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R. Bello, M. Bello (2015)
Agricultural Machinery Management
Jude Liu, R. Grisso, J. Cundiff (2013)
Harvest Systems and Analysis for Herbaceous Biomass
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Large square baling and bale handling efficiency - a case study.Agricultural sciences, 2012
J. Cundiff, R. Grisso, D. McCullough (2011)
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AgriEngineering Concept Paper Predicting Field Eciency of Round-Baling Operations in High-Yielding Biomass Crops 1 , 1 2 Robert “Bobby” Grisso * , John S. Cundi and Erin G. Webb Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, USA; jcundi@vt.edu Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA; webbeg@ornl.gov * Correspondence: rgrisso@vt.edu; Tel.: +1-540-231-1980 Received: 20 June 2020; Accepted: 19 July 2020; Published: 22 July 2020 Abstract: Model simulations for bioenergy harvest planning need to utilize equipment-capacity relationships for equipment operating under the high-yield conditions typical of a biomass crop. These performance assumptions have a direct bearing on the estimates of machine capacity, the number of machines required, and, therefore, the cost to fulfill the biorefinery plant demands for a given harvest window. Typically, two major issues in these models have been poorly understood: the available time required to complete the harvest operation (often called probability of workdays) and the capacity of the harvest equipment as impacted by yield. Simulations use annual yield estimates, which incorporate weather events, to demonstrate year-to-year eects. Some simulations also incorporate potential yield increases from genetically modified energy crops. There are limited field performance data for most current forage equipment used for harvesting high-yield biomass crops. Analysis shows that the impact of wrap/eject time for round balers resulted in a 50% reduction in achieved throughput capacity (Mg/h). After the maximum throughput is reached, the cost of the round bale operation (3.23 USD/Mg) is double that of the large-square baler (1.63 USD/Mg). The round baler achieved throughput capacity is 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler. Keywords: balers; machinery modeling; energy crop; geo-referenced data; harvest; herbaceous biomass; machinery management 1. Introduction Herbaceous biomass can contribute to the emerging bio-economy as a feedstock for electricity generation, process steam, liquid fuel, commodity chemicals, and other bioproducts. The Southeast USA has unique biomass potential [1] because of: high annual rainfall, considerable land that can be diverted to biomass production without significant competition with food and feed production, and an established woody biomass industry. Grasses, such as switchgrass, are one of the most significant potential sources of biomass. An advantage of switchgrass is that it can be harvested much like hay, which is a well-known operation amongst farmers in the region, and, unlike woody biomass, it provides an annual harvest, and, thus, provides an annual income to the producer. The two most commonly employed methods of grass harvesting are round and large-square baling. Although large-square balers can achieve a higher field capacity (ha/h), round bales oer several attractive features for the Southeast. Even in a humid environment, round bales can typically be stored under ambient conditions in the field, whereas large-square bales require covered storage. Round balers are less expensive to purchase and operate as they require smaller tractors than large-square balers, an advantage for the smaller farms [2]. Due to high variability of machine capacity within a field, a consistent relationship has not yet been developed for predicting in-field performance of round balers. Such data are needed to define and AgriEngineering 2020, 2, 447–457; doi:10.3390/agriengineering2030030 www.mdpi.com/journal/agriengineering AgriEngineering 2020, 2 448 simulate harvest of biomass for energy applications. Typically, two major issues are poorly represented in these models [3]: available working time during the time window in which the operation is required to be completed and the capacity of forage equipment as impacted by yield. Machinery performance assumptions have a direct bearing on estimates of the number of equipment units needed and the cost to fulfill biorefinery demand during the harvest window. There have been only a few published reports documenting field studies of switchgrass harvest experiments. Plus, most current forage equipment, and emerging technology modifications to this equipment, have limited performance data [4–6] for operation in high-yielding conditions. Simulation of annual yield estimates, which incorporate the weather during the growing season, are often integrated into these models to demonstrate year-to-year eects on biomass feedstock costs. Some simulations show the increased yield potential from genetically modified energy crops. As an example, the modified Integrated Biomass Supply Analysis and Logistics Model (IBSAL) [7] is applied to harvesting stover, straw, and switchgrass with yields ranging from 2 to 7 