetable crop residues, this study aims to expand the range of viable feedstocks for bioen-ergy production. In particular, greenhouse crops such as tomato, cucumber, eggplant, andsummer squash are cultivated extensively in Canadian greenhouses [28], which generatesEnergies 2025, 18, 2284 3 of 22substantial yet underutilized post-harvest foliage [29]. These materials offer significantbioenergy potential, particularly for localized use in greenhouse heating systems.Recent studies have increasingly validated the practical application of greenhousecrop residues as a sustainable energy source for farm and greenhouse operations. Jadischkeand Lubitz (2025) evaluated several strategies for managing vegetable production waste,reinforcing the value of biomass conversion [30]. Faidallah et al. (2022) demonstrated thatusing okra and cotton stalks in a biomass heating system not only maintained optimalgreenhouse conditions but also enhanced crop yield and enabled biochar-based carbonsequestration [31]. Huang et al. (2020) showed that a biomass-fueled gas–soil heat ex-changer effectively increased greenhouse air and soil temperatures, proving both effectiveand economically viable [32]. Perron (2023) further advanced this concept by evaluatinga biomass polygeneration system in Québec, which recovered nearly 50% of waste heatannually, emphasizing energy efficiency through thermal storage [33]. Finally, ReinosoMoreno et al. (2019) enhanced the fuel quality of greenhouse residues in Spain throughdrying, contamination control, and blending, enabling their efficient use in biomass boilersand contributing to a closed-loop system by recycling CO2 for greenhouse enrichment [34].Together, these studies confirm the viability and sustainability of converting greenhouseresidues into renewable thermal energy.2. ObjectivesDespite advancements in biomass pelletization research, significant knowledge gapsremain regarding the densification of agricultural residues in batch scale. Existing studiespredominantly focus on woody biomass, leaving the unique characteristics of agriculturalresidues underexplored. Moreover, the relationship between single and batch-scale pel-letization properties remains unclear, hindering industrial-scale adoption. This researchseeks to comprehensively analyze the pelletization properties of vegetable crop residues,including tomato, eggplant, cucumber, summer squash, corn, and soybean, under a con-trolled condition batch process, evaluate the factors influencing pellet quality and energyconsumption, and develop predictive models for optimizing the pelletization process.By evaluating the pelletization potential of vegetable crop residues, this study addressesenvironmental challenges by promoting sustainable waste management and renewableenergy generation. Through the conversion of biomass into high-density pellets, it enhancesresource circularity and supports the advancement of bioenergy technologies, contributingto the broader goal of sustainable agricultural waste utilization.3. Material and Methods3.1. Sample Preparation and Infeed Material CharacterizationThe horticultural crops eggplant and tomato were initially grown as seedlings in agreenhouse for six weeks before being transplanted to the field. Cucumber and summersquash, on the other hand, were directly seeded in the field. The agricultural crops corn andsoybean were cultivated at the Lods Agronomy Research Centre, while tomato, eggplant,cucumber, and summer squash were grown at the Horticultural Centre on the MacdonaldCampus of McGill University, Canada. Corn and soybean were included as conventionalopen-field crops that are extensively cultivated and well-documented in biomass research,thus serving as agricultural benchmarks for comparison. Additionally, a sawdust sampleconsisting of a 50/50 blend of lodgepole pine and white spruce was obtained from PremiumPellet Co., British Columbia, to serve as a commercial reference material for comparativeanalysis. This selection of biomasses also aligns with the previous study by Gholami B.et al., 2025, which examined the single pellet densification of these same feedstocks [35].This study scales up to a batch pelletization, addressing applied challenges in large-scaleEnergies 2025, 18, 2284 4 of 22biomass utilization. The foliage samples contained a moisture content of approximately5–10% (wet basis) upon arrival. Prior to further processing, all samples were groundusing a knife mill (Model SM100, Retsch Inc., Newtown, PA, USA) fitted with a 4 mmperforated screen. The ground samples were then stored in air-tight containers to preventmoisture absorption.Ash content was determined following the procedure outlined by Sluiter et al.(2008) [36]. The analysis was performed in quadruplicate by subjecting the ground samplesto dry oxidation at 550–600 ◦C in a muffle furnace. The residual mass post-combustion wasrecorded as the ash content and expressed as a percentage of the initial biomass weight [36].The energy content of the biomass was evaluated by measuring the Gross Calorific Value(GCV) using an oxygen bomb calorimeter (Model 6100, Parr Instrument Company, Moline,IL, USA), following the ASTM standard D-2015. Each measurement was conducted in fourreplicates to ensure accuracy and reproducibility. Extractive content was determined ona dry basis using a Soxhlet extraction unit [37]. The lignin content was assessed throughthe Klason lignin method, which quantifies the acid-insoluble fraction of lignin in thebiomass [38]. All extractions and lignin analyses were repeated four times to confirmdata consistency. Elemental composition (carbon, hydrogen, nitrogen, and oxygen) of theground biomass was assessed using an Elemental Analyzer (FISONS EA 1108—ThermoFisher Scientific, Waltham, MA, USA). The analysis was performed in quadruplicate toensure precision.The true density (TD) of the biomass samples was determined using a gas pycnome-ter (Model MVP-D160-E, Quantachrome Instruments, Boynton Beach, FL, USA), withfive replicates performed per sample to enhance result reproducibility. The bulk density(BD) was measured by filling a container (internal dimensions: 100 × 100 × 100 mm)with the ground biomass and recording its mass. Particle size distribution was assessedthrough mechanical sieving following the ANSI/ASAE standard S319.4 (ASAE, 2008b),utilizing a Ro-Tap shaker (Tyler Industrial Products, Cleveland, OH, USA). The analysiswas carried out in four replicates. Shape parameters of biomass particles were determinedthrough image analysis using ImageJ software (Version 1.53K, National Institutes of Health,Bethesda, MD, USA). Over 1000 randomly selected particles were analyzed to extract width(W), length (L), area (A), and perimeter (P). The aspect ratio (AR) and equivalent particlediameter (Deq) were calculated using the following equations [39,40]:AR =WL(1)Deq =√4Aπ(2)where AR is the aspect ratio (dimensionless), W is the maximum width, and L is themaximum length of each particle. Additionally, A is the projected two-dimensional area ofthe particle yielding an equivalent diameter (Deq) in units of length.3.2. PelletizationA flat die pellet mill (GEMCO Energy-ZLSP 300B, Anyang GEMCO Energy MachineryCo., Anyang, China) was used to pelletize all the samples (Figure 1). The pellet die had6 mm diameter holes, a counterbore design, with a total thickness of 26 mm, an effectivethickness of 20 