Non-destructive Method for Estimating the Leaf Area of Pear cv. ‘Triunfo’

Oliveira, Vinícius de Souza; Santos, Karina Tonini dos; Morais, Andréia Lopes de; Santos, Gleyce Pereira; Santos, Jéssica Sayuri Hassuda; Schmildt, Omar; Czepak, Marcio Paulo; Gontijo, Ivoney; Alexandre, Rodrigo Sobreira; Schmildt, Edílson Romais

doi:10.5539/jas.v11n7p14

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…According to Maldaner et al (18), equations fitted with only one dimension of the leaf surface are more effective, since these models reduce the number of measurements in the estimation of leaf area by 50%, compared to models fitted based on the combination of measurements, which for Oliveira et al (10) makes the work easier to be carried out in the field. However, according to Espindula et al ( 19) these models must be well calibrated so that there is no biased estimation by these equations.…”

Section: Resultsmentioning

confidence: 99%

“…The use of regression models generated from allometric measurements of leaves to estimate their area is a useful methodology in morphogenic studies (5), and has already been reported for several species such as Helianthus annuus L. (6), Crambe abyssinica (7), Jatropha curcas (2), Passiflora mucronata (8), Litchi chinensis Sonn. (9) and Pyrus communis L. (10). However, studies involving eggplant and eggplant were not found in the literature.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical models in determining leaf area in eggplant and scarlet eggplant seedlings

Hell

Oliveira

Santos

et al. 2022

Braz J Exp Des Data Anal Inferential Stats

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The objective of this study was to obtain the best mathematical equation that estimates the leaf area seedlings of eggplant (Solanum melongena) and scarlet eggplant (Solanum gilo Raddi) through the linear dimensions of the leaves. Leaves of seedlings produced in a protected environment in the horticulture sector of the Instituto Federal do Espírito Santo – Campus Itapina, Colatina, in the Northwest region of the State of Espírito Santo, Brazil, were used. At 45 days after sowing, the length (L) along the midrib and the maximum width (W) of the leaf blade were determined, the product of the multiplication between the length and width (LW) and the observed leaf area (OLA). With the measurements in hand, the first degree linear model equations were obtained, potencyand its respective coefficient of determination. it was foundby analysis of covariance the possible adequacy of only one model to meet the two species. The models were validated, through a sample of leaves intended for this purpose, where their values of L, W and LW were substituted in the modeling equations, obtaining the estimated leaf area (ELA). A simple linear equation was fitted ELA and OLA. The hypotheses H0: β0 = 0 versus Ha: β0 ≠ 0 and H0: β1 = 1 versus Ha: β1 ≠ 1 were tested by Student's t test at 5% probability. The mean absolute error (MAE) and the root mean square error (RMSE) were also determined for all equations. The power () and exponential () model equations better predicted the area of eggplant and scarlet eggplant leaves, being the most recommended for these species.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical models in determining leaf area in eggplant and scarlet eggplant seedlings

Hell

Oliveira

Santos

et al. 2022

Braz J Exp Des Data Anal Inferential Stats

View full text Add to dashboard Cite

show abstract

“…The main advantage of the ME is that it allows for non-destructive estimation of leaf area through the simple measurement of leaf length and width in situ. The ME has been widely used to estimate the leaf areas of various plant species, including woody plants [26,27], herbaceous plants [26,28,29], lianas [26,30], monocots [26,31,32], Magnoliids [25,26], ferns [26], and important crop species such as maize [33], pear [34], and grapes [35,36]. However, to apply the ME to estimate leaf area, a species-specific proportionality constant, known as the Montgomery parameter, must be determined in advance.…”

Section: Introductionmentioning

confidence: 99%

Leaf Area Estimation by Photographing Leaves Sandwiched between Transparent Clear File Folder Sheets

Koyama

2023

Horticulturae

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Image analysis is a promising method for in situ leaf area measurement. However, as leaves are three-dimensional, the use of two-dimensional images captured using a digital camera can result in underestimation. To overcome this problem, we tested a clear folder method. Before photographing leaves with a digital camera, we flattened the leaves by sandwiching them between a pair of transparent plastic clear file folder sheets, which are stationery implements for carrying documents. Although similar methods have been previously proposed, their applicability to species with different leaf shapes has never been investigated. We tested the efficacy of this method using 12 species from various taxa (monocots, magnoliids, and basal and core eudicots) and leaf morphology (entire vs. lobed, simple vs. compound leaves, small and large leaves). Individual leaf areas and the Montgomery parameters obtained using this method were then compared with those obtained using the standard method, which employs a flatbed digital scanner. We observed strong correlations (R2 > 0.98) between the camera and scanner data. The regression slopes were close to unity (0.96–1.01) and the intercepts were close to zero. These findings suggest that the clear folder method can be used as an inexpensive alternative method to estimate the area of leaves in situ with acceptable accuracy. An introductory manual for readers unfamiliar with image analysis using ImageJ is presented in the end of the paper.

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Allometric models for non-destructive leaf area measurement of stevia: an in depth and complete analysis

2021

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Leaf area measurement is pivotal for plant physiologists. Hence, accurate measurement of their leaf area is incredibly relevant in agronomic terms. The plant Stevia rebaudiana is a sucrose-free plant species that is now vital to the global production of sucrose-free foods. Here, we estimated S. rebaudiana leaf area using a nondestructive methodology comprising allometric equations. Through leaf length (L), leaf width (W), and/or their product (LW) the leaf area was determined. One thousand leaves were sampled from four distinct S. rebaudiana genotypes for model construction. Linear or power models were generated, and the best equation was selected using a statistical criterion. The statistical criteria indicated that the linear models best suited all genotypes tested, included a function of LW, exhibited increased stability, and precisely estimated coefficients. ANOVA revealed that both generalized and combined equations were feasible. Nevertheless, grouping all genotypes into a single model was not possible as the genotype leaf architectures were very dissimilar.

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Non-destructive Method for Estimating the Leaf Area of Pear cv. ‘Triunfo’

Cited by 3 publications

References 13 publications

Mathematical models in determining leaf area in eggplant and scarlet eggplant seedlings

Mathematical models in determining leaf area in eggplant and scarlet eggplant seedlings

Leaf Area Estimation by Photographing Leaves Sandwiched between Transparent Clear File Folder Sheets

Allometric models for non-destructive leaf area measurement of stevia: an in depth and complete analysis

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