Berm-Leveling Machine for Peach Orchards: Incorporation of Tree-Sensing Feature and Profitability Study

Root collar excavation extends the productive life of peach trees in Armillaria root rot-infested soil, but the process requires trees to be planted on berms. Berm-planted peach orchards restrict the mobility of workers and machinery and can lead to increased erosion in furrows on either side of the berms. The current inter-tree berm-leveling machine depends on the driver's command to dodge the peach trees. The objectives of this thesis were to (1) integrate the feeler, infrared, and LiDAR-based tree sensing systems in the berm-leveling machine to make the soil excavating head's movement independent, (2) measure the impact of finger weeder-based mechanism in collapsing the standing berm mound around peach tree trunks, and (3) project the impact of owning and operating a berm-leveling machine on the Net Present Value (NPV) of ARR-infested peach orchards. The feeler, Single-Infrared Sensing (S-IRS), and Dual-Infrared Sensing (D-IRS)-based tree detection systems were installed into the berm-leveling machine and individually tested over experimental berms with stakes placed for peach trees. The sensing approaches were analyzed for berm-leveling precision, with the uniformity of the remaining berm mound’s length serving as a key indicator. The results of Fligner-Killeen and Levene’s variance tests suggest a practically equal degree of berm-leveling precision. The LiDAR sensor did not work continuously during field trials, inhibiting its data collection. The finger weeder mechanism did not create an immediate visible impact on the standing berm-mound volume during the field tests, and its quantitative assessment yielded inconclusive results. The berm-leveling machine's fixed and variable costs were estimated and used to estimate the impact of owning and operating it in ARR-infested peach orchards. The average NPV of hypothetical treatment orchards, where inter-tree berms were leveled using the berm-leveling machine, and conventional orchards, where berms were left in place, were simulated using Monte Carlo Simulation (MCS). The results indicated that adoption of the berm-leveling machine is less profitable, with the viability gap shrinking upon lower initial investment cost of the machine, lower peach yield, lower peach price, higher discount rate, early ARR outbreak, or higher ARR-caused tree mortality. Achieving concurrent leveling of the standing berm mounds left around the tree trunks can further enhance the value proposition of the berm-leveling machine and improve its profitability potential. To this end, evaluating stacked multiple finger weeders or larger tip finger weeder attachments offers one route of design improvement.

Publication Details

Journal
TigerPrints (Clemson University)
Published
2025-05-01
Primary Topic
Tree Root and Stability Studies
Type
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article

Berm-Leveling Machine for Peach Orchards: Incorporation of Tree-Sensing Feature and Profitability Study

TigerPrints (Clemson University)
Tree Root and Stability Studies
article

Berm-Leveling Machine for Peach Orchards: Incorporation of Tree-Sensing Feature and Profitability Study

article en

Abstract

Root collar excavation extends the productive life of peach trees in Armillaria root rot-infested soil, but the process requires trees to be planted on berms. Berm-planted peach orchards restrict the mobility of workers and machinery and can lead to increased erosion in furrows on either side of the berms. The current inter-tree berm-leveling machine depends on the driver's command to dodge the peach trees. The objectives of this thesis were to (1) integrate the feeler, infrared, and LiDAR-based tree sensing systems in the berm-leveling machine to make the soil excavating head's movement independent, (2) measure the impact of finger weeder-based mechanism in collapsing the standing berm mound around peach tree trunks, and (3) project the impact of owning and operating a berm-leveling machine on the Net Present Value (NPV) of ARR-infested peach orchards. The feeler, Single-Infrared Sensing (S-IRS), and Dual-Infrared Sensing (D-IRS)-based tree detection systems were installed into the berm-leveling machine and individually tested over experimental berms with stakes placed for peach trees. The sensing approaches were analyzed for berm-leveling precision, with the uniformity of the remaining berm mound’s length serving as a key indicator. The results of Fligner-Killeen and Levene’s variance tests suggest a practically equal degree of berm-leveling precision. The LiDAR sensor did not work continuously during field trials, inhibiting its data collection. The finger weeder mechanism did not create an immediate visible impact on the standing berm-mound volume during the field tests, and its quantitative assessment yielded inconclusive results. The berm-leveling machine's fixed and variable costs were estimated and used to estimate the impact of owning and operating it in ARR-infested peach orchards. The average NPV of hypothetical treatment orchards, where inter-tree berms were leveled using the berm-leveling machine, and conventional orchards, where berms were left in place, were simulated using Monte Carlo Simulation (MCS). The results indicated that adoption of the berm-leveling machine is less profitable, with the viability gap shrinking upon lower initial investment cost of the machine, lower peach yield, lower peach price, higher discount rate, early ARR outbreak, or higher ARR-caused tree mortality. Achieving concurrent leveling of the standing berm mounds left around the tree trunks can further enhance the value proposition of the berm-leveling machine and improve its profitability potential. To this end, evaluating stacked multiple finger weeders or larger tip finger weeder attachments offers one route of design improvement.

TigerPrints (Clemson University)
Openalex Percentile: Top 53%
Tree Root and Stability Studies
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