Abstract: 【Objectives】 The spatial and temporal distribution of color indexes of canopy (G, NRI, NGI, NBI, G/R and G/B) and the indexes of N nutrition in rice plants were studied to determine the best color parameters and regression equations for nitrogen with a digital camera, and provide a theoretical basis and technical approach for monitoring plant nitrogen status of rice and precision management of nitrogen fertilization. 【Methods】 Field experiments were carried out from May to September 2013 in rice growing season at the Experimental Farm of Huazhong Agricultural University (3028 08N, 1142136E). A two-line indica hybrid (Liangyou6326) was chosen as test cultivar. Four N treatments: N 0, 75, 150 and 225 kg/ha were designed and recorded as N0, N75, N150, N225, respectively. A color digital camera (D700, Nikon, Japan) with a resolution of 12.0 mega pixels was employed to capture color images of rice canopy at the tillering, jointing, booting and filling stage. The image resolution was 19361296 pixels of 14 bit for red, green and blue. The images of size 2.72 MB were transferred in joint photographic experts group (JPEG) format to a computer and processed with Adobe Photoshop 7.0 to extract color information for studying possibility of using digital image analysis method for plant N status diagnosis and for determining the best color parameters and regression equations in rice. 【Results】 Compared with N0, the biomass, leaf N content, plant total N content, N accumulation and canopy NDVI values of rice with N treatments at the tillering stage, jointing stage, booting stage and filling stage are averagely increased by 40.7%-98.0%, 42.4%-72.4%, 36.2%-85.3%, 125.5%-209.1% and 51.3%-60.6%, respectively, at mature stage, the average increase of yield are from 60.1% to 117.0%. Compared with other plant canopy color parameters, the normalized redness intensity (NRI), calculated as R/(R+G+B), is much better as it has better correlations with the index of N-nutrient in rice plants, rice yield and canopy NDVI values at the different growth stages. An integrated linear regression equation could be used for describing the relationship between NRI and leaf N content, plant total N content, N accumulation, canopy NDVI values, yield at different growing stages and nitrogen levels of rice. 【Conclusions】 The digital image processing technique is usable in detecting the N nutrition in rice and has advantages of fast, stable results, easy to apply, and non-destructive. Simultaneously, the color parameter NRI has a preferable interrelation with the index of N-nutrition and yield than others, thus NRI is suitable for rapid diagnosis of nitrogen nutrition, and the digital image processing technique method shows the potential of being used in fast rice nitrogen diagnosis without damage.