Abstract: Abstract: Leaf wilting is a common symptom in plants responding to drought stress. Early wilting detection is very important for precision crop management. In this paper, plant morphology was monitored to determine plant water status. A laser scanner was used to obtain three-dimensional (3D) images of plants based on the principle of triangulation. Four wilting indices based on plant morphology were developed and tested using different mathematical methods. The plant wilting indices included differential geometry; 2D Fourier transformatio; top projected leaf area (TPLA); and standard deviation (SD). Experiments were conducted to verify the effectiveness of each wilting index for characterizing plant water status. Zucchini plants were selected because of their sensitivity to variations in soil water content and environmental parameters. These parameters included solar radiation, air temperature and ambient relative humidity. Zucchini seeds were individually sown in greenhouse pots. Two weeks later, the young plant emerged from the pot soil, and three of the healthiest plants were chosen as test samples. The substrate water content for these plants was maintained at 0.06-0.08 kg/kg (relatively dry), 0.17-0.20 kg/kg (moderately dry) and 0.30-0.32 kg/kg (wet). The fourth leaf of each plant was scanned at 30-minute interval between 8 am and 5 pm over 10 days. Concurrently, the environmental parameters and plant stem diameter were measured at 5-minute interval. The data obtained indicated a correlation between the wilting indices and the environmental parameters. It also showed that the wilting indices were affected by the diameter of the plant stem. The results showed that the diurnal variation process on wilting index based on differential geometry correlated with environmental parameters. For example, stronger solar radiation and higher air temperature lead to a larger index value and vice versa. The wilting index exhibited strong linear correlations with solar radiation, ambient temperature and stem diameter, where the coefficients of correlation were 0.734, 0.785 and 0.845, respectively. The quantitative regression between wilting index based on differential geometry and stem diameter indicated that wilting index based on differential geometry could be used to reflect plant water deficit stress conditions, which was consistent with previous studies. A correlation analysis was carried out to determine the effectiveness of each index. The absolute values of correlation coefficients between TPLA and wilting index based on differential geometry, wilting index based on 2D Fourier transformation, were above 0.895, suggesting that these indices were well-correlated with plant wilting. The correlation coefficients between SD and other wilting indices were around 0.76, indicating a poor approach for comparison. To verify the accuracy of these indices, the correlations between each wilting index and the environmental parameters were analyzed. The regression results showed well-correlated linear relations with R2 above 0.806 between wilting index and air temperature, and R2 above 0.720 between wilting index and solar radiation. However, the correlation between wilting indices and stem diameter was poor. The correlation coefficients of wilting index based on differential geometry, wilting index based on 2D Fourier transformation and TPLA with stem diameter were above 0.800, while only 0.64 between SD and stem diameter. It was concluded that wilting index based on differential geometry, wilting index based on 2D Fourier transformation and TPLA performed better than SD for identifying plant water status. This paper suggests a novel, non-invasive and accurate method for monitoring plant water status.