Allometric relationship and leaf area modeling estimation on chia by non-destructive method

Abstract

This study aimed to obtain equations to estimate leaf area from linear leaf dimensions and establish the allometric relationship between leaf area and the number of leaves on the main stem of chia (Salvia hispanica L.) at different sowing times. The experiment was conducted in the agricultural year 2016/2017 on five sowing times in Santa Maria, RS, Brazil, in a randomized block design with four repetitions. In each plot, ten random plants were marked weekly during the vegetative phase to determine the number of leaves (NL) in the main stem, and three of these for the determination of leaf area (LA). A total of 70 leaves of different sizes were used to calibrate the model. Another 106 leaves were used to test the predictive capacity of the equations by various statistical indices. The length (L) and the largest leaf width (W) were measured. Leaf collection was carried out during the cycle, in all sowing times to represent all leaf sizes. The linear, quadratic, exponential, and potential models were adjusted. The non-destructive method, through the linear dimensions of the leaf, is appropriate for estimating the leaf area in chia. The general equation LA = 0.642 (L x W) can be used to estimate the leaf area of the chia plants without loss of precision. The potential model is appropriate to characterize the allometric relationship between leaf area evolution and the number of leaves accumulated in the main stem of chia at different sowing times.

Allometric models to estimate peanuts leaflets area by non-destructive method

“…The present study showed that the best equations to estimate the LA of peanut cultivars were those that used LW, compared to equations that used only one leaflet dimension (L or W), with the best criteria and adjustments of the models used (Guimarães et al 2019, Macário et al 2020, Goergen et al 2021, except for the exponential model, in which the best equations were those that used L of the leaflets (Ribeiro et al 2020).…”

“…Generally, linear models are the most used to estimate the leaf area of agricultural and forest species (Gomes et al 2020, Goergen et al 2021, Hernandéz-Fernandez et al 2021, Mela et al 2022). However, it is assumed that these models are used with losses in precision, which often occurs due to the high values of the intercepts (β0) of the regression line (Santos et al 2021).…”

Nondestructive method for estimating the leaf area of sapodilla from linear leaf dimensions

“…The models presented coefficient of determination (R²) values of above 0.86, indicating that at least 86% of the variations in sapodilla LA were explained by the equations proposed for the estimation (Table 1). The equations that used the LW value presented the best criteria for estimating the LA of the species, giving the best fits of the regression models (Macário et al, 2020;Goergen et al, 2021). The exception was the exponential model, where the best criteria were observed in the equation in which the WW value was used (Ribeiro et al, 2020).…”

Allometric equations for estimating the leaf area of Thespesia populnea by linear dimensions of leaf blades

“…The determination coefficients (R²) of the equations obtained were higher than 0.83, indicating that at least 83% of the variations observed in the leaf areas of T. populnea were explained by the models constructed using linear dimensions of the leaf limbs. The allometric equations that were obtained from the product between length and width (LW), compared to those that employed L or W, provided the greatest adjustments to the regression models (Guimarães et al 2019, Goergen et al 2021, Lucena et al 2021, Cargnelutti Filho et al 2021, Toebe et al 2021, as well as the best criteria to satisfactorily estimate the leaf area of T. populnea, except for the cubic model, in which the best equation was obtained using the product between length and length of leaf limbs (LL).…”