Grading by fruit density: an effective way to control the drying characteristics and quality of mulberry

DOI: https://doi.org/10.21203/rs.3.rs-2790639/v1

Abstract

Reducing waste and controlling fruit quality is a challenge for processors. In order to enhance the quality of the products, dried fruit manufacturers devoted to develop reliable methods for measuring ripeness. In this study, a densimetric flotation technique was adopted to separate mulberries into five distinct ripening stages (D1–D5, 0.905–1.055 g/cm3). The impact of ripening on mulberry water status, distribution, microstructure, drying characteristics, and product quality was investigated. As ripening progressed, water binding capability initially dropped and then increased, and water distribution and cell microstructure shifted, which led to a shortening of the drying time followed by an extension. Ripeness has a substantial impact on the volatile composition, colour, texture, and sensory quality of dried fruits. D1 fruits were not suitable for drying due to their intact cellular structure, long drying time, and poor product sensory quality. D4 and D5 fruits, on the other hand, had short drying times, and their products had a robust fruity aroma, better palatability, and overall acceptance. This made them ideal for the drying process. The findings in the present research have practical implications for identifying as well as drying effectively during mulberry ripening.

1. Introduction

Mulberry (Morus nigra), a member of the genus Morus and family Moraceae, originates from China and is widely cultivated and consumed worldwide (Tabakoglu & Karaca, 2018). Its alluring sensory properties and high nutritional value have made mulberry fruits highly coveted since ancient times (Li et al., 2021). Mulberry has also traditionally been used to cure fevers and sore throats in China and Korea (Wang et al., 2019). A lot of health benefits of mulberries have been documented in modern scientific research, including antioxidative, antitumor, antiatherosclerotic, neuroprotective, and immunomodulatory properties (Yuan & Zhao, 2017). Mulberry is a seasonal, soft fruit that is typically consumed fresh, but its high moisture content accelerates decay and leads to significant product losses (Kipcak & Doymaz, 2020). For the purpose of extending the shelf life of the mulberry fruit, a variety of preservation methods such as drying, juicing, canning, and freezing, have been developed. Among these methods, the drying of mulberry during the off-season is an excellent means to extend its availability while at the same time, maintaining the quality of the fruit (Chen et al., 2017).

Conventional drying methods, which include sun drying and hot air drying was frequently employed for the drying of fruits, but they exhibit low energy efficiency, prolonged drying time, and substandard product quality (Gu et al., 2022). Heat pump drying (HPD) technology has been implemented in fruit drying procedures so as to overcome these limitations (Salehi, 2021). As an environmentally friendly technology, HPD technology uses the reverse Carnot cycle to recover energy from environmental exhaust gases and independently regulate air temperature and humidity (Hou et al., 2020). Plenty of investigations, including those involving grape pomace (51% reduction) and lemon slices (31.5% reduction), have shown that HPD is effective in lowering drying energy consumption (Taşeri et al., 2018; Lee et al., 2021). Furthermore, the HPD enhanced the appearance quality of jujube slices by promoting uniform water diffusion, lowering ΔE value, and reducing shrinkage ratios (Hou et al., 2020). These benefits have led to the application of HPD for the dehydration of a variety of fruits, including bananas (Singh et al., 2020), kiwifruits (Liu et al., 2020), and tomatoes (Jeyaprakash et al., 2020). However, HPD technology has not yet been extensively researched for drying mulberries.

Premium quality dried fruits have become increasingly popular in recent years, largely driven by maturity stage of fresh fruits (Li et al., 2022). Numerous investigations demonstrated that the maturity level during harvest has a huge impact on the fruit's physicochemical characteristics, which in turn influence its drying behaviour. For instance, grapes harvested at high ripeness levels contain more free water content, which makes drying more effective (Wang et al., 2017). When a mango ripens, pectin is degraded and the fruit's cell walls are visibly damaged, which significantly impacts the fruit's drying characteristics (Li et al., 2022). Besides, the quality of dried products is influenced by the ripeness level of fruits. Based on the findings of Wang et al. (2017), raisins made from higher ripeness grapes were preferred by consumers owing to their superior colour and texture qualities. Alkalthamet et al. (2021) reported that drying high-maturity avocado pulp increased its total phenolic content and its stronger capacity to scavenge DPPH free radicals. Not all fruits with high levels of ripeness, nevertheless, enhance drying effectiveness and quality. Among overripe kiwifruits, water diffusion was hindered by severe damage to cellular tissue structure, which slowed the drying process (Wang et al., 2022a). Similar observations have been made during the ripening and drying of apricots (Deng et al., 2019). Furthermore, the heterogeneity of fruit ripening generates instances of both under-drying and over-drying, leading to energy wastage as well as product quality deterioration (Li et al., 2022). Currently, the impact and underlying mechanisms of the mulberry ripening stage on drying characteristics remain elusive. As a result, comprehending how maturity affects drying is crucial for enhancing the drying efficiency and product quality of mulberries. Low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) are non-invasive and quantitative techniques that have been extensively applied to detect the distribution and status of water at the time of ripening and processing (Liu et al., 2021). Wang et al. (2017) revealed that grapes primarily contain free water and semi-bound water, and their proportions change as the fruit ripens. Similarly, Wang et al. (2022a) highlighted that free water progressively accumulates towards the centre of kiwifruit during postharvest ripening and that its migration path is closely linked to microstructure. A thorough understanding of the evolution of microstructure, water status, as well as distribution during mulberry ripening is instrumental in exploring the drying mechanism.