mm, and a relief depth of 3 mm. To ensure a uniform pelletization setup,the gap between the die and roller was precisely adjusted to approximately 1 mm using theadjustment nut, optimizing compression efficiency and pellet formation consistency. Priorto pelletization, the moisture content of all biomass samples was measured and adjustedto 11.50–12.50% through controlled water spraying. To achieve homogeneous moistureEnergies 2025, 18, 2284 5 of 22distribution, the biomass materials were conditioned in a cement mixer for a minimum of60 min. Furthermore, a 30 min warm-up phase was necessary to optimize the performanceof the pellet mill. During this stage, a preconditioning mixture comprising sawdust, finewhite sand, and engine oil in a ratio of 0.5/0.3/0.2 was utilized to elevate the temperatureof the die and roller while simultaneously filling residual voids within the pelletizationchamber and roller gears, ensuring process stability.Energies 2025, 18, 2284 5 of 24 consistency. Prior to pelletization, the moisture content of all biomass samples was measured and adjusted to 11.50–12.50% through controlled water spraying. To achieve homogeneous moisture distribution, th biomass materi ls were conditioned in a cement mixer for a mini um of 60 min. Furthermore, a 30 min w m-up phase was n cessary to ptimiz the performa ce of the p llet mill. Dur ng this stage, a preconditioning mixtur comprisi g sawdust, fine white sand, and engine oil in a ratio of 0.5/0.3/0.2 was utilized t elevate the temp ature of the die and roller whil multaneously filling residual vo ds within the pelletization chamber and roller gears, ensuring process stability. Figure 1. Flat die pellet mill equipped with a custom hopper and feeding system with capability of adjusting the feed rate. Approximately 2 kg of biomass was utilized for each pelletization trial. Each biomass type was tested in replicated trials under identical operating conditions. All equipment- related and process-related parameters, including die and roller gap, feed rate, conditioning time, and target moisture content, were held constant throughout the study to ensure a controlled experimental environment. The objective was to isolate the effect of inherent biomass characteristics on pelletization performance. As this study involved no independent treatment variables, statistical comparisons were conducted using mean comparison methods across replications. The least squares mean (LS) method at p = 0.05 was used to assess significant differences in pellet quality and energy consumption parameters among biomass types. To maintain a uniform feed rate, which is a critical parameter influencing pelletization efficiency [16,41], an in-house-built hopper and feeder system equipped with inverters was employed. Both the hopper and feeder were operated at a 20 Hz frequency to enhance material flowability and facilitate consistent feeding into the pelletization chamber. Following the pelletization process, the produced pellets were cooled and subsequently screened to remove fine particles and unpelletized material. The final pellet samples were stored in air-tight containers to prevent moisture reabsorption and ensure consistency for subsequent quality assessments. i re 1. Flat die pe let i l equipped ith a custo ho er a fee i g s ste it ca a ilit fa j sti t e fee r t .Approximately 2 kg of biomass was utilized for each pelletization trial. Each biomasstype was tested in replicated trials under identical operating conditions. All equip ent-related and process-related parameters, including die and roller gap, feed rate, conditioningtime, and target moisture content, were held constant throughout the study to ensure acontrolled experimental environment. The objective was to isolate the effect of inherentbiomass characteristics on pelletization performance. As this study involved no indepen-dent treatment variables, statistical comparisons were conducted using mean comparisonmethods across replications. The least squares mean (LS) method at p = 0.05 was used toassess significant differences in pellet quality and energy consumption parameters amongbiomass types. To maintain a uniform feed rate, which is a critical parameter influencingpelletization efficiency [16,41], an in-house-built hopper and feeder system equipped withinverters was employed. Both the hopper and feeder were operated at a 20 Hz frequency toenhance material flowability and facilitate consistent feeding into the pelletization chamber.Following the pelletization process, the produced pellets were cooled and subsequentlyscreened to remove fine particles and unpelletized material. The final pellet samples werestored in air-tight containers to prevent moisture reabsorption and ensure consistency forsubsequent quality assessments.3.3. Pelletization Energy ConsumptionThe energy consumption during the pelletization process was monitored and quanti-fied according to [24] using a digital three-phase power data logger (AEMC 8336 PowerPadIII, Dover, NH, USA), which was connected to measure the input currents supplied to theEnergies 2025, 18, 2284 6 of 22flat die pellet mill. Since the operational energy demand of the pellet mill is influenced byits mechanical configuration, it was essential to distinguish between the baseline energyrequirement of the equipment and the actual energy needed for pelletization [24].To determine the net energy consumption specific to each biomass type, the energyrequired to run the pellet mill under no-load conditions, referred to as pellet mill energyconsumption (PMEC), was first measured. This baseline value was subtracted from thetotal pelletization energy consumption (TPEC) recorded during biomass pelletization toobtain the net pelletization energy consumption (NPEC), according to Equation (3). The netspecific pelletization energy consumption (NSPEC) for each biomass was then calculatedby normalizing the NPEC to the mass of the processed biomass in tons (Equation (4)) [24].This approach provides an accurate measure of the energy efficiency of the pelletizationprocess for different biomass types.NPEC(kWh) = TPEC− PMEC (3)NSPEC(kWh/t) =NPEC(kWh)in f eed material mass (t)(4)3.4. Pellet Color IndexThe color characteristics of the biomass pellets were evaluated using a spectropho-tometer (CM5-Konica Minolta, Konica Minolta, Tokyo, Japan), operating in reflectancemode. Prior to each measurement, the instrument was calibrated using a standard whitereference plate to ensure accuracy and consistency. Color assessment was based on theCIE Lab (CIELAB) color space, where L* represents lightness (ranging from 0 = black to100 = white), a* corresponds to the red–green axis (positive values indicating red, negativevalues indicating green), and b* denotes the yellow–blue axis (positive values indicatingyellow, negative values indicating blue). To minimize variability, each sample was mea-sured five times, and the mean values of L*, a*, and b* were recorded for subsequentanalysis [42]. The overall color variation (∆E) between the raw biomass and the pelletizedsamples was determined using the following equation:∆Ei =√(ai − a0)2 + (bi − b0)2 + (Li − L0)2 (5)where i represents the color index of the biomass, and 0 corresponds to the color index ofthe pelletized sample.3.5. Bulk DensityThe bulk density (BDe) of the pelletized biomass was determined by measuring themass of the pellets