Abstract
ABSTRACT Leaf area is an essential variable for the quantification of other important leaf characteristics in physiological studies of plants, such as normalized photosynthetic rate and normalized phosphorus content. That is one of the reasons for the need of fast and accurate methods to estimate leaf area. The objective of this work was to fit linear or non-linear regression models to predict the individual leaf area of six species of forage legumes, based on digital images analyzed with the package LeafArea, R software. In a field experiment, 100 leaves were randomly collected from the following species: Crotalaria juncea (L.), Canavalia ensiformis (L.), Cajanus cajan (L.), Dolichos lablab (L.), Mucuna cinereum (L.), and Mucuna aterrima (Piper & Tracy) Merr., in which the central leaflet length and width were measured. Afterwards, digital images of each leaf were processed in R software for leaf area estimation. These estimates were used to fit leaf area prediction models; in fact, seventy leaves were used to fit the models; the rest of them were used for model validation. For the six species, the complete second-degree polynomial model, or derivative submodels, can be used to predict leaf area as a function of length and width of the central leaflet, presenting R² above 0.98 and percentage absolute mean error below 9%. In these models, the effect of leaf width is generally greater than the leaf length. The R package LeafArea showed to be a very efficient tool for the estimation of leaf area through the execution of the software ImageJ, with high precision and easy calibration.
Highlights
Forage legumes (Fabaceae family), such as lablab (Dolichos lablab L.) and crotalaria (Crotalaria juncea L.), are widely cultivated as green fertilizers because of their biological and nitrogen-fixation capacity in the soil (Philippot et al, 2013), which increases the availability of this nutrient for conventional crops
The objective of this work was to fit regression models, linear or non-linear, to predict the individual leaf area of six cultivated species of forage legumes, based on digital images analyzed with the R package LeafArea
For M. cinereum (Cargnelutti Filho et al, 2012) and C. ensiformis (Toebe et al, 2012), linear models using leaf width and length were well fitted, presenting R2 of 0.992 and 0.978, respectively, corroborating the results found here
Summary
Forage legumes (Fabaceae family), such as lablab (Dolichos lablab L.) and crotalaria (Crotalaria juncea L.), are widely cultivated as green fertilizers because of their biological and nitrogen-fixation capacity in the soil (Philippot et al, 2013), which increases the availability of this nutrient for conventional crops (e.g. maize) These plants provide a very efficient plant cover (Perin et al, 2004), help to control weeds (Monquero et al, 2009), provide animal feed (Fiallos et al, 2012) and soil protection against mechanical damage, and avoid losses of nutrients by leaching and/or percolation (Souza et al, 2012). Accurate measurements of leaf area usually require the use of expensive equipment, making this type of procedure unviable, especially in large scale
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