Switchgrass (SG) (Panicum virgatum L.) cv. Alamo stands were cultivated and harvested in 2017 in Vonore, TN. The SG with leaves and stalks was processed via two-stage grinding; at stage-1, the hammer mill (Bliss Industries LLC, Ponca city, OK) was fitted with a 76.2 mm screen, while at stage-2, it was fitted with a 6.35 mm (1/4-in.) screen. The ground SG biomass was shipped to INL in super-sacks for further pelleting. The chemical composition of the received biomass was 38 ± 1% cellulose, 28 ± 1% hemicellulose, 21 ± 0% lignin, 5 ± 0% extractives, and 5 ± 0% acetyl contents.

Clean southern yellow pine (SYP) (Pinus spp.) residues with a 152.4 mm (6-in.) stem diameter were harvested from the mature stands at the School of Forestry and Wildlife Sciences at Auburn University, AL, in 2017. The biomass was chipped, dried to about a 10% (w.b.) moisture content, and then shipped to INL. At INL, the pine chips were further ground using a hammer mill (Bliss Industries LLC, Ponca city, OK) fitted with a 6.35 mm screen. The ground SYP and SG were reconditioned to high moistures (20 and 25%, w.b.) and used to test the high-moisture pelleting process either individually or in blends of 25:75, 50:50, and 75:25, respectively. A pilot-scale ring-die pellet mill was used for conducting the pelleting studies on SG, pine, and their blends. Pioneer pellet mill model number: 35A- 75-80HP, serial number 3193, Bliss Industries, LLC, (Ponca City, OK), was used in the present pelleting studies. According to the manufacturer, the recommended break pressure for operating the pellet mill is 1,000 psi. This mill is designed for overall reliability and maximum efficiency and ease of operation. During the pelleting process, the die and collar assembly were protected by a hydraulic overload system, which stops the main motors when an overload situation occurs.

For the 2.5-ton demonstration of high-moisture pelleting, SYP tops of 50.8 mm (2-in.) and 152.4 mm (6-in.) diameter were screened and selected. About 50 pine trees were harvested in 2018 from the mature stands of the School of Forestry and Wildlife Sciences at Auburn University, AL, to gather sufficient biomass between 2,000 and 3,000 kg and further dried to about 10% (w.b.) before shipping to INL. These pine residues were ground at INL using a Bliss hammer mill fitted with a 6.35 mm screen size. The ground material was then blended with either 40% or 50% of the previously obtained SG. The chemical composition of the 2-in. (50.8 mm) SYP was 29 ± 0% cellulose, 20 ± 0% hemicellulose, 38 ± 1% lignin, 10 ± 0% extractives, and 1.5 ± 0% acetyl contents, whereas the chemical composition of the 6-in. (152.4 mm) SYP was 36 ± 0% cellulose, 22 ± 0% hemicellulose, 36 ± 1% lignin, 6 ± 0% extractives, and 2 ± 0% acetyl contents.

A pilot-scale ring-die pellet mill at INL with a throughput capacity of 1 ton/h, as shown in Figure 1, was used for both the preliminary testing of SG-SYP blends and for the 2.5-ton high pelleting demonstration. The pellet mill is set-up with a ribbon blender, which pre-conditions the biomass moisture, a steam conditioner that adds moisture and heat during pelleting, and data loggers for recording the pelleting parameters, including conveyor speed, amperage, power, pressure, and steam usage. It also has various pellet dies with different compression (L/D) ratios. During the preliminary pelleting of SYP, SG, and their blends, three L/D ratios (e.g., 5, 7, 9) and two moisture levels (20 and 25% w.b.) were tested for five different biomass blends, as shown in Table 1. Based on the preliminary results, we selected an L/D ratio of 9 and a moisture content of 20% (w.b.) for the 2.5-ton pelleting demonstration of 2-in. (50.8 mm) and 6-in. (152.4 mm) SYP blended with SG. During the demonstration, about 1,000 kg of 6-in. (152.4 mm) SYP-50, 227 kg of 6-in. (152.4 mm) SYP-60, 1,000 kg of 2-in. (50.8 mm) SYP-60, and 227 kg of 2-in. (50.8 mm) SYP-50 blends were pelleted using the parameters listed in Table 1. These tests were conducted to understand the impact of blend ratios, L/D ratios, and moisture content on pellet physico-chemical properties, namely ash content, higher heating value (HHV), density (e.g., unit, bulk and tapped), and durability, as well as pelleting energy consumption.