contained within a standardized container with inner dimensionsof 100 × 100 × 100 mm. The pellets were carefully poured into the container withoutcompaction, ensuring a natural settling condition. The total mass of the biomass within thefixed volume was recorded, and the bulk density was calculated as the ratio of the mass (g)to the container volume (cm3) in 5 replications. This method provides a reliable estimationof the bulk density, which is a crucial parameter for evaluating the storage, handling, andtransport efficiency of the pelletized biomass.3.6. Bulk Durability IndexThe bulk durability (BDu) of the pellets was assessed using the tumbler (Figure 2),following the ANSI/ASAE Standard S269.4 (ASAE, 2007). In this method, approximately500 g of pellets was placed in a durability testing chamber, which consists of a rotatingdrum with internal baffles. The drum was rotated at 50 rpm for 10 min, subjecting theEnergies 2025, 18, 2284 7 of 22pellets to controlled impact and abrasion forces. After tumbling, the pellets were carefullyremoved and sieved using a standard 3.15 mm mesh with round perforations to separateintact pellets from broken fragments and fines [43]. The pellet durability index (PDI) wasthen calculated as the percentage ratio of the mass of intact pellets to the initial mass beforetumbling according to Equation (6). This standardized approach ensures a consistentevaluation of pellet durability, which is a critical parameter for assessing resistance tomechanical degradation during handling, storage, and transportation, and the equation isshown as follows:BDu(%) =M fMi× 100 (6)where M f is the mass of pellets after tumbling and screening, and Mi is the initial mass ofthe pellets, which is 500 g based on the standard.Energies 2025, 18, 2284 7 of 24 3.6. Bulk Durability Index The bulk durability (BDu) of the pellets was assessed using the tumbler (Figure 2), following the ANSI/ASAE Standard S269.4 (ASAE, 2007). In this method, approximately 500 g of pellets was placed in a durability testing chamber, which consists of a rotating drum with internal baffles. The drum was rotated at 50 rpm for 10 min, subjecting the pellets to controlled impact and abrasion forces. After tumbling, the pellets were carefully removed and siev using a standard 3.15 mm mesh with rou d perforations to separate intact pellets from broke fr gments and fines [43]. The pellet durability index (PDI) was then calculated as the percentage ratio of the mass of intact pellets to the initial mass before tumbling according to Equation (6). This standardized a proach ensures consist nt evaluation of pellet durability, which is a critical parameter for assessing resista ce to mechanical degradation during handling, storage, and transportation, and the equation is shown as follows: 𝐵𝐷௨(%) =𝑀௙𝑀௜ × 100 (6)where 𝑀௙ is the mass of pellets after tumbling and screening, and 𝑀௜ is the initial mass of the pellets, which is 500 g based on the standard. Figure 2. Tumbler unit for measuring bulk durability index according to [43]. 3.7. Pellet Moisture Uptake The moisture uptake performance of the pellets was evaluated using a humidity chamber (Memmert HCP50, FRG, Germany) to simulate real-world storage and transportation conditions. The chamber was set to 40% relative humidity at 90 °C, providing an optimal environment for assessing the moisture absorption capacity of the pellets. The experiment was conducted over a 30-day period in three replicates to ensure that the pellets reached moisture equilibrium. Monitoring moisture uptake is essential, as it directly impacts pellet stability, mechanical integrity, and combustion efficiency during storage and transport. This parameter is particularly critical for biomass pellets shipped overseas, where exposure to fluctuating humidity levels can lead to swelling, microbial degradation, and reduced energy value, potentially compromising their quality and usability. . l r it for easuring bulk durability index a cording to [43].3.7. Pellet Moisture UptakeThe moisture uptake performance of the pellets was evaluated using a humidity cham-ber (Memmert HCP50, FRG, Germany) to simulate real-world storage and transportationconditions. The chamber was set to 40% relative humidity at 90 ◦C, providing an optimalenvironment for assessing the moisture absorption capacity of the pellets. The experimentwas conducted over a 30-day period in three replicates to ensure that the pellets reachedmoisture equilibrium. Monitoring moisture uptake is essential, as it directly impacts pelletstability, mechanical integrity, and combustion efficiency during storage and transport.This parameter is particularly critical for biomass pellets shipped overseas, where exposureto fluctuating humidity levels can lead to swelling, microbial degradatio , and reducedenergy value, potentially compromising their qualit and usability.4. Results and DiscussionPellets were successfully produced in batch scale using a flat die pellet mill, from sixdifferent types of biomasses, including corn, soybean, tomato, eggplant, cucumber, andsummer squash stalks, each exhibiting distinct characteristics (Figure 3). The variations inbiomass composition significantly influenced the physical properties of the pellets, withnoticeable differences in color, highlighting the impact of chemical composition duringthe pelletization process [35,44,45]. Despite these variations, the batch production methodmaintained consistency in pellet formation, demonstrating its effectiveness in handlingdiverse biomass sources. This section explores the relationship between biomass propertiesand pellet quality in a scaled-up production setting, providing insights into optimizingfeedstock selection and process parameters for improved efficiency and uniformity inbiomass pellet production.Energies 2025, 18, 2284 8 of 22Energies 2025, 18, 2284 8 of 24 4. Results and Discussion Pellets were successfully produced in batch scale using a flat die pellet mill, from six different types of biomasses, including corn, soybean, tomato, eggplant, cucumber, and summer squash stalks, each exhibiting distinct characteristics (Figure 3). The variations in biomass composition significantly influenced the physical properties of the pellets, with noticeable differences in color, highlighting the impact of chemical composition during the pelletization process [35,44,45]. Despite these variations, the batch production method maintained consistency in pellet formation, demonstrating its effectiveness in handling diverse biomass sources. This section explores the relationship between biomass properties and pellet quality in a scaled-up production setting, providing insights into optimizing feedstock selection and process parameters for improved efficiency and uniformity in biomass pellet production. Figure 3. Pelletized biomasses from crops foliage using a flat die pellet mill in a batch process: (A) corn, (B) soybean, (C) tomato, (D) eggplant, (E) cucumber, (F) summer squash, and (G) sawdust. 