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Article

Sun-Drying and Melatonin Treatment Effects on Apricot Color, Phytochemical, and Antioxidant Properties

by
Rukiye Zengin
1,
Yılmaz Uğur
2,
Yasemin Levent
1,
Selim Erdoğan
3,
Harlene Hatterman-Valenti
4 and
Ozkan Kaya
4,5,6,*
1
Republic of Türkiye Ministry of Agriculture and Forestry, General Directorate of Agricultural Research and Policies, Apricot Research Institute, 44090 Malatya, Türkiye
2
Health Services Vocational School, Inonu University, 44280 Malatya, Türkiye
3
Pharmacy Faculty, Inonu University, 44280 Malatya, Türkiye
4
Department of Plant Sciences, North Dakota State University, Fargo, ND 58102, USA
5
Republic of Türkiye Ministry of Agriculture and Forestry, General Directorate of Agricultural Research and Policies, Erzincan Horticultural Research Institute, 24060 Erzincan, Türkiye
6
Department of Life Sciences, Western Caspian University, 1001 Baku, Azerbaijan
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(2), 508; https://doi.org/10.3390/app15020508
Submission received: 26 November 2024 / Revised: 14 December 2024 / Accepted: 6 January 2025 / Published: 7 January 2025
(This article belongs to the Special Issue Fruit Breeding, Nutrition and Processing Technologies)
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Versions Notes

Abstract

:
Post-harvest deterioration of fruit quality represents a significant challenge in the dried fruit industry, particularly affecting the preservation of nutritional compounds and sensory attributes during the drying process. This research examined the potential protective effects of exogenous melatonin supplementation on the preservation of selected quality metrics and antioxidant characteristics in sun-dried apricots, utilizing a comparative analysis across disparate melatonin concentrations (10, 100, and 1000 µM). Our research findings demonstrated that melatonin treatment, particularly at 100 µM concentration, significantly enhanced quality preservation in sun-dried apricots. Specifically, the treatment resulted in improved color retention (increased L*, a*, and b* values), reduced oxidative stress markers (MDA and H2O2), and optimized sugar composition (glucose: 18.99 g/100 g, fructose: 12.58 g/100 g, sucrose: 15.52 g/100 g). The melatonin treatment at 100 µM concentration proved particularly effective, revealing the most significant results. Specifically, this concentration resulted in the highest β-carotene levels, reaching 223.07 mg/kg. These findings suggest promising applications for commercial-scale implementation through either dipping or spraying methods. The non-toxic nature of melatonin and its demonstrated efficacy in preserving fruit quality parameters position it as a valuable post-harvest treatment option in the fruit supply chain. This research contributes significantly to advancing sustainable post-harvest preservation strategies, though further investigation into melatonin stability and standardization of application protocols remains necessary for optimal commercial implementation.

1. Introduction

The preservation of fruit quality during post-harvest processing remains a significant challenge in the global food industry, particularly in regions where dried fruit production constitutes a major agricultural sector. Turkey maintains a dominant position in global apricot production, contributing approximately 65% of world production, with the Malatya region serving as the primary production center and contributing 80–90% of the country’s dried apricot output [1,2]. Apricot (Prunus armeniaca L.), being inherently climacteric in nature, undergoes rapid ripening and softening immediately after harvest, presenting significant challenges for preservation [3]. Additionally, its high-water content makes it particularly susceptible to pathogenic microorganisms, necessitating effective preservation methods. Traditional preservation approaches have predominantly relied on sulfur dioxide (SO2) treatment, widely employed in dried apricot production to maintain color, facilitate drying, and extend shelf life while preventing insect infestation [4,5]. However, increasing food safety concerns regarding sulfur residues have led to a growing consumer demand for naturally dried apricots, prompting significant efforts to reduce or eliminate sulfur use in dried apricot processing [6,7,8]. Sun-dried apricots, while more natural and increasingly popular among health-conscious consumers, face significant challenges due to the complex enzymatic and non-enzymatic changes during the drying process. These changes result in unwanted color darkening, potential nutrient loss, and undesirable taste development, significantly affecting the product’s market value and consumer acceptance [9,10,11].
Among these quality-related challenges in sun-dried apricot production, the most critical issue stems from post-harvest browning reactions, which substantially impact the overall quality and marketability of dried fruits worldwide. These reactions manifest through two distinct but interconnected pathways: enzymatic and non-enzymatic (maillard reactions) processes. The enzymatic browning process, primarily initiated by polyphenol oxidases (PPO), triggers a complex biochemical cascade that ultimately results in melanin formation [12]. This intricate process begins with the PPO-catalyzed oxidation of endogenous phenolic compounds to o-quinones, subsequently followed by non-enzymatic secondary reactions (condensation or polymerization) that produce melanins—complex brown polymers responsible for surface discoloration. The process becomes particularly complex due to the formation of numerous intermediates that can be catalyzed by PPO, creating a cascade of reactions that significantly affect product quality. Parallel to this, non-enzymatic Maillard reactions occur during processing or storage when amino groups interact with reducing sugars (carbonyl groups), producing melanoidins that dramatically influence the sensory properties, stability, and nutritional content of food products [13]. Traditional approaches to controlling these reactions have relied heavily on chemical inhibitors; however, their use has become increasingly restricted due to mounting safety concerns and stricter regulatory requirements, creating an urgent need for natural, sustainable alternatives [14]. In this regard, melatonin has emerged as a remarkably promising molecule for enhancing antioxidant defense and providing resistance against environmental stress factors in plants [15]. This naturally occurring compound has garnered significant scientific attention due to its multifaceted role in post-harvest management, functioning simultaneously as both a radical scavenger and antioxidant. Extensive research has demonstrated its diverse effects, including reducing oxidative damage, improving antioxidant defense mechanisms, preserving fruit energy, and inhibiting browning through sophisticated regulation of ROS (reactive oxygen species) metabolism [16,17]. The endogenous melatonin content in fruits and vegetables exhibits considerable variation, ranging between 0.1 and 1000 ng·g−1, while exogenous melatonin demonstrates remarkable ability to regulate both climacteric and non-climacteric fruit ripening through complex interactions with ethylene and abscisic acid signaling components [18].
Recent scientific investigations have particularly focused on melatonin’s effectiveness in managing browning reactions during storage and on the shelf life of post-harvest horticultural products [19]. This versatile compound has shown exceptional promise in regulating various metabolites associated with improving nutritional quality, maintaining product integrity under diverse storage conditions, and preventing post-harvest diseases and decay through its potent antioxidant properties [20]. Furthermore, research since 2017 has increasingly concentrated on melatonin’s role in enhancing fruit production and preserving post-harvest fruit quality, with numerous studies highlighting its potential as a natural preservation agent [21]. The role of melatonin in regulating post-harvest hormone levels in fruits and vegetables has been extensively documented in multiple studies [15,16]. Notably, melatonin significantly delays fruit and vegetable senescence by inhibiting ethylene and abscisic acid accumulation [17,18,19]. The multifaceted biological functions of post-harvest melatonin are intricately linked to its interactions with reactive oxygen species, plant hormones, and other signaling molecules. Exogenous melatonin application enhances antioxidant defense systems, providing protection against oxidative damage and preserving post-harvest fruit energy. Its effect on maintaining fruit flesh firmness is primarily attributed to the inhibition of enzymes associated with cell wall and starch degradation. Furthermore, melatonin reduces fruit discoloration by inhibiting polyphenol oxidase enzyme activity [17,18,19,20].
While extensive research exists documenting melatonin’s effects on fresh fruits, including apricots, systematic studies examining its impact on processed fruits, particularly sun-dried apricots, remain notably limited. Given the significant economic importance of dried apricot production and the growing demand for natural preservation methods, this study aims to investigate the effects of melatonin application in dried apricot production, focusing on quality preservation and color retention throughout the drying process. The primary objectives include examining the reduction of ROS accumulation and analyzing changes in oxidative stress indicators (MDA and H2O2) during the drying process under melatonin treatment. Additionally, this paper evaluates the potential benefits of exogenous melatonin (N-acetyl-5-methoxytryptamine) application as a bio-stimulant in commercial-scale dried apricot production, including the optimization of treatment parameters and the assessment of long-term stability during storage.

