Kinetic Modeling of Quality Changes and Shelf Life Prediction of Dried Coconut Chips

Abstract

The color, texture and rancidity of dried fruit are critical parameters to control for consumer acceptance. The goal of this research was to investigate the kinetics of color parameter changes and texture in terms of the crispness and peroxide value (PV) of dried coconut chips by using zero-, first- and second-order kinetic reactions during storage at different temperatures, as well as shelf life prediction using the accelerated method. The outcomes demonstrated that the zero-order kinetic reaction was appropriate to describe the change in color, crispness and PV of dried coconut chips during storage (R² = 0.9690–0.9899). The rancidity had a higher correlation than the texture and color changes used to assign the quality essence. The activation energy (E_a) for the PV change was 11.83 kJ/mol. Therefore, the shelf life expectancy of the dried coconut chips was estimated to be 144, 128 and 115 days at 35, 45 and 55 °C, respectively. Meanwhile, the shelf life of products stored at ambient temperature was 159 days, and those products were stored in the refrigerator for 194 days. The findings provide retailers and consumers the ability to choose the ideal temperature and storage time for dried coconut chips in order to ensure the product’s quality.

1. Introduction

Aromatic coconut (Cocos nucifera Linn.) is one of the most important industrial crops in Thailand. In general, young coconuts are rich in protein and fatty acids in the kernel and high in sugar and other nutrients, including minerals and amino acids, in the water [1], Therefore, these have distinct flavors that are popular with people all around the world. However, consumers do not appreciate mature coconut because the sweet taste of the water has decreased and the kernel has hardened. Post-harvest processing provides a different alternative for stabilizing the price of mature coconuts and increasing their storage life, which increases the value of mature coconut products.

Dried coconut chips, which are crisp and tasty, have recently become one of the most popular ready-to-eat snack foods. The production of dried coconut chips occurs with 8–9-month mature coconut kernel osmotically dehydrated with sugar syrup and dried as the chips, which can be a high value-added product and a premium product on the market. The dried coconut chips on the market shelf may be exposed to environmental elements such temperature, humidity, oxygen and light. Therefore, the evaluation of its storability is important. These factors influence rapid changes in physical and chemical quality, such as a decrease in crispness, an increase in darkness and a change in smell flavor, which all affect consumer acceptability [2,3]. As a consequence, dried fruit must be prepared with sulfur dioxide and packaged in opaque packaging to prevent both enzymatic and non-enzymatic browning reactions during drying and storage [4], in addition to being placed in opaque packaging to preserve the color, texture and flavor. Therefore, the evaluation of a product’s quality during storage is important.

The shelf life of dried food, which can be calculated using either a direct or indirect method, determines its quality until it is altered in a way that consumers find unsatisfactory or exceeds the accepted food quality standards. The product is stored for a long time and monitored until it fails to reach the specifications in the direct method. In the indirect method, the shelf life of a product is estimated by storing it under extreme conditions (e.g., increasing the storage temperature), which increases the rate of food quality degradation, such as a color parameter or chemical composition, in order to assess food behavior and shelf life across a short period of time [5,6]. As a consequence, accelerated shelf life testing (ASLT), based on the Arrhenius model, has been widely used to predict shelf lives because it can estimate food expiration dates significantly earlier than with real-time tests, which is advantageous for determining commercial decisions. The Arrhenius equation is widely used for shelf life predictions under various temperature and time conditions [7,8]. Furthermore, the ASLT was used to estimate the shelf lives of batuan fruit powder [9], shallot powder [10], and freeze-dried durian [11]. According to Dak et al. [12], the kinetics of quality parameter change in dried pomegranate arils was zero-order, and the shelf life was predicted to be between 96 and 187 days under accelerated storage conditions based on chemical parameter changes. Hyun et al. [13] examined the quality and shelf life of dried persimmons based on the color parameter during storage. Meanwhile, according to Phothapaeree et al. [14], the kinetic browning behaviors of ΔE can be utilized to evaluate the shelf life of dried bananas. Quality change observation and shelf life prediction of dried coconut chips will be conducted based on previous background knowledge. The objectives of this research were to (1) use zero- and first-order kinetic reactions to explain the quality characteristics of dried coconut chips during storage and (2) use the Arrhenius equation with accelerated temperatures to predict the shelf life of dried coconut chips.

