Introduction
Cotton (Gossypium hirsutum L.) is a strategic industrial crop, vital as the world's primary source of natural fiber and a significant source of edible oil and animal feed. Despite its importance to Iran's economy, a substantial "yield gap" exists between farmer-achieved yields and potential yields under optimal conditions. This gap, largely from suboptimal management, is a critical concern as Iran seeks to regain self-sufficiency in cotton production. While other regions have been studied, the specific agro-ecological conditions and local practices in Behshahr County, Mazandaran, necessitate a dedicated regional investigation. This study aimed to quantify the irrigated cotton yield gap in the Miankaleh region and identify the relative contribution of the most significant management factors using the Comparative Performance Analysis (CPA) method.

Materials and Methods
This survey-based research was conducted over two consecutive growing seasons (2021–2022) across 88 irrigated cotton farms in the Miankaleh district, selected to represent local diversity in management and yield. Data were collected via farmer interviews and field visits, covering farm characteristics, crop establishment, nutrition management, crop protection strategies, and irrigation practices. The Comparative Performance Analysis (CPA) method was employed. A stepwise multiple regression model was developed using SAS software to establish a quantitative function relating final yield to management factors. Qualitative variables were coded as binary (0/1). This model was used to estimate the potential yield (using optimal values for significant variables) and compare it to the average actual yield (using mean observed values), thereby quantifying the total yield gap and the contribution of each limiting factor.

Results and Disscusion
The average actual seed cotton yield was 2103 kg ha^-1, while the estimated potential yield was 4620 kg ha^-1, revealing a substantial yield gap of 2518 kg ha^-1. This indicates farmers are realizing only 45.5% of their potential, leaving a 54.5% manageable yield gap. The wide yield variation (649 to 4370 kg ha^-1) confirmed the profound impact of management. The stepwise regression analysis (r = 0.70) identified four key management variables as the primary determinants. Pest management emerged as the most critical domain. The "number of pesticide applications" was the single most important factor, explaining 55% of the total yield gap. Its strong positive correlation indicated that higher yields were associated with more frequent spraying, a reactive response to severe pest pressure (especially cotton bollworm) reported in 90% of farms. The second most important factor was the "amount of top-dress nitrogen," accounting for 36% of the gap. Its positive coefficient confirmed that current nitrogen application rates were, on average, suboptimal. Conversely, the "use of Proclaim Fit" (6% share) and the "use of Fenproxymate (Ortus)" (3% share) both showed a significant negative correlation with yield. This paradox was not due to pesticide inefficiency. Instead, these chemicals served as "proxy variables", indicating a critical flaw in management timing. Farmers used these specific chemicals as a late-stage response to severe infestations, after economic damage thresholds had been exceeded.

Conclusion
In conclusion, the cotton yield gap in the Behshahr region is substantial at 54.5% (2518 kg ha^-1). This gap is primarily driven by two key management domains: suboptimal pest management (collectively accounting for 64% of the gap) and inadequate nitrogen fertilization (36%). The pest management issue is systemic, characterized by severe outbreaks and a reactive, poorly-timed control strategy. To effectively close this gap, agricultural extension programs must prioritize farmer education in two main areas. First, a shift from reactive spraying to proactive Integrated Pest Management (IPM) is essential, including training in field scouting, economic thresholds, and proper pesticide selection. Second, promoting balanced, soil-test-based nitrogen application strategies is crucial for optimizing plant nutrition. These targeted interventions offer the most practical pathway to enhancing cotton productivity in the region.