Allometric models for estimating the leaf area of lisianthus (Eustoma grandiflorum) using a non-destructive method

Abstract

Lisianthus (Eustoma grandiflorum) is a cut flower grown due to the wide diversity of colors and longevity in the post-harvest. The leaf area measurement is fundamental in plants because the leaves are directly related to several processes such as transpiration, radiation interception and CO 2 fixation that enable the plant to grow. The objective of the work was to determine an allometric equation for estimating the leaf area of lisianthus from linear dimensions. 200 leaves were collected and the leaf length (L), leaf width (W), product between length and width (LW) and real leaf area (LA) were measured. The criteria for determining the best model were the highest determination coefficient (R 2 ), Willmott's concordance index (d), lowest Akaike information criterion (AIC), root mean square error (RMSE) and BIAS index closest to zero. The most suitable model for estimating the leaf area of lisianthus is the linear w = 1.387*LW.

A non-destructive method for leaflet area prediction of Spondias tuberosa Arruda: an approach to regression models

“…According to Williams and Martinson (2003), the accepted models should have R 2 greater than 0.95, indicating greater predictive capacity and lower dispersion. The results of the present study corroborate those observed for Vitis vinifera (Buttaro et al 2015), Eustoma grandiflorum (Dias et al 2022), and Malus domestica (Boyaci and Küçükönder 2022), in which the most appropriate models were the linear model without intercept and power to estimate LA.…”

“…Several studies have used linear dimensions to determine leaf area with precision. Salazar et al (2018) proposed the use of the product of length and width using polynomial regressions to estimate the leaf area of cacao (Theobroma cacao L.) with a coefficient of determination of 98%, and this use is reported for several species, such as Ceiba glaziovii (Ribeiro et al 2022), Eustoma grandiflorum (Dias et al 2022), watermelon (Rouphael et al 2010), Forsythia viridissima, Ligustrum lucidum, Ligustrum sinense, Osmanthus fragrans, Syringa oblata var. alba (Shi et al 2019), and Malus domestica cultivars (Boyaci and Küçükönder 2022).…”

Non-destructive method for estimating chrysanthemum leaf area

“…The model identified (ŷ = 0.6611*LW 0.9490 ) is relevant for studies of ornamental plants such as chrysanthemum, since from the knowledge of leaf area it is possible to analyze growth, development and photosynthetic rates, in addition to conducting studies of shading, landscape capacity and ecology of the species (Dias et al, 2022). Therefore, using accurate equations to estimate chrysanthemum leaf area by measuring leaf area using nonlinear models is a methodology as efficient as destructive methods.…”

“…In addition, the model studied can be even more efficient, since it is not necessary to destroy the plant to estimate its leaf area. The use of the product between length and width (LW) to estimate leaf area was more efficient for chrysanthemum as well as for Solanum melongena (Hinnah et al, 2014), Brassica napus (Cargnelutti et al, 2015), Bambusa vulgaris (Montelatto et al, 2021), Thunbergia grandiflora (Mela et al, 2022) and Eustoma grandiflorum (Dias et al, 2022). The development of mathematical equations for leaf area estimation provides a crucial and convenient method for quickly determining leaf area, which can be easily adapted for field use and allows for multiple evaluations of the same plants throughout their growth cycle (Goergen et al, 2021).…”

Leaf area estimation of Congea tomentosa using a non-destructive method

“…The equation ŷ = 0.63 × LW constructed from (Silva et al, 2020), Theobroma cacao (Schmildt et al, 2017), Manihot sp. (Leite et al, 2021), Erythrina velutina (Ribeiro et al, 2022), Juglans regia (Keramatlou et al, 2015), Talinum triangulare, Talinum paniculatum (Oliveira et al, 2019) and Eustoma grandiflorum (Dias et al, 2022). By estimating the leaf area using non-destructive models, it is possible to explain plants' agronomic and physiological behavior concerning the availability of radiation and water (Salazar et al, 2018).…”