Leaf blade area estimate of <i>Digitaria pentzii</i> under different cutting Heights

Bezerra, Raul Caco Alves; Leite, Mauricio Luiz de Mello Vieira; Almeida, Mirna Clarissa Rodrigues de; Lucena, Leandro Ricardo Rodrigues de; Simões, Vicente José Laamon Pinto; Sales, Aldo Torres

doi:10.1590/1809-6891v21e-54719

Acessibilidade / Reportar erro

Brasil

Ciência Animal Brasileira

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Zootecnia • Ciênc. anim. bras. 21 • 2020 • https://doi.org/10.1590/1809-6891v21e-54719 copy

Leaf blade area estimate of Digitaria pentzii under different cutting Heights

Estimativa de área da lâmina foliar de Digitaria pentzii sob diferentes alturas de corte

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Pasture studies require information on leaf area, as it is one of the main parameters for evaluation of plant growth. Thus, the objective of this study was to estimate the leaf blade area of pangolão grass (Digitaria pentzii Stent.) using non-destructive methods by regression model analysis. The experimental design consisted of randomized blocks, with three cutting heights (10, 15, and 20 cm) and four replications. Three hundred leaf blades of pangolão grass were randomly collected, and their respective lengths (L) and widths (W) determined using a digital caliper. The leaf blade area of pangolão grass was estimated by the gravimetric method, using linear and power regression models to explain the leaf blade area as a function of the product of L and maximum W. The real leaf blade area presented an average value of 18.64 cm², ranging from 4.29 to 45.95 cm². The leaf blade area of pangolão grass, regardless of cutting height, was estimated with greater accuracy by the power model. The power model, Ŷ=LW^1.007, can be used to estimate the leaf blade area of pangolão grass based on leaf blade L and W values.

Keywords:
modeling; non-destructive method; pangolão grass

Models	Explanatory Variables
Models	LW
Linear	$Y_{i} = β_{0} + β_{1} {LW}_{i} + ε_{i}$
Power	$Y_{i} = β_{0} {LW}_{i}^{β_{1}} ε_{i}$

Variables	Min.	Mean	Standard deviation	Max.
Cutting height: 10 cm
RLA (cm²)	5.06	20.67	7.52	39.60
L (cm)	6.50	17.45	4.23	28.10
W (cm)	0.64	1.19	0.26	1.89
LW (cm²)	5.33	21.43	8.68	43.02
Cutting height: 15 cm
RLA (cm²)	5.57	17.79	9.95	45.95
L(cm)	5.90	14.74	6.15	31.90
W (cm)	0.27	1.03	0.32	1.85
LW (cm²)	2.66	16.46	11.32	54.24
Cutting height: 20 cm
RLA (cm²)	4.29	17.48	7.88	43.02
L(cm)	5.70	15.25	4.85	28.50
W(cm)	0.69	1.11	0.24	1.67
LW (cm²)	4.51	17.76	8.46	46.17
Regardless of cutting height
RLA (cm²)	4.29	18.64	8.61	45.95
L(cm)	5.70	15.81	5.26	31.90
W(cm)	0.27	1.11	0.28	1.89
LW (cm²)	2.66	18.55	9.78	54.24

Model	Equation real Leaf area	Adequacy criteria of the models
Model	Equation real Leaf area	R²	SSR	AIC	d
Cutting height: 10 cm
Linear	$\hat{Y} = 0.947 LW$	99.06	455.21	439.35	0.981
Power	$\hat{Y} = {LW}^{0.99}$	99.86	436.60	-153.34	0.981
Cutting height: 15 cm
Linear	$\hat{Y} = 1.002 LW$	96.46	1467.47	556.40	0.967
Power	$\hat{Y} = {LW}^{1.04}$	99.16	1299.26	14.21	0.969
Cutting height: 20 cm
Linear	$\hat{Y} = 0.969 LW$	98.86	416.93	430.56	0.983
Power	$\hat{Y} = {CL}^{0.997}$	99.79	412.49	125.68	0.983
Regardless of cutting height
Linear	$\hat{Y} = 0.97 LW$	98.09	2410.64	1480.52	0.975
Power	$\hat{Y} = {LW}^{1.007}$	99.57	2337.58	153.42	0.975

Universidade Federal de Goiás Universidade Federal de Goiás, Escola de Veterinária e Zootecnia, Campus II, Caixa Postal 131, CEP: 74001-970, Tel.: (55 62) 3521-1568, Fax: (55 62) 3521-1566 - Goiânia - GO - Brazil
E-mail: revistacab@gmail.com

Acompanhe os números deste periódico no seu leitor de RSS

[1] *Correspondent - nopalea21@yahoo.com.br