Effect of Temperature and Concentration on the Density of Clarified Pineapple Juice

Abstract

The effect of temperature and soluble solids concentration on density of clear pineapple juices was studied. The density was determined with soluble solids content from 10 to 64.1°Brix, and temperatures between 10 to 70°C with 10°C increments. The aim of this work was to develop suitable mathematical models for the use in concentration process by evaporation. The density of pineapple juice was strongly affected by soluble solids concentration, while it was relatively less affected by temperature. Different models were developed as a function of soluble solids content and temperature.

Keywords:

• Density
• Pineapple juice
• Temperature
• Soluble solids content

INTRODUCTION

Pineapple (Ananas comosus) is one of the most important commercial tropical fruits and is recognized as one of the most popular fruits and flavours around the world. The market for NFC (not from concentrate) pineapple juice and concentrate has undoubtedly become one of the largest ones in Europe.[1] According to FAO's Tropical Fruit Commodity Notes,[2] from 1999–2003, Costa Rica, Côte d'Ivoire and Philippines have become the largest exporting markets of fresh pineapple fruit. However, Thailand and Indonesia are the largest processors of NFC and concentrates.

Pineapple fruit is squeezed with the action of mills and screw-presses resulting in single strength juice after pasteurization.[3] Nonetheless, most of the commercial pineapple juice is made from concentrate, usually obtained by thermal concentration. In this respect, some insight into the physical properties of food is fundamental to analyse the unit operations that are implemented in food industry. Studies of these properties and their responses to process conditions are necessary because of tow main reasons. First, because they influence the treatment applied in the process, and second, because they become reliable indicators of the quality of food.

Thus, physical properties of foods are fundamental parameters used in the designing and calculations of both equipment and control processes.[4] They are also very important for the developing of new industrial products with desired properties or for quality improvement of already existing ones.[5] The transport phenomena (momentum, heat, and mass) can be applied for determining efficiency of food systems if engineering data are available.[6] Density of fruit juices (concentrate and intermediate products), is greatly affected by both solids content and temperature. For this reason, it becomes essential to get to know the physical property values of fruit juices as a function of temperature and concentration.

For grape juice, density data has been measured by different authors working with different varieties of grapes, soluble solid concentrations, and temperatures.[7–10] Empirical equations that related the density with soluble solids concentration and temperature for juice of apple (Malus domestica) were proposed by Aguado and Ibarz[11] and Constenla et al.[12] Alvarado and Romero[13] proposed an equation for density as a function of concentration and temperature for different fruit juices. Data and equations of density for cloudy and depectinised juice of crab apples (Malus floribunda) were reported by Cepeda and Villarán.[14] Ibarz and Miguelsanz[15] studied the variation of the density of a depectinised and clarified pear juice with temperature and concentration of soluble solids. Ramos and Ibarz[16] carried out a similar study in depectinised and clarified peach and orange juice. In a previous work, Garza et al.[17] studied the effect of temperature on density of a concentrated pineapple juice with a soluble solids content of 64.1°Brix. Unfortunately, at present there are few data relating to pineapple juice as a function of temperature and concentration. A more extensive study on the effect of temperature and concentration on density of pineapple juice are reported in this paper. The aim of this research is to determine the density of depectinised and clarified pineapple juice and to model the effect of temperature (10–70°C) and soluble solids contents (10–64.1°Brix).

MATERIALS AND METHODS

The experimental study was carried out from raw materials supplied by a factory located near Lleida (Spain). Samples used were obtained from pineapple juice concentrate, previously depectinised and clarified through manufacture, with a soluble solid concentration of 64.1°Brix. Samples of 10, 20, 30, 40, 50 and 60°Brix were obtained by dilution of the original concentrated juice with distilled water. The sample of concentrated juice was characterized by the following physicochemical determinations: pH and acidity, in accordance with AOAC,[18] formol index,[19] sugars,[20] and soluble solids contents measured in triplicate as°Brix, using an Atago RX-1000 digital refractometer (Atago Company Ltd., Tokyo, Japan) at 20°C.

