Optimization on formulation of foamed overripe canistel powder using response surface methodology

Pertiwi, Sri Rejeki Retna; Sunarya, Rifki; Rohmayanti, Titi; , Aminullah

doi:10.1590/0100-29452020145

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Revista Brasileira de Fruticultura

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Processing • Rev. Bras. Frutic. 42 (3) • 2020 • https://doi.org/10.1590/0100-29452020145 copy

Optimization on formulation of foamed overripe canistel powder using response surface methodology

Otimização da formulação do pó canistel de sobreposição de espuma usando a metodologia de superfície de resposta

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Overripe canistel fruit was generally consumed and not yet widely utilized. The objective of this research was to study and determine the optimum formulation for water, egg albumin, and maltodextrin concentration in making canistel powder using the foam-mat drying method. Optimization was conducted by Response Surface Methodology (RSM) simple mixture of Design-Expert 7.0 software. The formulas used in this study were water of 50-55%, egg albumin of 15-20%, maltodextrin of 5-10% with a total of 75%, and overripe canistel fruit of 25%. The responses of yield, moisture, and beta carotene concentration were analyzed. The results showed that the higher the maltodextrin and the egg albumin concentration led to the higher the powder yield. The use of maltodextrin decreased moisture content and beta carotene concentration of canistel powder, while egg albumin increased them. In addition, the optimum solution was water of 50.00%, egg albumin of 16.88%, maltodextrin of 8.12%, and overripe canistel of 25%, which resulted in a yield of 54.90%, moisture content of 7.07%, and beta carotene of 2.65 mg.kg-1. Validation of the optimum solution was a yield of 61.20%, moisture content of 7.09%, and beta carotene of 0.63 mg.kg-1, which were within the 95% prediction interval low and high.

Index terms
Pouteria campechiana; overripe canistel fruit; foam-mat drying; surface analysis

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[TFN0701] ^*
CI = Confidence Interval, PI = Prediction Interval

Formula	(A) Water (%)	(B) Egg albumin (%)	(C) Maltodextrin (%)
1	51.67	16.67	6.66
2	52.50	17.50	5.00
3	52.50	15.00	7.50
4	53.33	15.83	5.83
5	50.00	15.00	10.00
6	50.00	15.00	10.00
7	50.00	20.00	5.00
8	55.00	15.00	5.00
9	50.00	20.00	5.00
10	50.00	17.50	7.50
11	52.50	17.50	5.00
12	50.83	18.33	5.83
13	55.00	15.00	5.00
14	50.83	15.83	8.33

Formula	Factor			Response
	Water	Egg albumin	Maltodextrin	Yield	Moisture content	Beta caroten concentration
	(%)	(%)	(%)	(%)	(%)	(mg.kg^-1)
1	51.67	16.67	6.66	53.81	10.47	2.74
2	52.50	17.50	5.00	46.21	11.17	0.00
3	52.50	15.00	7.50	43.60	11.62	2.90
4	53.33	15.83	5.83	40.32	10.72	2.06
5	50.00	15.00	10.00	59.07	9.54	1.87
6	50.00	15.00	10.00	58.69	8.79	2.24
7	50.00	20.00	5.00	50.05	8.21	1.52
8	55.00	15.00	5.00	35.33	10.26	1.42
9	50.00	20.00	5.00	46.11	12.37	1.63
10	50.00	17.50	7.50	54.27	6.91	2.56
11	52.50	17.50	5.00	42.69	8.84	1.53
12	50.83	18.33	5.83	48.35	9.02	3.02
13	55.00	15.00	5.00	30.80	11.03	0.00
14	50.83	15.83	8.33	48.11	8.64	1.65

Source	Sum of squares	df	Mean square	F value		p-value
Model	752.87	2	376.43		35.78		< 0.0001
Linear Mixture	752.87	2	376.43		35.78		< 0.0001
Residual	115.73	11	10.52
Lack of Fit	91.40	7	13.06		2.15		0.2401
Pure Error	24.33	4	6.08
Cor Total	868.60	13

Std. Dev.	3.24	R-Squared	0.8668
Mean	46.96	Adj R-Squared	0.8425
C.V. %	6.91	Pred R-Squared	0.8007
PRESS	173.13	Adeq Precision	15.7792

Source	Sum of squares	df	Mean square	F value	p-value
Model	16.44	5	3.29	2.00	0.1836
Linear Mixture	6.48	2	3.24	1.97	0.2020
AB	0.12	1	0.12	0.07	0.7976
AC	3.83	1	3.83	2.33	0.1658
BC	7.01	1	7.01	4.25	0.0731
Residual	13.18	8	1.65
Lack of Fit	1.24	4	0.31	0.10	0.9749
Pure Error	11.94	4	2.98
Cor Total	29.63	13

Std. Dev.	1.2836	R-Squared	0.5551
Mean	9.8269	Adj R-Squared	0.2770
C.V. %	13.0623	Pred R-Squared	-0.5222
PRESS	45.0967	Adeq Precision	5.6062

Element	Goal	Lower Limit	Upper Limit	Lower Weight	Upper Weight	Importance
Water	is in range	50	55	1	1	3
Egg albumn	is in range	15	20	1	1	3
Maltodextrin	is in range	5	10	1	1	3
Yield	maximize	30.80	59.07	1	1	4
Moisture content	minimize	6.91	12.37	1	1	5
Beta carotene	is in range	0.00	3.02	1	1	3

Response	Prediction	Validation	95% CI low	95% CI high	95% PI low	95% PI high
Yield	54.90	61.20	52.08	57.72	47.22	62.58
Moisture Content	7.07	7.09	4.69	9.44	3.27	10.86
Beta Carotene	2.65	0.63	1.22	4.08	0.37	4.93

Source	Sum of squares		df	Mean square		F value	p-value
Model	6.51		5	1.30		2.19	0.1545
Linear Mixture	2.91		2	1.46		2.46	0.1474
AB	0.04		1	0.04		0.07	0.7978
AC	2.36		1	2.36		3.98	0.0811
BC	0.85		1	0.85		1.44	0.2651
Residual	4.74		8	0.59
Lack of Fit	2.49		4	0.62		1.11	0.4624
Pure Error	2.25		4	0.56
Cor Total	11.25		13
Std. Dev.	0.7701	R-Squared			0.5784
Mean	1.7957	Adj R-Squared			0.3148
C.V. %	42.8856	Pred R-Squared			-0.0920
PRESS	12.2875	Adeq Precision			4.1135