By placing sheets underneath the tree and shaking the branches, mulberries are usually collected, producing a lot of fruit with variable ripeness (Wang et al., 2022b). In contrast to apple, apricot, and mango, mulberry's skin colour does not accurately represent how ripe it was at harvest (Wang et al., 2022c). There can be significant ripeness variations among mulberries with the same dark purple skin (Wang et al., 2022b), necessitating a reliable approach to determining their maturity. The flotation method can be used to categorise the maturity of mulberries according to fruit density (Wang et al., 2022b). However, previous research examined only physicochemical properties and did not take drying effects into consideration. Furthermore, few studies have explored the effects of maturity on dried mulberries in terms of aroma components, colour, texture, and sensory quality. Hence, this study is designed to explore (1) the influence of maturation stages on mulberry drying behaviour and to uncover potential mechanisms by assessing changes in the water state and distribution, and cellular structure; (2) investigate the comprehensive effects of ripeness on dried mulberry's volatile profiles, colour, texture, and sensory characteristics for providing useful implications for quality classification and drying effectiveness.

2. Materials And Methods

2.1. Plant materials

Mulberries (Morus nigra L, Hongguo no.2) were harvested at commercial ripeness (fruits with dark red) and obtained from the Shaanxi Sericulture and Silk Research Institute in the Zhouzhi County (Shaanxi, China, Shaanxi, China, 34o16'-56o24'N, 108o4'-27o95'E) during May 2022. There are 700 mm of rainfall per year, located at an elevation of 525 m with average annual temperature of 13.2°C in this region. A total of 80 kg of commercially ripe mulberries was randomly harvested from forty 10-year-old trees. After harvest, fruits were transported to a lab for ripeness grading, and those with mechanical damage, disease, or insect damage were discarded.

2.2. Fruit grading

As shown in Fig. 1, mulberry's density was determined by flotation in ethanol solutions (61.9%, 47.5%, 27.8%, and 3.0% v/v) and saline solutions (3.7% and 7.7% g/g) at 20°C for 20s (Wang et al., 2022b). Briefly, Mulberries were put into the less-dense solution and “floating” fruits were regarded to have the same density as the solution. These fruits were separated from those that sank. Mulberries that sank were removed and introduced into the next denser solution. Based on the initial density, mulberries were divided into five groups: D1 (0.905–0.935 g/cm3), D2 (0.935–0.965 g/cm3), D3 (0.965–0.995 g/cm3), D4 (0.995–1.025 g/cm3), and D5 (1.025–1.055 g/cm3) (Liu, 2002; Liu, Ma, & Liu, 2013). Wang et al. (2022b) reported that mulberries were soaked in low concentrations of ethanol and sodium chloride for short periods with negligible nutrient loss and minimal changes in peel structure. Fruits were washed three times with water after flotation before being analyzed. The physicochemical properties, drying characteristics, and cell microstructure of mulberry fruits were determined using 5 kg of fruits from each density group.

2.3. Total soluble solids (TSS) and titratable acidity (TA)

The digital hand-held refractometer (Atago, Japan) was used to determine TSS (°Brix) at 25°C. The TA of the fruits was determined by titrating 10 g of homogeneous flesh in distilled water with 0.1 M NaOH and expressing the results in g citric acid/100 mL (Lin et al., 2020).

2.4. Mulberry drying

Based on the preliminary experiment, the drying experiments were carried out at the optimal conditions. A wire mesh screen tray was used to evenly spread fruits (4 kg) of different density groupsand dried by a heat pump dryer (ZWH-KFY-BT4I/HG, Zhengxu New Energy Equipment Technology Co, China) at 60°C, 15% relative humidity, and 2.0 m/s air velocity. The drying process was repeated for each density group three times. The water loss was measured by weighing mass changes as samples were removed from the drying chamber periodically using an electronic balance (EL104, Mettler Toledo, USA). After fruits reaching 10% moisture content (wet basis), drying was discontinued (Li et al., 2021).

2.4.1. Moisture ratio (MR)

The MR of mulberries during drying was calculated from equation Eq. (1) (Deng et al., 2019):

$$MR{\text{=}}\frac{{{M_t} - {M_e}}}{{{M_0} - {M_e}}}$$
1

where Mt, M0, and Me are moisture content at time t, time 0, and equilibrium, respectively, g/g (dry basis).

The Me is relatively small compared to Mt or M0, and Eq. (1) is usually simplified as Eq. (2) (Deng et al., 2019):

$$MR{\text{=}}\frac{{{M_t}}}{{{M_0}}}$$
2

2.4.2. Drying rate (DR)

The DR was calculated according to Eq. (3) (Deng et al., 2019):

$$DR=\frac{{{M_t} - {M_{t+\Delta t}}}}{{\Delta t}}$$
3

M t , and Mt+Δt are the moisture contents at t and t + Δt, respectively. where Δt are drying time between two sampling, h.

2.5. Low field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI)

LF-NMR analyzer (20 MHz, Niumag Corporation, China) with 0.5 T (35°C) was used to study mulberries with different density groups (Li et al., 2021). Mulberries were put in the scanner as a whole. Proton transverse relaxation time (T2) decay was measured using the Carr-Purcel-Meiboom-Gill (CPMG) pulse sequence. For signal collection, the following pulse parameters were selected: time waiting (TW) of 2500 ms; echo time (TE) of 0.2 ms; echo count (NC) of 14000; and number of scans (NS) of 8. A multiple-spin-echo (MSE) sequence was used to obtain proton-weighted images of the mulberries. The following parameters were set for MRI: 80mm field of view, 3mm slice width, 2mm slice gap, 20ms TE, and 500ms repetition time.

