Evaluation of a proximal vision data acquisition system for measuring spatial variability in lettuce growth

Abstract

[Abstract]: In-field crop mapping provides the growth and yield data required to spatially manage inputs such as irrigation water and fertiliser. This study evaluated the potential to use low cost cameras as proximal sensors to spatially map lettuce growth throughout a growing season. Two 9 x 11 m measurement plots of 42 sampling points each were established within a sprinkler irrigated lettuce crop. Ten non-uniform irrigations were applied during the season. After each irrigation, the canopy and head diameter of two plants at each sampling point were physically measured. Colour digital cameras were also used to capture images of the lettuces from either 1.15 m or 10 m above the ground surface. Image processing software was then used to calculate the individual plant canopy area and lettuce head diameter. The lettuce growth measurements obtained using the 1.15 m camera were generally well correlated (R2 = 0.73-0.89) with the physical measurements 23 days after transplanting. Weaker correlations (R2 = 0.35-0.74) were observed at earlier dates possibly due to physical measurement errors of plant size early in the season. The correlations between the canopy measurements obtained using the 10 m camera and the physical measurements were generally 0.1 to 0.2 lower than those obtained using the 1.15 m camera, presumably due to lower pixel resolution. Correlations between the head diameter obtained using the 1.15 m camera and the physical measurements ranged from 0.83 to 0.92