dry-Mg/ha for straw and stover, and 5 to 50 dry-Mg/ha for switchgrass. While many system eects of crop yield—such as supply radius [7]—have been studied, the impact of yield on round-baler performance has not been modeled. The mode of operation of round balers, to accumulate grass and then stop to wrap or tie and drop the bale, dierentiate it from other agricultural equipment that can be simulated as a continuous operation. Most agricultural field operations—such as planting, mowing and even rectangular baling—can be easily modeled as function of yield. Round baling, however, is not a continuous operation in that the baler must stop for a specified time to package and drop the bale. Whereas increasing yield typically increases field eciency of continuous field operations, the same is not true for a round baler. In both rectangular and round-baling, the number of bales per field is directly correlated to yield; assuming all bales have approximately equal mass, higher yielding fields produce more bales. As the number of bales increases, so does the number of times that the baler must stop. This time to package and drop bales can significantly decrease field eciency and is not accounted for in most previous modeling studies of herbaceous biomass harvest operations. The purpose of this study is to develop a mathematical relationship between yield and round-baling field eciency to predict how the capacity of biomass balers is impacted by high-yielding bioenergy crops. This relationship will be used in modeling a switchgrass harvest operation to more accurately quantify the impact of yield on harvest cost. 2. Materials and Methods Model simulations for bioenergy planning need to utilize equipment capacity when operating under actual field conditions. Throughput for agricultural machinery is expressed by Srivastava et al. [8] as: v W Y E C = (1) where: C = material capacity sometimes referred to as throughput, Mg/h v = field speed, km/h W = implement working width, m E = field eciency, decimal Y = unit yield of the field, Mg/ha K = 10 km-m/ha. Some models calculate capacity in their simulation using the typical average speed, field eciency, and width from the American Society of Agricultural and Biological Engineers (ASABE) Standards [9,10] and assume that these parameters remain constant regardless of yield. Machinery management relationships for these assumptions are shown in Figure 1. The eective speed (green line) is a speed with the field eciency incorporated, and the field capacity (blue line) is constant over the range of AgriEngineering 2020, 2 449 AgriEngineering 2020, 3 FOR PEER REVIEW 3 over the range of yields. The throughput (red line) is linearly related to yield as given in Equation (1). yields. The throughput (red line) is linearly related to yield as given in Equation (1). Srivastava et al. [8] Srivastava et al. [8] stated that capacity measurements can be on the basis of area covered per unit stated that capacity measurements can be on the basis of area covered per unit time (field capacity, time (field capacity, Cf, ha/h) or of material processed per unit time (Cm, Mg/h), and these two C , ha/h) or of material processed per unit time (C , Mg/h), and these two capacities are related by f m capacities are related by the following: the following: C = (2) (2) C = The travel speed of balers, forage choppers, and other machines used to harvest herbaceous The travel speed of balers, forage choppers, and other machines used to harvest herbaceous biomass are limited by the throughput (C ) of the machine; these are capacity-limited machines. For a biomass are limited by the throughput (Cm) of the machine; these are capacity-limited machines. For a given C , W, and Y, Equation (1) can be used to find the allowable or eective travel speed. given Cm, W, and Y, Equation (1) can be used to find the allowable or effective travel speed. Forage machines will jam if a throughput greater than the maximum design throughput (C ) is mx Forage machines will jam if a throughput greater than the maximum design throughput (Cmx) is introduced into the machine. The yield (Y ) at which the maximum throughput is achieved can be introduced into the machine. The yield (Yc c) at which the maximum throughput is achieved can be expressed as: expressed as: mx Y = (3) Y = C (3) Figure 1. Results obtained by assuming that speed and capacity are constant for all yields. Equations Figure 1. Results obtained by assuming that speed and capacity are constant for all yields. (1), (2), and (4) are used assuming operating parameters: W = 6.7 m, v = 10.9 km/h, Ef = 0.74, and Yc = Equations (1), (2) and (4) are used assuming operating parameters: W = 6.7 m, v = 10.9 km/h, E = 0.74, 5.6 Mg/ha. and Y = 5.6 Mg/ha. This relationship is shown in Figure 2 and compared with the result obtained with the constant This relationship is shown in Figure 2 and compared with the result obtained with the constant assumptions. The field capacity (ha/h) begins to decline, for example, when the maximum assumptions. The field capacity (ha/h) begins to decline, for example, when the maximum throughput throughput (Cmx = 30.8 Mg/h) is reached. (C = 30.8 Mg/h) is reached. mx The capacity limit feature is characteristic