2. Materials and Methods

2.1. Material Preparation

After pollination, two-layer kernels of 8-month-old aromatic coconuts from the Damnoen Saduak district in Ratchaburi, Thailand were transferred to the Faculty of Agro-Industry at the Prachinburi Campus of King Mongkut’s University of Technology North Bangkok. The coconut shells were sliced open, the kernel was separated from the shells, and the brown skin was removed. The coconut kernels were washed with clean water, drained on sieves for 10 min and then chopped into 1 × 5 × 1 cm pieces (length × width × thickness).

2.2. Preparation of Dried Coconut Chips

A total of 100 g of fresh coconut pieces (The sample had a moisture content of 67.95% wet basis, reduced sugar content of 0.84 mg/mL, 4.67° Brix for the total soluble solids and a pH of 7.09.) was weighed, and pretreatment using the osmotic, blanching and bleaching methods was conducted. These samples were soaked in a sucrose solution (2% (w/v)) for 15 min before being blanched at 80 ± 3 °C for 2 min and then soaked in potassium metabisulfite, with KMS (0.03% (w/v)) being at a weight ratio of 1:3 for 5 min. (The residual sulfite in the final product was 16.31 ppm.) After pretreatment, the coconut pieces were dried by the tray drying method at 60 ± 2 °C for 20 h and an air velocity of 0.25 m/s. (The final moisture of the product was 3–4% wet basis) The 25 grams of coconut chips were preserved in aluminum foil pouches at temperatures of 35, 45 and 55 °C, respectively. Changes in color, browning index (BI), texture and peroxide value (PV) were examined after the products were collected every week from different collections for 15 weeks.

2.3. Quality Analysis

2.3.1. Color Properties

The color parameters L*, a* and b* of dried coconuts were measured with a HunterLab Colorflex 45/0 Spectrophotometer (Hunter Laboratories, Reston, VA, USA). The values are reported as L* (degree of brightness to darkness), a* (degree of redness (+) to greenness (−) and b* (degree of yellowness (+) to blueness (−). The total color difference (ΔE) and browning index (BI) were calculated according to Saini and Sharma [15] using the following formulas:

$$\mathrm{Total\; color\; difference}(\Delta E)=\sqrt{{(L_0^{*}-L^{*})}^2+{(a_0^{*}-a^{*})}^2+{(b_0^{*}-b^{*})}^2}$$

(1)

where the index “0” indicates the dried coconut chips at the initial day of storage, whereas the letters without an index correspond to the parameters of the dried samples:

$$\mathrm{Browning\; index} \left(\mathrm{BI}\right)=\frac{100(x-0.31)}{0.17}$$

(2)

$$inwhichx=\frac{a^{*}+1.75L^{*}}{5.645L^{*}+a^{*}-3.012b^{*}}$$

(3)

2.3.2. Texture Measurement

The textural properties of the product were evaluated by using a texture analyzer. The machine was equipped with the Blade Set-type blade probe. The blade was set to cut through the center of the dried coconut chips. The measurement conditions were as follows: a mode for measuring the force in compression, test speed of 2.0 mm/s, distance of 10 mm, automatic trigger force and load cell of 25 kg. The crispness value was determined by a graphical method, namely counting the number of breakage peaks of the product.

2.3.3. Peroxide Value (PV) Measurement

The peroxide value (PV) was determined using a titration method according to AOAC (2000) 965.33 [16]. Five grams of a sample was placed into a 250-mL flask. Subsequently, 30 mL CH₃COOH-CHCl₃ was added to the sample. A saturated KI solution (0.5 mL) was added, followed by 1 min of shaking and adding 30 mL deionized water to the mixture. The mixture was then slowly titrated using 0.01 M Na₂S₂O₃. The PV was calculated according to the following Equations (4):

$$\mathrm{PV}(\mathrm{meq}/\mathrm{kg})=\frac{(S-B)\times N\times 1000}{Sampleweight\left(g\right)}\times 100$$

(4)

where S is the sample titration (mL), B is the blank titration (mL) and N is the normality of Na₂S₂O₃.

2.4. Accelerated Shelf Life Testing (ASLT) of Dried Coconut Chips

For the accelerated storage experiment, the dried coconut chips were stored at 35, 45 and 55 °C. The data calculated were the kinetic modeling and shelf lives for the three accelerated temperatures.

