Controlled-Release Fertilizer on Growth of <i>Melanoxylon brauna</i> Schott Seedlings

Gibson, Elbya Leão; Gonçalves, Elzimar de Oliveira; Santos, Aline Ramalho Dos; Araújo, Emanuel França; Caldeira, Marcos Vinicius Winckler

doi:10.1590/2179-8087.041818

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Original Article, Silviculture • Floresta Ambient. 26 (spe1) • 2019 • https://doi.org/10.1590/2179-8087.041818 copy

Controlled-Release Fertilizer on Growth of Melanoxylon brauna Schott Seedlings

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Melanoxylon brauna is a tree species native to the Atlantic Forest of high ecological and economic value. The objective of this study was to evaluate the growth and nutritional status of seedlings of two Melanoxylon brauna cultivars grown in substrate with different controlled-release fertilizer doses (CRF). The experiment was arranged in a randomized block 4 × 2 factorial design, with four CRF doses (0, 2, 4, and 8 kg m^-3) and two seed origins (Viçosa-MG and Linhares-ES), with four replicates and 126 seedlings per plot. At 60, 90, and 120 days after emergence, seedlings were collected to measure variables related to emergence, growth, and nutrition. The greatest growth and best nutritional status were found for seedlings originated from seeds collected in Linhares at CRF dose of 8 kg m^-3. On the other hand, seedlings originated from seeds collected in Viçosa showed low emergence and high plant mortality.

Keywords:
brauna; plant propagation; forestry; forest legume; forest nutrition

Municipality	Köppen Classification	Average rainfall	Days per year with rainfall	Average compensated temperature	Average altitude	Relative humidity	Sunshine
Municipality	(1948)	(mm year^-1)	Days per year with rainfall	Average compensated temperature	Average altitude	(%)	hours
Viçosa	Cwa	1289	92	20.1	690	80.3	2.098.2
Linhares	Aw	1267	116	24.0	33	83	2.182.3

N	P₂O₅	K₂O	Mg	S	Fe	Cu	Mn	Mo	Grain diameter	1000 seed weight
%									Mm	g
13.00	6.00	16.00	1.40	10.00	0.26	0.05	0.06	0.015	1.5 – 2.5	9.58

pH	N	P	K	Ca	Mg	S	CE	Density
(H₂O)	g kg^-1						mS cm^-1	g cm^-3
6.2.	11.5	9.0	5.2	15.0	7.2	4.5	0.4	0.35

SV	DF	Mean square
		ESI	E	MET	M 60	M 90	M 120
		ESI	(%)	(days)	(%)	(%)	(%.)
Origin	3	1.209**	82.34**	0.6980^ns	2.771^ns	24.577*	107.534*
Rate	1	0.0057^ns	0.230^ns	0.2609^ns	4.085^ns	5.901^ns	3.109^ns
D × P	3	0.012^ns	0.701^ns	0.340^ns	2.345^ns	3.806^ns	5.504^ns
Block	3	0.014^ns	0.727^ns	0.3185^ns	17.44^ns	2.324^ns	4.101^ns
Error	21	0.0059	0.321	0.300	4.649	8.319	2.584
CV %		6.08	15.35	13.98	60.93	52.15	22.05
Mean ES		1.160 a	27.48 a	15.59 a	14.84 a	21.90 a	29.48 a
Mean MG		0.162 b	3.67 b	13.81 a	18.95 a	51.97 b	87.29 b

Variable	Equation	R²	Optimal dose	Estimated maximum value
H 60	$n s = (\hat{Y} = \bar{Y} = 3.21)$	-	-	-
H 90	$\hat{Y} = 5.132 + 0.7924 * * x$	0.88	8.00	11.47 cm plant^-1
H120	$\hat{Y} = 6.5702 + 1.3377 * * x$	0.86	8.00	17.27 cm plant^-1
Inc H90	$\hat{Y} = 2.1597 + 0.7229 * * x$	0.86	8.00	7.94 cm plant^-1momth^-1
Inc H120	$\hat{Y} = 0.7057 + 1.303 * * x - 0.09145 * * x^{2}$	0.97	7.12	5.34 cm plant^-1momth ^-1
CD 60	$n s (\hat{Y} = \bar{Y} = 1.61)$	-	-	-
CD 90	$\hat{Y} = 1.4835 + 0.1297 * * x$	0.83	8.00	2.52 mm plant^-1
CD 120	$\hat{Y} = 1.82745 + 0.17524 * * x$	0.81	8.00	3.22 mm plant^-1
Inc DC90	$\hat{Y} = 0.181 + 0.2904 * * x - 0.0239 * * x^{2}$	0.98	6.07	1.06 mm plant^-1momth ^-1
Inc DC120	$\hat{Y} = 0.258716 + 0.1335 * * x - 0.0239 * * x^{2}$	0.98	6.28	0.67 mm plant^-1momth ^-1
LN 60	$n s (\hat{Y} = \bar{Y} = 9.86)$	-	-	-
LN 90	$\hat{Y} = 4.968 + 2.055 * * x - 0.149311 * * x^{2}$	0.99	6.88	12.03 Un. plant^-1
LN 120	$\hat{Y} = 5.139 + 2.518 * * x - 0.1887 * * x^{2}$	0.99	6.67	13.54 Un. plant^-1
LC 60	$\hat{Y} = 25.97805 + 1.21621 * * x$	0.84	8.00	35.70 ug cm²plant^-
LC 90	$\hat{Y} = 28.159 + 3.137 * x - 0.2786 * x^{2}$	0.97	5.62	36.99 ug cm²plant^-
LC 120	$\hat{Y} = 21.079 + 4.767 * * x - 0.37243 * * x^{2}$	0.99	6.39	36.33 ug cm²plant^-

Variable	Equation	R²	Optimal dose	Estimated maximum value
RL	$\hat{Y} = 18.2150 + 2.0725 * * x$	0.86	8.00	34.79 cm plant^-1
SDM	Ŷ = 0.11788 + 0.412254**x	0.99	8.00	3.41 g plant ^-1
RDM	$\hat{Y} = - 0.00991 + 0.08763 * * x$	0.98	8.00	0.69 g plant ^-1
TDM	$\hat{Y} = 0.10797 + 0.49989 * * x$	0.99	8.00	4.10 g plant ^-1
DQI	$\hat{Y} = 0.00617 + 0.04851 * * x$	0.99	8.00	0.39
APSH	$\hat{Y} = 0.83857 + 1.9081 * * x$	0.78	8.00	16.10 mg plant ^-1
ACaSH	$\hat{Y} = 0.5143 + 2.2617 * * x$	0.79	8.00	18.60 mg plant ^-1
AMgSH	$\hat{Y} = 0.0396 + 0.5605 * * x$	0.81	8.00	4.52 mg plant ^-1
ASSH	$\hat{Y} = 0.079096 + 0.5833 * * x$	0.96	8.00	4.74 mg plant ^-1

Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro Rodovia BR 465 Km 7, CEP 23897-000, Tel.: (21) 2682 0558 | (21) 3787-4033 - Seropédica - RJ - Brazil
E-mail: floram@ufrrj.br

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[1] Elbya Leão Gibson Programa de Pós-graduação em Ciências Florestais, Departamento de Ciências Florestais e da Madeira, Universidade Federal do Espírito Santos – UFES, Av. Gov. Lindemberg, 316, Centro, CEP 29550-000, Jerônimo Monteiro, ES, Brasil e-mail: elbyagibson@hotmail.com