of all forage equipment. While most forage equipment The capacity limit feature is characteristic of all forage equipment. While most forage equipment used in conventional haying operations will never operate with this restriction because the yields are used in conventional haying operations will never operate with this restriction because the yields are too low, there is good potential that machines will be capacity-limited in high-yielding energy crops too low, there is good potential that machines will be capacity-limited in high-yielding energy crops [6]. [6]. As a result, the relationship used in models must use a lower field capacity than expected based As a result, the relationship used in models must use a lower field capacity than expected based on the on the ASABE data [9]. The lower field capacity impacts the number of machines required to harvest ASABE data [9]. The lower field capacity impacts the number of machines required to harvest a given a given area, which, in turn, impacts the harvest cost calculations. area, which, in turn, impacts the harvest cost calculations. The area that can be covered in unit time for an operation (planting, cultivation, harvesting) is The area that can be covered in unit time for an operation (planting, cultivation, harvesting) is called field capacity (Cf, ha/h) and is a product of the processing width and effective speed of the called field capacity (C , ha/h) and is a product of the processing width and eective speed of the machine. Since width and speed are f easily measured, field capacity measurements are not complex. machine. Since width and speed are easily measured, field capacity measurements are not complex. AgriEngineering 2020, 2 450 AgriEngineering 2020, 3 FOR PEER REVIEW 4 For forage machines, such as mowers, rakes, mower-conditioners, or windrowers, the material For forage machines, such as mowers, rakes, mower-conditioners, or windrowers, the material handling handling capacity may not be as critical and only the field capacity is measured. The key issue is to capacity may not be as critical and only the field capacity is measured. The key issue is to better better understand the machine’s maximum throughput limits. Maximum throughput has not been understand the machine’s maximum throughput limits. Maximum throughput has not been advertised advertised by the manufacturers because the value is impacted by crop characteristics and operator by the manufacturers because the value is impacted by crop characteristics and operator skill, however skill, however this value is a critical parameter to properly assess machine performance in high-yield this value is a critical parameter to properly assess machine performance in high-yield conditions [6]. conditions [6]. Figure 2. The impact of maximum throughput, showing how achieved field capacity and speed Figure 2. The impact of maximum throughput, showing how achieved field capacity and speed decrease as yield increases. Equations (1), (2), and (4) are used and assumed operating conditions are: decrease as yield increases. Equations (1), (2) and (4) are used and assumed operating conditions are: W = 6.7 m, v = 10.9 km/h, Ef = 0.74, Cmx = 30.8 Mg/h, Yc = 5.6 Mg/ha. W = 6.7 m, v = 10.9 km/h, E = 0.74, C = 30.8 Mg/h, Y = 5.6 Mg/ha. mx c Most machines will not reach maximum throughput in convention forage harvesting. Most machines will not reach maximum throughput in convention forage harvesting. Occasionally, Occasionally, if a baler is used to bale a windrow that has been created by raking multiple rows into if a baler is used to bale a windrow that has been created by raking multiple rows into a single windrow, a single windrow, it can be operated near or exceed its maximum throughput. In this case, the it can be operated near or exceed its maximum throughput. In this case, the machine’s performance machine’s performance will be altered as shown in Figure 2. will be altered as shown in Figure 2. The material handling capacity is very important for both forage harvesters and balers (and The material handling capacity is very important for both forage harvesters and balers equipment in higher throughput situations). Material handling capacity is the maximum feed rate (and equipment in higher throughput situations). Material handling capacity is the maximum (maximum throughput, Cmx) that can be accommodated on a sustained basis. This typically is a feed rate (maximum throughput, C ) that can be accommodated on a sustained basis. This typically mx design limitation of the machine. For example, the feed mechanism of a chopper is adjusted so that it is a design limitation of the machine. For example, the feed mechanism of a chopper is adjusted so is sequenced with the forward speed. Forage harvester throughput is the product of mass processed that it is sequenced with the forward speed. Forage harvester throughput is the product of mass per unit travel distance (for example, kg/m) times the forward speed of the harvester (km/h). The processed per unit travel distance (for example, kg/m) times the forward speed of the harvester (km/h). product of these two parameters then gives capacity in kg/h. The mass per unit distance can be The product of these two