4.1. Color Index Parameters The results of the color parameter analysis are shown is Table 1. The results show significant variations in the color parameters (L*, a*, and b*) among different pellet types, indicating diverse responses to the pelletization process. Sawdust exhibited the highest lightness (L* = 69.2), maintaining its original brightness with minimal color transformation (ΔE = 5.8), making it the most visually stable biomass. In contrast, summer squash (L* = 38.9) and cucumber (L* = 41.1) exhibited the lowest lightness values, suggesting significant darkening due to pelletization. The red–green parameter (a*) varied slightly across biomass types, with sawdust, corn, and soybean showing the highest red component (a* ~ 4.5), while summer squash and cucumber had the lowest values, indicating a greener tint (a* ~ 3). The blue–yellow component (b*) was highest in sawdust (b* = 21.0), making it the most yellowish, whereas summer squash (b* = 13.1) had the lowest, indicating less yellow saturation. Figure 3. Pelletized biomasses from crops foliage using a flat die pellet mill in a batch process:(A) corn, (B) soybean, (C) tomato, (D) eggplant, (E) cucumber, (F) summer squash, and (G) sawdust.4.1. Color I eThe res lts f t t r alysis are shown is Table 1. The result showsignificant vari ti ra eters (L*, a*, and b*) among diff rent pellet types,indicatin di i tion roce s. Sawdust exhibited the highestlightnes (L* i t i i its original brightne s with minimal c lor transformation(∆E = 5.8), making it he most visually stable biomass. In contrast, ummer squash (L* = 38.9)and cucumber (L* = 41.1) exhibited the lowest lightness l , suggesting significantdarkening due to pelletization. The red–green parameter (a*) varied slightly across biomasstypes, with sawdust, corn, and soybean showing the highest red component (a* ∼ 4.5),while summer squash and cucumber had the lowest values, indicating a greener tint(a* ∼ 3). The blue–yellow component (b*) was highest in sawdust (b* = 21.0), aking itthe most yellowish, whereas summer squash (b* = 13.1) had the lowest, indicating lessyellow saturation.Table 1. The mean comparison analysis of color index of various pellets.PelletsColor Parameters (-)L* a* b* ∆EiCorn 49.0 c 4.6 a 17.5 b 13.3 bcSoybean 52.5 b 4.5 a 17.6 b 13.6 bcTomato 43.0 d 3.3 b 15.9 c 18.8 aEggplant 41.8 de 4.3 a 16.9 bc 12.6 cCucumber 41.1 e 3.3 b 15.6 c 19.8 aSummersquash 38.9 f 2.5 b 13.1 d 14.8 bSawdust 69.2 a 4.6 a 21.0 a 5.8 dPr > F (Model) <0.0001 <0.0001 <0.0001 <0.0001Significant Yes Yes Yes YesNote: Values followed by different letters (a to f) within a column show significant differences in each parameteramong various samples (p < 0.05) based on a least-square means comparisons using Tukey’s HSD test.Among all biomasses, cucumber (∆E = 19.8) and tomato (∆E = 18.8) experiencedthe most significant total color change in comparison to their ground biomass, implyinggreater sensitivity to heat and pressure during pelletization. Corn and soybean exhibitedmoderate transformations (∆E∼ 13.5), while eggplant (∆E = 12.6) remained relatively stable.Energies 2025, 18, 2284 9 of 22These color variations can be attributed to thermal degradation, oxidation, and chemicalchanges in lignin and hemicellulose during the densification process [44,45]. The significantdifferences (p < 0.0001) in color parameters indicate that pelletization influences the visualproperties of biomass, with certain feedstocks undergoing more drastic alterations thanothers. Sawdust, due to its minimal ∆E, appears to be the most resistant to color change,whereas foliage from agricultural crops such as cucumber and tomato are more prone tonoticeable shifts. Recent research by Gholami B. et al. 2025 showed that these variationsin color are attributed to differences in inorganic elemental composition including P, S, Cl,K, Ca, Cu, and Zn, which can affect the ash, heating value, and thermal stability of thesebiomass pellets [35].A detailed correlation analysis by Gholami B. et al. 2025 revealed that the inorganiccomposition of the biomass played a measurable role in influencing pellet color indices [35].Specifically, higher concentrations of calcium (Ca), potassium (K), and zinc (Zn) werefound to be negatively correlated with the L* value, indicating that increased levels of theseelements contributed to darker pellet surfaces, likely due to enhanced light absorption orcatalytic degradation reactions during densification [46,47]. Similarly, sulfur (S) and chlo-rine (Cl) exhibited negative correlations with both a* and b* values, suggesting a tendencytoward greener and less yellow pellet tones, respectively, which is potentially linked totheir involvement in thermochemical transformations and volatile compound release [48].In contrast, copper (Cu) demonstrated a positive correlation with L*, indicating that itspresence may be associated with increased surface brightness in the final pellet. Thesefindings highlight the multifactorial nature of pellet color development and the potentialof elemental profiling as a supplementary tool for assessing biomass transformation dur-ing pelletization. Understanding these color characteristics can provide insights into thecombustion properties, processing behavior, and suitability of these biomass pellets forvarious applications.4.2. Pelletization EnergyThe results of pelletization performance parameters of various biomass samples aresummarized in Table 2. The moisture content across all biomass samples remained almostconstant, ranging between 11.80% and 12.10%, confirming effective moisture adjustmentbefore pelletization. This consistency is essential, as variations in MC could significantlyaffect pellet quality, energy consumption, and overall pelletization efficiency [18,19]. Sincethe moisture content was well-regulated, the observed differences in pelletization perfor-mance, feeding rate, and net specific pelletization energy consumption (NSPEC) can beattributed to the intrinsic physical and chemical properties of each biomass rather thanmoisture-related effects.Across all samples, the pellet mass was consistently lower than the infeed materialmass, primarily due to material loss during pelletization, indicating that a portion of thematerial remains within the die and pelletization chamber. Another source of material lossis attributed to the fine particles and unpelletized biomass that are screened by sieving thepellets using a standardized 3.15 mm sieve with round perforations. These two sourcesof material loss affect the pelletization performance directly. Soybean (5.9%) and tomato(4.1%) exhibited the highest fine particle content, indicating higher material loss, whichcontributed to their lower pelletization performance. In contrast, biomasses like corn(1.6%), cucumber (1.7%), and summer squash (1.9%) generated fewer fines, leading tohigher pelletization performance.The feeding rate varied among biomass types even though a constant frequency of20 Hz was used for both hopper and feeder, reflecting differences in flowability characteris-tics of biomasses. Sawdust (19.7 g/s), tomato (18.1 g/s), cucumber (16.9 g/s), and summerEnergies 2025, 18, 2284 10 of 22squash (16.4 g/s) exhibited the highest feed rates, indicating superior material flowabilityand ease of movement into the pellet mill. These biomasses likely had optimal particlesize distribution and lower inter-particle friction, facilitating smoother feeding. This obser-vation is consistent with the findings of a previous study by Gholami B. et al. (2024), asreported in their paper [49]. In contrast, corn (13.1 g/s) and eggplant (13.7 g/s) displayedlower feed rates, suggesting increased friction and lower bulk density that reduced theirability to flow consistently into the mill.Table 2. Mass