Power consumption data during pelleting were logged using LabVIEW (National Instruments, Austin, TX). An APT power monitor meter (Applied Power Technologies, Inc., San Jose, CA) connected to the pellet mill recorded the power consumption during the high-moisture pelleting in kilowatts. The no-load power was recorded by running the pellet mill empty. The specific energy consumption (SEC) was calculated by subtracting the no-load kW from the full-load power using Eq. 1. S E C = ( F u l l   l o a d   p o w e r   ( k W ) − N o   l o a d   p o w e r   ( k W ) )   ×   t i m e   ( h ) W e i g h t   o f   b i o m a s s   p r o c e s s e d   ( t o n ) (1)

Samples from preliminary pelleting tests (N = 30) were characterized off-line using a desktop DA 7250 SD NIR spectrometer (Perten Instruments AB, Hägersten, Sweden). During the 2.5-ton pelleting demonstration, samples of approximately 25 g were manually collected every 2.5 min from the outfeed pellet conveyor and subjected to at-line NIR spectroscopy using the same DA 7250 SD instrument. The at-line NIR scans were meticulously time-stamped and the corresponding pellet temperature was recorded by using a hand-held infrared thermometer. The pellet moisture content was also determined in duplicate by drying at 105°C until constant weight. The pellet samples for both the at- and off-line NIR analysis were packed twice. For each repack, the samples were scanned twice in the range of 950–1,650 nm. The sample temperature and moisture content at the time of NIR analysis are provided in Supplementary Table S1.

The bulk density and geometric mean particle length of switchgrass (SG) after passing through a 6.35 mm screen were 104 kg/m³ and 1.25 mm, respectively. Determination of particle size distribution indicated that milling of SG in two stages led to more fines in the grind. In the case of 6-in. (152.4 mm) SYP residues used for the preliminary tests, the geometric mean particle length and bulk density were determined to be 0.91 mm and 190 kg/m³, respectively, at a moisture content of about 10% (w.b.).

The ultimate analysis, ash content, and HHV of the raw material are provided in Table 2. Both the 2-in. (50.8 mm) SYP and SG biomass contained twice the amount of ash when compared to the 6-in. (152.4 mm) SYP biomass. Our previous work has also shown that the 2-in. (50.8 mm) SYP biomass (4,595 mg/kg) contained significantly higher amounts of combined alkali and alkaline earth metals (Ca, K, Mg, Na) when compared to SG (2,198 mg/kg) and 6-in. (152.4 mm) SYP (2,472 mg/kg) biomasses (Edmunds et al., 2018). The carbon content of SYP was also appreciably higher than the SG, but the HHV differed by only 5% between these raw materials. Ash could reduce the performance of biomass conversion reactors, whereas alkali and alkaline earth metals can specifically affect the composition and yield of downstream products during thermochemical conversion of lignocellulosic feedstocks (Edmunds et al., 2018; Kim et al., 2018). Hence, blending these raw materials could potentially reduce heterogeneity and improve their downstream conversion properties.

In the case of the 100% pine pellets, 5–10% (w.b.) moisture loss was observed during the pelleting process. A higher moisture loss of 10% (w.b.) was observed at a lower L/D ratio of 5 compared to L/D ratios of 7 and 9. The unit, bulk, and tapped densities at different moisture levels and L/D ratios were in the range of 1,096–1,169, 471–569, and 518–616 kg/m³, respectively. The durability was in the range of 89–95%, where a higher L/D ratio and lower moisture content were found to be beneficial. The physico-chemical properties of all pellet blends are provided in Table 3, Supplementary Tables S2 and S3, and the appearance of the pellets is depicted in Figure 2.