parameters then gives capacity in kg/h. The mass per unit distance can be measured before the material enters the harvester or as it leaves. One method uses the crop yield and measured before the material enters the harvester or as it leaves. One method uses the crop yield and effective machine width to obtain an estimate of the feed rate into the machine per unit of forward eective machine width to obtain an estimate of the feed rate into the machine per unit of forward travel. With the second method, the processed material is caught in a container for a given travel travel. distanc W eith and the then weigh second method, ed. Feed the ratepr can be d ocessed etermined fo material isr caught a baler by in measur a container ing the foraver a given age time travel distance requireand d to p then rodu weighed. ce a bale a Feed nd w rate eighcan ing t be o d determined etermine the for ma asbaler s in an by av measuring erage bale [ the 11].average When th time e machine operates in a field with a high yield, the field capacity (ha/h) decreases because of a reduction required to produce a bale and weighing to determine the mass in an average bale [11]. When the in field efficiency (more bales dropped per unit area), and because the operator is reducing the machine operates in a field with a high yield, the field capacity (ha/h) decreases because of a reduction forward speed to limit the amount of material flowing through the machine. If the equipment is in field eciency (more bales dropped per unit area), and because the operator is reducing the forward operating at maximum throughput (Cmx) in a field with yield (Y), the effective travel speed with an speed to limit the amount of material flowing through the machine. If the equipment is operating operating width (W), is given by: at maximum throughput (C ) in a field with yield (Y), the eective travel speed with an operating mx width (W), is given by: AgriEngineering 2020, 2 451 K C 1 mx AgriEngineering 2020, 3 FOR PEER REVIEW 5 v = (4) W Y where: v = the eective field speed, including a consideration of field eciency, km/h. K ⋅C 𝑣 = (4) W⋅Y Impact of Higher Yield on Round Balers where: ve = the effective field speed, including a consideration of field efficiency, km/h. Since the round baler stops to wrap and eject a bale, field capacity (ha/h) is directly impacted when Impact of Higher Yield on there are more bales Round Balers per unit ar ea harvested. The mass of a single bale (B ) is impacted by how the baler is operated. This factor is not addressed here. The time to form a bale and the time to Since the round baler stops to wrap and eject a bale, field capacity (ha/h) is directly impacted wrap/eject the bale can be easily measured. The achieved field capacity (C ) is given by: fa when there are more bales per unit area harvested. The mass of a single bale (Bm) is impacted by how the baler is operated. This factor is not addressed here. The time to form a bale and the time to wrap/eject the bale can be easily measured. The achiev med field capacity (Cfa) is given by: C = (5) fa B t m w C K m 2 C = (5) B t where: C K B /C = the time to form a bale, h m m where: Bm/Cm = the time to form a bale, h t = time to wrap/eject a bale, s tw = time to wrap/eject a bale, s K = 3600 s/h. K2 = 3600 sec/h. Throughput (C ), with wrap/eject time, can be used to calculate an “achieved” capacity: Throughput (Cm), with wrap/eject time, can be used to calculate an “achieved” capacity: C = (6) fa C = C t m w 1 +C ⋅ t (6) B K m 2 B ⋅ K In this form of the achieved capacity equation, it is easier to see the impact of the wrap/eject In this form of the achieved capacity equation, it is easier to see the impact of the wrap/eject time time has on the constant capacity assumption (Figure 3). The impact of cumulative wrap/eject time has on the constant capacity assumption (Figure 3). The impact of cumulative wrap/eject time on on achieved field capacity as yield increases is large and does impact the capacity parameter used in achieved field capacity as yield increases is large and does impact the capacity parameter used in most models. most models. Figure 3. Impact of bale wrap/eject time on achieved field capacity, speed, and achieved throughput. Figure 3. Impact of bale wrap/eject time on achieved field capacity, speed, and achieved throughput. Using Equations (1), (2), (4), and (6) and assuming operating conditions of: W = 6.7 m, v = 10.9 km/h, Using Equations (1), (2), (4) and (6) and assuming operating conditions of: W = 6.7 m, v = 10.9 km/h, E Ef = 0.74, Cmx = 30.8 Mg/h, Yc = 5.6 Mg/ha, Bm = 0.52 Mg, and tw = 32 s. = 0.74, C = 30.8 Mg/h, Y = 5.6 Mg/ha, B = 0.52 Mg, and t = 32 s. mx c m w AgriEngineering 2020, 2 452 Since the system eciency (E = E E ) can be represented by 2 terms, E dealing with the s f e f AgriEngineering 2020, 3 FOR PEER REVIEW 6 productivity issues and E representing the wrap/eject process, Equation (6) can be rewritten as: Since the system efficiency (Es = Ef × Ee) can be represented by 2 terms, Ef dealing with the C = C E E (7) fa f f productivity issues and Ee representing the wrap/eject process, Equation (6) can be rewritten as: C =C ⋅E ⋅E (7) where: E , the wrap/eject eciency, is given by: where: Ee, the