2. Materials and Methods

2.1. Plant Material and Treatments

Hacıhaliloğlu apricot cultivar, which is predominantly used in dried apricot production, was harvested at maturity stage (soluble solids content: 24.35%; pH: 4.86; titratable acidity: 0.53%) from the orchard of the Apricot Research Institute Directorate (Malatya, Türkiye). After excluding damaged fruits, apricots were randomly divided into groups of 15 kg each (5 kg per replicate) and immersed in 5 L of different melatonin solutions (10 μM, 100 μM, and 1000 μM) for 10 min at room temperature. The melatonin concentration ranges (10, 100, and 1000 µM) were systematically selected based on a comprehensive review of recent post-harvest research. These concentrations represented a logarithmic scale that encompasses low, moderate, and high dosage levels, enabling a comprehensive assessment of melatonin’s potential protective effects. Specifically, the 100 µM concentration was informed by previous studies demonstrating its efficacy in preserving fruit quality [22], while the 10 µM and 1000 µM concentrations were included to explore potential dose-dependent responses and establish a comparative framework for evaluating melatonin’s impact on apricot preservation. Apricots immersed in distilled water served as a control. The immersion process was conducted in a dark environment to prevent light-induced degradation of melatonin solutions.

2.2. Sun-Dried Apricot Production

The treated apricots were placed on drying racks for sun drying. The pitting procedure was strategically implemented following the initial drying phase, specifically when the apricots had reached an intermediate moisture content. After the initial dehydration stage, the fruits underwent mechanical pitting, followed by a secondary drying process. During this subsequent drying phase, the moisture content was systematically reduced to the target range of 10–20%, ensuring optimal preservation and quality maintenance. The temporal progression of the drying protocol involved a carefully controlled two-stage approach: an initial dehydration period, mechanical core removal, and a final drying phase to achieve the desired moisture equilibrium. Subsequently, the samples were stored at +4 °C until analysis. The steps followed during the drying process are illustrated in Figure 1.

2.3. Some Physicochemical and Biochemical Analysis of Apricot Fruits

2.3.1. Color Measurement

Fruit color was measured on both opposite sides of the fruit using a color measurement device (Minolta CR 400, Osaka, Japan) in the CIE L*, a*, b* color space. Measurements were performed in triplicate.

2.3.2. Determination of Total Phenolic Content (TPC) and Antioxidant Capacity

Sample extraction was performed according to the method reported by Zengin et al. [23]. TPC was determined using the Folin–Ciocalteu reagent method as previously reported. The calibration curve was prepared using gallic acid and results were expressed as mg gallic acid equivalent (GAE)/100 g. The antioxidant capacity of the samples was evaluated using two different methods: 2,2-diphenyl-1-picrylhydrazyl (DPPH) and cupric ion reducing antioxidant capacity (CUPRAC). The reaction system contained 100 µL of sample extract and 3900 µL of DPPH radical. The resulting reaction mixture was thoroughly mixed and incubated in the dark at room temperature for 30 min. At the end of the period, absorbance values were measured at 517 nm and results were expressed as mg Trolox equivalent/100 g [24]. The antioxidant capacities of apricot samples were determined according to the method reported by Apak et al. [25]. For this, 1 mL of copper(II) chloride solution (10−2 M), 1 mL of neocuproine (7.5 × 10−3 M), and 1 mL of ammonium acetate buffer (pH = 7) were mixed. To this, 100 µL of sample extract was added. The final volume was brought to 4.1 mL by adding 1 mL of distilled water. The resulting mixture was incubated in the dark for 1 h. At the end of the period, the absorbance of the mixture was measured at 450 nm. Results were determined as Trolox Equivalent (mg TE/100 g) [25].