2.4.1. Quality Kinetic Modeling of Dried Coconut Chips during Storage

The change in food color, crispness and PV during storage was studied by zero-, first- and second order degradation reaction kinetics using Equations (5)–(7), respectively:

$$Zeroorderkinetics;A_t-A_0=-kt$$

(5)

$$Firstorderkinetics;ln{A}_t-ln{A}_0=-kt$$

(6)

$$Secondorderkinetics;\frac{1}{A_t}-\frac{1}{A_0}=-kt$$

(7)

where k is the degradation rate constant (day⁻¹), A₀ is the initial value (quality parameter) and A_t is the measured value (quality parameter) at the storage time t).

After obtaining the data (zero-, first- and second-order), the best model was then chosen for calculating the product shelf life using the Arrhenius model according to Equation (8):

$$Arrheniusequation;lnk=ln{k}_0-\frac{E_a}{RT}$$

(8)

where k is the reaction rate constant, k₀ is the Arrhenius constant, E_a is the activation energy (kcal/mol), R is the gas constant = 8.314 J/K mol and T is the absolute reaction temperature (°K). The most affecting parameters were determined from the lowest activation energy (E_a).

2.4.2. Shelf Life of Dried Coconut Chips

After knowing the key parameters, the shelf life of dried coconut chips was predicted using Equations (9)–(11) for the zero-, first- and second-order reactions, respectively:

$$Zeroorderreaction;t_s=\frac{N_0-N_t}{k_T}$$

(9)

$$Firstorderreaction;t_s=\frac{ln\left(\frac{N_0}{N_t}\right)}{k_T}$$

(10)

$$Secondorderreaction;t_s=\frac{\left(\frac{1}{N_0}\right)-\left(\frac{1}{N_t}\right)}{k_T}$$

(11)

where t_s is the storage time, N₀ is the value at the beginning of the shelf life, N_t is the value at the end of the shelf life and k_T is the value k at storage time temperature T.

2.5. Statistical Analysis

To determine the storage time was significant for the parameters studied, and the results were analyzed using one-way ANOVA (p < 0.05) through SPSS V.25 software for Windows (SPSS Institute Inc., Chicago, IL, USA). The performance of the fitting models in the regression analysis method was evaluated by using the solver tool from Microsoft Excel©2013, and the fitting was evaluated using the higher coefficient of determination (R²).

3. Results and Discussion

3.1. The Quality of Dried Coconut Chips

The dried coconut chips were prepared from coconut kernels. The flavor was adjusted using sucrose syrup, food additives were used to prevent color changes in the dried product due to browning reactions, and the products were dried at 60 °C for 20 h. The aw and moisture content of all dried products did not exceed 0.5 and 4% during storage, respectively (data not shown), indicating that they were dry foods. When referring to food additives, food additives in the sulfide group (i.e., sulfiting agents) such as KMS were used in this study. The use of KMS in food is ubiquitous because it is cheap and easy to use. Nevertheless, KMS is recognized as safe in small amounts for consumption. A maximum limit of 200 mg SO₂ per kg of dried coconut is accepted by most countries, including Thailand [17]. In this investigation, the quantity of SO₂ that remained in the dried coconut chips was 16.31 ppm (data not shown), which was below the food law’s acceptable limits, indicating that the product is safe for consumer health and suitable for sale. However, dried coconut chips were placed on the market at varying temperatures, depending on the appropriate temperature at each retail location, each of which had a varied effect on the chemical and physical quality. Therefore, quality changes in dried coconut chips stored under various conditions must be investigated.

3.1.1. Color Properties

Figure 1 shows the changes in color L*, a*, b* and ΔE as well as the BI value in the dried coconut chips during 15 weeks of storage at different temperatures (35, 45 and 55 °C), with a significant difference visible (p < 0.05). Color is a key aspect of dried food quality, and consumers prefer a light, consistent color. At increasing storage temperatures and for longer periods, these quality attributes changed. All samples became darker throughout the period, with L* values decreasing from 82.87 ± 0.71 to 76.58 ± 0.87, 72.89 ± 0.45 and 70.18 ± 0.12 at storage temperatures of 35, 45 and 55 °C, respectively (Figure 1a). The drying process and sugar content induced a non-enzymatic Maillard browning reaction, which resulted in the color change in the dried product [18]. Additionally, the dried coconut was soaked in KMS solution before drying to prevent color changes in the dried product from the SO₂ content, which showed an antioxidant property to prevent browning of the product and which subsequently decreased during storage [19]. It was also possible that the dried samples could lose their lightness. Moreover, the browning reaction could be also explained by an increase in the a* and b* values. The redness-greenness scale is illustrated in Figure 1b, where the dried coconut chips display a greenness scale as the negative a* value (−0.76 ± 0.08) at the initial day, whereas the a* value tended to increase, ranging from −0.09 to 9.07 at the end of the storage period. The b* value varied from 7.82 ± 0.32 (initial) to a final value ranging from 14.19 to 34.07 (15 weeks of storage), indicating that the browning tone of the dried product was increasing in intensity, as shown in Figure 1c. As a result of this study, the browning reaction may have occurred during storage, causing the product to appear brown, similar to the increasing brown color in garlic slices [20] and dried mushrooms [21].