wrap/eject efficiency, is given by: E = (8) t C 1 w m 1 + E = B K m 2 t ⋅ C (8) B ∙ K This shows that the wrap/eject eciency is a function of the input variables (C , with v, W, and This shows that the wrap/eject efficiency is a function of the input variables (Cm, with v, W, and E ) that are typically used in machinery management and cost models. The new functions that are Ef) that are typically used in machinery management and cost models. The new functions that are required for round bales is the time to wrap/eject per bale (t ), the mass of an average bale (B ), w m required for round bales is the time to wrap/eject per bale (tw), the mass of an average bale (Bm), and and the yield (Y). The yield can be an average for a given field or the annual average for all fields the yield (Y). The yield can be an average for a given field or the annual average for all fields harvested, thus it is a known input to the model. While the two eciencies could remain together, harvested, thus it is a known input to the model. While the two efficiencies could remain together, one component is a function of yield and may reinforce that additional modelling consideration is one component is a function of yield and may reinforce that additional modelling consideration is warrantied especially when yields are high. warrantied especially when yields are high. 3. Results 3. Results 3.1. Example Use of Relationships 3.1. Example Use of Relationships As an example, suppose a round baler with a working width (W) of 6.7 m, theoretical field speed As an example, suppose a round baler with a working width (W) of 6.7 m, theoretical field speed (v) of 0.9 km/h, and eective field eciency (E ) of 74%. The baler has a maximum throughput of (v) of 0.9 km/h, and effective field efficiency (Ef) of 74%. The baler has a maximum throughput of 30.8 30.8 Mg/h, thus the critical yield at the transition (Y ) is 5.6 Mg/ha. The baler creates bales with a mass Mg/h, thus the critical yield at the transition (Yc) is 5.6 Mg/ha. The baler creates bales with a mass (Bm) (B ) of 0.51 Mg and the time (t ) to wrap/eject a bale is 32 s. When field data is added in Figure 3, m w of 0.51 Mg and the time (tw) to wrap/eject a bale is 32 s. When field data is added in Figure 3, the the curves show the impact of both the maximum throughput restriction and bale warp/eject time curves show the impact of both the maximum throughput restriction and bale warp/eject time (Figure (Figure 4). Grisso et al. [3] provide measured field performance data, and this is shown in Figure 4 4). Grisso et al. [3] provide measured field performance data, and this is shown in Figure 4 for for comparison. comparison. Figure 4. Data from field observations [3] compared with Equations (1), (2), (4), and (6) and assuming Figure 4. Data from field observations [3] compared with Equations (1), (2), (4) and (6) and assuming operating conditions of: W = 6.7 m, v = 10.9 km/h, Ef = 0.74, Cmx = 30.8 Mg/h, Yc = 5.6 Mg/ha, operating conditions of: W = 6.7 m, v = 10.9 km/h, E = 0.74, C = 30.8 Mg/h, Y = 5.6 Mg/ha, f mx c Bm = 0.52 Mg, and tw = 32 s. B = 0.52 Mg, and t = 32 s. m w AgriEngineering 2020, 2 453 Similar findings were shown in Martelli et al. [12]. While operating in giant reed and switchgrass, they observed that throughput capacities in switchgrass were 11.9 and 12.1 Mg/h for a round and large-square baler, respectively. They also observed that the actual field capacity of the large-square baler was 35% (giant reed) and 18% (switchgrass) higher than the round baler. While the field eciency was more impacted in the giant reed (0.55) for the round baler compared to 0.74 for the large-square baler. They assumed the increase of biomass flowing through the balers was the reason for these dierences. They also noted the highest values of field eciency were measured with the large-square baler because this machine ties and ejects the bale without stopping, while the round baler stops to wrap/eject the bale, thus reducing the field eciency and, consequently, the actual field capacity. The values of capacity reported in the literature are highly variable and only in a few cases measured during field trials. Kemmerer and Liu [13] reported a field capacity of 13 Mg/h for switchgrass baling. Shinners et al. [5] reported productivity values, based on field trails, ranging from 17.7 to 20.3 Mg/h for switchgrass round-baling with net wrap and 25.2 Mg/h for large-square-baling, values in the range compared in our study. Womac et al. [6] reported productivity in round-baling switchgrass in the range 16.1 to 26.8 Mg/h but with an eective field speed ranging from 7.9 to 14.0 km/h. 3.2. Impact on Cost Calculations In the cost analysis, both round and square balers were used to show the impact of the throughput and yield on the cost to own and operate the machines. The cost factors and assumptions are shown in Table 1. The square baler has a higher purchase price and has higher maintenance costs when compared to the round baler. The balers were operated at 9 km/h, 7 m width, with a C at 71 Mg/h, mx and 75% eective field eciency. The round bales weighed 0.52 Mg and took (t ) 31 s to wrap/eject. Table 1. Machinery cost factors for the balers using the notation