ABSTRACT
This research was conducted with the aim of determining the most suitable rice harvesting method in the paddy fields of Guilan province using the Analytic Hierarchy Process (AHP). Three harvesting methods, including two-stage harvesting (manual + thresher), two-stage harvesting (reaper + thresher), and one-stage harvesting (special rice combine harvester), were evaluated based on eight main criteria: effective field capacity, harvesting losses, total harvesting cost, required labor force, energy consumption, fuel consumption, pollutant emissions, and adaptability to field conditions. The results indicated that among the criteria, effective field capacity with a weight of 0.304 had the highest importance, and pollutant emissions with a weight of 0.037 had the lowest importance from the experts’ perspective. In the final prioritization of options, the one-stage harvesting method (special rice combine harvester) was identified as the most suitable method, achieving the highest score. This method was preferred due to its highest field capacity, lowest total cost, reduced labor requirement, and high operational efficiency compared to other methods. The two-stage harvesting (reaper + thresher) showed moderate performance and is a suitable option in resource-limited conditions. The two-stage harvesting (manual + thresher), despite its high adaptability to various land conditions and lowest pollutant emissions, had the lowest priority from economic and operational perspectives. The calculated inconsistency rate (0.02) indicated a high consistency and reliability of the results. This study suggests that mechanizing rice harvesting can significantly increase productivity, save time, and reduce costs, while manual or semi-mechanized harvesting serves as alternative options in specific situations with land and human resource constraints. The obtained results can assist decision-makers and farmers in Guilan province in selecting the appropriate harvesting method and improving paddy field performanceare.

Introduction

Rice is a staple food and a major agricultural commodity in Iran, particularly in Gilan province, which significantly contributes to national rice production. Efficient harvesting is a critical stage in paddy cultivation, as it directly influences yield, operational costs, labor requirements, and environmental sustainability. Traditional harvesting methods, often based on manual labor or two-stage processes combining cutting and threshing separately, are widely practiced in smallholder farms. However, they are associated with high labor demand, prolonged harvesting periods, and increased post-harvest losses. Mechanized harvesting, including single-stage combine harvesters, offers potential advantages in terms of productivity and cost-efficiency; yet, it can increase energy consumption, fuel usage, and pollutant emissions, highlighting trade-offs between operational efficiency and environmental impacts. Previous studies have examined individual aspects of rice harvesting, but few have systematically integrated technical, economic, and environmental criteria to guide method selection. This study addresses this gap by evaluating and prioritizing rice harvesting methods in Gilan using a multi-criteria decision-making approach. Specifically, the research objectives are to (i) identify and quantify the relative importance of harvesting criteria, (ii) compare single-stage mechanized, two-stage mechanized, and manual harvesting methods, and (iii) provide evidence-based recommendations for optimizing rice harvesting strategies. By employing the Analytic Hierarchy Process (AHP), the study provides a structured framework to support decision-making, offering both theoretical insights into sustainable agricultural management and practical guidance for farmers and policymakers.

Materials and methods
This study identified the optimal rice harvesting method in Gilan province using the Analytic Hierarchy Process (AHP). Three methods (manual+thresher, walk-behind harvester+thresher, combine harvester) were evaluated across the 2023-2024 season in key districts. Eight criteria—effective farm capacity, harvesting losses, total cost, labor, energy, fuel consumption, emissions, and field adaptability—were identified through literature review and expert consultation. Operational definitions and qualitative assessments (for adaptability) were established.
A three-level AHP structure was developed, with experts performing pairwise comparisons using Saaty’s 9-point scale. Thirty experts (academics, executives, farmers) were purposively selected. Questionnaires underwent content validity checks, and expert judgments were aggregated using geometric means after ensuring consistency (inconsistency ratio < 0.1). Relative weights of criteria and options were calculated, and final option weights were determined via linear combination. Robustness was tested through sensitivity analysis, varying criteria weights by ±5%, ±10%, and ±20%. All analyses were conducted using Expert Choice software (v11).

Results and discussion
The results showed that effective field capacity held the highest priority (weight = 0.304), indicating that maximizing harvested area per unit time is the most decisive factor for both farmers and agricultural experts in Gilan province. Conversely, pollutant emissions (weight = 0.037) were ranked lowest, suggesting that environmental considerations currently play a minor role in harvesting decisions. Among intermediate criteria, harvest losses received a relatively high weight, reflecting farmers’ emphasis on minimizing yield losses and ensuring product quality, often over economic concerns. In pairwise comparison of harvesting methods, the one-step harvesting method (full-feed rice combine) achieved the highest weights in effective field capacity (0.649), total cost (0.606), labor requirement (0.648), and energy efficiency (0.437). This method demonstrated superior operational performance by integrating cutting and threshing simultaneously, reducing labor dependency, and lowering overall costs. However, it exhibited the highest levels of fuel consumption (0.474) and pollutant emissions (0.395), largely due to continuous engine operation and higher diesel usage. The two-step manual + thresher method showed better adaptability to local field conditions (weight = 0.637) and lower emissions and fuel consumption, making it more suitable for small, uneven, or waterlogged fields. Despite these advantages, its low field capacity and high labor requirements reduced its overall preference. According to the integrated weighting of all criteria, the one-step harvesting method ranked first, followed by the two-step (reaper + thresher) and two-step (manual + thresher) methods. Sensitivity analysis confirmed the robustness of the AHP results, identifying effective field capacity as the most influential criterion, followed by harvest losses, total cost, and labor requirement. Overall, the model demonstrated strong internal consistency and stability across multiple weighting scenarios.

Conclusion
This study identified the one-step rice harvesting method using a full-feed combine as the most suitable option for the paddy fields of Gilan province. The superiority of this method stems from its higher field efficiency, reduced total operational cost, lower labor requirement, and greater energy-use effectiveness compared with other alternatives. In contrast, the two-step manual + thresher method ranked lowest due to its higher labor dependence and operational expenses. Nevertheless, in small-scale or irregular fields with high soil moisture, the manual-based two-step method remains more adaptable, emphasizing the importance of aligning harvesting technology with field conditions and mechanization infrastructure. The consistency ratio (0.02) validated the reliability of the AHP framework and the robustness of expert judgments. Findings highlighted effective field capacity as the most influential factor in decision-making, underlining the central role of operational efficiency in the mechanization of rice harvesting. Overall, adopting the full-feed combine harvester is recommended as an optimal strategy for improving productivity, reducing costs, and advancing sustainable mechanization in Gilan’s paddy systems, while adaptive multi-method approaches may be suitable under specific local constraints.