in-flow, performance parameters, and energy consumption of flat die pellet mill for thepelletization of crop foliage.Samples MC(wb, %)InfeedMaterialMass (g)ProducedPellet Mass(g)FineParticle(%)PelletizationPerformance(%)FeedingTime (s)Feed Rate(g/s)NSPEC(kWh/t)Corn 12.10 2058.3 2011.5 2.3 95.5 157 13.1 33.0Soybean 11.80 2041.5 1961.9 5.9 90.4 150 13.6 49.6Tomato 12.00 2150.0 2017.5 4.1 90.0 119 18.1 28.2Eggplant 12.05 2085.0 1913.4 1.6 90.3 152 13.7 32.4Cucumber 12.10 2152.8 2088.7 1.7 95.4 127 16.9 21.8Summer squash 12.05 1987.8 1945.9 1.9 96.0 121 16.4 18.7Sawdust 11.90 2167.6 2038.5 3.3 91.0 110 19.7 47.3Pelletization performance and the net specific pelletization energy consumption(NSPEC) values revealed significant differences in pelletization efficiency. Summer squash(96.0%) and corn (95.5%) exhibited the highest pelletization performance, with minimal ma-terial loss. Soybean (90.4%) and tomato (90.0%) had the lowest pelletization performance,indicating greater material loss. The NSPEC values showed that soybean (49.6 kWh/t) andsawdust (47.3 kWh/t) required the highest energy consumption, likely attributed to theirgreater resistance to densification due to their larger particle sizes. In contrast, summersquash (18.7 kWh/t) and cucumber (21.8 kWh/t) exhibited the lowest NSPEC values,confirming their superior plasticity and compaction efficiency. The results of the NSPECare investigated more in the following sections to identify the key parameters influencingits performance.The high pelletization energy requirement in sawdust and soybean can be attributed totheir larger particle sizes. The results of the particle size analysis by Gholami B. et al. (2024)support this observation [49]. This is mainly because larger particles resist compressiondue to irregular packing, leading to higher friction in the die and requiring greater forceto deform and bond during pelletization [50,51]. This increases mechanical resistance andenergy consumption during the pelletization process. Corn, tomato, and eggplant fallwithin an intermediate energy range, reflecting a balance between fiber rigidity, particlesize, and chemical composition. In contrast, cucumber (21.8 kWh/t) and summer squash(18.7 kWh/t) require the lowest pelletization energy, suggesting that smaller particle sizescontribute to easier compression and densification. The possible justification is that thesmaller particles fill voids efficiently and reduce resistance to compression, while theirincreased surface area enhances bonding and improves interlocking, leading to higherpellet durability [52,53].Another possible factor contributing to the variation in net specific energy requiredfor pelletization is the mechanical properties of the biomass materials. The mechanicalcharacteristics and microstructure of tomato stems [54], corn stalks [55], and cucumberstems [56,57] have been extensively studied in recent years. Findings indicate that cornstalks exhibit higher shear strength, tensile strength, and elasticity modulus than tomatostems, while tomato stems possess superior mechanical properties compared to cucumberstems [54–57]. Additionally, recent research by Gholami B. et al. (2024) reported that saw-Energies 2025, 18, 2284 11 of 22dust, corn, and soybean required higher grinding energy compared to summer squash andcucumber [49]. This suggests that sawdust, soybean, and corn are stiffer and more elastic,whereas summer squash and cucumber, which require less grinding energy, are typicallymore plastic and softer.The elastic modulus, which represents a material’s stiffness or resistance to defor-mation, also plays a crucial role in pelletization efficiency. The elasticity in biomass isattributed to the existence of the lignin component [15]. A higher modulus signifiesgreater rigidity, requiring higher compression force to achieve compaction. Materials witha high elastic modulus are more resistant to deformation, demanding greater pressurefor densification [58]. Additionally, they store more elastic energy, which may result in aspring-back effect, causing pellets to expand slightly after exiting the die [58]. Furthermore,these materials are more challenging to densify, as their structure requires higher energyinput to break fibers and facilitate particle rearrangement during pelletization.4.3. Pellet Quality Analysis: Bulk Density and Bulk DurabilityThe bulk density (BDe) and bulk durability (BDu) of biomass pellets are critical indi-cators of the pellet quality affecting mechanical integrity, transport efficiency, and storagestability [59]. The results of the pellet bulk density and bulk durability analysis are shownin Table 3. The results indicate that pellet bulk density, pellet bulk durability, and netspecific pelletization energy consumption vary significantly among the tested biomass sam-ples. Cucumber exhibited the highest bulk density (691.2 kg/m3) and durability (97.9%),making it the most compact and durable pellet material. This was closely followed by sum-mer squash (665.5 kg/m3, 96.6%) and tomato (663.3 kg/m3, 96.9%). In contrast, soybean(586.8 kg/m3) and sawdust (612.5 kg/m3) had the lowest bulk density, suggesting a looserpellet structure. The highest durability was observed in cucumber (97.9%) and corn (97.6%),while soybean pellets had the lowest (92.3%), indicating its weaker cohesion and tendencyto form less-durable pellets.The values of bulk density of the pellets are comparable to those reported for ricestraw (640 to 650 kg/m3) [60] and wheat straw (480 to 550 kg/m3) [61,62]. The bulk dura-bility values of the pellets in this study are also consistent with those reported for wheatstraw (90 to 97%) [61,62] and rice straw (92 to 95%) [63,64]. These findings indicate thatvegetable crop residues, when properly processed under controlled pelletizing condi-tions, can achieve compaction and mechanical integrity comparable to, or even exceeding,that of traditional agricultural residues such as rice and wheat straw. This performancehighlights their potential for efficient storage, transport, and integration into large-scalebioenergy applications.The correlation analysis in Table 3 reveals that lignin content, carbon-to-oxygen (C/O)ratio, biomass bulk density (BD), and particle size (D50) influence the bulk density of thepellet to varying degrees. Interestingly, this observation is consistent with the findings ofGholami B. et al. (2025) on the pelletization of the same material using a manual pelletpress mill [35]. The correlation between lignin (r = −0.566) and the C/O ratio (=−0.750)with pellet bulk density indicates that biomasses such as sawdust, corn, and soybeanwith a higher lignin content exhibit lower pellet bulk density. This may be due to thehigher lignin content in these biomass materials, which can hinder their ability to compactefficiently. However, this observation contrasts with findings from previous studies, whereseveral researchers have suggested that lignin functions as a natural binder, enhancingpellet quality [11,15]. Although lignin plays a crucial role in improving pellet strength, itsinfluence on compaction efficiency is complex. The elastic properties of certain biomasstypes, which are influenced by their lignin composition and structural characteristics,may alter their densification behavior, ultimately affecting how efficiently they compactEnergies 2025, 18, 2284 12 of 22during the pelletization