2.3.3. Sugar Content in Fruits

The individual sugar content in the samples was determined using high-performance liquid chromatography (HPLC, Shimadzu, Japan) according to the method reported by Yaman [26]. Samples (0.5 g) were extracted in 10 mL of distilled water. The resulting supernatants were filtered through a 0.45 μm filter (Millex-HN nylon membrane, Millipore, Darmstadt, Germany). Separation was performed using a Carbosep CHO 87C column (300 × 7.8 mm) at 80 °C with a refractive index detector (Shimadzu RID-10A, Kyoto, Japan). Ultra-pure water was used as the mobile phase (flow rate: 0.6 mL/min). Glucose, fructose, sucrose, and sorbitol standards were purchased from Sigma for calibration curves.

2.3.4. Melatonin Analysis with UFLC-FD in Fruits

Melatonin standard (≥98% purity) was purchased from Sigma Aldrich (CAS number: 73-31-4), maintaining the precise scientific reporting style of the original Turkish statement. Melatonin content was determined according to the method reported by Uğur et al. [27]. Apricot samples were extracted in a mixture of methanol:water:hydrochloric acid (70:29.9:0.1%, v/v/v) and detected and quantified using a UFLC-FD (Shimadzu Technologies, Kyoto, Japan) device. Chromatographic separation was performed on a C18 column (Welch Welchrom 250 mm × 4.6 mm, 5 µm). A mixture of methanol:water:acetic acid (55:44.9:0.1, %) was used as the mobile phase. Isocratic elution was performed with a 1 mL/min flow rate at 25 °C and the injection volume was 20 mL.

2.3.5. Beta-Carotene Determination in HPLC System in Fruits

The beta-carotene content of dried apricots was analyzed with some modifications to the method reported by Karabulut et al. [1]. Apricot sample (0.5 g) was extracted with 10 mL of extraction solution (methanol:tetrahydrofuran, 1:1). The extract was filtered through a 0.45 μm membrane filter and analyzed in the HPLC-DAD system. Chromatographic separation was performed on a Luna C8 column (150 mm × 4.6 mm, 5 µm from Phenomenex) at 35 °C. In the separation based on isocratic elution, a 100% methanol mobile phase was used at a solvent flow rate of 1 mL/min.

2.3.6. Malondialdehyde (MDA) Content in Fruits

The thiobarbituric acid (TBA) method was used to determine the MDA content in the apricot samples. Samples (0.2 g) were completely homogenized in 10% (w/w) trichloroacetic acid (TCA) solution and incubated on ice for 30 min. Then, the samples were centrifuged at 10,000× g at 4 °C for 20 min. The supernatant part was taken into separate tubes. For the next stage, 0.67% thiobarbituric acid solution was prepared: 0.67 g TBA was weighed and prepared in a 100 mL volumetric flask with 10% TCA solution prepared for extraction (initially a turbid solution was formed due to lack of dissolution, but complete dissolution was achieved with a short ultrasonic application). For the reaction system, 1.6 mL of 0.67% TBA (prepared with 10% TCA) solution was added to 1.6 mL of supernatant. The resulting mixtures were thoroughly mixed and incubated in a water bath at 100 °C for 30 min and then quickly cooled on ice at the end of the period. The absorbance values of the mixtures were measured at 450, 532, and 600 nm wavelengths. The 0.67% TBA (with 10% TCA solution) solution was used as a blank. The obtained data were calculated using the equations given below [28,29].
C = 6.45 × (A532 − A600) − 0.56 × A450
MDA (µmol/L) = C × 2 (Total volume of sample extract; Vt, mL)/1.6 (volume of extract during measurement, Vs, mL) × W (weight of sample)

2.3.7. H2O2 Content in Fruits

H2O2 content was determined with some modifications to the method reported by Wang et al. [30]. Apricot sample (1.0 g) was homogenized with 5 mL of 0.1% trichloroacetic acid. After incubation in an ice bath for 1 h, the homogenate was centrifuged at 10,000× g and 4 °C for 20 min. Supernatants were taken into separate tubes for analysis. The reaction system contains 0.5 mL supernatant or standard, 1 mL 10 mM potassium phosphate buffer (pH 7.0), and 2 mL 1 M potassium iodide. The resulting mixtures were incubated at room temperature in the dark for 1 h. H2O2 was used as a standard. For 100 mL of 1 M stock, 8.75 mL H2O2 (35%) was made up to 100 mL with water. A 1 mM intermediate stock was prepared from the resulting solution. H2O2 standards in the range of 50–1000 µM were used for the calibration curve. The absorbance values of the samples were measured against the blank at 390 nm. When preparing the blank, distilled water was used instead of supernatant, and other components were added in the same way. Results were calculated using the given equation and expressed as µmol/g.
H2O2 (µmol/g) = (C × DF)/(W × 1000)
C: Value calculated with the calibration equation, DF: Amount of solvent used in extraction, W: Sample amount

2.4. Statistical Analysis

All results are given as mean ± standard deviation. Statistical analyses were performed using JMP Pro 13 software (SAS Version V.9.4, SAS Institute, Cary, NC, USA). To better elucidate the relationships between melatonin applications and the examined parameters, correlation analysis was performed using the SRPLOT online platform (https://www.bioinformatics.com.cn/en, accessed 21 October 2024). Additionally, a hierarchical clustering heat map was generated to visualize the relationships and intensities between the applications and examined parameters. Furthermore, Principal Component Analysis (PCA) was conducted using GraphPad Prism version 9.3.1 (GraphPad Software, LLC, San Diego, CA, USA) to determine the directionality of relationships between applications and examined parameters, and the results were interpreted using biplot analysis according to the methodology established by Evgenidis et al. [31].