In the case of the 75% pine pellets, there was a moisture loss of 6–8% (w.b.). A higher moisture loss was observed at a higher L/D ratio of 9 and higher blend moisture content of 25% (w.b.). The unit, bulk, and tapped densities were in the range of 799–1,117, 450–573, 499–631 kg/m³, respectively, and the durability was 85–93%. A higher moisture content and a lower L/D ratio reduced the density and durability of 75% pine pellets.

In the case of the 50% pine pellets, a moisture loss of 6–10% (w.b.) was observed during pelleting and a higher L/D ratio of 9 as well as a higher blend moisture content of 25% (w.b.) resulted in greater losses. The unit, bulk, and tapped densities were in the range of 1,087–1,115, 516–572, 569–623 kg/m³, respectively, and the maximum durability was observed for a lower blend moisture content and L/D ratio of 9. Overall, the durability values were in the range of 85–95% for the different pelleting parameters.

For the 25% pine pellets, a moisture loss in the range of 5–9% (w.b.) was observed, and a higher blend moisture content of 24% (w.b.) and a L/D ratio of 9 resulted in greater losses. The unit, bulk, and tapped densities were the lowest at an L/D ratio of 5 and a blend moisture content of 19% (w.b.). Overall, the unit, bulk, and tapped densities were in the range of 889–1,146, 465–607, 510–654 kg/m³, respectively. The lowest durability of 83% was observed at an L/D ratio of 5 and a blend moisture content of 20% (w.b.), whereas a maximum durability of 95% was observed at a L/D ratio of 9 and a moisture content of about 20% (w.b.).

In the case of the 100% SG pellets, the moisture loss was similar to 100% pine pellets (about 5–10%, w. b.), but interestingly, higher moisture losses were recorded at higher L/D ratios of 7 and 9. The unit, bulk, and tapped densities were between 991 and 1,156, 499–552, and 546–621 kg/m³, respectively, and durability was between 85 and 95%. Overall, higher L/D ratios of 7 and 9 and a lower moisture content of about 20% (w.b.) maximized the durability of 100% SG pellets, as can be seen in Table 3.

Drying the pellets at 70°C for 2–3 h was aimed at reducing the moisture content to <10% (w.b.); however, it also affected pellet density and durability. In the case of unit density, a loss of about 40–50 kg/m³ was observed, whereas the bulk and tapped densities decreased by 20–25 kg/m³. The pellet durability changed between −4.7% and +1.9%, and most pellet treatments experienced a decrease in durability because of low temperature drying, as observed in Supplementary Table S2. The trends observed for blended SYP and SG pellets in terms of bulk density and durability matched our earlier studies with corn stover, lodgepole pine, and municipal solid waste (MSW) (Tumuluru, 2014; Tumuluru et al., 2015; Tumuluru, 2016; Tumuluru and Mwamufiya, 2021), where higher moisture in the biomass reduced the density and higher L/D ratio increased the durability.

Specific energy consumption (SEC) of the pelleting process was determined as per Eq. 1 and provided in Table 3. Based on the results, a higher pelleting moisture and L/D ratio led to an increase in pelleting energy. In the case of 100% pine pellets, the lowest energy consumption was observed at 20% (w.b.) pelleting moisture and an L/D ratio of 9, as can be seen in Table 3. Increasing the moisture content increased the pelleting energy to 130–140 kWh/ton for different L/D ratios. Compared to 100% pine, the 100% SG pellets consumed more energy. For example, at an L/D ratio of 9 and 20% (w.b.) moisture content, energy consumption of 100% SG pellet was 123 kWh/ton, whereas the 100% pine only consumed 105 kWh/ton of energy. Further increasing the moisture content and lowering the L/D ratio to 5 increased the pelleting energy to about 176 kWh/ton. In the blended feedstocks, higher amounts of pine (75%) reduced the energy consumption to about 102–110 kWh/ton for the L/D ratios of 7 and 9. In the case of the 50% pine biomass, energy consumption increased to a range of 124–155 kWh/ton for the different L/D ratios (5–9) and moisture contents (20–25%, w. b.). In the case of 75% SG blends, the lowest energy consumption (125 kWh/ton) was observed at a pelleting moisture content of 20% (w.b.) and an L/D ratio of 9.