Relative density data were measured by pycnometers of 25 ml capacity at temperatures from 10 to 70°C, at 10°C intervals. In order to verify possible changes in their volume due to thermal expansion, each pycnometer had been previously calibrated with distilled water through a heating process, whereby the sample pycnometer was weighed at 10°C intervals from 10 to 70°C. A Digiterm 3000613 (Selecta, Barcelona, Spain) thermostatic water bath was used to control the temperature. Pycnometers were filled with the pineapple juice samples and placed in the thermostatic bath until reaching the specified temperature. Pycnometers were then quickly weighed in an analytical balance (Salter ER-120A, A&D Co. Ltd. Japan) with 0.0001 g precision. Measurements were made in triplicate at 10, 20, 30, 40, 50, 60, and 70°C with of soluble solids concentrations of 10, 20, 30, 40, 50, 60, and 64.1°Brix.

Experimental data were fitted to four different models (linear, quadratic, exponential, exponential quadratic) using Statgraphics version 7.0 software (STSC Inc., Reckville, MD, USA). In all cases, estimated parameters are given with their respective confidence intervals (p = 0.05), as a result of the standard error of estimates by the Student-t adjusted at the degree of freedom. Fitting accuracy was evaluated through the analysis of R² and the plot of prediction error.

RESULTS AND DISCUSSION

Table 1 shows the results of the physicochemical characterization of pineapple juice concentrate of 64.1°Brix. The experimental results obtained for the density of depectinised and clarified pineapple juices at several temperatures and concentrations are shown in Table 2. Density values obtained for pineapple juice can be compared with values obtained in previous studies as regards depectinised and clarified juices such as pear juice,[15] peach and orange juices,[16] Malus floribunda juice,[14] or clear grape juice.[10] According to the data presented in Table 2, increase in concentration and decrease in temperature result in density increase. As for all assayed temperatures, density was found to be strongly affected by juice concentration.

Table 1 Physical and chemical characteristics of depectinised and clarified pineapple juice concentrate

pH	4.86
Acidity (g/l citric acid)	13.7
Soluble solids (°Brix)	64.1
Total moisture content (%)	33.2
Formol index (ml 0.1 N NaOH/100 ml)	37
Glucose (g/l)	135.23
Fructose (g/l)	127.85
Sucrose (g/l)	361.92

Table 2 Experimental values for density (in g/cm³) at different concentration and temperature for a depectinised and clarified pineapple juice

	Density (g/cm^3)
Temperature (°C)	64.1 Brix	60 Brix	50 Brix	40 Brix	30 Brix	20 Brix	10 Brix
10	1.320	1.296	1.240	1.185	1.135	1.086	1.042
20	1.317	1.292	1.237	1.181	1.132	1.085	1.040
30	1.307	1.285	1.233	1.177	1.129	1.081	1.036
40	1.301	1.279	1.228	1.172	1.125	1.077	1.033
50	1.294	1.272	1.222	1.167	1.120	1.072	1.028
60	1.285	1.264	1.215	1.160	1.113	1.066	1.022
70	1.277	1.256	1.208	1.153	1.107	1.060	1.017

As a case in point, at 10°C, pineapple juice density increased from 1.042 g/cm³ at 10°Brix soluble solids content to 1.320 g/cm³ at 64.1°Brix, which involves an increase by 26.7%. Similar increases in density (around 26%) are observed in all assayed range of temperatures. However, these increase decrease slightly at higher temperature. Consequently, through a concentration increase from 10 to 64.1°Brix, densities at 70°C were increased by 25.6%. Density was also slightly affected by temperature as, through a concentration of 64.1°Brix, density decreased by 3.3% with a temperature increase from 10 to 70°C. These resulting data seems to corroborate the study of Zuritz et al.[10] on clear grape juice whereby it was reported that, at 80°C, density increased by 24.11% for a concentration increase from 22.9 to 70.6°Brix. I was also stated that, with a soluble solids content of 70.6°Brix, density decreased by 2.69%, under a temperature increase from 20 to 80°C. Cepeda and Villarán[14] have studied the density of depectinised Malus floribunda juice at 25°C, finding out that density increased by 27.5%, for a concentration increase from 17.6 to 70°Brix.

In order to model the single effect of temperature or concentration on density, experimental values were fitted to those models proposed by Aguado and Ibarz[11] who studied the variation of density with temperature and concentration in clarified apple juice. These models are linear, quadratic, exponential and quadratic exponential as shown in the 1–4) below:

(1)

(2)

(3)

(4)

where ρ is density in g/cm³; a, b and c are constants; and P is the variable to model, temperature (°C) or concentration (°Brix). Equations that resulted in low residual square error were selected from the models for density variation in temperature and concentration. Finally, correlation coefficient and F values and the reliability interval for each of the variables were also calculated.

