Evaluation of the Kinetics of Drying Sweet Chili ( Capsicum annuum ) in a Tray Dryer

This study establishes the kinetics regarding the drying process of sweet chili (Capsicum annuum), in order to obtain flour through a tray dryer. The sweet chili samples of 9±0.2° Brix, humidity 91.18% and green coloration were adapted to 2.3×2.3 cm dimensions, dried at 50, 60 and 70°C temperatures on a tray dryer with forced air at 2.7m/s, continual weight. The drying curves were adjusted to 12 mathematical models, determined through adjusted R and the Sum of Squared Errors (SSE) that the Midilli and Kucuk model best describe the drying process at a 50°C temperature (R of 0.9976 and SSE of 0.012), at 60°C (R of 0.9972 SSE of 0.011) and 70°C (R of 0.9960 SSE of 0.012).


INTRODUCTION
Sweet chili (Capsicum annuum) is a product typically cultivated in Colombia informally; this subsector is poorly structured, with the possibility of technification due to the low production costs and the profitability it has, mainly in Valle del Cauca and Cordoba department (Asohofrucol, 2013).Regarding the Caribbean region, sweet chili production is very important and it is considered a main component in the food manufacturing like stews, sauces, soups and canned products because of its peculiar flavor and scent.The variety of uses of sweet chili, favors the fact that it is considered an added value, developing products like chili flour for later commercialization as condiment, guaranteeing with its preservation a more stable market against the ever-changing prices due to the supply and demand (Asohofrucol, 2013).
Drying is one of the oldest methods for food preservation; nowadays it serves that purpose along with ensuring the food quality and a commercial alternative for markets (Estrada Velázquez, 2006).Dehydrated products, compared to fresh ones, offer great advantages because of their larger life span due to the reduction of water conteined which also favors the microorganism reduction and the enzymatic activity (González et al., 2008).The study of temperature, time and drying speed variables, are determined by the quality of the product; therefore, an excess of drying air exposure would deteriorate the sweet chili flour while low exposure would neglect the correct dehydration.In both situations the organoleptic characteristics would be altered (Krokida and Maroulis, 2001 quoted by Vega et al., 2005;Colina, 2010).
The following investigation is oriented to determine the kinetics regarding the drying process of sweet chili (Capsicum annuum), in order to obtain flour through a forced air tray dryer.

Obtaining prime materials and adequacy of the sample:
The chili was obtained at a public market of the city of Monteria, with a green coloration, fresh and uniform with a 9-10 °Brix and 91-92% humidity, apt for processing and consumption, sane with the absence of damages caused by bumps, microorganisms or insects.Samples of chili were superficially washed with drinking water, the seeds inside were taken out through a parallel cut and samples of approximately 0.1 cm thickness, 2.3 cm length and 2.3 cm width were obtained.

Determination of the humidity content and initial water activity (aw):
Previous to the drying trials, initial humidity of the fresh sweet chili was established using the described method on the (AOAC, 2003).With the obtained value, the dry weight of the sample was calculated for each temperature.In addition, the aw of the fresh samples was determined by equipment from the brand Novasina, LabMaster-aw model at 25°C, with three repetitions for both tests.

Sweet chili samples dehydration:
In order to determine the drying curves, 50 g samples of sweet chili were used, with known dimensions they were placed on the tray, verifying they completely covered the base and were put into the drying chamber of the convection oven, brand Technicook, model MINICONV, dimensions 580 mm width, 630 mm depth, 435 mm height, Laboratory tray GIPAVE from the University of Cordoba, Berastegui campus.
Treatment temperature conditions of 50, 60 and 70°C were applied, drying air speed of 2.7 ms -1 .A weight control of the samples is being held every 5 min throughout the process until constant weight values were obtained, using an analytical scale (Mettler PC4000 with 0.01 g accuracy).This procedure was applied to every treatment with three repetitions.

