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Harvested hay or biomass are traditionally baled for better handling and they are transported to the outlet for final utilization. For better management of bale logistics, producers often aggregate bales into stacks so that bale-hauling equipment can haul multiple bales for improved efficiency. Objectives of this research include simulation of bale collection logistics after forming subfield stacks, evaluation of location effects of bale stack and field outlet, the number of stacks, transported bales/trip, and other field parameters on logistics distances (aggregation, transportation, and total). The software ‘R’ performed the simulation, statistical analysis, and data visualization. Formation of bale stacks decoupled aggregation and transportation components. Stacks formation thus allows for aggregation and transportation to be performed at different times. Increasing the number of subfield stacks and the number of transported bales/trip significantly reduced the total logistics distances. The order for the best bale stack and outlet locations was: middle, near middle, mid-edge along the length, mid-edge along the width, and finally, corners. Except for swath and windrow variation, the studied field variables had a highly significant influence on the logistics distances. Increased bales/trip (≥6) reduced the variations of outlet locations. Locating the field outlet at or near the center of the field along with an appropriate number of square subfields with stacks at the middle, and increased bales/trip will be the most efficient infield logistics strategy. [ABSTRACT FROM AUTHOR]

Abstract: Biomass bales often need to be aggregated (collected into groups and transported) to a field-edge stack or a temporary storage before utilization. Several logistics scenarios for aggregation involving equipment and aggregation strategies were modeled and evaluated. Cumulative Euclidean distance criteria evaluated the various aggregation scenarios. Application of a single-bale loader that aggregated bales individually was considered as the “control” scenario with which others were compared. A computer simulation program developed determined bale coordinates in ideal and random layouts that evaluated aggregation scenarios. Simulation results exhibited a “diamond pattern” of bales on ideal layout and a “random pattern” emerged when ≥10% variation was introduced. Statistical analysis revealed that the effect of field shape, swath width, biomass yield, and randomness on bale layout did not affect aggregation logistics, while area and number of bales handled had significant effects. Number of bales handled in the direct method significantly influenced the efficiency. Self-loading bale picker with minimum distance path (MDP, 80%) and parallel transport of loader and truck with MDP (78%) were ranked the highest, and single-bale central grouping the lowest (29%) among 19 methods studied. The MDP was found significantly more efficient (4%–16%) than the baler path. Simplistic methods, namely a direct triple-bale loader with MDP (64%–66%), or a loader and truck handling six bales running parallel with MDP (75%–82%) were highly efficient. Great savings on cumulative distances that directly influence time, fuel, and cost were realized when the number of bales handled was increased or additional equipment was utilized. [Copyright &y& Elsevier]

Infield bale aggregation is essential for bale removal and preparing the field for subsequent crops, which can be more efficiently performed using the modern automatic bale picker (ABP) that supports multiple bales/trip (BPT) than commonly used tractors. But the energy involved in the bale aggregation logistics using ABP has not been thoroughly evaluated. Therefore, the energy involved in the bale aggregation, in terms of fuel consumption, was studied for different logistic scenarios using a tractor (control) and ABP through a user-developed simulation program in R. Different variables such as field areas (8 to 259 ha), biomass yields (3–40 Mg ha − 1), four outlet locations, and five equipment speeds (6.6–10.5 km h − 1) using realistic equipment turning paths were used in the simulation. The Nebraska Tractor Test general method and fuel efficiency method were considered for the fuel consumption calculations. Fuel consumption for the ABP (8–259 ha) with 8 BPT on an average decreased by 72 % and 53 % compared to a tractor with 1 and 2 BPT, respectively, based on logistics distance and equipment operation. Field area, biomass yield, and BPT were the most influential variables affecting logistics distance; while, field area, biomass yield, BPT, and equipment speed affecting the operation time and fuel quantity. Convenient prediction models (multi-variate nonlinear) for logistics distance, operation time, and fuel quantity, using the influential field variables, produced very good fits ( R 2 ≥ 0.98). Overall, an ABP with a capacity of 8 BPT, split which can also handle 11 BPT, is recommended considering the logistics energy. • Bale aggregation with tractor and automatic bale picker (ABP) were simulated using R. • Field area, biomass yield, and bales/trip (BPT) were influential variables for modeling. • ABP with 8 BPT greatly decreased the logistics distance and fuel compared to tractor. • Multi-variate models predicted logistics distances, operation time, and fuel quantity. [ABSTRACT FROM AUTHOR]