Figure 1 shows that density decreased with increasing temperature for fixed soluble solids contents. Experimental data were fitted to proposed models (Eqs. 1–4). Given the results obtained from the regression analysis, correlation coefficients were found to range in all cases from 0.9844 to 0.9999. In addition, values of parameter a, and absolute value of parameter b, increased with increasing concentration. Nonetheless, values of parameter c, in quadratic and exponential quadratic models, were eventually disregarded as they found insignificant (10⁻⁶ order). Then, quadratic and exponential quadratic models become linear and exponential models. Therefore, it may be suggested that a linear model, due to its appropriate fitting and simplicity, may help to predict density as a function of temperature.

Figure 1 Density of depectinised and clarified pineapple juice at different soluble solids content as a function of temperature, together with the linear fitting.

Concerning the effect of concentration, density variation under fixed temperature augmented with increasing concentration under a similar temperature effect (Fig. 2). Thus, a linear model can be proposed so as to predict pineapple juice density as a function of concentration. According to Cepeda and Villarán,[14] who reported these results at 25°C, the density variation of clarified and depectinised juice of Malus floribunda with concentration is found to be linear.

Figure 2 Density of depectinised and clarified pineapple juice at different temperatures as a function of concentration, together with the linear fitting.

Combined Effect of Concentration and Temperature on Density

From the perspective of engineering, working out simple equations that allow computing density values from temperature and concentration may be of ultimate importance. In this respect, several models have already been proposed so as to predict the resulting effect of combining concentration and temperature on fruit juices density. Zuritz et al.[10] have suggested a second-degree polynomial to correlated clear grape juice density as a function of concentration (from a range between 22.9 and 70.6°Brix) and of temperature (between 20 and 80°C). Ramos and Ibarz[16] have also reported that the best fitting model for depectinased and clarified peach and orange juices is a four-term polynomial model. Ibarz and Miguelsanz,[15] have also proposed a four-term polynomial model for depectinised and clarified pear juice for 10–71°Brix concentration, and 5–70°C temperatures.

This paper, has attempted to describe density variation through the combined effect of temperature and concentration according to the models proposed by Aguado and Ibarz[11] in their previously mentioned study of clarified apple juice density. These models are presented in the equations below:

Table 3 Fitting parameters for equations to predict the variation of density of depectinised and clarified pineapple juice with temperature and soluble solids concentration

Equation model	A	−b·10^4	c·10^3	d·10^6	R^2
ρ = a + bT + cC + dC ^2	1.010±0.004	5.41±0.9	4.1±0.2	11±3	0.9982
ρ = (a + bT)exp(cC + dC ^2)	1.006±0.003	4.6±0.3	4.3±0.1	0.4±2.1	0.9988
ρ = (a + cC + dC ^2)exp(bT)	1.007±0.003	4.7±0.3	4.2±0.1	12±3	0.9988
ρ = a exp(bT + cC + dC ^2)	1.006±0.003	4.7±0.3	4.3±0.1	0.4±2.1	0.9988

(5)

(6)

(7)

(8)

where ρ is density in g/cm³; a, b, c and d are constants; T is temperature i(°C); and C is concentration (°Brix). Given the results in Table 3, there is positive fitting between the density measured data and the mathematical models proposed (Eqs. 5–8), with resulting R² values higher than 0.998 in all cases. Consequently, all four equations would be suitable so as to predict the density value of pineapple juices over the assayed range of temperature and soluble solids concentration. In order to select the best fitting equation, predicted values of density obtained from the proposed models were plotted versus experimental values, and statistical analysis was also applied. Overall, the resulting equation was the following:

(9)

Figure 3 shows the response surface obtained from Eq. (9). Correspondingly, linear regression and paired t-test were applied in order to compare predicted and measured density values for depectinised and clarified pineapple juices for the proposed model (Eq. 9). The statistical correlation curve showed reasonable agreement; the calculated slope was 0.999 ± 0.007 and the intercept 0.001 ± 0.008, with a correlation coefficient r = 0.9997. No statistical differences (p = 0.05) were found with regard to slope and intercept theoretical values (1.00 and 0.00, respectively). Therefore, the predicted density data of pineapplejuices agreed with the experimental data thus confirming the validity of the proposed model as shown in Eq. (9). Consequently, this mathematical model, expressed as a function of temperature and soluble solids content conditions, can accurately predict pineapple juice density during concentration processes.

Figure 3 Combined effect of temperature and soluble solids content on density of pineapple juice represented as a response surface, as predicted by Eq. (9).