Abstract
ABSTRACT Leaf area measurements are used in agronomic studies to evaluate plant growth, light interception, photosynthetic rates, and plant transpiration. It constitute an important indicator of crop productivity, for which the evaluation method must be fast, accurate, and of low cost. The objective of this study was to compare different indirect methods to estimate leaf area in pornunça (Manihot sp.). The research was carried out under field conditions from August 2017 to January 2019 in the semiarid region of Pernambuco State, Northeastern Brazil. Three methods were tested: linear dimensions of leaf (length, width, and the number of lobes), digital image, and leaf scanned image, analyzing 150 healthy leaves from 120 plants of pornunça at different growth stages. The criteria used to determine the best model(s) were a high coefficient of determination, low Akaike information criterion, low sum of squares of residuals, and high Willmott index. Independent of the method of determination, the power models showed the best criteria of adequacy for estimating the leaf area of the pornunça. The digital image, using the power model (Y=LW0.77NL0.49, where L and W are the leaf length and width, and NL is the number of lobes in the leaf) was the best non-destructive method for estimating the leaf area in pornunça plants.
Highlights
Pornunça (Manihot sp.) is a member of the Euphorbiaceae family and descendant of the cassava (M. esculenta) and maniçoba (M. pseudoglaziovii) (Silva et al, 2017), which stands out for its high leaf production, elevated tolerance to waterthermal stress, high accumulation of starch, and high protein content (Alencar et al, 2015).Leaf area is a valuable morphological measure for determining the leaf area ratio and leaf area index (Schmildt et al, 2014)
The highest mean leaf area was observed in the real leaf area (RLA) (136.42 cm2), indicating that all indirect methods slightly underestimated the leaf area when compared to RLA
The highest positive correlation was observed for RLA and digital leaf area (DLA) (r = 0.94; p ≤ 0.0001), but high positive correlations were observed between RLA and length by width (LW) and scanned leaf area (SLA) (Figure 2)
Summary
Pornunça (Manihot sp.) is a member of the Euphorbiaceae family and descendant of the cassava (M. esculenta) and maniçoba (M. pseudoglaziovii) (Silva et al, 2017), which stands out for its high leaf production, elevated tolerance to waterthermal stress, high accumulation of starch, and high protein content (Alencar et al, 2015).Leaf area is a valuable morphological measure for determining the leaf area ratio and leaf area index (Schmildt et al, 2014). Regression models used to explain the digital leaf area (DLA) and scanner (SLA) in relation to the explanatory variables: real leaf area (RLA) and product length by width (LW) are described below: Linear models: DLAi = β0 + β1RLAi + εi; SLAi = β0 + β1RLAi + εi; DLAi = β0 + β1LWi + εi; SLAi = β0 + β1LWi + εi
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