3. Results and Discussion

3.1. Effect of Exogenous Melatonin on Sun-Dried Apricot Color

Our study investigated the effects of exogenous melatonin application on the color parameters of sun-dried apricots and the results revealed significant changes in L* (lightness), a* (redness), and b* (yellowness) values across different melatonin concentrations. Melatonin treatments generally resulted in higher L* values compared to the control, with 100 µM-MT (28.74) and 1000 µM-MT (28.84) treatments showing statistically significant increases in lightness (p < 0.05). All melatonin treatments increased the a* value, indicating enhanced redness, with the 100 µM-MT treatment yielding the highest a* value (6.67). Similarly, b* values were significantly higher in melatonin-treated samples, particularly at 100 µM-MT (11.33) and 1000 µM-MT (11.15) concentrations, suggesting enhanced yellowness (Table 1). These findings demonstrate that melatonin application has a protective effect against color darkening during the drying process. The increase in L* values align with the previous research by Xiao et al. [32], who reported similar effects in fresh-cut products. However, our L* values were slightly lower than those reported for untreated sun-dried Hacıhaliloğlu apricots in previous studies, which may be attributed to variations in the drying conditions or the initial fruit characteristics. This discrepancy warrants further investigation to optimize the drying process for color retention. On the other hand, the observed increases in both a* and b* values suggest that melatonin not only prevents darkening but also enhances the vibrant colors of the apricots. This color preservation effect could be attributed to melatonin’s antioxidant properties, potentially inhibiting the degradation of carotenoids and other pigments responsible for the characteristic color of apricots. Our results are consistent with Karabulut’s [1] findings that decreased L* and b* values indicate color darkening, as evidenced by the lower values in our control group. Interestingly, our data suggest a concentration-dependent effect of melatonin on color parameters, with 100 µM-MT generally showing the most pronounced effects. The lack of further improvements with the 1000 µM-MT treatment indicates a possible saturation point in melatonin’s protective effects. This finding has important implications for optimizing melatonin application in commercial drying processes, suggesting there is an optimal concentration that balances color preservation with treatment costs. While our study clearly demonstrates the positive effects of melatonin on color retention in sun-dried apricots, the underlying mechanisms warrant further investigation. Potential explanations for melatonin’s effects include its antioxidant activity, enzyme inhibition in browning reactions, and membrane stabilization. Future studies should, in this regard, focus on elucidating these mechanisms through biochemical analyses and exploring the impact of these color changes on consumer perception through sensory evaluations. In general, our results indicate that exogenous melatonin application is a promising approach for preserving the desirable color characteristics of sun-dried apricots. The treatment not only prevents excessive darkening but also enhances the vibrant red and yellow hues that are attractive to consumers. These findings have significant implications for the dried fruit industry, potentially leading to improved product quality and consumer acceptance.

3.2. Evaluation of Oxidative Stress Markers and Antioxidant Content in Melatonin-Treated Dried Apricots

Our study elucidated the intricate biochemical responses of dried apricots to exogenous melatonin application, focusing on oxidative stress markers and antioxidant content. Our findings indicated a nuanced interplay between melatonin concentration and various physiological parameters, offering valuable insights into post-harvest fruit preservation strategies. The results demonstrated that exogenous melatonin application significantly influences oxidative stress markers and antioxidant content in dried apricots, with higher concentrations (100 µM and 1000 µM) effectively mitigating lipid peroxidation and hydrogen peroxide accumulation while modulating β-carotene levels. In our results, malondialdehyde (MDA) and hydrogen peroxide (H2O2) levels, key indicators of oxidative stress, exhibited significant reductions in apricots treated with higher concentrations of melatonin (100 µM and 1000 µM) compared to the control and low-dose (10 µM) treatments (Table 2). The 100 µM melatonin treatment resulted in the lowest MDA accumulation (16.55 µmol/L) and significantly reduced H2O2 levels (0.76 µmol/g), demonstrating its efficacy in mitigating oxidative damage. This observation aligns with the findings of Kakaei et al. [33], who reported lower MDA and H2O2 accumulation in melatonin-treated white mulberry fruits. The decrease in these oxidative stress markers suggests that melatonin effectively mitigates lipid peroxidation and cellular damage, corroborating its role as a potent antioxidant [34,35]. The concentration-dependent effect of melatonin on oxidative stress markers underscores the importance of dosage optimization in post-harvest treatments. Intriguingly, melatonin was undetectable in all treatment groups post-drying (Table 2), an outcome that may be attributed to the molecule’s susceptibility to degradation under the harsh conditions of sun-drying, including heat and light exposure. As Arnao et al. [15] noted, the short half-life of melatonin and limited information on its persistence in fruit tissues support our observations. This finding underscores the need for further research into melatonin stability and alternative application methods in fruit preservation. The rapid degradation of melatonin during processing raises questions about the duration of its protective effects and the potential for developing more stable formulations or application techniques to prolong its efficacy throughout the drying process.
On the other hand, the β-carotene content exhibited significant variation among treatments, with the 100 µM melatonin application yielding the highest content (223.07 mg/kg) as shown in Table 2. This result surpasses the range reported by Coşkun et al. [36] for the Hacıhaliloğlu dried apricot variety (30.00–33.30 mg/100 g), suggesting a potential protective effect of melatonin on carotenoid preservation. However, the non-linear relationship between melatonin concentration and β-carotene content warrants further investigation as it may indicate complex interactions between antioxidant systems in response to exogenous melatonin application. The observed increase in β-carotene content at 100 µM melatonin, followed by a decrease at 1000 µM, suggests the existence of an optimal concentration for preserving this important antioxidant compound. The observed variations in biochemical parameters across treatments highlight the concentration-dependent effects of melatonin. The 100 µM melatonin application emerged as particularly effective in reducing oxidative stress markers while enhancing β-carotene retention. These findings align with the growing body of evidence supporting melatonin’s role in modulating fruit physiology and quality attributes during post-harvest processing [37,38]. While our results demonstrate promising outcomes with melatonin treatment, it is crucial to acknowledge the nuanced statistical variations across different concentrations. Although we observed beneficial trends with the 100 µM melatonin application, many parameters showed no statistically significant differences between the 100 µM and 1000 µM treatments. These parameters include color measurements, MDA, H2O2, glucose, fructose, sucrose, total phenolic content (TPC), and antioxidant capacity assessed by DPPH and CUPRAC methods. This observation underscores the importance of careful interpretation and suggests that the optimal melatonin concentration may not always correlate linearly with improved fruit characteristics. The 100 µM concentration was highlighted as particularly effective primarily due to its statistically significant differences from the control and low-dose (10 µM) groups in key parameters such as MDA levels and β-carotene content. However, the lack of significant differences between 100 µM and 1000 µM treatments indicates potentially diminishing returns at higher melatonin concentrations. This finding emphasizes the need for precise dosage optimization in post-harvest fruit treatments and suggests that future studies should focus on more granular concentration ranges to elucidate the most effective melatonin application strategy.
The differential responses to various melatonin concentrations emphasize the complexity of the fruit’s physiological response to exogenous antioxidants and underscore the importance of fine-tuning treatment protocols for optimal efficacy. It is also worth noting that the absence of detectable melatonin post-drying does not necessarily negate its beneficial effects. As suggested by Wang [30] and Zheng et al. [39], melatonin may exert its protective influence through the activation of endogenous antioxidant systems or by triggering stress response pathways prior to its degradation. This hypothesis is supported by the persistent effects observed in oxidative stress markers and β-carotene content, despite the absence of detectable melatonin in the final product. In this regard, future research should aim to elucidate the molecular mechanisms underlying these lasting effects and explore potential synergies between melatonin and other endogenous antioxidant systems in dried fruits. Melatonin demonstrates a robust antioxidant mechanism by eliminating free radicals and enhancing oxidation resistance [30,37]. Notably, it mitigates lipid peroxidation under various stress conditions, preventing damage to phospholipid bilayers and preserving cellular membrane structural integrity [39]. Excessive ROS accumulation catalyzes oxidation reactions in lipid and protein systems, increasing membrane lipid peroxidation. Consequently, this leads to compartmentalization disruption in cell membranes, facilitating contact between polyphenol oxidase and phenolic substrates, which triggers enzymatic browning reactions [34,35]. During the sun-drying of apricots, melatonin functions as a defense mechanism against oxidation reactions induced by heat and light exposure. This critical effect supports the literature’s perspective of melatonin as an effective antioxidant capable of inhibiting phenolic compound oxidation [15,35,39]. Our experimental results substantiate the proposed antioxidant mechanism of melatonin, demonstrating a concentration-dependent protective effect that is particularly evident in the 100 µM treatment. The observed significant reductions in oxidative stress markers, such as MDA and H2O2, align precisely with the proposed mechanism of free radical elimination and membrane structural preservation. These findings empirically validate the theoretical framework of melatonin’s role in mitigating oxidative stress and enzymatic browning during sun-drying, underscoring its potential as a natural, effective preservation strategy for dried apricots.