and definitions given in ASABE Standard [10]. Cost Factors Round Large-Square Purchase price (USD) 45,000 112,000 Design life (h) 1500 3000 Interest rate (%) 8% 8% Tax rate: 1.00% 1.00% Housing: 0.75% 0.75% RF 0.43 0.1 RF 1.8 1.8 Labor cost (including benefits) (USD/h) 15 15 Salvage value 10% 10% These balers were used to harvest switchgrass for a biorefinery that requires 3000 Mg/day. The results presented here are similar in focus to the analysis completed by Shastri et al. [14]. The analysis is based on having the annual potential of 1200, 960, 720, 480, and 240 h to perform the baling operation. The annual hours define the ability of a set of machines to complete the harvest in a scheduled time-frame. The results in Table 2 were calculated using the procedures given in ASABE Standard [10]. If a 10-h work day is assumed, then the annual hours can be completed in 120, 96, 72, 48, and 24 workdays, respectively. The hourly cost (operating plus ownership) over the chosen range of annual operating hours for the round baler ranged from 105 USD/h to 116 USD/h, while the large-square baler ranged from 116 USD/h to 142 USD/h. AgriEngineering 2020, 2 454 AgriEngineering 2020, 3 FOR PEER REVIEW 8 Table 2. Cost factors for balers as a function of annual use. (n = number of useful yrs of design life). Table 2. Cost factors for balers as a function of annual use. (n = number of useful yrs of design life). Round Baler Large-Square Baler Round Baler Large-Square Baler h n USD/h USD Annual n USD/h USD Annual h n USD/h USD Annual n USD/h USD Annual 12001200 1.1.33 105.37 1 105.37 26,44 126,4455 2.5 2.5116.06 1 116.06 39 139,271,271 960 1.6 106.02 101,781 3.1 117.68 112,973 960 1.6 106.02 101,781 3.1 117.68 112,973 720 2.1 107.11 77,118 4.2 120.38 86,676 720 2.1 107.11 77,118 4.2 120.38 86,676 480 3.1 109.28 52,454 6.3 125.79 60,379 480 3.1 109.28 52,454 6.3 125.79 60,379 240 6.3 115.80 27,791 12.5 142.01 34,081 240 6.3 115.80 27,791 12.5 142.01 34,081 Figures 5 and 6 show the increase in the number of round and large-square balers, respectively, Figure 5; Figure 6 show the increase in the number of round and large-square balers, that will be required as annual use and yield increases. As the number of available hours increases, it is respectively, that will be required as annual use and yield increases. As the number of available hours obvious that fewer bale units will be required. After the maximum throughput is reached by the baler, increases, it is obvious that fewer bale units will be required. After the maximum throughput is no additional balers are required as the yield increases. There is a dramatic impact on the eect of the reached by the baler, no additional balers are required as the yield increases. There is a dramatic wrap/eject time of the round baler, as observed in Figure 5. The round baler will need 10–25% more impact on the effect of the wrap/eject time of the round baler, as observed in Figure 5. The round balers due to loss in achieved field capacity. This will increase the need for additional labor (drivers) baler will need 10–25% more balers due to loss in achieved field capacity. This will increase the need and power units. for additional labor (drivers) and power units. Figure 7 shows the cost per Mg to bale the switchgrass with round and large-square balers. At low Figure 7 shows the cost per Mg to bale the switchgrass with round and large-square balers. At yields, the capacities of the two balers are about the same, as well as their costs. However, as the yield low yields, the capacities of the two balers are about the same, as well as their costs. However, as the increases—and the impact of the wrap/eject time greatly increases—the cost of the operation of the yield increases—and the impact of the wrap/eject time greatly increases—the cost of the operation of round baler increases, because the baler is moving material through the machine at a lower rate. After the round baler increases, because the baler is moving material through the machine at a lower rate. the maximum throughput is reached, the cost of the round bale operation (3.23 USD/Mg) is double that After the maximum throughput is reached, the cost of the round bale operation (3.23 USD/Mg) is of the large-square baler operation (1.63 USD/Mg). The round baler achieved throughput capacity is double that of the large-square baler operation (1.63 USD/Mg). The round baler achieved throughput more than 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler. This demonstrates capacity is more than 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler. This that no matter which baler is used, the best operating conditions for minimal cost (USD/Mg) occurs at demonstrates that no matter which baler is used, the best operating conditions for minimal cost maximum throughput (C ). mx (USD/Mg) occurs at maximum throughput (Cmx). Figure 5. Number of round balers required to supply a 3000 Mg/day biorefinery. The solid red line is Figure 5. Number of round balers required to supply a 3000 Mg/day biorefinery. The solid red line is the theoretical throughput capacity of the baler and the dashed line is the baler-achieved throughput the theoretical throughput capacity of the baler and the dashed