Drying curves construction and mathematical models of the drying kinetics:
For the drying curve construction, the Geankoplis (1993) method was used for which a data conversion of the humidity on a humid base content (water kg/humid product kg) to dry base humidity content (water kg/dry solid kg) was made, using Eq. ( 1) (Zuluaga et al., 2010): where, ܺ ௧ = Humidity content on dry base on time ܹ = Humid solid weight ܹ ௦ = Dry solid weight After establishing the humidity content balance (X*), the value of free humidity content was calculated (X) on the food for each value of ܺ ௧ , Eq. ( 2) (Zuluaga et al., 2010): where, X = Free humidity content ܺ ௧ = Dry base humidity content in time ܺ * = Balance humidity content Then, the speed R was calculated in time for each temperature, through Eq. ( 3) (Colina, 2010): where, R = Drying speed ‫ܮ‬ ௦ = kg of used dry solid A = Superficial area exposed to drying Afterwards, a graph of the humidity content of the dry based product was made, opposite to time in order to determine the drying curves and the graph of the drying speed opposite to the free humidity of the product in order to determine the drying phases.
With the purpose of determining the mathematical modeling of the experimental data drying curves the adjustment to those 12 models were evaluated (Table 1) using as a dependent variable the humidity reason (MR), calculated through Eq. ( 4) (Michalewicz et al., 2011) and the nonlinear regression method for the estimation of the model constants: where, X = The humidity content on a specific lapse of time ܺ = The balance humidity content ܺ = The initial humidity content, all expressed in water g/dry matter The criteria used to evaluate the quality of the obtained adjustment of the proposed models over the experimental data were the adjusted R 2 adjusted and the Sum of Squared Errors (SSE).Low SSE and high R 2 values were used as criteria to indicate the high adjustment of the model (Espinosa, 2013).
The diffusion coefficient was calculated using a diffusion model from the second law of Fick for an infinite plate geometry and the uniform distribution of the initial humidity Eq. ( 5) obtaining the value from the slope of the In (MR) graph in function of time for each temperature (Michalewicz et al., 2011): where, ‫ܦ‬ = The effective coefficient of water diffusivity (m 2 s -1 ) t = Time in hours L = The thickness factor of the finite plate (m) To determine the activation energy, it was taken into account the fact that the drying temperature influence over water diffusion in food follows an Arrhenius-type tendency (see Eq. 6), obtaining the value from the slope of the Ln ‫ܦ‬ graph in function of the temperature inverse ( ଵ ் ) and the Arrhenius factor ‫ܦ(‬ ) of the ordinate in the origin (Vega et al., 2005): where, ‫ܧ‬ = The activation energy of the diffusion R = The gas constant T = The absolute temperature ‫ܦ‬ = The diffusion for high humidity contents For The experimental analysis, the nonlinear regression method was used, in order to estimate the model constant, selecting the model that fit best, using as choosing criteria the adjusted R 2 and the Sum of Squared Errors (SEE).The data was processed and evaluated through the Statgraphics Centurion XVI software.A completely random experimental design was applied, having as treatment the air drying temperature on three levels (50, 60 y 70°C) and three repetitions of each for a total of 9 experimental units.The results were Analyzed through a Variance Analysis (ANOVA) in order to determine if significant statistical differences existed at a 95% reliability rate.The significant differences were established using the Tukey test with a reliability rate of 95% in the statistical program Statgraphic Centurion XVI (16.2.04 version) and Microsoft Excel.

Sample characterization and adequacy:
The selected samples of sweet chili were green, presenting 9±0.2 °Brix, firmness (lbf) 12-16 and were geometrically fitted with the following dimensions: 0,1 cm de thick, 2.3 cm length and 2.3 cm width approximately (Fig. 1).The humidity content of the fresh product was ) at three temperatures (50, 60 and 70°C), evidencing through variance ANOVA analysis a highly significant influence of the temperature over sweet chili drying time, with a significant level of 5%.After the Tukey media comparison test it was observed significant differences among the three studied levels, because when the temperature is increased, the drying time lowers significantly, taking up less time to finalize the drying process at 70°C (230 min) than for 50°C (435 min) and 60°C (315 min), up until it reaches the same balanced humidity.Similar effects of the temperature over the process were obtained for red pepper (Vega et al., 2005), Chilean papaya (Vega and Lemus, 2006), guava (Hincapié et al., 2011) and Tabasco (Arrieta et al., 2015).Also, an initial drying phase is distinguished within the first 75 min at 50°C, 80 min at 60°C and 90 min at 70°C, in which the humidity loss on dry base of the sample has a lineal behavior of (R 2 >90%), just like the drying speed for the same period of time, power assigned to the quick redistribution of humidity and the migration to the surface (Hincapié et al., 2011).After this phase the speed slows down faster until it reaches the humidity balance.It is characteristic because in it, most of the drying process happens, because humidity is spreaded with less speed through a solid.
Drying speed curves: In Fig. 3 we can appreciate the behavior of the drying speed of sweet chili (Capsicum annuum L.) through the three temperatures (50, 60 and 70°C), from which can be deduced (with the obtained ANOVA analysis) that the kinetics of drying of the sweet chili depend on the drying air temperature, being highly influential with a significance level of 5%.After going through with the Tukey tests the significant differences were observed among the three evaluated levels, due to the fact that when the air drying temperature is increased, the drying speed increases, appreciating initial average speeds at 70°C for 2.26 kg of water, h -1 m -2 , a significant higher value than the ones presented at 60°C with a speed of 1.78 kg of water h -1 m -2 and this one at 50°C of 1.37 kg of water h -1 m -2 of speed.In Fig. 3 the drying speed phases are illustrated, evidencing an absence of the constant speed span and the induction period, because the dried, at the moment of the sample being introduced, was at the required temperature.In addition, a fast-speed decreasing period is presented which makes the surface harden followed by a slower decreasing period in which the product surface is completely dry and the vaporization level starts to move, which is why the evaporated water goes through the solid in order to reach the air current so the samples start evidencing a more accentuated shrinking in this period (Jhonson, 2013).Similar effects of temperature over drying speed were reported on studies over drying peppers (Vega et al., 2005), Plantains (Sandoval-Torres et al., 2006), raspberry laminas (Jhonson, 2013) and Tabasco (Arrieta et al., 2015).

