Abstract:Leaf area measurements are of the main parameters used in agronomic studies to evaluate plant growth. The current study used a non-destructive method based on linear leaf dimensions (length and width) to select the regression model to estimate millet (Pennisetum glaucum) leaf area. For two millet genotype (IPA BULK 1 BF and ADR 300) 128 randomly-chosen leaves were measured at different vegetative growth stages. Measures of length and width of each leaf were made using digital calipers. Leaf area was measured u… Show more
“…The best fit model was used to predict the weight of the cladodes as a function of thickness (T) and product between L and W (LW), and regression studies were performed using linear, gamma and power models ( Table 1). The linear and power models with normal distributions assumed that the response of the dependent variable was in the range of -∞ to ∞, and the gamma models with gamma distributions assumed that the response of the dependent variable was in the range of 0 to ∞ (Lucena et al, 2018b;Leite et al, 2017;Leite et al, 2019), (Table 1). Table 1.…”
The forage palm is one of the main forages of ruminants in semiarid regions. Measurements of leaf area are required in agronomic studies because they are one of the main parameters used to evaluate plant growth. The objective of this study was to validate and define the best models for estimating the area and weight of Giant Sweet clone (Nopalea cochenillifera) forage cladodes in a non-destructive way based on the linear dimensions of length, width and thickness. There were 432 randomly measured cladodes at 550 days after planting. The length, width and thickness of each cladode were measured using a digital calliper. The cladodes were weighed individually. The cladode area was calculated by the gravimetric method. The power regression model was the most efficient method to explain the cladode area as a function of the product of length by width, while the gamma model was the most efficient method to explain the weight of cladodes as a function of the product of length by width and thickness. The power model, and gamma model, = 0.536T + 0.028LW, were used to determine the area and weight of Nopalea cochenillifera Giant Sweet clone cladodes, respectively, based on the values of linear dimensions measured independently of the order of the cladode.
“…The best fit model was used to predict the weight of the cladodes as a function of thickness (T) and product between L and W (LW), and regression studies were performed using linear, gamma and power models ( Table 1). The linear and power models with normal distributions assumed that the response of the dependent variable was in the range of -∞ to ∞, and the gamma models with gamma distributions assumed that the response of the dependent variable was in the range of 0 to ∞ (Lucena et al, 2018b;Leite et al, 2017;Leite et al, 2019), (Table 1). Table 1.…”
The forage palm is one of the main forages of ruminants in semiarid regions. Measurements of leaf area are required in agronomic studies because they are one of the main parameters used to evaluate plant growth. The objective of this study was to validate and define the best models for estimating the area and weight of Giant Sweet clone (Nopalea cochenillifera) forage cladodes in a non-destructive way based on the linear dimensions of length, width and thickness. There were 432 randomly measured cladodes at 550 days after planting. The length, width and thickness of each cladode were measured using a digital calliper. The cladodes were weighed individually. The cladode area was calculated by the gravimetric method. The power regression model was the most efficient method to explain the cladode area as a function of the product of length by width, while the gamma model was the most efficient method to explain the weight of cladodes as a function of the product of length by width and thickness. The power model, and gamma model, = 0.536T + 0.028LW, were used to determine the area and weight of Nopalea cochenillifera Giant Sweet clone cladodes, respectively, based on the values of linear dimensions measured independently of the order of the cladode.
