Heat and mass transfer coefficients and modeling of infrared drying of banana slices

Baptestini, Fernanda Machado; Corrêa, Paulo Cesar; Oliveira, Gabriel Henrique Horta de; Botelho, Fernando Mendes; Oliveira, Ana Paula Lelis Rodrigues de

doi:10.1590/0034-737X201764050002

Acessibilidade / Reportar erro

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Agricultural Engineering • Rev. Ceres 64 (5) • Sep-Oct 2017 • https://doi.org/10.1590/0034-737X201764050002 copy

Heat and mass transfer coefficients and modeling of infrared drying of banana slices

Coeficientes de transferência de calor e massa e modelagem da secagem por infravermelho de fatias de banana

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Banana is one of the most consumed fruits in the world, having a large part of its production performed in tropical countries. This product possesses a wide range of vitamins and minerals, being an important component of the alimentation worldwide. However, the shelf life of bananas is short, thus requiring procedures to prevent the quality loss and increase the shelf life. One of these procedures widely used is drying. This work aimed to study the infrared drying process of banana slices (cv. Prata) and determine the heat and mass transfer coefficients of this process. In addition, effective diffusion coefficient and relationship between ripening stages of banana and drying were obtained. Banana slices at four different ripening stages were dried using a dryer with infrared heating source with four different temperatures (65, 75, 85, and 95 ºC). Midilli model was the one that best represented infrared drying of banana slices. Heat and mass transfer coefficients varied, respectively, between 46.84 and 70.54 W m^-2 K^-1 and 0.040 to 0.0632 m s^-1 for temperature range, at the different ripening stages. Effective diffusion coefficient ranged from 1.96 to 3.59 × 10^-15 m² s^-1. Activation energy encountered were 16.392, 29.531, 23.194, and 25.206 kJ mol^-1 for 2^nd, 3^rd, 5^th, and 7^th ripening stages, respectively. Ripening stages did not affect the infrared drying of bananas.

Key words:
ripening; effective diffusion coefficient; mathematical modeling; Musa spp

Universidade Federal de Viçosa Av. Peter Henry Rolfs, s/n, 36570-000 Viçosa, Minas Gerais Brasil, Tel./Fax: (55 31) 3612-2078 - Viçosa - MG - Brazil
E-mail: ceres@ufv.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] *Corresponding author: gabriel.oliveira@ifsudestemg.edu.br

Model name	Model	Equation
Diffusion approximation (Yaldiz & Ertekin, 2001Yaldiz O & Ertekin C (2001) Thin layer solar drying some different vegetables. Drying Technology, 19:583-597.)	$M R = a e x p (- k t) + (1 - a) e x p (- k b t)$	(2)
Two-Terms (Henderson, 1974Henderson SM (1974) Progress in developing the thin-layer drying equation. Transactions of the ASAE, 17:1167-1168.)	$M R = a e x p (- k t) + b e x p (- g t)$	(3)
Henderson & Pabis (Henderson & Pabis, 1961Henderson SM & Pabis S (1961) Grain drying theory. I. Temperature effect on drying coeffiient. Journal of Agriculture Engineering Research, 6:169-174.)	$M R = a e x p (- k t)$	(4)
Midilli (*Midilli et al., 2002*Midilli A, Kucuk H & Yapar Z (2002) A new model for single layer drying. Drying Technology, 20:1503-1513.)	$M R = a e x p (- k t^{n}) + b t$	(5)
Logarithmic (*Yagcioglu et al., 1999*Yagcioglu A, Degirmencioglu A & Cagatay F (1999) Drying characteristic of laurel leaves under different conditions. In: 7th International Congress on Agricultural Mechanization and Energy, Adana. Proceedings, Ege University. p.565-569.)	$M R = a e x p (- k t) + b$	(6)
Verma (*Verma et al., 1985*Verma LR, Bucklin RA, Endan JB & Wratten FT (1985) Effects of drying air parameters on rice dryingmodels. Transaction of ASAE, 28:296-301.)	$M R = a e x p (- k t) + (1 - a) e x p (- g t)$	(7)
Page (Diamente & Munro, 1993Diamente LM, Munro PA (1993) Mathematical modelling of the thin layer solar drying of sweet potato slices. Solar Energy, 51:271-276.)	$M R = e x p (- k t^{n})$	(8)

Ripening stage	Temperature (°C)
Ripening stage	65	75	85	95
h_c (W m^-2 K^-1)				95
2^nd	55.50	57.46	59.56	70.53
3^rd	51.69	55.10	57.11	68.46
5^th	56.50	57.88	61.57	64.68
7^th	50.89	46.85	60.10	62.81
Average	53.64	54.32	59.58	66.62
Regression equation: $h_{c} = 23.1872 + {0.4419}^{* *} \times T$				R²: 0.9028
h_m (m s^-1)
2^nd	0.0473	0.0496	0.0523	0.0632
3^rd	0.0440	0.0476	0.0501	0.0614
5^th	0.0481	0.0500	0.0528	0.0580
7^th	0.0433	0.0404	0.0527	0.0563
Average	0.0457	0.0469	0.0520	0.0597
Regression equation: $h_{m} = 0.01133 + {0.0005}^{* *} \times T$				R²: 0.9118

T (ºC)	Model name	R² (%)	MRE (%)	SDE (decimal d.b.)
65	Diffusion approximation	99.98	10.98	0.0032
	Two-terms	99.98	10.85	0.0031
	Henderson and Pabis	99.66	10.68	0.0136
	Logarithmic	99.73	23.23	0.0122
	Midilli	99.98	3.78	0.0031
	Page	99.95	15.94	0.0052
	Verma	99.98	10.98	0.0032
75	Diffusion approximation	99.99	7.39	0.0023
	Two-terms	99.99	7.28	0.0022
	Henderson and Pabis	99.72	11.67	0.0123
	Logarithmic	99.79	21.42	0.0107
	Midilli	99.98	4.04	0.0030
	Page	99.97	10.92	0.0040
	Verma	99.99	7.39	0.0023
85	Diffusion approximation	99.98	7.77	0.0032
	Two-terms	99.98	7.73	0.0032
	Henderson and Pabis	99.61	15.61	0.0147
	Logarithmic	99.72	13.51	0.0123
	Midilli	99.96	9.48	0.0046
	Page	99.95	9.15	0.0049
	Verma	99.98	7.77	0.0032
95	Diffusion approximation	99.98	5.15	0.0025
	Two-terms	99.99	5.12	0.0024
	Henderson and Pabis	99.62	12.44	0.0147
	Logarithmic	99.72	14.47	0.0127
	Midilli	99.98	5.97	0.0036
	Page	99.96	8.04	0.0047
	Verma	99.99	5.15	0.0025

Ripening stage	T (°C)
Ripening stage	65	75	85	95
2^nd	2.45×10^-15	2.88×10^-15	3.17×10^-15	3.94×10^-15
3^rd	1.62×10^-15	2.32×10^-15	3.45×10^-15	3.44×10^-15
5^th	1.87×10^-15	2.50×10^-15	2.93×10^-15	3.64×10^-15
7^th	1.87×10^-15	2.56×10^-15	2.74×10^-15	3.34×10^-15
Average	1.96×10^-15	2.57×10^-15	3.07×10^-15	3.59×10^-15
Regression equation: $D_{e f} = - 2.0 \times 10^{{- 15}^{}} + 5.0 \times 10^{{- 17}^{}} \times T$			R²: 0.9980