2.6. Cell microstructure

It was reported by Yao et al. (2020) and Wang et al. (2022a) that sections were cut, fixed, and dehydrated from the center of the mulberries, and that scanning electron microscopy (SEM) (SU3500, Hitachi, Japan) and transmission electron microscopy (TEM) (Tecnai G2, FEI Systems, USA) were used to observe the specimens. According to preliminary experiments, during D1 to D3 stage, there are small morphological changes in fruit cells due to the continuous maturation of fruit. Therefore, microscopic morphological observations were conducted on D3, D4, and D5 fruits with significant morphological changes. SEM: gold sprayed for 120 s on the sections and then viewed by a SEM with a 15 kV voltage and 350 magnification. TEM: an upright Leica DM6 B microscope, Leica DFC7000 T camera, and the LASX program were used to examine the target region.

2.7. Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS)

HS-GC-IMS (Flavourspec®, G.A.S, Dortmund, Germany) was used to establish volatile component fingerprints in dried mulberry samples following by Zhou et al. (2022). Table 1 shows the conditions for gas chromatography and the specific analysis. The dried mulberry powder (0.5 g) was placed in 20 mL headspace glasses. After incubation at 70°C for 20 min, samples were injected with nitrogen at the following flow rates: 0–2 min-2 mL/min; 2–10 min-2–10 mL/min; 10–20 min-10–100 mL/min. All tests were repeated three times. Standardization was carried out with n-ketones C4-C9 (Sigma, USA) with retention index (RI) was linear (R2 > 0.996). GC-IMS library (Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany) was analyzed for volatile compounds by comparing RI with drift time. To analyze sample data from different perspectives, laboratory Analytical Viewer software (LAV) was used along with three plug-ins (Gallery Plot, Reporter, and Dynamic PCA).

Table 1

Analysis and gas chromatography conditions.

Gas phase-ion mobility spectrometry unit

Autosampler unit

Column type

FS-SE-54-CB-1, 15 m ×

0.53 mm

Syringe temperature

85°C

Column temperature

60°C

Injection volume

500 µL

IMS temperature

45°C

Incubation time

20 min

Carrier gas

N2

Incubation speed

500 rpm

Analysis time

20 min

Incubation temperature

40°C

2.8. Colour and texture evaluation

A chromameter (HunterLab, USA) was used to measure the skin color of dried mulberry samples in terms of L* (lightness), a* (redness and greenness), and b* (yellowness and blueness). A texture analyzer (TA-XT plus, Stable Micro System, UK) was used to measure the textural properties of dried mulberries produced from D1-D5 fruits. The maximum force generated during the squeeze testing of whole dried mulberries was measured after squeezing them with a 20 mm diameter probe at the mid-axis, waiting 5 s between bites, and speed of 1 mm/s (Wang et al., 2017). A quantitative analysis was conducted by measuring the hardness (N), gumminess (N), and chewiness (N) of the samples. A random sample of 30 dried mulberries from each group was used for each analysis.

2.9. Sensory evaluation

A panel of ten experienced members (four men and four women, ages 24–55, from NWAFU, China) was selected to sensory evaluation. A preparatory workshop was conducted before testing with panelists to ensure each panelist was well-prepared to discuss and clarify the sensory attributes being assessed. The sensory attributes including appearance (fruit color, color uniformity, dried mulberry size and uniformity), flavor (caramel, spice, sweetness, sourness, bitterness, and astringency), texture (hardness, gumminess, and chewiness), and overall acceptability (Wang et al., 2017). Test processing was conducted under controlled temperatures, adequate lighting, and odor-free conditions. The palate was cleansed with tap water between samples. Twenty dried mulberries were selected randomly from each maturity group for testing. A panel of experience members evaluated each sample and assigned a value between 1 and 9, with 9 representing very acceptable and 1 representing very unacceptable. After evaluating a given sample, each panelist rated its overall acceptability from 1 to 9.

2.10. Statistical analysis

A statistical analysis was conducted using SPSS (version 17.0; SPSS Inc., Chicago, IL). Differences in variance (ANOVA) were analysed using the Duncan test for p < 0.05. SPSS 17.0 was used to calculate simple linear correlations (Pearsons'r).

3. Results And Discussion

3.1. Changes in TSS and TA

Fruit taste and consumer acceptance are largely determined by TSS, TA, and TSS/TA ratio (Tiziana et al., 2021). TSS, TA, and TSS/TA ratios during mulberry ripening are summarised in Fig. 2. As anticipated, during the ripening process, the TSS content significantly increased and the TA content significantly decreased, going from 11.9 to 21.5 °Brix and 1.21 to 0.66 g/100 mL, respectively. It appears that organic acid degradation and sugar accumulation occurred during mulberry ripening. In general, a higher TSS level is associated with sweeter fruit when acidity is reduced (Schulz et al., 2019). Technology ripeness parameters such as the TSS/TA ratio are often utilised to determine fruit maturity (Kim et al., 2023). As depicted in Fig. 8, correlation analyses indicated a statistically significant positive correlation (p < 0.05, r=0.92) between fruit density and TSS/TA ratio. An important relationship exists between TSS/TA ratio and fruit density (p < 0.05), indicating higher fruit density with higher ripeness. Likewise, Aubert et al. (2019) and Wang et al. (2013) also reported a good correlation between fruit density and ripeness, which may be related to fruit filling at harvest. These findings revealed that mulberry maturity can be classified by fruit density.