The total color difference (ΔE) is a color parameter used to characterize the variation of colors in foods throughout processing. The higher the ΔE value, the higher the color difference between the storage day and the initial day. The effect of the temperature and time of storage on ΔE increased significantly (p < 0.05), as shown in Figure 1d. (For 35–55 °C at 15 weeks of storage, the report showed 8.97, 17.68 and 30.76, respectively.) Cserhalmi et al. [22] reported that consumers can verify whether the color of the food sample changes by using the ΔE value, which indicates that the color should be finely visible when the ΔE value exceeds 3.0. Thus, the consumer could detect a change in product color beginning in weeks 7, 3 and 1 at storage temperatures of 35, 45 and 55 °C, respectively. The browning index (BI) can be another index that represents the purity of brown and can be used to determine the degree of visible browning in a product in both enzymatic and non-enzymatic staining procedures [15,23]. Furthermore, both an increase in the L* value and a decrease in the a* value are positively correlated to the product’s BI value [24,25,26]. According to the results, the BI value of the dried coconut chips (Figure 1e) increased significantly (p < 0.05) as the storage time increased, and the rate of the BI obviously depended on the storage temperature. As a result, when dried coconut chips are stored at high temperatures for a long time, these become more brownish than when stored at low temperatures.

3.1.2. Texture Analysis

The dried coconut chip products stored in aluminum foil pouches were evaluated for their crispness by using the texture analysis technique. The number of peaks from product breakage were recorded, and a large number of peaks indicates a crispier product. As a consequence, the crispness of the dried coconut chips decreased significantly (p < 0.05) with increased storage time, regardless of the storage temperature. The number of peaks in the initial product was 14.12, as seen in Figure 1f. As the temperature of storage increased from 35 to 55 °C, humidity from the air could penetrate into the package, decreasing the crispness of the product and decreasing the amount of peaks to the range of 6.07–0.23 (at 15 weeks of storage). The present results are in agreement with those of Sra et al. [27], who found that the dried product has high hygroscopic properties for the reabsorption of humidity.

The aluminum foil container, on the other hand, is typically resistant to humidity and oxygen penetration. Moreover, Miranda et al. [19] stated that the dried product lost its texture during storage due to an increase in temperature storage caused by the glass transition temperature (T_g) being lower than the storage temperature, which affected the quality and stability of the dried fruit, including texture changes.

3.1.3. Peroxide Value

In dried products, the peroxide value (PV) is commonly used as a biomarker of primary oxidative fat. The coconut kernel is a component of the coconut fruit that has a high lipid content and may be susceptible to oxidation following processing. The oxidative level of a dried product is represented by the amount of peroxide present, which causes it to become rancid. As a general guideline, the PV should not exceed 10–20 meq/kg fat to avoid a rancid flavor [28], which is an important factor for consumer acceptability. In this research, the peroxide value of the dried coconut chips increased statistically significantly (p < 0.05) with the storage time as a function of the temperature during storage, and the PV level not exceeding the standard was 18.80 ± 0.44, 18.53 ± 0.11 and 16.51 ± 0.11 meq/kg for the samples stored at 35, 45, and 55 °C for 15, 12 and 10 weeks, respectively (Figure 1g). The increased PV during the storage time was due to the penetration of atmospheric oxygen into the package. Accumulated oxygen reacts to the free fatty acids in food to provoke a lipid oxidation reaction. Because of the high fat content in coconut kernels, this reaction causes rancidity to occur continuously and rapidly [1]. Furthermore, higher temperature storage is positively correlated with an increasing peroxide content. Lipid oxidation can be stimulated by high temperatures. As a result, the peroxide content of the dried coconut chips was enhanced.

