To reduce the yield gap, specifying yield constraints in a particular area is necessary. A complete yield gap assessment method must provide information regarding potential yield, actual yield, and causes of the gap and their importance. Therefore, documenting the production process to explain crop management factors in each area is very important. The objective of the study was to perform a rice yield gap analysis by using comparative performance analysis (CPA) and boundary-line analysis (BLA). Data were gathered from about 100 paddy fields in Neka, eastern Mazandaran province, one of the major rice producing regions in Iran, in 2015 and 2016. All agricultural practices from nursery preparation to harvest have been recorded for improved rice cultivars. CPA focuses on the ability to estimate potential yield and the reason for a yield gap. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data from paddy fields monitoring. The documenting analysis shows that the range of paddy yield in 100 fields varied from 6100 to 8200 kg ha–¹. Potential yields were 9241 kg ha–¹ for CPA method, and 7999 kg ha–¹ for BLA method. Furthermore, yield gap predicted 2047 kg ha–¹ for CPA method and 874 kg ha–¹ for BLA method. In BLA, the average relative yield and relative yield gap of the 13 investigated variables were 89.75% and 10.25% respectively. These results show the importance of each management factor in yield gap. It was concluded that CPA and BLA as applied in the study is a cheap and simple method that, without the need for expensive experimentation, is able to detect yield gap and its causes in a district. From these results, it can be said that the calculated yield gap is close to the definition given for the utilised yield gap and shows the difference between the actual yield and attainable yield in relation to the environmental conditions of the region.

中文翻译：

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生产过程的大规模评估和水稻产量差距分析的比较性能分析和边界线分析方法

为了减小良率差距，必须在特定区域指定良率约束。完整的产量差距评估方法必须提供有关潜在产量、实际产量、差距原因及其重要性的信息。因此，记录生产过程以解释每个区域的作物管理因素非常重要。该研究的目的是通过使用比较性能分析 (CPA) 和边界线分析 (BLA) 进行水稻产量差距分析。2015 年和 2016 年，从伊朗主要水稻产区之一马赞德兰省东部 Neka 的约 100 个稻田收集了数据。从育苗准备到收获的所有农业实践都记录了改良水稻品种。CPA 侧重于估计潜在收益的能力和收益差距的原因。边界线被拟合到稻田监测数据中作物产量与管理变量数据云的边缘。记录分析表明，100 个田地的水稻产量范围从 6100 到 8200 kg ha–¹。CPA 方法的潜在产量为 9241 kg ha–¹，BLA 方法的潜在产量为 7999 kg ha–¹。此外，产量差距预测为 CPA 方法为 2047 kg ha-1，BLA 方法为 874 kg ha-1。在 BLA 中，13 个调查变量的平均相对产量和相对产量差距分别为 89.75% 和 10.25%。这些结果显示了每个管理因素在产量差距中的重要性。得出的结论是，研究中应用的 CPA 和 BLA 是一种廉价且简单的方法，无需进行昂贵的实验，就能够检测一个地区的产量差距及其原因。从这些结果来看，