A new optical instrument for fast measurement of fruit tree nitrogen status was designed and fabricated. Multi-color LEDs were used as light source, a portable spectrophotometer as optical detector, and an optic fiber as light signal transmission medium. In the paper, the principle of using multi-color LEDs for the measurement of fruit tree nitrogen status was first introduced. Then, the method of using error back propagation artificial neural network (BP-ANN) for calibration modeling was elaborated. Reflective light intensities of Multi-color LEDs were taken as the incoming signals to BP-ANN. The structure of BP-ANN with three layers has been optimized to minimize its calibration error. In the test, total 200 leave samples picked from Huang-hua pear trees planted in three orchards with different levels of nitrogen fertilizing. Among them, 150 samples were selected randomly out for calibration set with the remaining 50 for prediction set. The result shows that correlation coefficient of R2 between predicted and measured values of nitrogen content reaches 0.93 with maximum prediction error less than 3.36(SPAD). The study suggests that the new optical method integrating multi-color LEDs with BP-ANN is promising for fast diagnosis of fruit tree mineral nutrition status.