3.2. Kinetics of the Quality Parameter of Dried Coconut Chips during Storage

The mathematical kinetic model is an extremely useful tool for food processing and quality prediction. Biochemical and physical responses that occur during processing are primarily responsible for variations in food quality. Each reaction has its own rate and kinetics. Nowadays, kinetic modeling allows us to quantify these dynamics and reaction rates. As a result, it is advantageous to predict reactions and maintain product quality. In this study, the color and texture characteristics were fitted to various kinetic models.

Table 1. The kinetic parameters of zero-, first- and second-order models for quality parameter in dried coconut chips.

		Zero-Order Model			First-Order Model			Second-Order Model
Parameter	Temperature (°C)	k (day−1)	C0	R2	k (day−1)	C0	R2	k (day−1)	C0	R2
L*	35	−0.4461	83.0140	0.9786	0.0056	−0.0023	0.9805	0.00007	0.0120	0.9821
	45	−0.6646	82.1930	0.9826	−0.0086	−8.8275	0.9838	0.0001	0.0121	0.9845
	55	−0.7441	81.3080	0.9778	0.0098	0.0176	0.9818	0.0051	0.0123	0.9845
a*	35	0.0489	−0.7455	0.9700	0.1485	−0.2000	0.9799	−0.5899	0.2609	0.8602
	45	0.2656	−1.1726	0.9690	−0.0443	0.5741	0.0981	0.1175	0.1411	0.0048
	55	0.6432	−0.5356	0.9791	−0.0094	0.1014	0.1325	0.0235	−0.0317	0.1325
b*	35	0.4533	−6.7475	0.9697	−0.0443	0.0940	0.9493	−0.0044	0.1361	0.9487
	45	0.8535	7.6502	0.9782	−0.0627	−0.0737	0.9785	−0.0049	0.1140	0.9326
	55	1.5996	9.9107	0.9641	−0.0845	−0.3208	0.8653	−0.0051	0.0926	0.7084
ΔE	35	0.6263	−0.6454	0.9899	−0.2041	−0.6064	0.8645	−0.1238	1.5432	0.5180
	45	1.0942	0.4296	0.9896	−0.1394	−0.1135	0.9598	−0.0225	0.3376	0.7922
	55	1.7787	3.5307	0.9793	−0.1266	−0.6286	0.8198	−0.0125	0.1818	0.5198
BI	35	0.7676	7.3399	0.9826	−0.0586	0.1022	0.9675	−0.0047	0.1172	0.9651
	45	1.8030	7.4887	0.9899	−0.0903	−0.0865	0.9862	−0.0051	0.0945	0.9169
	55	3.9983	9.6440	0.9820	−0.1220	−0.4206	0.8927	−0.0048	0.0722	0.6730
Crispness	35	−0.4378	13.0190	0.9710	0.0401	0.0931	0.9409	0.0043	0.0750	0.9255
	45	−0.5778	12.3920	0.9699	0.0549	0.1417	0.9440	0.0067	0.0771	0.9635
	55	−0.7759	12.3400	0.9696	0.1780	−0.2746	0.7111	0.1152	0.4013	0.2741
PV	35	1.5062	−3.7713	0.9898	−0.0086	0.0928	0.1325	−0.0348	0.5180	0.0849
	45	1.7780	−2.4436	0.9841	0	0	n/a *	−0.0372	0.4857	0.2109
	55	1.9958	−1.1741	0.9728	0	0	n/a *	−0.0251	0.3342	0.1654

* Not applicable.

shows the results of a regression study of the zero-order, first-order and second-order reaction kinetics in dried coconut during storage at various temperatures.

The color changes fit better with the zero-order reaction models with higher R² values (R² varied from 0.9641 to 0.9899). This demonstrates that the color of the dried coconut chips degraded linearly. Similarly, several authors have reported in the literature that zero-order kinetic models can predict color parameter changes in a linear format during storage (e.g., for pineapple [15], button mushrooms [29] and kiwi [7]). For dried coconut chips, the kinetic rate constants of the color parameters were slower at 35 °C than at 45 or 55 °C by 0.67 and 0.60 times for the L* value, 0.18 and 0.08 times for the a* value, 0.53 and 0.28 times for the b* value, 0.57 and 0.35 times for the ΔE value and 0.43 and 0.19 times for the BI, respectively. This result might be explained by the fact that high-temperature storage accelerated pigment oxidation, resulting in a decrease in the brightness of the dried coconut chips, an increase in the reddish hue and a significant increase in the rate of browning and color change (p < 0.05). Depending on the temperature of storage, the best model for crispness and PV change was a zero-order model, with R² values of 0.9696–0.9710 and 0.9728–0.9898. The kinetic rate reaction for the crispness and PV of the product stored at 55 °C changed by 1.78–2.06 and 1.12–1.33 times when compared with the lower temperature, respectively. The experiment results in this study clearly demonstrate that at higher temperatures, the crispness decreased, and the oxidative rancidity reaction in the dried coconut chips occurred more quickly.