Multivariate models constructed by combining the NIR data and the pelleting process variables indicated that the L/D ratio (R² = 0.72) and bulk density (R² = 0.50) had positive correlations with pellet durability, as shown in Supplementary Figure S1 (Supplementary data), whereas the pine content (R² = 0.26) exhibited a mild negative correlation to the bulk density, and the pelleting moisture content had no correlation to the pellet bulk density (R² = 0.09) or durability (R² = 0.002). Hence, we determined that an L/D ratio of 9 is desirable to improve pellet durability, whereas the blending of pine residues with SG would improve pelleting energy consumption.

Following the preliminary pilot-scale studies on SYP, SG, and their blends, subsequent demonstration on a 2.5-ton scale were conducted. The L/D ratio of 9 and moisture content of about 20% (w.b.) were selected since these pelleting conditions resulted in higher pellet quality, in terms of bulk density and durability, at lower energy consumption. Pine top residues of 2-in. (50.8 mm) and 6-in. (152.4 mm) diameter were selected to investigate the impact of lower quality feedstock (i.e., 50.8 mm pine tops) on final pellet properties. The grind properties, namely geometric mean particle length and D50 (median particle size) of the 2-in. (50.8 mm) pine residues were 1.22 and 1.30 mm, respectively, and those of 6-in. (152.4 mm) pine residues were 0.99 and 1.06 mm, respectively. The grinding energies for 2-in. (50.8 mm) and 6-in. (152.4 mm) pine residues were 24.3 and 23.3 kWh/ton, respectively. Hence, the pelleting properties were not significantly different for the two types of pine residues tested.

On the other hand, differences in physical properties of the pellets were observed due to the pine blend ratio and pine residue size, as shown in Table 5. In the case of 6-in. (152.4 mm) pine residues, the 60% blend resulted in higher unit density, but the bulk and tapped density, as well as the durability, were not significantly different compared to the 50% blend. The energy consumption was slightly higher for the 50% blend of 6-in. (152.4 mm) SYP at 98 kWh/ton when compared to the 60% blend (89 kWh/ton). In the case of 2-in. (50.8 mm) SYP residues, a 60% blend produced pellets with lower unit, bulk, and tapped densities, as well as durability, but the SEC was lower at 87 kWh/ton than that of the 50% blend (95 kWh/ton). Among the four tested blends, 2-in. (50.8 mm) SYP-60 produced lower quality pellets, whereas 6-in. (152.4 mm) SYP-50 produced comparably higher quality pellets. Higher SYP content led to lower pelleting energy consumption. Changes in pine blend ratio and stem diameter had no significant effect on the elemental composition, ash content, and HHV of the pellets, as shown in Table 5, which shows that blending of 6-in. (152.4 mm) and 2-in. (50.8 mm) pine tops with SG led to homogenization of chemical properties.

