Abstract: In order to detect tomato chlorophyll content convenient, simple and fast, based on spectral analysis technology, a new version of crop growth condition detector was developed, which is used to predict chlorophyll content of tomato leaf in the greenhouse. Two wavebands, 527 nm and 762 nm, were selected as characteristic wavelength used in the instrument. The instrument is consisted of a Y-type optic fiber, two silicon photocells, a signal processing unit and CPU. It has a friendly human-machine interface. According to the measured spectral reflectance, spectral spectrum coefficient of tomato leaf can be calculated. The spectral coefficient is used to predict chlorophyll content of tomato leaf in greenhouse. STM32F103RBT6, based on ARM Cortex-M3 kernel, was selected as the main processor of instrument to carry on digital converter, data processing, storage and so on. In addition, users have an option in saving data，either into a USB-memory stick, or into the computer or SD card through the interface. The performance test shows that the instrument has good flexibility and high accuracy. Furthermore, the instrument is easily operated with low-cost, high-precision, high application values.