line is the baler-achieved throughput after adjustment for the bale wrap/eject time. after adjustment for the bale wrap/eject time. AgriEngineering 2020, 2 455 AgriEngineering 2020, 3 FOR PEER REVIEW 9 AgriEngineering 2020, 3 FOR PEER REVIEW 9 Figure 6. The impact of the number of large-square balers required to supply a 3000 Mg/day Figure 6. The impact of the number of large-square balers required to supply a 3000 Mg/day biorefinery. The solid red line is the theoretical capacity of the baler (no consideration of design Figure 6. biorefinery T . hThe e imsolid pact o red f th line e numb is the er o theor f la etical rge-sq capacity uare balers required of the baler (no to supply a 30 consideration00 Mg/day of design maximum throughput) and the dashed line is the baler-achieved throughput after accounting for biorefinery. The sol maximum throughput) id red and lin the e is the theore dashed linetical is the capacity baler-achieved of the baler (no consi throughput after deratio accounting n of design for throughput restrictions. maximu throughput m throughp restrictions. ut) and the dashed line is the baler-achieved throughput after accounting for throughput restrictions. Figure 7. The cost per Mg to operate the square and round balers for annual use of 1200 h. The solid red line is the theoretical capacity of the baler and the dashed line is the baler-achieved throughput Figure 7. The cost per Mg to operate the square and round balers for annual use of 1200 h. The solid Figure 7. The cost per Mg to operate the square and round balers for annual use of 1200 h. The solid after accounting for throughput restrictions. red line is the theoretical capacity of the baler and the dashed line is the baler-achieved throughput red line is the theoretical capacity of the baler and the dashed line is the baler-achieved throughput after accounting for throughput restrictions. after accounting for throughput restrictions. The literature has several cost comparison studies with conflicting results. For example, in Martelli et al. [12] field trials, the baling costs with the round baler were less than the large-square The literature has several cost comparison studies with conflicting results. For example, in The literature has several cost comparison studies with conflicting results. For example, in baler for giant reed and switchgrass. They acknowledged that their analysis was optimized by Martelli et al. [12] field trials, the baling costs with the round baler were less than the large-square Martelli et al. [12] field trials, the baling costs with the round baler were less than the large-square baler excluding an inefficient annual underutilization of the machinery. Thorsell et al. [15] estimated a baler for giant reed and switchgrass. They acknowledged that their analysis was optimized by for giant reed and switchgrass. They acknowledged that their analysis was optimized by excluding lower cost for harvesting switchgrass while using a large rectangular baler than with a large-round excluding an inefficient annual underutilization of the machinery. Thorsell et al. [15] estimated a an inecient annual underutilization of the machinery. Thorsell et al. [15] estimated a lower cost bale system. Cundiff et al. [16] found values 2.5 times higher for a large-square baler than a round lower cost for harvesting switchgrass while using a large rectangular baler than with a large-round baler: 4.06 USD/Mg and 1.59 USD/Mg, respectively, in their analysis. Both of these simulated studies bale system. Cundiff et al. [16] found values 2.5 times higher for a large-square baler than a round did not compensate for the reduction of field capacity of the round baler experienced during biomass baler: 4.06 USD/Mg and 1.59 USD/Mg, respectively, in their analysis. Both of these simulated studies did not compensate for the reduction of field capacity of the round baler experienced during biomass AgriEngineering 2020, 2 456 for harvesting switchgrass while using a large rectangular baler than with a large-round bale system. Cundi et al. [16] found values 2.5 times higher for a large-square baler than a round baler: 4.06 USD/Mg and 1.59 USD/Mg, respectively, in their analysis. Both of these simulated studies did not compensate for the reduction of field capacity of the round baler experienced during biomass baling. We believe that adjusting according to Equation (8) will make these simulations more realistic to field conditions. 