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We evaluated factors influencing the development of autumn red coloration in leaves of sugar maple (Acer saccharum Marsh.) by measuring mineral nutrient and carbohydrate concentrations, water content, and phenology of color development of leaves from 16 mature open-grown trees on 12 dates from June through October 1999. Mean foliar nutrient and carbohydrate concentrations and water content were generally within the range published for healthy sugar maple trees. However, foliar nitrogen (N) concentrations were near deficiency values for some trees. The timing and extent of red leaf coloration was consistently correlated with both foliar N concentrations and starch or sugar concentrations, which also varied with N status. Leaves of trees with low foliar N concentrations turned red earlier and more completely than those of trees with high foliar N concentrations. Low-N trees also had higher foliar starch concentrations than high-N trees. During the autumn development of red leaf coloration, foliar starch, glucose and fructose concentrations were positively correlated with red leaf color expression. At peak red expression, the concentrations of glucose, fructose, sucrose and stachyose were all positively correlated with red color expressed as a percent of total leaf area.

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Changes in foliar color are a valuable indicator of plant nutrition and health. Leaf color is measured with visual scales and inexpensive plant color guides that are easy to use, but not quantitatively rigorous, or by employing sophisticated instrumentation including chlorophyll meters, reflectometers, and spectrophotometers that are costly and may require special training. Digital color analysis has become an increasingly popular and cost-effective method utilized by resource managers and scientists for evaluating foliar nutrition and health in response to environmental stresses. Working with colorful autumn samples of sugar maple (Acer saccharum Marsh.) leaves, we developed and tested a new method of digital image analysis that uses Scion Image or NIH image public domain software to quantify leaf color. This publication provides step-by-step instructions for using this software to measure the percentage green and red in leaves, colors of particular importance for the assessment of plant health. Comparisons of results from digital analyses of 326 scanned images of leaves and concurrent spectrophotometric measures of chlorophyll a, chlorophyll b, and anthocyanins verify that image analysis provides a reliable quantitative measure of leaf color and the relative concentrations of underlying plant pigments.