3.2. Drying characteristics

As shown in Figure. 3, the drying characteristics of mulberries at various stages of ripeness were evaluated. With the exception of D5 fruits, drying time decreased as ripeness advanced. It is interesting to note that D5 fruits drying slower in comparison to D4 fruits, and the difference is statistically significant (P < 0.05). Specifically, the drying times of fruits at stages D1, D2, D3, D4, and D5 were 21.4, 18.3, 16.7, 13.9, and 14.8 h, respectively. There was a huge drop in drying time for D4 fruits, which was 35.05%, 24.04%, 20.14%, and 6.47% lower than those at stages D1, D2, D3 and D5. Similar findings on fruit ripening affected its drying time has been reported in earlier investigations regarding kiwifruit (Wang et al., 2022a), bananas (Zhou et al., 2022), apricots (Deng et al., 2019), and mangoes (Li et al., 2022). As illustrated in Fig. 8, correlation analyses showed a statistically significant negative correlation (p < 0.05, r=-0.9) between fruit density, TSS/TA ratio, and drying time. It has been suggested by Wang et al. (2017) that high-maturity grapes dried faster due to increased free water content during fruit ripening. Besides, the transformation of insoluble pectin to soluble pectin increases the permeability of apricot fruit cells during ripening, lowers water resistance, and promotes drying (Kovacs et al., 2008). In D4 fruits, these factors may play a crucial role in the shorter drying time. Besides, drying rates decreased as the drying process progressed (Fig. 3B), possibly due to decreases in tissue permeability and an increase in water binding force (Deng et al., 2019). Karacabey & Buzrul (2017) reported the majority of agricultural products to exhibit a progressively decreasing speed in the drying process.

It's interesting to note that the drying rate of D5 fruits was much lower than that of D4 fruits, which made drying significantly longer. Similarly, Li et al. (2020) pointed out that over-mature mango fruits had severely disrupted cell wall structures and clumped together, which prevented water from diffusing and migrating through the protocytoplasm, and a longer drying time. Furthermore, the hydrogen bonding between small molecules of sugar and water molecules leads to the crust phenomenon, which hinders water migration and extends the drying time of over-maturity fruits (Li et al., 2022). Thus, the steady rise in fruit drying rates from D1 to D4 may be caused by changes in internal water status and cell tissue structure. The slowing of D5 fruits' drying rate, on the other hand, may be caused by the collapse of tissue structures coupled with the production of sugar carapace, which offset the higher tissue permeability throughout the later drying period.

3.3. Water distribution changes during mulberry ripening and drying

The knowledge of water status in fresh mulberry fruits during ripeness is crucial for the regulation of the drying process (Li et al., 2021). LF-NMR technology offers a rapid, efficient, and non-invasive method for determining water distribution in food products (Li et al., 2022). Figure 4I-A illustrates the transverse relaxation time (T2) curves for mulberry samples with various maturation stages. The first peak (T21, 0.1-5 ms), which had the shortest relaxation time, was attributed to strongly bound water with polymer particles; the second peak (T22, 5–50 ms), which had the second-shortest relaxation time, was attributed to weakly bound water in the cytoplasm; the third peak (T23, 50-1000 ms), which had the longest relaxation time, was attributed to free water in vacuoles and intercellular spaces (Wang et al., 2022a). There was a dominant peak for T23, indicating that free water was the predominant form of moisture in mulberry fruit. Hence, further analysis of T23's relaxation time and peak area is required. Figure 4I-B displayed that the relaxation time and peak area of T23 exhibited an overall upward trend during mulberry maturation, ranging from 188.9 ms to 499.5 ms and from 3618.6 a.u•s to 4456.6 a.u•s, respectively. This might probably be attributed to the modification of intracellular water status and the alteration of cell wall constituents during fruit ripening (Wang et al., 2022a). Similarly, ripening-induced changes in the cell wall structure and internal water states affect the relaxation time of mango (Li et al., 2022). Additionally, Wang et al. (2021) reported that the changes in hydrophilic groups of cell wall pectin during fruit maturation can have an impact on hydrogen protons and raise the T2 value. Furthermore, the peak areas of T21 and T22 gradually decreased during ripening (Fig. 4I-A), suggesting that bound water is being converted into free water. Interestingly, not all fruits displayed the same tendencies as mulberries. The content of bound water significantly increased in grapes druing ripening (Wang et al., 2017), while kiwifruit had a significant decrease in free water content (Wang et al., 2022a). The T2 value and water freedom are closely associated, and the higher the T2 value, the greater the water freedom and the easier the removal, further elucidating the mechanism of fast drying in ripe mulberries (Xu & Li, 2015). Compared to D4 fruits, D5 fruits had significantly higher peak areas of T23 (p < 0.05), but their water freedom was drastically reduced. The reduction of water freedom may be attributed to the over-ripening of D5 fruits, which disrupts water channels of intercellular pathways and results in caking areas (Khan et al., 2016). D5 mulberries, therefore, dried more slowly than D4 mulberries. The prolonged drying time of D5 fruits may also be due to the high sugar content of these fruits, which may affect the water molecule translational motility (Raffo et al., 2005). Moreover, correlation analyses indicated a statistically significant positive correlation (p < 0.05, r=0.9) between fruit density and T23 and A23 (Fig. 8). According to the findings of this study, water status differ across the ripening stages of mulberries, and further investigation into water distribution utilising MRI analysis is needed to better understand this process.

The spatial distribution of water in the longitudinal section of mulberry during ripening is depicted in Figure. 4Ⅲ. False-colour images display red and blue colours to represent high and low proton densities, respectively. The peel, the seed-containing pulp, and the central column are the three distinct parts of the fruit. The signal intensity is strong in the seed-containing pulp area with divergent radiation. Additionally, there are significant signal gaps between the red regions, caused primarily by drupelet gaps. The central signal of D1 fruit is scattered, and the area of high proton density spreads outward with increasing maturity, indicating that the water has migrated (Wang et al., 2022a). Notably, a characteristic light green signal is observed in the central column of fruits (D2-D5), which may be caused by the gradual fibrosis of the central column in mature fruits. The density signal of seed-containing pulp increases gradually throughout the process of ripening, indicating higher ripeness of fruits with more free water. Changes in water degree of freedom, distribution position, and signal intensity further elucidate mechanism of the mulberry drying rate change.