Edmunds et al. (2018) observed that the major advantage of blending woody and herbaceous biomass, such as pine and SG, is the improvement in chemical composition. The limitations of herbaceous biomass for bioenergy production are their lower energy density, issues related to storage, handling, and transportation (Sahoo and Mani, 2016; Sahoo and Mani, 2017). According to Edmunds et al. (2018), Tumuluru et al. (2015), and Sahoo and Mani (2017), herbaceous biomasses typically have a bulk density of 150–160 kg/m³. Ray et al. (2017) concluded that low density biomasses require more resources for transportation and shipping, which increases cost. These limitations pose a severe challenge to the utilization of herbaceous biomass on a commercial scale. In addition, woody biomasses have higher carbon and lower ash contents, whereas herbaceous biomasses have lower carbon and higher ash contents. Blending with woody biomass could therefore help to overcome herbaceous feedstock limitations regarding carbon and ash content and improve their specifications for different conversion scenarios. In thermochemical conversion, desired specifications are high calorific value, and carbon content, but low volatiles, nitrogen, and ash contents. Most herbaceous biomasses, such as corn stover and SG, have higher ash content, lower calorific value, and lower carbon content. Hence, Tumuluru and Fillerup (2020) concluded that blending SG and corn stover with lodgepole pine helped to improve the proximate and ultimate composition and calorific value and made the feedstocks more suitable for preprocessing, such as densification, and for further downstream conversion.

A major challenge of blending woody and herbaceous biomass is particle segregation during storage, feeding, and handling. One approach to address this challenge is to densify the blended biomass. Tumuluru et al. (2011) suggested that pellet mills, briquette presses, cubers, agglomerators, and tablet presses help to improve the bulk density of biomass feedstocks. Densification not only improves the density, but also avoids particle segregation. Among the various densification systems, pelleting is the most used method for densifying the biomass. But the major challenge in using pellets for biorefinery operations is the cost. Drying biomass to less than 10% (w.b.) moisture content for future pelleting is the major energy consumer in conventional pelleting processes (Lamers et al., 2015). At Idaho National Laboratory we have developed a high-moisture pelleting process that eliminates the high-temperature drying step in pellet production, thus reducing the cost and making pelleting an environment-friendly process. Eliminating high-temperature drying also reduces volatile organic emissions during pelleting. In a techno-economic analysis, Lamers et al. (2015) indicated that a 40% reduction in pellet production costs could be achieved by switching to low temperature dryers, such as grain or belt dryers that operate at a significantly lower cost. In addition, the major advantage of high-moisture pelleting is the versatility of designing pellets with different densities, whereas the conventional method would produce pellets with very high densities (>700 kg/m³) that are more suitable for long-distance transportation. According to Tumuluru (2016), if pellets are transported by truck, very high bulk densities are not needed to fill the truck to its full capacity. If the pellets are to be transported shorter distances, such as 200–300 miles, they do not need to meet the durability standards set for long-distance transportation. Tumuluru (2016) also suggested that the cost of pellet production using conventional methods cannot be completely offset by saving on transportation costs, especially if the transportation distances are less than 200–300 miles. A recent study conducted by Tumuluru and Mwamufiya (2021) found that transportation costs decreased by about 43% for MSW pellets as compared to non-pelleted material if the transportation distance was >15 miles. Therefore, the high-moisture pelleting tested in this study can make pelleting more cost-effective and environmentally friendly for biorefineries, as it avoids the expensive drying methods commonly used by the industry.

Biomass physical and chemical properties significantly affected pellet quality. The lignin component of plant biomass is considered as a natural binding agent and plays an essential role in the densification process in terms of pellet quality and energy consumption. In the present study, SYP residues containing higher lignin required less pelleting energy as compared to SG. Also, blending SYP with SG helped to reduce the SEC and improved pellet properties, such as durability. Studies conducted by Tumuluru and Fillerup (2020) on briquetting blends of lodgepole pine, SG, and corn stover showed that the addition of pine decreased energy consumption and increased the durability of SG briquettes. Tumuluru et al. (2012) also found that grasses have lower lignin content, require higher pelleting energy, and produce pellets with lower density and durability. This limitation can be overcome by blending grasses with woody biomass. The current study also indicated that, blending SYP with SG improved the chemical composition—especially the lignin and ash contents—and particle size distribution, which helped to produce good quality pellets at lower energy consumption. In addition, blending improved the pelleting characteristics due to better interlocking ability and flowability of the biomass in the pellet die.