3.3. Effects of Exogenous Melatonin Application on Sugar Composition, Total Phenolic Content and Antioxidant Capacity in Dried Apricots

Our comprehensive investigation into the effects of exogenous melatonin (MT) treatments on dried apricots revealed significant impacts on both sugar composition and antioxidant properties, presenting several noteworthy findings that contribute to our understanding of post-harvest fruit preservation (Table 3). Regarding sugar composition analysis, the 100 µM-MT treatment emerged as the optimal concentration for preserving and enhancing sugar content, yielding significantly higher levels of glucose (18.99 g/100 g), fructose (12.58 g/100 g), and sucrose (15.52 g/100 g) compared to the control samples (p < 0.05). These findings align with previous research by Akin et al. [40] and Karabulut et al. [11], who emphasized the critical influence of harvest timing and drying conditions on sugar composition. Our results extend this understanding by demonstrating that melatonin treatment can effectively modulate these changes during the drying process. The observed variations in sucrose levels across treatments can be attributed to acid hydrolysis during drying, which converts sucrose to reducing sugars (glucose and fructose), as previously documented by Karabulut et al. [1] and Özbek et al. [6]. This conversion process is particularly relevant in our findings, where we observed a complex relationship between different sugar components. The subsequent reduction in reducing sugars can be explained by their participation in Maillard reactions, leading to the formation of melanins—high molecular weight reactive intermediates that influence both color and flavor, as recently described by Niu et al. [41]. Sorbitol content in our samples ranged from 22.99 to 23.94 g/100 g, with the 100 µM-MT treatment showing the highest values. These findings are particularly significant when compared to the previous research by Erdoğan-Orhan and Kartal [42], who reported that Malatya apricots contain distinctively higher sorbitol levels (16.91–26.84 mg/100 g) compared to other varieties. Our results not only confirm these high sorbitol levels but also suggest that melatonin treatment may help preserve this characteristic during the drying process.
Our investigation into the effects of melatonin (MT) treatment on dried apricots revealed intricate patterns in antioxidant properties and phenolic content distribution. The total phenolic content (TPC) analysis demonstrated remarkable consistency between the control (243.68 ± 14.02 mg GAE/100 g) and 10 µM-MT treatments (243.52 ± 5.68 mg GAE/100 g), while higher concentration treatments showed significantly reduced values (p < 0.05). This pattern suggests a potential threshold effect in melatonin’s interaction with phenolic compounds during the drying process. The elevated TPC levels observed in the control group can be attributed to the formation of melanin compounds during drying, a phenomenon well-documented in the recent literature [43,44]. In our results, the antioxidant capacity measurements revealed significant variations across different analytical methods, providing crucial insights into the complex nature of antioxidant mechanisms in dried fruits. The DPPH radical scavenging activity exhibited peak values in the 10 µM-MT treatment (111.30 ± 11.13 mg TE/100 g), with notably lower activity in the 100 µM-MT treatment (86.48 mg TE/100 g). This finding aligns with previous research by Madrau et al. [45], who reported similar patterns in sun-dried apricots, attributing these variations to the formation of Maillard reaction products with enhanced antioxidant capacity. The CUPRAC analysis consistently demonstrated higher values compared to DPPH results across all treatments, with the control group showing exceptional activity (634.72 ± 26.98 mg TE/100 g). This methodological divergence can be primarily attributed to CUPRAC’s enhanced sensitivity to flavonoid compounds, particularly quercetin and kaempferol, as elucidated by Alajil et al. [46]. The effectiveness of melatonin treatment can be fundamentally attributed to its unique molecular architecture, specifically its indole ring structure, which facilitates efficient reactions with free radicals [47]. This structural characteristic explains its robust antioxidant activity across varying concentrations. The relatively lower TPC values observed in higher melatonin concentrations may be explained by Boutin’s [48] groundbreaking observation regarding the chemical modification of radical scavenging molecules during radical capture. This transformation process creates significant challenges in evaluating melatonin’s effectiveness using conventional UV-based color measurement methods, as various metabolites may form during the process.
Our findings strongly support melatonin’s potential as a safe and non-toxic post-harvest treatment option, as corroborated by Feng et al. [49]. The complex relationship between treatment concentration and antioxidant parameters reveals a nuanced pattern: while 100 µM-MT appears optimal for sugar preservation, lower concentrations (10 µM-MT) demonstrate superior efficacy in maintaining antioxidant properties. The consistently elevated CUPRAC values across treatments indicate a substantial presence of flavonoid compounds, emphasizing the importance of employing multiple analytical methods for comprehensive antioxidant capacity assessment. The antioxidant compounds play a crucial role in protecting biomolecules, such as proteins and lipids, from oxidative damage by delaying their oxidation, as reported by Mahmoud et al. [50]. Melatonin’s dual hydrophilic and lipophilic properties contribute to its effectiveness as a post-harvest preservation agent for fruits and vegetables [33]. The compound’s ability to facilitate reactions with alkyl peroxide and hydroxyl free radicals demonstrates its versatility in antioxidant mechanisms. It is, however, crucial to acknowledge that the spectrophotometric methods employed for TPC determination are not entirely specific and may detect various easily oxidizable compounds under analysis conditions [44]. This limitation underscores the need for more specific analytical approaches in future research to better understand the precise mechanisms of melatonin’s antioxidant effects. The formation of new compounds during radical scavenging, as observed by Boutin [48], suggests the need for more sophisticated analytical techniques to track these transformations. These findings have significant implications for the fruit processing industry.