Further analyses to transverse relaxation time were carried out on mulberries with different maturities during the drying process for a better understanding of the drying process (Figure. 4Ⅲ). During drying, T23's peak area declined while its relaxation time-shifted left. It offers further insight into the mechanism of falling-rate drying in mulberries since the water content as well as the water mobility is reduced. Moreover, the peak area of T22 decreased rapidly in the initial stages of drying, which is in line with the findings of Li et al. (2021). By destroying cell membranes, heat may enhance weakly bound water's degree of freedom and increase its mobility, which may explain this phenomenon. A small T21 peak was also observed in all dried fruits, exhibiting that bound water was still present after drying.

3.4. TEM analysis

Internal water distribution and drying behaviour are influenced by the microstructure of fruit cells (Wang et al., 2022a). Since fruit ripening occurs continuously, D3, D4, and D5 fruits as representative samples were captured (Fig. 5). The cells of D3 fruits are characterised by uniform size and shape, and close proximity to each other, resembling a typical honeycomb structure. Due to the degradation of cell wall pectin, the fruit's morphology undergoes elongation, forming numerous folds (Li et al., 2022). Wang et al. (2022a) and Liu et al. (2017) have reported that pectin in cell walls gradually degrades during fruit ripening, weakening cell support and altering the microstructure of the cells. A TEM image of D3 fruits shows that ML is clearly visible in the cell wall but it gradually disappears as the fruit matures (Fig. 5A). Previous study claimed that the cell wall structure of apricots is destroyed during maturation, causing water migration and a reduction in drying time (Deng et al., 2019). Besides, the structure of cell walls changed during mulberry ripening, and the loosening of cell walls facilitates water migration, which explains why D4 fruits have higher drying efficiency. However, a high concentration of water-soluble pectin-producing agglomerates (Fig. 5A, red circle) results in severe damage and overlapping of cell walls in D5 fruits (Cardenas-Perez et al., 2018). By reducing water freedom and hindering water migration, these aggregates in fruit tissue extend drying times (Li et al., 2022). The microstructure changes during mulberry ripening support the hypothesis that cell walls of polysaccharide matrix are degraded and depolymerized, which leads to increased water freedom. As reported by Wang and Hartel (2021), overripe mangoes dry slower due to the formation of hydrogen bonds between water and a high concentration of small molecular sugars, which form clumps during drying, increase the binding power of water and inhibit its flow during the drying process. Overripe fruits have a lower drying rate due to the increase in TSS content as well as the collapse and agglomeration of cell walls, which impair water molecules' translational mobility. This offset the increase in water freedom caused by pectin depolymerisation, ultimately resulting in the deceleration of the drying rate of D5 fruits.

3.5. Effects of postharvest maturity on volatile compounds of dried mulberry

The identification information for all volatile profiles in dried mulberries is presented in Table 2 and Figure. 6. Retention indexes (RI) and drift times (Dt) of standards used in ion mobility systems (IMS) were compared to identify volatiles. A total of 56 typical target components in dried mulberries have been found utilising the GC×IMS library, including 12 aldehydes, 8 alcohols, 5 esters, 8 ketones, and others. 18 volatile compounds such as monomers and dimers yielded different product ions by HS-GC-IMS on the basis of their concentration. While these productions exhibited similar retention times, they displayed varying drift times (Wang et al., 2022a). Figure 6(A) depicts the fingerprints of volatile components in dried mulberry under various stages of ripeness. In the fingerprint, volatile substances are represented by dots; the redder the dot, the higher content the compound is. Moreover, the qualitative differences in concentrations of volatile compounds between dried mulberries at various ripeness stages are shown in the Fig. 6(B). Reference spectra were obtained from dried fruit in the D1 stage, and spectra in D2-D5 dried fruits were deducted from the reference. A red spot denotes a compound concentration that is higher than the reference, while a blue spot denotes a compound concentration that is lower. Dried mulberries of varying ripeness have comparable fingerprints, as seen in Fig. 6A and 6B, but the signal intensity varies.

Table 2

HS-GC-IMS integration parameters of volatile compounds of samples.

NO.

Metabolite

CAS#

Formula

MW

RI

RT (sec)

Dt (a.u)

Comment

1

Acetic acid monomer

C64197

C2H4O2

60.1

1491.5

1126.161

1.0564

Monomer

2

Acetic acid dimer

C64197

C2H4O2

60.1

1489.5

1119.364

1.1618

Dimer

3

Furfural monomer

C98011

C5H4O2

96.1

1485.3

1104.798

1.0888

Monomer

4

Furfural dimer

C98011

C5H4O2

96.1

1484.4

1101.885

1.335

Dimer

5

2-Cyclohexenone monomer

C930687

C6H8O

96.1

1439.6

960.116

1.1287

Monomer

6

2-Cyclohexenone dimer

C930687

C6H8O

96.1

1439.6

960.116

1.3885

Dimer

7

Nonan-2-one

C821556

C9H18O

142.2

1397.5

843.594

1.4096

 

8

Nonanal

C124196

C9H18O

142.2

1405.6

864.956

1.4789

 

9

1-Hexanol

C111273

C6H14O

102.2

1368.1

770.767

1.332

 

10

(E)-2-heptenal monomer

C18829555

C7H12O

112.2

1331.7

689.202

1.2575

Monomer

11

(E)-2-heptenal dimer

C18829555

C7H12O

112.2

1331.7

689.202

1.6716

Dimer

12

Acetoine monomer

C513860

C4H8O2

88.1

1296.6

618.71

1.0651

Monomer

13

Acetoin dimer

C513860

C4H8O2

88.1

1296.4

618.238

1.3306

Dimer

14

1-Pentanol monomer

C71410

C5H12O

88.1

1261.6

562.04

1.2572

Monomer

15

1-Pentanol dimer

C71410

C5H12O

88.1

1261.2

561.568

1.5178

Dimer

16

2-Hexenal

C505577

C6H10O

98.1

1227.6

512.455

1.1832

 