Tumuluru and Fillerup (2020) studied the briquetting characteristics of woody and herbaceous biomass blends and concluded that the blend moisture content and screen size of the grind affected briquette quality. A smaller hammer mill screen (4.8 mm size) and a lower blend moisture content of 12% (w.b.) resulted in the maximum unit and bulk density values. Our current results indicated that both moisture content and compression ratio of the die (L/D ratio) affected pellet quality. An L/D ratio of 9 and a lower moisture content of 20% maximized the pellet unit, bulk, and tapped densities. Said et al. (2015) studied the pelleting of rice straw in a flat die mill and showed that the bulk density decreased with an increase in moisture content, as observed in the present study. Studies conducted by Jackson et al. (2016) on corn stover at about 20–26% (w.b.) moisture content showed that pellets with bulk densities between 500 and 600 kg/m³ could be produced. Serrano et al. (2011) used barley straw and came to a similar conclusion that pellet bulk density decreases with an increase in the moisture content of the feedstock. Rhén et al. (2005) investigated the pelleting of Norway spruce at different preheating temperatures and pressures and reported that preheating temperature and moisture content significantly affected the bulk density of the pellets. These observations have been corroborated by the present research findings, whereas higher moisture reduced the bulk density of the SG-SYP pellets.

Studies on rice straw pelleting in a flat die mill by Said et al. (2015) concluded that increasing the moisture content to 17% (w.b.) increased pellet durability. Studies on briquetting the blends of woody and herbaceous biomass by Tumuluru and Fillerup (2020) indicated that durability increased with an increase in hammer mill screen size to 12.7 mm and increasing the moisture content to 15–18% (w.b.). These authors reasoned that increases in briquette durability could be because of the interlocking of larger particles during the compression and extrusion processes. Harun and Afzal (2015) found that higher percentages of woody biomass in the blend of pine and SG increased the pellet strength and durability values. The present research corroborates this observation and supports that the blending SYP with SG produces a good quality pellet in terms of density and durability. Pelleting studies conducted by Tumuluru (2018) using high-moisture woody and herbaceous biomass also determined that woody biomass with higher lignin content produced pellets with higher bulk density and durability. In the present study, pellets produced using pure SYP had higher durability values of >95% at a lower moisture content and higher L/D ratio of the pellet die. For SG, the maximum durability was 95% for a higher L/D ratio of 9 and feedstock moisture content of 20 and 25% (w.b.). The lower durability values of pure SG pellets could be attributed to the lower lignin content. But blending SG with SYP improved the pellet durability at a lower L/D ratio and higher moisture content. Our study also showed that a higher L/D ratio resulted in higher durability of the pellets, which may be because higher residence times of pine and SG particles in the die could induce glass transition of the lignocellulosic components and promote particle binding.

Moisture loss of about 5–10% (w.b.) was observed when SYP and SG blends were pelleted at higher moisture content of 20 and 25% (w.b.). This observation corroborates our earlier works (Tumuluru, 2014; Tumuluru, 2016; Tumuluru, 2019) on corn stover, SG, and lodgepole pine blends, where the loss of moisture depended on the initial moisture content of the feedstock. Higher initial moisture content and larger L/D ratios led to greater moisture losses during pelleting. Moisture losses may occur during pelleting due to flash-off when the pellets are compressed and extruded out of the die. Tumuluru (2016) reasoned that losing moisture during pelleting can be attributed both to frictional heat developed in the die and to further cooling, which can dry most of the pellet surface moisture, resulting in partially dried pellets.