In terms of shelf life prediction, the Arrhenius equation and accelerated shelf life testing (ASLT) were used to simulate the kinetic prediction for all of the quality parameters and the shelf life (

Table 2. The kinetic parameters of zero-order models for quality parameter in dried coconut chips.

Parameter	Arrhenius Equation	Ea (kJ/mol)	R2
L*	ln k = 7.6734 − (2598.6/T)	21.60	0.9162
a*	ln k = 39.489 − (13,055/T)	108.54	0.9728
b*	ln k = 19.877 − (6367.5/T)	52.94	0.9997
ΔE	ln k = 16.664 − (5274.6/T)	43.85	0.9995
BI	ln k = 26.803 − (8336.6/T)	69.31	1.0000
Crispness	ln k = 10.299 − (3479.5/T)	28.92	0.9315
PV	ln k = 5.0393 − (1423.9/T)	11.83	0.9928

). The Arrhenius model was used to describe the reaction rate constant that was temperature-dependent, which is quite applicable to food products, by calculating the activation energy (E_a) and explaining each quality change in the dried coconut chips by the temperature based on these reaction rate constants [30].

The results demonstrate that the PV seemed to have the lowest E_a value (11.83 kJ/mol), indicating that the storage temperature had an influence on the rancidity in the dried coconut chips before changes in texture and color. According to Van Boekel [31], a high E_a value suggests that some chemical reactions in food, such as browning, are very slow at low temperatures but relatively fast at high temperatures. Furthermore, when performing accelerated shelf life testing (ASLT) and predicting the shelf life of dried coconut, the reaction rate constant changes (k) shown in

Table 3. The shelf life of dried coconut chips store at various temperatures with PV parameters.

Storage Temperature (°C)	ln k	k Value	Shelf Life (Days)
35	0.4167	1.5169	144
45	0.5616	1.7535	128
55	0.6981	2.0099	115

were considered. The k value at the storage time was calculated using the Arrhenius equation’s linear regression, as well as a plot of 1/T and ln k. The k value can describe the rate of change in a parameter. For instance, in the experiment, the k of PV was 1.5169 at 35 °C, indicating that the increase in rancidity occurring in the products was 1.5169 units per day at a storage temperature of 35 °C, whereas the product presented rancidity which occurred faster at higher temperatures (k value between 1.7535 and 2.0099 at storage temperatures of 45 and 55 °C, respectively).

3.3. Prediction of the Shelf Life of Dried Coconut Chips

Based on the Arrhenius results, the PV changes in the coconut chips were recognized as the major form of deterioration. The difference between the initial PV and the predetermined critical PV was used to calculate the shelf life. The dried coconut chips had a shelf life of 144, 128 and 115 days, translating to 20.6, 18.3 and 16.4 weeks or 4 months and 22 days, 4 months and 6 days and 3 months and 23 days at storage temperature of 35, 45 and 50 °C, respectively (Table 3). Dried foods are occasionally kept at room temperature (about 25 °C) or in the refrigerator (about 8 °C). As shown in Figure 2, the relationship between the logarithm of the shelf life of dried coconut chips (ln t_s) and storage temperature (T) can be used to predict the shelf life of dried coconut chips in storage at various temperatures. The shelf life of dried coconut chips packaged in aluminum foil pouches and stored at 25 and 8 °C were reported to be 159 and 194 days, translating to 22.7 and 27.7 weeks or 5 months and 6 days and 6 months and 11 days, respectively.

4. Conclusions

This research demonstrates that the color index, texture parameters and PV can all be utilized to estimate the shelf life of dried coconut chips when stored at different temperatures. The dried coconut chips that were stored at a temperature of 55 °C for a prolonged period turned brown and had a higher PV, and these samples also showed a loss of crispiness. A zero-order kinetic response was used to assess the reaction of the color, texture and PV change during storage. At higher temperatures, the PV attributes changed faster than the texture and color attributes. According to the results of this study, rancidity is one of the first characteristics that can be recognized when dried coconut chips start to lose their quality, and it can be controlled by decreasing the storage temperature.