17

3-Methyl-1-butanol monomer

C123513

C5H12O

88.1

1217

497.815

1.2488

Monomer

18

3-Methyl-1-butanol dimer

C123513

C5H12O

88.1

1217

497.815

1.4976

Dimer

19

Heptanal monomer

C111717

C7H14O

114.2

1195.5

469.48

1.3376

Monomer

20

Heptanal dimer

C111717

C7H14O

114.2

1195.1

469.008

1.6974

Dimer

21

Butan-1-ol monomer

C71363

C4H10O

74.1

1154.5

422.097

1.1835

Monomer

22

Butan-1-ol dimer

C71363

C4H10O

74.1

1154

421.585

1.3827

Dimer

23

E-2-pentenal

C1576870

C5H8O

84.1

1142.8

409.536

1.1179

 

24

(Z)-2-pentenal

C1576869

C5H8O

84.1

1140.1

406.716

1.3435

 

25

1,4-Dimethylbenzene

C106423

C8H10

106.2

1141.5

408.254

1.0762

 

26

Hexanal monomer

C66251

C6H12O

100.2

1100.5

367.238

1.2662

Monomer

27

Hexanal dimer

C66251

C6H12O

100.2

1100.5

367.238

1.5623

Dimer

28

2-Pentanol

C6032297

C5H12O

88.1

1103.2

369.802

1.474

 

29

Butyl acetate

C123864

C6H12O2

116.2

1077.1

348.519

1.2357

 

30

α-Fenchene

C471841

C10H16

136.2

1061.2

336.703

1.2024

 

31

Pentan-2-one monomer

C107879

C5H10O

86.1

1039.9

321.522

1.1394

Monomer

32

Pentan-2-one dimer

C107879

C5H10O

86.1

1039.9

321.522

1.3624

Dimer

33

1-Propanol

C71238

C3H8O

60.1

1028.5

313.641

1.1113

 

34

2,3-Butanedione

C431038

C4H6O2

86.1

1027.5

312.945

1.1803

 

35

Methyl butanoate

C623427

C5H10O2

102.1

1022.7

309.7

1.1528

 

36

Pentanal

C110623

C5H10O

86.1

1000.4

295.096

1.4218

 

37

Ethanol

C64175

C2H6O

46.1

948.5

270.06

1.142

 

38

2-Methylbutanal

C96173

C5H10O

86.1

923.6

259.091

1.4007

 

39

Ethyl acetate dimer

C141786

C4H8O2

88.1

898

248.266

1.3361

Dimer

40

Ethyl acetate monomer

C141786

C4H8O2

88.1

905.7

251.504

1.1064

Monomer

41

Propan-2-one

C67641

C3H6O

58.1

842.7

226.43

1.1153

 

42

Propanal dimer

C123386

C3H6O

58.1

827

220.601

1.1419

Dimer

43

Propanal monomer

C123386

C3H6O

58.1

827

220.601

1.065

Monomer

44

Acrolein

C107028

C3H4O

56.1

869.1

236.619

1.0583

 

45

Butan-2-one dimer

C78933

C4H8O

72.1

914

255.004

1.245

Dimer

46

Butan-2-one monomer

C78933

C4H8O

72.1

914

255.004

1.0658

Monomer

47

1-Penten-3-one dimer

C1629589

C5H8O

84.1

1011.4

302.176

1.3145

Dimer

48

1-Penten-3-one monomer

C1629589

C5H8O

84.1

1013.3

303.476

1.0827

Monomer

49

Alpha-pinene

C80568

C10H16

136.2

1039.1

320.933

1.3108

 

50

Cyclotene dimer

C80717

C6H8O2

112.1

1052.7

330.521

1.502

Dimer

51

Cyclotene monomer

C80717

C6H8O2

112.1

1056.1

332.992

1.1309

Monomer

52

2-Methyl-1-propanol monomer

C78831

C4H10O

74.1

1106.2

372.672

1.1718

Monomer

53

2-Methyl-1-propanol dimer

C78831

C4H10O

74.1

1105.5

371.987

1.3677

Dimer

54

n-Pentyl butanoate

C540181

C9H18O2

158.2

1085.8

355.2

1.4163

 

55

Ethyl butanoate dimer

C105544

C6H12O2

116.2

1052.2

330.192

1.5579

Dimer

56

Ethyl butanoate monomer

C105544

C6H12O2

116.2

1054.1

331.563

1.2069

Monomer

Notes: MW, molecular mass; RI, retention index; Rt, retention time; Dt, drift time.