process [11]. The findings also demonstrate that a higher biomassbulk density (BD) enhances pellet bulk density (r = 0.615), while particle size (D50)correlates with pellet density (r = −0.510), confirming their influence on densification.This observation aligns with previous studies, which have reported that smaller particlesizes reduce void spaces, improve packing efficiency, and enhance inter-particle bonding,leading to denser pellets [52,53].Energy consumption for pelletization (NSPEC) varied widely across biomass types,with summer squash (18.7 kWh/t) and cucumber (21.8 kWh/t) being the most energy-efficient materials, while soybean (49.6 kWh/t) and sawdust (47.3 kWh/t) required themost energy for pelletization. Notably, cucumber and summer squash required the leastenergy, reflecting superior compaction behavior and plasticity, while soybean and sawdustexhibited the highest energy demand due to greater resistance to densification. Whencompared to values reported for traditional agricultural residues, such as rice husk andwheat straw, the NSPEC values in this study are considerably lower. The literature suggeststhat energy requirements for pelletizing wheat straw and switchgrass typically fall withinthe range of 55–65 kWh/t and 110–130 kWh/t, respectively, depending on pellet mill typeand feedstock conditioning [61,65]. This discrepancy suggests that the greenhouse residuesused in this study, under optimized moisture content and particle size, possess favorablemechanical properties that enable efficient pelletization with reduced energy input.This lower energy requirement for cucumber and summer squash implies a potentiallysignificant reduction in operational costs, particularly when scaled to industrial pelletproduction volumes. For context, wood pellet production costs (including raw materialacquisition, drying, grinding, and pelletization) are estimated to be roughly USD 180 perton, depending on feedstock prices and regional electricity rates [66]. Since greenhousecrop residues are often treated as waste streams, they could offer cost advantages if sourcedlocally or through agricultural partnerships. Thus, residues such as cucumber and summersquash foliage may present economically viable alternatives to traditional wood pellets.The significant correlation between BDe and NSPEC (r = −0.913) indicates that mate-rials requiring lower energy for pelletization tend to form denser pellets. This relationshipsuggests that biomass with lower resistance to compression achieves higher compaction,resulting in increased pellet density. Conversely, materials that require higher energy inputfor pellet formation may exhibit lower bulk density due to greater resistance during thepelletization process. This is likely because denser materials compact more easily, requir-ing less mechanical effort [67,68]. Similarly, BDu correlated with NSPEC (r = −0.663),suggesting that materials requiring lower energy for pelletization tend to produce moredurable pellets. This implies that such materials undergo plastic deformation more effi-ciently, facilitating better compaction and particle bonding, which enhances pellet integrityand durability.The factors influencing the bulk durability of the pellets appear to be less straight-forward, as the correlations with biomass properties are relatively weak and inconsistent.While ash content (r = 0.304) and extractives (r = 0.410) show some degree of positivecorrelation with BDu, lignin content (r = −0.065) and particle size (r = 0.031) exhibitnegligible relationships. These results suggest that intrinsic biomass properties alone maynot be the primary determinants of pellet durability. The lack of strong correlations in thisstudy implies that pellet durability is likely influenced more by process parameters, suchas moisture content, die temperature, and feeding rate, as well as equipment performanceduring pelletization [24,69]. These factors could play a critical role in determining themechanical integrity of pellets and should be investigated further to better understandtheir impact on durability.Energies 2025, 18, 2284 13 of 22Table 3. Pellet bulk density, bulk durability, and the correlation of physio-chemical biomass properties with pellet BDe, BDu, and specific pelletization energy.PropertiesGround Foliage Samples Correlations withCorn Soybean Tomato Eggplant Cucumber SummerSquash SawdustPellet BDe(kg/m3)Pellet BDu(%)NSPEC(kWh/t)Pellet BDe (kg/m3) 629.4 c 586.8 e 663.3 b 630.1 c 691.2 a 665.5 b 612.5 d 1 0.729 −0.913Pellet BDu (%) 97.6 b 92.3 e 96.9 c 96.6 d 97.9 a 96.6 d 96.6 d 0.729 1 −0.663NSPEC (kWh/t) 33.0 c 49.6 a 28.2 d 32.4 c 21.8 e 18.7 f 47.3 b −0.913 −0.663 1Extractive (%, db) 5.7 a 1.5 d 4.8 b 4.4 b 1.8 cd 1.7 cd 2.2 c 0.018 0.410 −0.111Lignin (%, db) 18.5 b 15.4 d 16.2 c 12.4 e 9.4 f 5.6 g 29.2 a −0.566 −0.065 0.754GCV (MJ/kg, db) 17.2 bc 17.5 b 14.8 d 16.7 c 14.3 d 13.6 e 21.0 a −0.758 −0.261 0.861Ash (%) 5.5 f 6.8 e 18.3 c 14.5 d 25.3 b 33.6 a 0.3 g 0.795 0.304 −0.890C/O ratio (-) 0.953 b 0.964 b 0.795 d 0.836 c 0.640 e 0.455 f 1.158 a −0.750 −0.280 0.889TD (g/cm3) 1.239 e 1.398 d 1.424 b 1.242 e 1.412 c 1.489 a 1.395 d 0.337 −0.178 −0.226BD (kg/m3) 107.7 f 200.2 c 259.9 b 196.4 d 259.5 b 289.0 a 186.9 e 0.615 0.038 −0.558D50 (mm) 0.71 b 0.67 c 0.61 d 0.69 b 0.65 c 0.59 e 0.85 a −0.510 0.031 0.670AR (-) 0.32 a 0.37 a 0.40 a 0.45 a 0.32 a 0.40 a 0.33 a −0.024 −0.022 −0.051Deq (mm) 1.9 ab 1.9 ab 1.3 b 2.2 a 1.9 ab 2.1 ab 2.6 a −0.211 0.019 0.169Note 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-square mean comparisonsusing Tukey’s HSD test. Note II: Values in bold show significant correlation by Pearson method at p = 0.05.Energies 2025, 18, 2284 14 of 22Several biomass properties significantly influenced the net specific energy requiredfor the pelletization. Lignin content (r = 0.754) and C/O ratio (r = 0.889) exhibiteda strong positive correlation with NSPEC, indicating that materials with higher ligninlevels or a higher carbon-to-oxygen ratio require more energy for pelletization. Saw-dust, which had the highest lignin content (29.2%), also exhibited one of the highestNSPEC values (47.3 kWh/t), confirming that high lignin content increases resistance duringcompression [11]. Similarly, soybean with 15.4% lignin content and a 0.964 C/O ratio hadthe highest NSPEC among all samples (49.6 kWh/t).On the other hand, the results showed a positive correlation between particle size(D50) and NSPEC (r = 0.670), indicating that larger particles require more energy forpelletization. This is likely due to their lower packing efficiency and increased resistanceduring compression, necessitating additional energy for crushing and deforming the largerparticles during densification process. Previous studies support this finding, which high-light that smaller particle sizes enhance pelletization efficiency by minimizing friction andmechanical resistance [52,53]. Optimizing particle size through pre-processing, such asgrinding, can therefore be a key strategy to lower energy consumption in pellet production.The results show that extractives, true density (TD), aspect ratio (AR), and equivalentdiameter (Deq) have minimal influence on pellet bulk density, durability, and pelletizationenergy consumption, as their correlations with these parameters are weak. These findingssuggest that physical properties may not be key determinants in pellet