While our results demonstrate promising outcomes with melatonin treatment, it is essential to critically examine the statistical significance of our findings across different concentrations. The observed variations in sugar composition and antioxidant capacity reveal a complex, non-linear relationship between melatonin concentration and the fruit quality parameters. Although we highlighted the 100 µM concentration as particularly effective for sugar preservation, the statistical similarities between 100 µM and 1000 µM treatments for several parameters warrant careful interpretation. The lack of statistically significant differences in total phenolic content (TPC), DPPH, and CUPRAC antioxidant capacity measurements between these concentrations suggests that higher melatonin doses may not consistently translate to proportional improvements in fruit quality (Table 4). This observation underscores the importance of precise dosage optimization and highlights the need for nuanced approaches to post-harvest fruit treatments. Future research should focus on more granular concentration ranges and employ advanced statistical techniques to elucidate the most effective melatonin application strategies, potentially revealing subtle mechanisms that our current analytical methods might not fully capture. Also, the observed patterns in both sugar composition and antioxidant capacity suggest that melatonin treatment protocols may need to be tailored to specific quality objectives. The safety and non-toxic nature of melatonin makes it a particularly attractive option for commercial applications in the fruit supply chain. However, the complex relationship between treatment concentration and the various quality parameters necessitates careful consideration when developing treatment protocols.

3.4. General Evaluation

Our multivariate statistical analyses revealed intricate relationships between melatonin application and various physiological parameters, providing novel insights into the complex mechanisms of melatonin’s action in post-harvest preservation (Figure 2). The results present compelling evidence for melatonin’s multifaceted role in maintaining fruit quality and modulating oxidative responses. The correlation analysis unveiled patterns that shed light on the interconnected nature of quality parameters and biochemical responses to melatonin treatment. Particularly striking were the strong positive correlations between color values (L*, a*, b*) and sugar content (glucose, fructose, sucrose), suggesting that melatonin’s influence on the fruit quality parameters operates through coordinated physiological pathways. This observation aligns with the findings of Ze et al. [19], who demonstrated similar correlations in melatonin-treated fruits during post-harvest storage. Interestingly, our results show even stronger correlations than previously reported, possibly due to the specific concentration ranges we employed. In our results, the robust negative correlations between oxidative stress markers (H2O2, MDA) and the quality parameters were particularly noteworthy. This inverse relationship strongly suggests that melatonin’s protective effects against oxidative damage directly contribute to quality preservation, supporting and extending the conclusions drawn by Wang et al. [21]. In our view, this finding represents a crucial mechanistic link between melatonin’s antioxidant properties and its practical applications in post-harvest preservation.
On the other hand, the PCA results (Figure 3) were remarkably revealing, with the first two components explaining an impressive 95.01% of the total variance—a level of explanation that exceeds many similar studies in the field. The clear separation of treatments based on physiological responses provides compelling evidence for melatonin’s concentration-dependent effects. The loading patterns we observed, particularly the clustering of color values and sugars on PC1’s positive axis with optimal representation by 100 and 1000 µM treatments, align with but also extend the findings of Feng et al. [49]. What we find particularly intriguing is how the PCA results suggest a possible threshold effect in melatonin’s action. The clustering of oxidative stress markers (MDA, H2O2) and antioxidant parameters (TPC (TFFM), DPPH, CUPRAC) on PC1’s negative axis, predominantly represented by the control and 10 µM treatments, indicates that there might be a critical concentration threshold below which melatonin’s protective effects are not fully activated. This observation is supported by the recent findings from Ahammed et al. [34] regarding ROS signaling in melatonin-mediated responses, but our results provide a more nuanced understanding of this concentration-dependent relationship. Perhaps the most striking aspect of our analysis was revealed through the hierarchical clustering, which provided an elegant visualization of melatonin’s dual functionality in stress protection and quality enhancement (Figure 4). The clear separation of parameters into distinct clusters not only validates our experimental approach but also reveals previously unrecognized patterns in melatonin’s mode of action. Our findings build upon and significantly extend the work of Zhang et al. [17], particularly in understanding the relationship between the antioxidative processes and quality parameters. The remarkable performance of the 100 µM treatment, especially in terms of sorbitol and β-carotene accumulation, suggests an optimal concentration range for practical applications. This observation is particularly relevant when considered alongside the recent findings of Kakaei et al. [33], though our results suggest even broader implications for post-harvest treatment protocols. Based on our findings, we propose that melatonin’s effects on fruit quality are more nuanced than previously thought. The clear dose-dependent responses we observed suggest that standardized treatment protocols may need to be tailored to specific crop types and storage conditions.
Melatonin (N-acetyl-5-methoxytryptamine) represents a naturally occurring multifunctional indolamine found extensively in plant species, synthesized from tryptophan, a rare amino acid in plant cells [51]. Its molecular complexity extends beyond a simple signaling molecule, functioning as a critical regulator in immune response, free radical scavenging, and cellular protection mechanisms. Importantly, from a food safety perspective, recent literature indicates a growing trend toward utilizing edible coatings and plant growth regulators in post-harvest research, driven by increasing consumer demand for natural preservation technologies [52]. Melatonin, emerging as a novel phytohormone, has garnered significant attention for its potential application in food preservation. Critically, toxicological assessments demonstrate promising safety profiles. In China, melatonin has been approved as a healthy food ingredient, while the United States Food and Drug Administration has classified it as a dietary supplement without documented severe side effects or toxicity concerns [53]. This regulatory recognition provides substantial scientific confidence in melatonin’s potential application in food processing, particularly in fruit preservation strategies. Our study’s findings not only corroborate these safety assessments but also highlight melatonin’s potential as a natural, non-toxic alternative to traditional chemical preservatives in dried apricot processing. The concentration-dependent responses observed, particularly at 100 µM, suggest a nuanced approach to leveraging melatonin’s protective capabilities while maintaining optimal food safety standards.