4. Summary and Conclusions A key relationship of round baler field performance was developed to show the impact of maximum throughput (C ) on baler field eciency and field capacity (ha/h). The assumption used in mx most prior biomass harvest modeling studies that capacity is negligibly impacted by yield is incorrect. Subsequently the number of machines required and the cost of round baler operations has often been underestimated. Impacts are shown for the round baler since a wrap/eject time is required for this baler. Relationships for the bale wrap/eject times were developed. In the round baler example, the impact of wrap/eject time was a 50% reduction in capacity. After the maximum throughput is reached, the cost of the round-baler operation (3.23 USD/Mg) is double that of the large-square-baler operation (1.63 USD/Mg). The round baler achieved throughput capacity is 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler. The function developed in this study to better account for the time required for round balers to package and drop bales in field eciency and field capacity calculations (Equation (8)) has application beyond studying the impact of yield on biomass harvest costs. It can also be applied to better predict the cost impacts of round baler design parameters, such as wrap or tie time and bale density. Multiple manufacturers have developed prototypes of continuous round balers. Assessing potential cost improvements of these more expensive continuous baler designs will require the more accurate assessment of conventional round-baler field performance provided in this study. Author Contributions: Conceptualization, R.B.G. and E.G.W.; methodology, J.S.C. and R.B.G.; writing—original draft preparation, R.B.G.; writing—review and editing, E.G.W. and J.S.C.; investigation, R.B.G. and E.G.W.; project administration, R.B.G. and E.G.W. All authors have read and agreed to the published version of the manuscript. Funding: This research was partially funded by the Department of Energy Oce of Biomass Program. Acknowledgments: The authors would like to express their appreciation to student worker, Aaron Bowman. Also, thanks go to Trip Webb for assistance with data analysis. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http: //energy.gov/downloads/doe-public-access-plan). Conflicts of Interest: The authors declare no conflict of interest. References 1. U.S. Department of Energy. U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry; Perlack, R.D., Stokes, B.J., Eds.; ORNL/TM-2011/224; Oak Ridge National Laboratory: Oak Ridge, TN, USA, 2011; 227p. 2. Liu, J.; Grisso, R.D.; Cundi, J.S. Harvest systems and analysis for herbaceous biomass, Chapter 6. In Biomass Now-Cultivation and Utilization; Book 2; Miodrag Darko Matovic, IntechOpen: London, UK, 2013; ISBN 980-953-51-1106-1. [CrossRef] 3. Grisso, R.D.; Moxley, G.; Webb, E.; Cundi, J.S.; Sokhansanj, S. In-field performance of hay balers using DGPS. In Proceedings of the 2013 ASABE Annual International Meeting, Kansas City, MO, USA, 21–24 July 2013; ASABE Paper No. 131538975. AgriEngineering 2020, 2 457 4. Bransby, D.I.; Sladden, S.E.; Downing, M. Yield eects on bale density and time required for commercial harvesting and baling of switchgrass. In Proceedings of the BIOENERGY ’96—The Seventh National Bioenergy Conference: Partnerships to Develop and Apply Biomass Technologies, Nashville, TN, USA, 15–20 September 1996. 5. Shinners, K.J.; Boettcher, G.C.; Muck, R.E.; Wiemer, P.J.; Casler, M.D. Harvest and storage of two perennial grasses as biomass feedstocks. Trans. ASABE 2010, 53, 359–370. [CrossRef] 6. Womac, A.R.; Hart, W.E.; Bita, V.S.P.; Kraus, T. Biomass harvesting of high-yield low-moisture switchgrass: Equipment performance and moisture relations. Appl. Eng. Agric. 2012, 28, 775–786. [CrossRef] 7. Sokhansanj, S.; Turhollow, A.F.; Wilkerson, E.G. Development of the Integrated Biomass Supply Analysis and Logistics Model (IBSAL); Technical Memorandum ORNL/TM-2006/57; Oak Ridge National Laboratory: Oak Ridge, TN, USA, 2008. 8. Srivastava, A.K.; Goering, C.E.; Rohrbach, R.P.; Buckmaster, D.R. Machinery Selection and Management. Chapter 15. In Engineering Principles of Agricultural Machines, 2nd ed.; Copyright American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2005; pp. 525–552. 9. ASABE. ASABE Standards, D497.7, Agricultural Machinery Management Data; Copyright American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2011. 10. ASABE. ASABE Standards, EP496.3, Agricultural Machinery Management; Copyright American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2006. 11. Grisso, R.D.; McCullough, D.; Cundi, J.S.; Judd, J.D. Harvest schedule to fill storage for year-round delivery of grasses to biorefinery. Biomass Bioenergy 2013, 55, 331–338. [CrossRef] 12. Martelli, R.; Bentini, M.; Monti, A. Harvest storage and handling of round and square bales of giant reed and switchgrass: An economic and technical evaluation. Biomass Bioenergy 2015, 83, 551–558. [CrossRef] 13. Kemmerer, B.; Liu, J. Large square baling and bale handling eciency e a case study. Agric. Sci. 2012, 3, 178–183. [CrossRef] 14. Shastri, Y.N.; Hansen, A.C.; Rodriguez, L.F.; Ting, K.C. Impact of probability of working day on planning and operation of biomass feedstock production systems. Biofuels Bioprod. Bioref. 2011, 6, 281–291. [CrossRef] 15. Thorsell, S.; Epplin, F.M.; Huhnke, R.L.; Taliaferro, C.M. Economics of a coordinated biorefinery feedstock harvest system: Lignocellulosic biomass harvest cost. Biomass Bioenergy 2004, 27, 327–337. [CrossRef] 16. Cundi, J.S.; Grisso, R.D.; McCullough, D. Comparison of bale operations for smaller production fields in the southeast. In Proceedings of the 2011 ASABE Annual International Meeting, Louisville, KY, USA, 7–10 August 2011; ASABE Paper No. 1110922. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
AgriEngineering – Multidisciplinary Digital Publishing Institute
Published: Jul 22, 2020
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