quality while otherfactors, such as process conditions and material composition, play a more dominant rolein influencing pellet characteristics, warranting further investigation into their effectson densification.4.4. Pellet Moisture Uptake AnalysisThe results of the moisture uptake of the pellets made from various biomasses arepresented in (Figure 4). To obtain the optimal performance of the humidity chamber,the test was run at 90% relative humidity and 40 ◦C temperature according to its user’smanual. The moisture uptake of biomass pellets varied significantly among the samples,demonstrating the effect of physicochemical properties on pellet moisture absorbance rate.Cucumber and summer squash exhibited the highest moisture uptake, reaching moisturecontents of approximately 38–41% (db) at equilibrium. Eggplant and tomato followed withmoderate moisture absorption in the range of 28–33% (db), while corn and soybean showedslightly lower moisture uptake, stabilizing around 24–27% (db). In contrast, sawdust hadthe lowest moisture absorption, with equilibrium moisture content around 16–18% (db),indicating superior resistance to humid conditions.The results indicate that ash content, lignin content, and the carbon-to-oxygen (C/O)ratio significantly influence moisture uptake in biomass pellets. Among these, ash contentexhibited a strong positive correlation with moisture absorption, where biomass types witha higher ash content, such as summer squash (33.6%) and cucumber (25.3%), absorbed themost moisture. This behavior can be attributed to the hygroscopic nature of certain mineralcompounds in ash, including potassium (K), sodium (Na), calcium (Ca), and magnesium(Mg) salts [70,71]. These minerals attract and retain water molecules, increasing the waterabsorption capacity of pellets. Additionally, some alkaline oxides (e.g., K2O, Na2O, andCaO) react with water to form hydroxides, further enhancing moisture retention [70]. Thisexplains why biomass with high ash content exhibited elevated moisture uptake despitetheir high bulk density and durability.Energies 2025, 18, 2284 15 of 22Energies 2025, 18, 2284 17 of 24 Figure 4. Moisture uptake of pellets made from various biomasses in a humidity chamber with 90% relative moisture content at 40 °C. 0510152025303540450 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500M C % ( db )Time (h)Corn Soybean Tomato Eggplant Cucumber Summer squash SawdustFigure 4. Moisture uptake of pellets made from various biomasses in a humidity chamber with 90% relative moisture content at 40 ◦C.Energies 2025, 18, 2284 16 of 22Conversely, lignin content played a critical role in reducing moisture uptake due to itshydrophobic properties [72]. Sawdust, which contained the highest lignin content (29.2%),showed the lowest moisture absorption among all samples. Lignin is known to act as anatural moisture barrier, repelling water and limiting the interaction between biomass andatmospheric humidity [72,73]. The strong inverse correlation between lignin content andmoisture uptake suggests that biomass with higher lignin concentrations, such as sawdust,maintains better moisture resistance, making it more suitable for long-term storage underhumid conditions. This highlights the importance of lignin-rich biomass for moisture-stablepellet production.The C/O ratio also influenced moisture uptake, with a strong negative correlationobserved between them. Biomasses with higher C/O ratios, such as sawdust (1.158),absorbed less moisture compared to those with lower C/O ratios, such as summer squash(0.455). A higher C/O ratio indicates a lower oxygen content, reducing the number ofhydrophilic functional groups available for water interaction [74]. This results in reducedaffinity for moisture, further supporting the idea that biomasses with high C/O ratiosexhibit better moisture resistance.Interestingly, pellets with high durability and bulk density, such as summer squash, cu-cumber, eggplant, and tomato, still exhibited high moisture absorption. This suggests that,while density and durability improve pellet integrity, they do not necessarily translate tolower moisture uptake. Instead, the intrinsic chemical composition of biomass, particularlyash and lignin content, plays a more crucial role in determining moisture resistance. Thesefindings underscore the importance of considering moisture uptake alongside durabilityand density when selecting biomass materials for pelletization, particularly for applicationsrequiring long-term storage in humid environments.4.5. Mathematical Modelling of Pellet Bulk Density and Bulk DurabilityScaling up from single-pellet parameters to predict bulk pellet properties is essentialfor optimizing large-scale pellet production and storage. Pellet density and pellet durabilityserve as fundamental indicators of pellet quality properties, as they influence how pelletscompact and withstand mechanical stress in bulk form [59]. To establish a predictiverelationship, a multilinear regression model (Figure 5) was developed, incorporating single-pellet density and durability as independent variables to estimate bulk pellet density (BDe)and bulk pellet durability (BDu). The regression model enables the prediction of bulkpellet characteristics based on measurable single-pellet properties, allowing for processoptimization without the need for large-scale experimental trials. This modeling wasconducted under controlled conditions, specifically with a pellet moisture content of 8–10%.Any deviation from this moisture range could alter pellet properties, potentially affectingthe accuracy and reliability of the model, and the model is shown as follows:BDe = 2408.3− 1563.6× SPDe − 20.7× SPDu + 18.1× SPDe × SPDu (7)BDu = −477.8 + 392.9× SPDe + 5.86× SPDu − 4× SPDe × SPDu (8)where BDe is predicted bulk density (kg/m3) with R2 = 0.936, BDu is predicted bulkdurability (%) with R2 = 0.861, SPDe is single pellet density in (g/mm3), and SPDu issingle pellet durability in (%).Energies 2025, 18, 2284 17 of 22Energies 2025, 18, 2284 18 of 24 4.5. Mathematical Modelling of Pellet Bulk Density and Bulk Durability Scaling up from single-pellet parameters to predict bulk pellet properties is essential for optimizing large-scale pellet production and storage. Pellet density and pellet durability serve as fundamental indicators of pellet quality properties, as they influence how pellets compact and withstand mechanical stress in bulk form [59]. To establish a predictive relationship, a multilinear regression model (Figure 5) was developed, incorporating single-pellet density and durability as independent variables to estimate bulk pellet density (BDe) and bulk pellet durability (BDu). The regression model enables the prediction of bulk pellet characteristics based on measurable single-pellet properties, allowing for process optimization without the need for large-scale experimental trials. This modeling was conducted under controlled conditions, specifically with a pellet moisture content of 8–10%. Any deviation from this moisture range could alter pellet properties, potentially affecting the accuracy and reliability of the model, and the model is shown as follows: 𝐵𝐷௘ = 2408.3 − 1563.6 × 𝑆𝑃𝐷௘ − 20.7 × 𝑆𝑃𝐷௨ + 18.1 × 𝑆𝑃𝐷௘ × 𝑆𝑃𝐷௨ (7)𝐵𝐷௨ = −477.8 + 392.9 × 𝑆𝑃𝐷௘ + 5.86 × 𝑆𝑃𝐷௨ − 4 × 𝑆𝑃𝐷௘ × 𝑆𝑃𝐷௨ (8)where 𝐵𝐷௘ is predicted bulk density (kg/m3) with 𝑅ଶ = 0.936 , 𝐵𝐷௨ is predicted bulk durability (%) with 𝑅ଶ = 0.861, 𝑆𝑃𝐷௘ is single pellet density in (g/mm3), and 𝑆𝑃𝐷௨ is single pellet durability in (%). Figure 5. Goodness of the prediction models for bulk durability and bulk durability. 