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Rice-based irrigated lowlands are the major cropping system in north of Iran. This experiment was carried out in split plot in basis of randomized complete block design with three replications at north of Iran in 2010. Main plot was nitrogen rates including (0, 50, 100 and 150 kg N ha^-1) applied as urea and sub plot was silicon rates (0, 300 and 600 kg ha^-1) applied as calcium silicate. Results showed that minimum of the plant height, flag leaf length, fourth inter-node bending moment and grain yield (4350 kg ha^-1) were obtained at N₀, as well as the maximum of the plant height, panicle length, flag leaf length, third inter-node length were observed at N₁₀₀ and N₁₅₀, respectively. But the highest of bending moment obtained for fourth inter-node and maximum grain yield (6063 kg ha^-1) was observed in N₁₅₀. Treatment Si₆₀₀ had increased significantly over control in plant height, stem length, panicle length, third inter-node length, third inter-node bending moment, cellulose, hemi-cellulose and lignin in relation to 7.76, 9.91, 30.18, 31.03, 18.71, 7.60, 34.50 and 26.26 %, respectively. Therefore treatment with N₁₅₀ and Si₆₀₀ had shown best results for agronomical indices and grain yield.

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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.

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