Aldehydes and esters make up the majority of the mulberry's aromatic components, which give the fruit a green, fresh, sweet aroma (Wang et al., 2023). Among these compounds, hexenal, 2-hexenal, ethyl acetate, and ethyl butyrate were commonly found in fruits, which play a crucial role in mulberry flavour (Chen et al., 2015; Wang et al., 2022c). Higher concentrations of ethyl acetate and ethyl butyrate were found in D4 and D5 dried mulberries, a sign of a stronger floral and fruit flavour. The high content of ethyl acetate and ethyl butyrate in D4 and D5 dried mulberries may be due to the presence of higher ethyl acetate and butyrate in fresh mulberries with greater ripeness (Wang et al., 2022). The decreased release of volatile esters in D4 and D5 fruits with high drying rates may also be an important contributing factor. Interestingly, the high content of pentan-2-one, nonanal, (E)-2-heptenal, and butyl acetate were only found in D4 and D5 fruits (Fig. 6C, region 2), so these substances can be employed as representative substances for high maturity dried mulberries. Wang et al. (2023) claimed that immature mulberries contain higher levels of C6 and C9 alcohols/aldehydes, which explains why the dried fruits obtained from D1 dried fruits have higher concentrations of nonanal and 1-hexanol. According to Hwang and Kim. (2020), 2-cyclohexenone is an essential aroma component responsible for the fresh odour in dried mulberries. Additionally, D1 dried fruits contained substantial amounts of 2-cyclohexenone. Based on these observations, dried mulberries from the D1 stage may possess more immature notes. It is closely related to varieties and drying methods that furfural is formed when sugars are dehydrated under acidic conditions (Politowicz et al., 2018). Interestingly, D1 dried fruits were the only ones showing high levels of furfural, possibly due to D1 fruits in highly acidic environments (Wang et al., 2022b). Longer drying time also resulted in higher furfural content in D1 dried fruits (Tontul & Topuz, 2017). As a flavour and quality parameter, furfural may have undesirable effects (Gong et al., 2021). Mulberry fruits of the D1 stage may not be suitable for dried fruit making owing to their highly immature and undesirable flavours. Furthermore, 1-penten-3-one, methyl butanoate, n-pentyl butanoate, acrolein, heptanal, and 1-pentanol are characteristic flavour substances for D1 dried fruits (Fig. 6C, region 1), and their higher content was only observed in D1 dried fruits.

In order to better distinguish differences in volatile compounds at different maturity stages, signal intensities of volatile compounds in dried mulberry were investigated utilising principal component analysis (PCA). The PCA of volatile compounds in dried mulberries with varying ripening is presented in Fig. 6D. The cumulative variance contribution rate of the first PC (70%) and the second PC (13%), among dried mulberry, was 83%. The PCA results show that samples with various levels of ripeness are clearly distinguished by PC1. Dried mulberries in high ripeness (D4, D5) and low ripeness (D1, D2) can describe the maximum positive and negative values of PC1. The aforementioned findings reveal that the volatile components of dried mulberries vary greatly depending on the level of maturity. Mulberry post-harvest processing and grading are facilitated by these findings.

3.6. Colour, TPA, and sensory evaluation analysis of dried mulberry

Consumer acceptability is largely influenced by colour and texture (Wang et al., 2017). During ripening, the colour of dried mulberries changed from reddish-black to completely black (Fig. 7A). The colour characteristics of dried mulberries at various maturation stages are displayed in Table 3. The L* value of dried mulberries was highest at the D1 stage (13.22) but decreased as fruits ripeness. All dried mulberries showed significant differences (p < 0.05) with the exception of the D2 and D3 groups. The a* value and b* value indicated similar trends, decreasing from 0.81 (D1) to 0.42 (D5) and from − 0.33 (D1) to -0.81 (D5), respectively. Interestingly, a significant colour variation was seen when dried mulberry was crushed (Fig. 7B). As the fruit matured, the mulberry powder (D1 dried fruits) gradually darkened due to differences in anthocyanin content (Wang et al., 2022b). As argued by Wang et al. (2022c), mulberries at low ripeness have lower pH values and higher total acid content. Additionally, anthocyanins are red in an acidic system, and the stronger the acidity, the redder the colour (Rawdkuen et al., 2020), which may be another important reason why D1 mulberry powder is redder. Consequently, D1 dried fruits may be a better choice for food additives to enhance the red colour in food.

Table 3

Effect of fruit maturity on colour and texture properties of dried mulberries

 

Colour

 

Texture

 

L*

a*

b*

 

Hardness (N)

Gumminess (N)

Chewiness (N)

D1

13.22 ± 0.3a

0.81 ± 0.08a

-0.33 ± 0.01a

 

35.86 ± 0.72a

18.62 ± 0.81a

12.94 ± 0.94a

D2

12.42 ± 0.2b

0.64 ± 0.05b

-0.32 ± 0.01a

 

30.10 ± 0.74b

17.89 ± 0.83a

10.78 ± 0.92a

D3

12.31 ± 0.3b

0.62 ± 0.04b

-0.42 ± 0.01b

 

25.51 ± 0.77c

17.73 ± 0.84a

10.67 ± 0.83a

D4

11.52 ± 0.2c

0.62 ± 0.03b

-0.61 ± 0.01c

 

21.71 ± 0.55d

14.35 ± 0.63b

7.44 ± 0.52b

D5

10.63 ± 0.3d

0.42 ± 0.05c

-0.81 ± 0.01d

 

17.70 ± 0.48e

10.81 ± 0.71c

3.83 ± 0.59c

Note: the different letters in the same column reveal significant differences (p < 0.05).

Table 3 illustrates the texture properties of dried mulberry under different ripeness at the same dehydration level. According to the findings, as the fruit matured, the dried mulberries' hardness, gumminess, and chewiness decreased, from 35.86 N to 17.7 N, from 18.62 N to 10.81 N, and from 12.94 N to 3.83 N, respectively. This is primarily explained by modifications to the cell wall structure (Li et al., 2023). Additionally, a significant difference (p༜0.05) in the hardness of dried mulberries was observed. The decline in cell wall strength during fruit maturation is due to polysaccharide degradation which is caused by pectin methylesterase, polygalacturonase, and cellulase activity (Pose et al., 2019). Similarly, a major collapse of the cell wall was seen in Fig. 5, which was related to the degradation of the middle lamella in the cell wall. Typically, the greater hardness, gumminess, and chewiness of dried fruit, the greater resistance required for the tooth to chew and swallow, which results in less palatability (Zou et al., 2013). The texture characteristics of raisins with varying ripeness were investigated by Wang et al. (2017) who found that raisins with low ripeness have hard and rough characteristics. Similar results have been observed in earlier studies on mangoes (Li et al., 2023). Therefore, to obtain a better textural property, mulberry fruits with higher maturity levels (D4 and D5 stage) may be ideal for drying processing.