5. Conclusions The findings of this study provide valuable insights into the pelletability of foliage from six greenhouse crops for bioenergy and biomaterial applications. Converting agricultural residues into pellets enhances energy density, transportability, and usability, offering a sustainable alternative to conventional biomass sources. This research bridges the gap between single-pellet analysis and batch-scale production, providing a comprehensive understanding of physicochemical properties, pellet quality, and energy consumption during pelletization. The results are particularly relevant for scaling up agricultural biomass utilization, reducing dependency on traditional wood-based feedstocks, and improving the efficiency of biomass-based renewable energy systems. These findings contribute to supply chain diversification, waste valorization, and 550600650700750550 600 650 700 750Bulk density (kg/m3 )Prediction (Bulk density (kg/m3))909294969810090 92 94 96 98 100Bulk durability (%)Prediction (Bulk durability (%))Figure 5. Goodness of the prediction models for bulk durability and bulk durability.5. ConclusionsThe findings of this study provide valuable insights into the pelletability of foliage fromsix greenhouse crops for bioenergy an biom terial applications. Conv rting agriculturalresidues into pellets nhances energy d nsity, transportability, and usability, offering asustainable alternative conventional biomass sources. This rese rch bridges the gapbetween single-pellet nalysis and batch-scale production, providing a comprehensiveunderstanding of physicoch mical properties, pellet quality, and energy consumptionduring pellet zatio . The results are particularly relevant for scaling up agricultural biomassutilization, reducing de endency on traditiona wood-b sed feedstocks, d improv theefficiency of biomass-based renewable energy systems. These fi dings contribute t supplychain diversificat on, waste valorizat o , and environmental sustain ility, making hemhighly applicable for biofu l production, bio-composite manufacturing, nd agriculturalresidue management. Key findings are shown as follows:• Successful batch-scale pellet production was achieved for six types of biomasses,demonstrating the viability of greenhouse crop residues as a sustainable feedstock forbioenergy applications.• Biomass composition significantly impacted pellet density, durability, color properties,and moisture uptake. Higher lignin content contributed to improved pellet cohesion,while ash content influenced moisture absorption and combustion properties.• Net specific pelletization energy consumption (NSPEC) varied across feedstocks, withcucumber (21.8 kWh/t) and summer squash (18.7 kWh/t) exhibiting the lowest energyrequirements, while soybean (49.6 kWh/t) and sawdust (47.3 kWh/t) required themost energy due to higher resistance to densification.• Cucumber and summer squash produced the most compact and durable pellets, withbulk density exceeding 665 kg/m3 and durability above 96%, making them idealcandidates for long-term storage and transportation.• Sawdust exhibited the lowest moisture absorption (16–18% db) due to its high lignincontent, while cucumber and summer squash had the highest moisture uptake (38–41%db), making them more susceptible to humidity related degradation.• A predictive model was developed to relate single-pellet density and durability tobulk pellet properties, providing a scalable framework for optimizing industrialpellet production.This study highlights the potential of agricultural and horticultural biomass residuesas a viable feedstock for pelletized biofuels, contributing to the circular economy, renewableEnergies 2025, 18, 2284 18 of 22energy production, and sustainable resource management. Future research should explorelong-term storage stability, combustion behavior, and industrial-scale process optimization,including moisture conte, die/roller gap, and feeding rate, to enhance the practical appli-cation of these biomass resources in global bioenergy markets. While the current studyconcentrated on the technical aspects of pelletization, subsequent investigations shouldbroaden the scope to include economic and environmental assessments. In particular,conducting a comprehensive techno-economic analysis (TEA) and life cycle assessment(LCA) is essential to evaluate the scalability, commercial viability, and sustainability ofutilizing greenhouse crop residues as bioenergy feedstocks. These future assessmentsshould incorporate factors such as carbon footprint, energy input costs, and market com-petitiveness in comparison to conventional wood pellets, thereby providing a more holisticevaluation of their potential in renewable energy systems.Author Contributions: O.G.B.: conceptualization, data curation, formal analysis, investigation,methodology, software, visualization, writing—original draft, writing—review and editing. S.S.:conceptualization, project administration, resources, supervision, validation, writing—review andediting. A.L.: conceptualization, project administration, resources, supervision. All authors haveread and agreed to the published version of the manuscript.Funding: This research was funded by the Natural Sciences and Engineering Research Council ofCanada (NSERC), grant number 11759. The funder was not involved in the study design, collection,analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.Data Availability Statement: The raw data supporting the conclusions of this article will be madeavailable by the authors on request.Acknowledgments: The authors gratefully acknowledge graduate support from NSERC (Grant#11759). The Biomass Canada Cluster (BMC) is also acknowledged for their support. Special thanksare extended to Premium Pellet Co., Vanderhoof, British Columbia, for supplying sawdust samples.Additionally, the authors sincerely appreciate the technical support provided by Jun Sian Lee andHamid Rezaei. During the preparation of this research paper, the authors used the ChatGPT-4o toolto enhance English and readability. After using this service, the authors reviewed and edited thecontent as needed and take full responsibility for the content of the publication.Conflicts of Interest: The authors declare that they have no known conflicts of financial interests orpersonal relationships that could have appeared to influence the work reported in this paper.AbbreviationsMC Moisture ContentGCV Gross Calorific ValueAC Ash ContentPSD Particle Size DistributionD50 50% of the particles have diameter less than the specific amountW WidthL LengthA AreaP PerimeterAR Aspect RatioDeq Equivalent DiameterBDe Pellet Bulk DensityBDu Pellet Bulk DurabilityTD Biomass True DensityBD Biomass Bulk DensitySPDe Single Pellet DensitySPDu Single Pellet DurabilityEnergies 2025, 18, 2284 19 of 22TPEC Total Pelletization Energy ConsumptionPMEC Pellet Mill Energy ConsumptionNPEC Net Pelletization Energy ConsumptionNSPEC Net Specific Pelletization Energy ConsumptionReferences1. 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Analysis of the Pelletability of Vegetable Crop Foliage Using a Commercial Flat Die Pellet Mill
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