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 offer 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 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,
5,
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 effects 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 effects 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, differentiate 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 efficiency 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 efficiency 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 efficiency 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:
where:
Cm = material capacity sometimes referred to as throughput, Mg/h
v = field speed, km/h
W = implement working width, m
Ef = field efficiency, decimal
Y = unit yield of the field, Mg/ha
K1 = 10 km-m/ha.
Some models calculate capacity in their simulation using the typical average speed, field efficiency, 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 effective speed (green line) is a speed with the field efficiency incorporated, and the field capacity (blue line) is constant over the range of yields. The throughput (red line) is linearly related to yield as given in Equation (1). Srivastava et al. [
8] stated that capacity measurements can be on the basis of area covered per unit time (field capacity, C
f, ha/h) or of material processed per unit time (C
m, Mg/h), and these two capacities are related by the following:
The travel speed of balers, forage choppers, and other machines used to harvest herbaceous biomass are limited by the throughput (Cm) of the machine; these are capacity-limited machines. For a 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
mx) is introduced into the machine. The yield (Y
c) at which the maximum throughput is achieved can be expressed as:
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 throughput (C
mx = 30.8 Mg/h) is reached.
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 too low, there is good potential that machines will be capacity-limited in high-yielding energy crops [
6]. As a result, the relationship used in models must use a lower field capacity than expected based on the ASABE data [
9]. The lower field capacity impacts the number of machines required to harvest a given 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 called field capacity (C
f, ha/h) and is a product of the processing width and effective speed of the machine. Since width and speed are easily measured, field capacity measurements are not complex. For forage machines, such as mowers, rakes, mower-conditioners, or windrowers, the material handling capacity may not be as critical and only the field capacity is measured. The key issue is to better understand the machine’s maximum throughput limits. Maximum throughput has not been advertised by the manufacturers because the value is impacted by crop characteristics and operator skill, however this value is a critical parameter to properly assess machine performance in high-yield conditions [
6].
Most machines will not reach maximum throughput in convention forage harvesting. Occasionally, if a baler is used to bale a windrow that has been created by raking multiple rows into a single windrow, it can be operated near or exceed its maximum throughput. In this case, the machine’s performance will be altered as shown in
Figure 2.
The material handling capacity is very important for both forage harvesters and balers (and equipment in higher throughput situations). Material handling capacity is the maximum feed rate (maximum throughput, C
mx) that can be accommodated on a sustained basis. This typically is a design limitation of the machine. For example, the feed mechanism of a chopper is adjusted so that it is sequenced with the forward speed. Forage harvester throughput is the product of mass processed per unit travel distance (for example, kg/m) times the forward speed of the harvester (km/h). 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 effective 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 distance and then weighed. Feed rate can be determined for a baler by measuring the average time required to produce a bale and weighing to determine the mass in an average bale [
11]. When the machine operates in a field with a high yield, the field capacity (ha/h) decreases because of a reduction in field efficiency (more bales dropped per unit area), and because the operator is reducing the forward speed to limit the amount of material flowing through the machine. If the equipment is operating at maximum throughput (C
mx) in a field with yield (Y), the effective travel speed with an operating width (W), is given by:
where:
ve = the effective field speed, including a consideration of field efficiency, km/h.
Impact of Higher Yield on Round Balers
Since the round baler stops to wrap and eject a bale, field capacity (ha/h) is directly impacted when there are more bales per unit area harvested. The mass of a single bale (B
m) 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 achieved field capacity (C
fa) is given by:
where:
Bm/Cm = the time to form a bale, h
tw = time to wrap/eject a bale, s
K2 = 3600 s/h.
Throughput (C
m), with wrap/eject time, can be used to calculate an “achieved” capacity:
In this form of the achieved capacity equation, it is easier to see the impact of the wrap/eject time has on the constant capacity assumption (
Figure 3). The impact of cumulative wrap/eject time on achieved field capacity as yield increases is large and does impact the capacity parameter used in most models.
Since the system efficiency (E
s = E
f × E
e) can be represented by 2 terms, E
f dealing with the productivity issues and E
e representing the wrap/eject process, Equation (6) can be rewritten as:
where: E
e, the wrap/eject efficiency, is given by:
This shows that the wrap/eject efficiency is a function of the input variables (Cm, with v, W, and 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 (tw), the mass of an average bale (Bm), and 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 efficiencies could remain together, one component is a function of yield and may reinforce that additional modelling consideration is warrantied especially when yields are high.