4. Conclusions

Based on our findings, exogenous melatonin application significantly improved the quality parameters of sun-dried apricots, with 100 µM emerging as the optimal concentration. The pre-drying application of 100 µM melatonin was found to be particularly effective. The treatment notably enhanced color retention by increasing L*, a*, and b* values, while effectively reducing oxidative stress markers (MDA and H2O2). The 100 µM melatonin treatment yielded the highest β-carotene content and optimal sugar composition, including glucose, fructose, and sucrose. Multivariate analysis revealed strong positive correlations between color values and sugar content, suggesting coordinated physiological responses to melatonin treatment. These findings have significant implications for both producers and consumers. For producers, melatonin treatment offers a practical, non-toxic solution for preserving dried apricot quality during processing, potentially leading to improved product marketability and reduced post-harvest losses. Indeed, the compound can be applied through dipping or spraying solutions, and both methods show promise for large-scale applications. The identified optimal concentration (100 µM) provides clear guidance for commercial applications. Due to its safety and non-toxic nature, it has high potential for use in post-harvest fruit supply chains. For consumers, the enhanced preservation of natural colors, sugars, and antioxidants means access to higher quality dried apricots with better nutritional value and sensory attributes. However, this study’s limitation lies in the rapid degradation of melatonin during the drying process, as evidenced by its undetectable levels in the final product. Additionally, there is no standardization for effective dose and application duration for the post-harvest use of the melatonin molecule. Future research should focus on developing more stable melatonin formulations or alternative application methods to extend its protective effects throughout the drying process. Studies are needed to reveal the effects of temperature and light on melatonin degradation kinetics in solutions to interpret melatonin stability in aqueous solutions used for fruit dipping. Additionally, investigating the molecular mechanisms behind melatonin’s lasting effects and conducting sensory evaluations would provide valuable insights for optimizing treatment protocols.

Author Contributions

Conceptualization, R.Z. and S.E.; methodology, Y.U. and S.E.; formal analysis, R.Z., Y.L., H.H.-V. and Y.U.; investigation, R.Z., O.K. and Y.L.; data curation, R.Z., O.K., H.H.-V. and S.E.; original draft preparation, R.Z., Y.U. and O.K.; writing—review and editing O.K. All authors have read and agreed to the published version of the manuscript.

Funding

No funding was received to support this research or manuscript.

