2018
DOI: 10.1590/1678-4499.2017106
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Models for leaf area estimation in dwarf pigeon pea by leaf dimensions

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Cited by 15 publications
(16 citation statements)
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“…Among the 1,452 leaves used for generation and among the 363 leaves used for validation of the models, the CV of the length x width product (LW) of the leaf blade and leaf area (Y) was approximately twice the CV of the length (L) and width (W) of the leaf blade (Table 2). A similar pattern was observed in leaves of coccoloba (Mariano et al, 2009), snap bean (Toebe et al, 2012), forage turnip (Cargnelutti et al, 2012), pigeon pea (Cargnelutti et al, 2015), yacon (Cunya et al, 2017), sunn hemp (Carvalho et al, 2017), dwarf pigeon pea (Pezzini et al, 2018), triticale (Toebe et al, 2019), and coffee (Cavallaro et al, 2020).…”
Section: Resultssupporting
confidence: 61%
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“…Among the 1,452 leaves used for generation and among the 363 leaves used for validation of the models, the CV of the length x width product (LW) of the leaf blade and leaf area (Y) was approximately twice the CV of the length (L) and width (W) of the leaf blade (Table 2). A similar pattern was observed in leaves of coccoloba (Mariano et al, 2009), snap bean (Toebe et al, 2012), forage turnip (Cargnelutti et al, 2012), pigeon pea (Cargnelutti et al, 2015), yacon (Cunya et al, 2017), sunn hemp (Carvalho et al, 2017), dwarf pigeon pea (Pezzini et al, 2018), triticale (Toebe et al, 2019), and coffee (Cavallaro et al, 2020).…”
Section: Resultssupporting
confidence: 61%
“…Alternatively, if the researcher wants to minimize the work and make only one measurement on the leaves, he/she should opt for W and for quadratic (Ŷ = -0.2884 + 1.1428x + 0.5832x 2 , R 2 = 0.9262) or power (Ŷ = 1.1536x 1.7752 , R 2 = 0.9260) models. However, these two models have a poorer fit when compared to the models generated from the LW (two measurements), but a better fit when compared to those generated from L. Models generated based on LW were recommended to estimate leaf area in species such as: coccoloba (Mariano et al, 2009), sunn hemp (Cardozo et al, 2011;Carvalho et al, 2017), snap beans (Lakitan et al, 2017), forage turnip (Cargnelutti et al, 2012), pigeon pea (Cargnelutti et al, 2015), yacon (Cunya et al, 2017), dwarf pigeon pea (Pezzini et al, 2018), triticale (Toebe et al, 2019), and coffee (Cavallaro et al, 2020 buckwheat, in which the linear model without intercept was also the most appropriate for estimating the leaf area of Coccoloba rosea (Ŷ = 0.7705x, R =0.98) and Coccoloba ramosissima (Ŷ = 0.7416x, R 2 =0.91), as a function of LW (x) (Mariano et al, 2009). For buckwheat, leaf area models were generated for the variety Hruszowska (Almehemdi et al, 2017), but with a methodology different from that used in the present study.…”
Section: Resultsmentioning
confidence: 99%
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“…Minimum, maximum, average, standard deviation and coefficient of variation in length along the midrib (L, cm), maximum width (W, cm), length of the product by the maximum width (LW, cm 2 ) and observed leaf area (OLA, cm 2 ) of Plectranthus barbatus Andrews leaves In relation to variability measured by CV, in the leaves sample used in the adjust of the regression equations, all the allometric measures (L, W, LW and OLA) showed values of CV very high (Table 1), according to Pimentel-Gomes' (2009) criteria. According to Pezzini et al (2018) the high value of CV is important for models generation, because it can be explained by the collection of leaves in several growth stages, characterizing the growth of the plants. In the 100 leaves used for validation, the variability found in the measures of L, W, LW and OLA was also considered high, according to Pimentel-Gomes' (2009) criteria, showing suitable for this type of analyze, as also stood out Schmildt, Hueso, Pinillos, Stellfeldt, and Cuevas (2017).…”
Section: Resultsmentioning
confidence: 99%
“…This finding leads to the need for developing a non-destructive measurement of the total leaf area of T. paniculatum. Pezzini et al (2018) agreed that a single-trait predictor (L or W) required less labor than the use of two traits (LW). Toebe et al (2019) reported that W was better than L for LA estimation in squash.…”
Section: Propagation Of Talinum Paniculatum Using Stem Cuttingsmentioning
confidence: 89%