This study was carried out to develop a real-time grouping system of chlorophyll contents of rice crop canopy for precision agriculture. The system measured reflected light energy of a rice canopy on a paddy field from visual to near-infrared range and analyzed the collected information of chlorophyll contents of rice crop canopy with given position data. The four filters, 560 nm $({pm}10nm)$, 650 nm $({pm}25nm)$, 700 nm $({pm}12nm)$, and 850 nm $({pm}40nm)$, were used for a multiple regression to estimate the chlorophyll contents of rice crop canopy. Every $0.2m^2$ area of the open field was inspected at a distance of 1 m above the rice canopy. According to the results of verification test, the chlorophyll content grouping by a commerical chlorophyll meter (SPAD) and by the developed system showed 58.7% match for five-stage chlorophyll contents of rice crop canopy grouping and 93.5% for the $five{pm}1-stage$ grouping. In addition, the results showed 63.0% match for three-stage grouping and 100.0% for the $three{pm}1-stage$ grouping.