Table 4 illustrates the sensory analysis profile of dried mulberries, including appearance, flavour, texture, and overall acceptability on a nine-point scale. Consumers often prioritise appearance while choosing fruit products, followed by flavour and texture (Wang et al., 2023). The appearance score of dried mulberries first increases and then decreases, with D3 and D4 samples obtaining the highest colour scores. Low scores for attractiveness were given to D1 dried fruits because they had uneven coloration, and appeared reddish and immature. Excessive ripening and cell collapse during drying caused severe skin and pulp shrinkage, which eventually results in a great decrease in the appearance score of D5 dried fruits. Additionally, flavour is another critical factor affecting consumer choice. The flavour score of dried fruits increased with fruits ripening since ripe mulberries are known to contain higher levels of TSS and lower TA, rendering them sweeter (Wang et al., 2023). The flavour score demonstrated a substantial negative correlation (p < 0.05, r < -0.9) with L* and a* value, and a significant positive correlation (p < 0.05, r = 0.88) with TSS/TA ratio, respectively (Fig. 8). Besides, low-maturity mulberries with high acidity subjected to extended drying periods produced furfural with an undesirable flavour and lower ester content, leading to a low dry flavour score. Furthermore, the texture of fruit plays a critical role in consumer choice as well. On the other hand, the dried fruits with high ripeness have a high texture score, which is similar to the research performed by Wang et al. (2017) and Li et al. (2023). Because of their greater hardness, gumminess, and chewiness, the dried fruits from low-maturity mulberries were less pleasant and scored lower. There was a higher overall acceptance score for dried fruits from D4 and D5 stages due to their uniform colour, lower acidity, and favourable taste. Moreover, correlation analyses revealed a statistically significant positive correlation (p < 0.05, r=0.9) between the overall acceptance score and appearance score, and texture score (Fig. 8). As a result, grading mulberry may be applied to produce dried mulberries as a means of obtaining higher sensory quality.

Table 4

Sensory attributes of dried mulberries from different ripeness fruits. (1 = dislike extremely, 9 = like extremely).

 

Ripeness

 

D1

D2

D3

D4

D5

AppearanceA

5.19 ± 0.21d

7.88 ± 0.23b

8.52 ± 0.30a

8.15 ± 0.11a

6.73 ± 0.21c

FlavourB

3.22 ± 0.11d

4.18 ± 0.21c

5.33 ± 0.22b

7.10 ± 0.18a

7.15 ± 0.13a

TextureC

4.11 ± 0.23c

5.82 ± 0.19b

5.99 ± 0.31b

7.22 ± 0.27a

7.53 ± 0.23a

Overall acceptability

5.02 ± 0.12c

5.23 ± 0.13c

6.84 ± 0.23b

7.96 ± 0.19a

8.15 ± 0.27a

Note: the different letters in the same row reveal significant differences (p < 0.05).
A Including fruit color, color uniformity, dried mulberry size and uniformity.
B Including caramel, spice, sweet, sour, bitter and astringent.
C Including hardness, gumminess, and chewiness.

4. Conclusions

By sorting the mulberries (D1–D5 stage, 0.905–1.055 g/cm3) via the flotation method in accordance with their density, a significant positive correlation was observed between the fruit density and ripeness. According to NMR analysis, mulberries dried quickly in stages D1 to D4 as a result of a decline in water binding capacity and an increase in free water content. However, cell shrinkage and collapse of D5 fruits reduce the mobility of transformed water molecules while prolonging their drying time. Additionally, post-harvest ripening substantially altered the aroma components, colour, texture, and sensory quality of dried mulberries. Because the dried mulberries from D1 fruits were high in total acid, furfural, and 1-cyclohexanone, they had more overtly unpleasant flavours and a pronounced sour taste, resulting in a lower score for flavour. In addition, D1 dried fruits were unsuitable for direct consumption due to uneven colour, poor palatability, as well as low overall acceptance. Nonetheless, crushed D1 dried fruits exhibited bright red colouring, implying potential as an additive for enhancing food's red colour. Conversely, D4 and D5 dried fruits had short drying times, strong fruit aroma, good palatability, and high overall acceptance, which makes them ideal for the drying process. Considering drying time, physicochemical properties, and volatile components, along with sensory evaluation, non-destructive maturation classification of mulberries in accordance with their density at harvest presents an interesting tool for getting effective and high-quality mulberry processing.

Declarations

Data Availability

The authors declare that data obtained during the development of this project is available to the reader, upon requirement to the corresponding author.

Acknowledgements

The authors gratefully acknowledge the Teaching and Research Core Facility at College of Life Science and Life Science Research Core Services, NWAFU for technical support.

Funding

This research was supported by the Engineering Technology Research Project of the Shaanxi Provincial Department of Science and Technology (2022ZY2-GCZX-01).

Author information

Authors and Affiliations

College of Food Science and Engineering, Northwest A&F University, Yangling, China.

Kunhua Wang, Qingyuan Li, Peiyun He, Xiaoran Jia, Wenxin Ren, Jun Wang, Huaide Xu.

Contributions

Kunhua Wang: Laboratory experiments, Conceptualization, Methodology, Software, Investigation, Writing - Original Draft.

Qingyuan Li: Laboratory experiments, Validation, Formal analysis, Data Curation.

Peiyun He: Validation, Formal analysis, Visualization. 

Xiaoran Jia: Validation, Formal analysis, Visualization. 

Wenxin Ren: Validation, Resources, Data Curation.

Jun Wang: Validation, Resources, Data Curation, Writing - Review & Editing,  Supervision.

Huaide Xu: Resources, Validation, Data Curation, Writing - Review & Editing, Supervision, Funding acquisition.

Corresponding author

Correspondence to Jun Wang and Huaide Xu.

Conflict of interests

The authors declare no conflict of interest.

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