Mathematical modeling of the drying curves:
The Midilli and Kucuk model is satisfactorily adjusted to the obtained experimental data for the construction of the sweet chili drying curves at 50, 60 and 70°C applied temperatures, with adjusted R 2 values superior to 99% and squared added values of the lowest error compared to the ones obtained for the remaining 11 evaluated models.In Table 2 the Midilli and Kucuk model parameter values are showing that the values of k and n are higher in treated chili at 70°C than the one treated at 60°C and 50°C.
Another drying products studies expose Midilli and Kucuk ad the model with the best fit regarding the dehydration behavior of yam (García-Mogollon et al., 2016).On parsley Lema et al. (2007) evaluated twelve mathematical models and found that the Logarithmic

Diffusion coefficient and activation energy:
To model the decreasing speed phase, the difusional model was used.The diffusion coefficient for each temperature was calculated from Fig. 5 where Ln (MR) is connected in relation of time.
The diffusion values presented significant differences (p<0.05)among the drying air temperatures (ANOVA), through the Tukey median comparison analysis it was discovered that diffusion levels at 50, 60 and 70°C present significant differences amongst each other.
In Table 3 we can observe that the diffusion values increased according to the increase of the drying air temperature which shows an intern resistance decrease of the solid with the increasing of temperature.Similar results were obtained in the chilean papaya (Vega and Lemus, 2006), mango (Ocampo, 2006) and parsley (Lema et al., 2007).Generally, the drying temperature influence over diffusion of the sweet chili water follows an Arrheniuslike tendency, using Fig. 6 in which Ln (Df) is in function of the temperature inverse (1/T), which permits the obtaining of a straight line, the slope representing the activation energy.
In Table 3 we can observe the activation energy which is found in the value range found in food material literature proposed by some authors: 28.39 kJ/mol for carrots (Doymaz, 2004); 39.7 kJ/mol for red pepper (Vega et al., 2005); 20 kJ/mol for potatoes and 149 kJ/mol for parsley (Lema et al., 2007).Said value represents the required energy to start the humidity diffusion of sweet chili, indicating the influence of the temperature in the process (Espinosa, 2013).

Fig. 1 :
Fig. 1: Samples of sweet chili for drying 91.189±0.01%and the water activity of the fresh sample was 0.84±0.01.Drying speed curves: In the Fig. 2 are shown the drying speed curves of sweet chili (Capsicum annuum L.) at three temperatures (50, 60 and 70°C), evidencing through variance ANOVA analysis a highly significant influence of the temperature over sweet chili drying time, with a significant level of 5%.After the Tukey media comparison test it was observed significant differences among the three studied levels, because when the temperature is increased, the drying time lowers significantly, taking up less time to finalize the drying process at 70°C (230 min) than for 50°C (435 min) and 60°C (315 min), up until it reaches the same balanced humidity.Similar effects of the temperature over the process were obtained for red pepper(Vega et al., 2005), Chilean papaya(Vega and Lemus, 2006), guava(Hincapié et al., 2011) and Tabasco(Arrieta et al., 2015).Also, an initial drying phase is distinguished within the first 75 min at 50°C, 80 min at 60°C and 90 min at 70°C, in which the humidity loss on dry base of the sample has a lineal behavior of (R 2 >90%), just like the drying speed for the same period of time, power assigned to the quick redistribution of humidity and the migration to the surface(Hincapié et al., 2011).After this phase the speed slows down faster until it reaches the humidity balance.It is characteristic because in it, most of the drying process happens, because humidity is spreaded with less speed through a solid.

Table 2 :
Midilli and Kucuk model constants for the temperatures of the paper Treatment Midilli and kucuk model parameters