Institutional Review Board Statement

Not applicable. The present study did not involve human subjects or animal experiments, therefore institutional review board approval was not required.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Flow diagram of sun-dried apricot production process.
Figure 1. Flow diagram of sun-dried apricot production process.
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Figure 2. Correlation matrix of physiological parameters in response to different melatonin concentrations. The intensity and size of circles represent correlation strength, while colors indicate correlation direction (blue for positive, red for negative correlation). Numbers show correlation coefficients (r) ranging from −1.00 to 1.00.
Figure 2. Correlation matrix of physiological parameters in response to different melatonin concentrations. The intensity and size of circles represent correlation strength, while colors indicate correlation direction (blue for positive, red for negative correlation). Numbers show correlation coefficients (r) ranging from −1.00 to 1.00.
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Figure 3. Biplot analysis of the effects of different melatonin concentrations on physiological parameters. Vector length indicates the magnitude of variable contribution, while vector direction shows the relationship between variables. Treatment clusters demonstrate concentration-dependent effects of melatonin (Control, 10, 100, and 1000 µM) on measured parameters.
Figure 3. Biplot analysis of the effects of different melatonin concentrations on physiological parameters. Vector length indicates the magnitude of variable contribution, while vector direction shows the relationship between variables. Treatment clusters demonstrate concentration-dependent effects of melatonin (Control, 10, 100, and 1000 µM) on measured parameters.
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Figure 4. Hierarchical clustering analysis of physiological parameters and their response to melatonin treatments. The color scale represents parameter values (red for high values, blue for low values). Dendrogram clustering on both axes reveals parameter associations and treatment similarities. Two main clusters separate oxidative stress markers (MDA, H2O2, TFMM-Total Phenolic Content, DPPH, and CUPRAC) from quality parameters (color values and sugars), with sorbitol and β-carotene forming a distinct subgroup. Treatment clustering demonstrates clear separation between high (100 and 1000 µM) and low (Control and 10 µM) melatonin concentrations.
Figure 4. Hierarchical clustering analysis of physiological parameters and their response to melatonin treatments. The color scale represents parameter values (red for high values, blue for low values). Dendrogram clustering on both axes reveals parameter associations and treatment similarities. Two main clusters separate oxidative stress markers (MDA, H2O2, TFMM-Total Phenolic Content, DPPH, and CUPRAC) from quality parameters (color values and sugars), with sorbitol and β-carotene forming a distinct subgroup. Treatment clustering demonstrates clear separation between high (100 and 1000 µM) and low (Control and 10 µM) melatonin concentrations.
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Table 1. The effect of exogenous melatonin application on the L*, a*, and b* values of sun-dried apricots.
Table 1. The effect of exogenous melatonin application on the L*, a*, and b* values of sun-dried apricots.
TreatmentsL*a*b*
Control26.91 ± 0.77 b4.98 ± 0.76 c9.44 ± 0.97 b
10 µM-MT27.40 ± 0.79 ab5.55 ± 0.60 bc10.15 ± 0.76 ab
100 µM-MT28.74 ± 0.47 a6.67 ± 0.13 a11.33 ± 0.26 a
1000 µM-MT28.84 ± 1.30 a6.35 ± 0.60 ab11.15 ± 1.04 a
MT: Melatonin. Each data point represents the average of three replicates (mean ± standard error). Letters in the same column indicate differences at the significance level of p < 0.05.
Table 2. Effects of exogenous melatonin application on biochemical parameters in dried apricots.
Table 2. Effects of exogenous melatonin application on biochemical parameters in dried apricots.
TreatmentsMDA
µmol/L		H2O2
µmol/g		Melatonin
ng/mL		β-Carotene
mg/kg
Control23.44 ± 3.03 a1.03 ± 0.11 aNd181.84 ± 2.11 b
10 µM-MT22.75 ± 5.33 ab1.00 ± 0.13 aNd190.57 ± 8.31 ab
100 µM-MT16.55 ± 3.45 b0.76 ± 0.07 bNd223.07 ± 32.05 a
1000 µM-MT18.50 ± 1.67 ab0.66 ± 0.01 bNd173.76 ± 26.02 b
MT: Melatonin. Nd: Not detected. Each data point represents the mean of three replicates (mean ± standard error). Letters in the same column indicate differences at p < 0.05 significance level.
Table 3. Sugar content of dried apricots after exogenous melatonin application.
Table 3. Sugar content of dried apricots after exogenous melatonin application.
TreatmentsGlucose
(g/100 g)		Fructose
(g/100 g)		Sucrose
(g/100 g)		Sorbitol
(g/100 g)
Control16.97 ± 0.12 b12.01 ± 0.46 b12.12 ± 0.26 c23.46 ± 0.56 ab
10 µM-MT17.16 ± 0.19 b12.11 ± 0.70 ab13.98 ± 1.31 b23.54 ± 0.21 ab
100 µM-MT18.99 ± 0.01 a12.58 ± 0.03 ab15.52 ± 0.11 a23.94 ± 0.24 a
1000 µM-MT18.84 ± 0.30 a12.86 ± 0.29 a14.82 ± 0.10 ab22.99 ± 0.37 b
MT: Melatonin. Each value represents the mean of three replicates (mean ± standard error). Letters in the same column indicate significant differences at p < 0.05.
Table 4. Total phenolic and antioxidant capacities of dried apricots after exogenous melatonin application.
Table 4. Total phenolic and antioxidant capacities of dried apricots after exogenous melatonin application.
TreatmentsTPC
(mg GAE/100 g)		DPPH
(mg TE/100 g)		CUPRAC
(mg TE/100 g)
Control243.68 ± 14.02 a100.13 ± 10.01 ab634.72 ± 26.98 a
10 µM-MT243.52 ± 5.68 a111.30 ± 11.13 a542.13 ± 8.10 b
100 µM-MT201.20 ± 19.59 b86.48 ± 7.75 b489.76 ± 26.67 c
1000 µM-MT207.71 ± 16.85 b90.34 ± 9.03 ab510.30 ± 29.13 bc
MT: Melatonin. Each value represents the mean of three replicates (mean ± standard error). Letters indicate differences at p < 0.05 significance level.
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MDPI and ACS Style

Zengin, R.; Uğur, Y.; Levent, Y.; Erdoğan, S.; Hatterman-Valenti, H.; Kaya, O. Sun-Drying and Melatonin Treatment Effects on Apricot Color, Phytochemical, and Antioxidant Properties. Appl. Sci. 2025, 15, 508. https://doi.org/10.3390/app15020508

AMA Style

Zengin R, Uğur Y, Levent Y, Erdoğan S, Hatterman-Valenti H, Kaya O. Sun-Drying and Melatonin Treatment Effects on Apricot Color, Phytochemical, and Antioxidant Properties. Applied Sciences. 2025; 15(2):508. https://doi.org/10.3390/app15020508

Chicago/Turabian Style

Zengin, Rukiye, Yılmaz Uğur, Yasemin Levent, Selim Erdoğan, Harlene Hatterman-Valenti, and Ozkan Kaya. 2025. "Sun-Drying and Melatonin Treatment Effects on Apricot Color, Phytochemical, and Antioxidant Properties" Applied Sciences 15, no. 2: 508. https://doi.org/10.3390/app15020508

APA Style

Zengin, R., Uğur, Y., Levent, Y., Erdoğan, S., Hatterman-Valenti, H., & Kaya, O. (2025). Sun-Drying and Melatonin Treatment Effects on Apricot Color, Phytochemical, and Antioxidant Properties. Applied Sciences, 15(2), 508. https://doi.org/10.3390/app15020508

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