A New Image Processing Based Technique to Determine Chlorophyll in Plants

Leaf colour is usually used as a guide for assessments of nutrient status and plant health. We propose a new inexpensive, hand-held and easy-to-use technique for the detection of chlorophyll content and foliar nitrogen content in plants based on leaf colour. This method provides a rapid analysis and data storage at minimal cost and does not require any technical or laboratory skills. Most of the existing methods that examined relationships between chlorophyll status and leaf colour were developed for particular species. These methods acquire leaf images using digital cameras, which can be sensitive to lighting conditions (colour, angle, flux density) and hence, require proper calibration. Our method analyses leaf colour images obtained from a digital scanner that requires minimal calibration compared as it has its one light source and the angle and distance between light and leaf are constant. Our new algorithm produced superior correlations with the true value of foliar chlorophyll content measured in the laboratory compared with existing non-destructive methods when applied to three different species (lettuce, broccoli and tomato).