“…Corroborating this assertion, several authors have tested and adjusted these models for other species, such as Crotalaria juncea [8], Litchi chinensis Sonn. [9], Artocarpus heterophyllus [10], Cucurbita moschata [11], Pennisetumglaucum [12] and Plectranthus barbatus Andrews [13]. Table 3 describes the nine models of equations generated for the estimation of the leaf area of Acacia mangium Willd.…”
Section: Ssionmentioning
confidence: 99%
“…Based on the leaf dimensions of several species and without the destruction of the sample, several studies have reported the use of mathematical models to estimate leaf area [8,9,10,11,12,13,14]. With respect to A. mangium Willd., A non-destructive methodology for the determination of its leaf area is of great importance, since there are no mathematical equations in the literature that allow this measurement in the specie.…”
The objective of this study was to determine the best equation for estimating the leaf area of Acacia mangium Willd. from the linear dimensions of the leaflets of non-destructive form. For this, 476 leaflets of plants belonging to Lajeado farm were collected in the municipality of Ecoporanga, in the north of the State of Espírito Santo, Brazil. From each leaflet was determined the length (L) along the main midrib, the largest width (W), the product of the multiplication between the length and the width (LW) the observed leaf area (OLA). For the modeling, we used 382 leaflets in which OLA was the dependent variable in function of L, W or LW as independent variable, being adjusted the linear models of first degree, quadratic and power. For the validation, the values of L, W and LW of 94 leaflets were replaced in the equations obtained in the modeling thus obtaining the estimated leaf area (ELA). The means of ELA and OLA were compared by Student's t test at 5% probability. . It was also determined the mean absolute error (MAE), the root mean square error (RMSE) and Willmott's index d. In order to select the best equation, the following criteria were used: : not significant of the comparison of the means of ELA and OLA, values of MAE and RMSE with closer to zero and index d closer to one. The power model equation represented by is the most adequate to predict the leaf area of Acacia mangium Willd. quickly and non-destructively.
“…Para determinação da área de cladódio são utilizados métodos indiretos e não destrutivos, permitindo avaliações sucessivas do mesmo cladódio (Lucena et al, 2019). O desenvolvimento de modelos de regressão a partir das medidas lineares de folhas para determinar a área foliar tem sido muito útil no estudo do crescimento e desenvolvimento das plantas (Achten et al, 2010).…”
Section: Introductionunclassified
“…O desenvolvimento de modelos de regressão a partir das medidas lineares de folhas para determinar a área foliar tem sido muito útil no estudo do crescimento e desenvolvimento das plantas (Achten et al, 2010). Os modelos matemáticos são vantajosos porque são rápidos, não destroem as plantas e são fáceis de manusear em condições de campo (Leite, Lucena, Cruz, Sá Júnior, & Simões, 2019). Diversos estudos utilizando dimensões lineares na estimativa da área de cladódio foram estabelecidos para várias espécies de cactáceas [Opuntia ficus-indica (Reis, Gazarini, Fonseca, & Ribeiro, 2016), O. stricta (Lucena, Leite, Simões, Simões, & Almeida, 2018), Nopalea cochenillifera (Lucena et al, 2019)], e geraram equações com alta precisão.…”
A palma é uma das principais forrageiras utilizadas na alimentação de ruminantes em regiões semiáridas. Medidas de área e peso de cladódio são necessárias em estudos agronômicos, sendo um dos principais parâmetros usados para avaliar o crescimento das cactáceas. Assim, objetivou-se definir os melhores modelos para estimativa de área e peso de cladódio da palma forrageira (Nopalea cochenillifera clone Doce Miúda) de forma não destrutiva com base nas dimensões lineares do cladódio. Para determinar a área e peso de cladódio, foram coletados, aleatoriamente, 582 cladódios, sendo 191 primários, 186 secundários e 205 terciários. Em seguida, os cladódios foram numerados e pesados individualmente. As dimensões lineares de comprimento (C), largura máxima (L) e espessura (E) de cada cladódio foram medidas com um paquímetro digital. A área do cladódio foi calculada pelo método gravimétrico. Foram utilizados os modelos de regressão linear, gamma e potência para explicar a área e peso de cladódio. Os critérios de avaliação dos modelos foram coeficiente de determinação, critério de informação de Akaike, soma de quadrado de resíduo e índice de Willmott. Os modelos potência foram os mais eficientes para explicar a área do cladódio (AC) em função do produto do comprimento pela largura, e peso do cladódio (PC) em função do produto do comprimento pela largura e espessura. Os modelos potência, =CL0.985 e =0,0045(E0,806 CL1,099), podem ser usados com maior precisão para estimar, respectivamente, a área e peso do cladódio do clone Doce Miúda com base nos valores das dimensões lineares do cladódio.
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