A framework for evaluating labor utilization and cost-saving strategies in mushroom harvesting through robotics

• Framework developed to evaluate labor utilization in large-scale mushroom farms. • Labor productivity and efficiency benchmarks guide farm management decisions. • Sensitivity analysis of labor cost-saving strategies using the proposed framework. • Optimal proportion of robotic automation improves labor utilization parameters. Mushroom harvesting is one of the most labor-intensive and time-sensitive operations in large-scale commercial production, and persistent labor shortages, rising wages, and poor workforce allocation can directly reduce farm profitability. This study proposes a farm-level decision-support framework to evaluate labor utilization and compare labor-improvement and robotic-harvesting strategies before implementation. The framework integrates farm production capacity, labor cost, labor productivity, and labor efficiency within a unified analytical workflow. Its practical applicability is demonstrated through a sensitivity-analysis-based case study of a large-scale commercial mushroom farm. Under the baseline scenario, whole-farm labor productivity was $111,094 per worker and labor efficiency was 28%. Sensitivity analysis demonstrated that worker-improvement strategies increased labor productivity by $125,000 to $132,000 per worker. At the same time, the optimized workforce-allocation scenario reduced labor efficiency from 28% to 25%, indicating a lower labor-cost share. Among the worker-based interventions, improving the harvesting rate of lower-performing workers from 35 to 65 lb/hr emerged as the most practical strategy. Robotic harvesting further increased annual revenue and labor productivity, although the marginal benefit declined beyond a threshold level of automation. Under simplified assumptions, estimated robot payback periods ranged from 0.5 to 0.7 years depending on harvesting speed. Overall, the proposed framework provides a structured basis for benchmarking, sensitivity analysis, and pre-implementation evaluation of labor- and automation-related strategies in mushroom harvesting and offers broader relevance for data-driven decision support in labor-intensive agricultural systems.