Abstract

Determination of photosynthetic area of a plant, leaf or cladode is a fundamental tool in study of transpiration intensity, specific leaf area and leaf area index. The objective of this study was to evaluate Nopalea cochenillifera (L.) Salm-Dyck). cladode area, in a non- destructive way, using digital images and test its relation with the variables: product of length and maximum width and real cladode area through regression models. The design used randomized blocks with three replicates and using the N. cochenillifera forage cactus clone, Giant Sweet. To determine the real cladode area of cactus forage, 432 cladodes in different stages of growth were randomly collected (162 primary cladodes, 127 secondary and 143 tertiary cladodes), all free from damage, disease or pest attacks. All cladodes were photographed with a digital camera (Sony Mark, model DSC-P72) generating a sample of 432 1200 x 2500 pixel digital images of N. cochenillifera cladodes. Linear, gamma and power regression models were adjusted to test the relation between the digital cladode area and the explanatory variables real cladode area and product of length by width. Models were evaluated with the following criteria: Coefficient of model determination, Akaike information criterion, sum of squares of residuals and Willmott index. The power model gave the best performance, with explanatory power higher than 99.5%, while the Willmott index exceeded 0.99. Sum of squares of residuals and Akaike information criterion had lower values. The digital cladode area of N. cochenillifera can be explained by the linear dimensions of cladodes in, and independent of, branching order. The digital cladode area (DCA) of N. cochenillifera can be explained as a function of the power model -DCA = LW0.98Sconsidering the product of length by width (LW) with explanatory variable, and by D-CA = RCA1.002considering real cladode area (RCA) with explanatory variable.

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