Multivariate predictive models constructed based on at-line or in-line NIR spectroscopic analysis could be a valuable resource for high-throughput and inexpensive characterization of chemical and physical changes in lignocellulosic feedstocks during thermochemical or physico-chemical conversion processes (Li et al., 2018; Hwang et al., 2021). Previous research has shown that NIR analysis in the 900–1700 nm region could be coupled with chemometric approaches to predict the cellulose (R² = 0.92), hemicellulose (R² = 0.84), and lignin (R² = 0.71) contents of various types of lignocellulosic pellets like corn stover, rice straw, pine, mahogany, and rubber wood (Feng et al., 2018). PLSR models developed based on NIR spectra have been used to predict HHV (R² = 0.92), carbon (R² = 0.85), and ash (R² = 0.51) content of bamboo culms (Posom and Sirisomboon, 2017). The moisture content (R² = 0.99) and calorific value (R² = 0.99) of dedicated bioenergy crops like Miscanthus and short rotation coppice willow have also been predicted with higher precision using the NIR-PLSR models (Fagan et al., 2011). However, prediction of ash content (R² = 0.58) was poor for these lignocellulosic feedstocks (Fagan et al., 2011).

Our previous study has shown that PLSR models developed based on Fourier transform infrared spectra could predict the ash content of hybrid poplar wood and bark, as well as SG biomass, with a higher accuracy (R² = 0.98; RMSE = 0.38–0.40%) (Edmunds et al., 2017). In this study, we employed NIR spectroscopy such that we could collect the pellet samples from the outfeed conveyor and perform rapid “at-line” or “off-line” characterizations. Despite the higher moisture content (11–16%) and temperature (50–55°C) of the pellet samples, at-line NIR spectroscopy provided comparable information to that of off-line NIR spectroscopy. Through the integration of pelleting process parameters, we could build a very good PLSR model (R² _c = 0.96; RMSE = 0.04–0.1%) for predicting the pellet ash content based on the at-line NIR spectra. However, the prediction accuracy of moisture, HHV, and carbon content was not comparably significant (R² _c = 0.81–0.85). Since PLSR modeling of lignocellulosic feedstocks is affected by the number of samples and the chemical composition range of the calibration and validation set (Kline et al., 2016), there is room for future improvement. Thus, at-line NIR spectroscopy was successfully deployed during the pelleting demonstration and multivariate models were developed for determining the chemical composition of blended feedstocks.

The robustness of PLSR prediction models improved significantly with the use of off-line NIR spectroscopy. Despite the smaller sample size (N = 30), wider variability of the pine and SG blends enhanced the prediction capability. Integration of pelleting process information with the NIR PCA scores improved the predictability of pellet pine ratio, ash content, HHV, bulk density, and durability (R² _c improved from 0.64 to 0.94) when compared to only using the NIR spectra. In previous research, integration of process temperature with online NIR spectroscopy enabled the PLS prediction of transesterification efficiency and bio-diesel production from soybean oil (Killner et al., 2011). In the near future, NIR-based sensing and multivariate modeling tools could be applied to develop machine learning techniques that can integrate in-/on-line data directly with process controllers to achieve real-time management of bioproduct manufacturing (Gargalo et al., 2020). Our work also provides the incentive for adapting NIR sensing to monitor industrial scale processing of lignocellulosic feedstocks.

Another important aspect of this study is the utilization of at-line NIR spectroscopy to classify the pellets based on the pine quality and blend ratio. In recent times, blending of feedstocks like that of pine and SG are often recommended to offset the uncertainty of continuous feedstock supply, and to improve the economic feasibility of biorefineries (Ray et al., 2017; Lan et al., 2020). Blending of lignocellulosic feedstocks has the advantage of homogenizing the conversion attributes of pellets, namely the moisture and ash contents (Tumuluru et al., 2012; Edmunds et al., 2018; Lan et al., 2020). Hence, developing a rapid NIR-based screening tool for the “quality control” attributes of blended lignocellulosic feedstocks will ensure successful implementation and operations of biomass conversion facilities. We periodically scanned a 2.5-ton feed of blended pine and SG pellets and developed at-line NIR spectroscopy-based PCA models. Results of PCA showed NIR signals from blended pellets containing higher quality pine residues (152.4 mm tops) and larger percentage of pine (60%) could be isolated based on their chemical signature for cellulose, hemicellulose, and lignin. To our knowledge, this will be the first study that utilizes at-line NIR spectroscopy to classify blended lignocellulosic feedstocks that are of notable relevance for bioenergy production in the U.S.