1 Introduction

Drying is one of the most common methods of food preservation. It is defined as the process of removing water content from a product involving simultaneous heat and mass transfer to reduce water activity, minimize product deterioration, and maintain the quality of the said product (EL-Mesery et al., 2022; Singh et al., 2018). Drying also reduces the product weight and volume, thus decreasing the price of storage, packaging, and transportation. Hence, it is a critical step for food preservation, especially for rural areas in developing countries where resources and infrastructures are limited (Srinivasan & Muthukumar, 2021). However, drying is an energy-intensive process, consuming between 7 and 15% of total industrial energy in developing countries (Anum et al., 2016). Using non-renewable energy sources such as fossil fuel or coal is not sustainable in the long run, requires higher costs, and harms the environment due to the greenhouse gas produced. Therefore, implementing renewable energy, such as solar energy, will greatly reduce energy costs and promote an environmentally-friendly process (Atalay et al., 2022; Aziz et al., 2021). Traditionally, most farmers from developing countries near the equator have utilized open sun drying. While easy to perform and cheap, it is not without several drawbacks, such as the inability to control the external parameters (temperature, airflow rate, etc.) during the drying process, long drying time, the need for large open spaces, exposure to contamination, and low product quality ( Kumar et al., 2016; Lamidi et al., 2019). On the other hand, solar drying is faster, more efficient, more hygienic, and can be controlled easily according to the dried product’s characteristics. This will ensure good product quality, lower crop losses, and a good drying rate while retaining the advantages of open sun drying (Fudholi et al., 2015a, 2015b; Udomkun et al., 2020). Generally, solar dryer utilizes a solar collector to convert solar radiation into thermal energy, which will be transferred to the dried material, usually by air (Dabra & Yadav, 2021). Recently, solar dryers have been developed in various types and configurations to improve their efficiency and allow them to operate in unfavourable weather, such as by using thermal storage materials or combining the solar dryer with external heat sources like biomass or Liquefied Petroleum Gas (Kumar & Singh, 2020; Yassen & Al-Kayiem, 2016).

In most drying studies, 4E analysis is the most commonly used method to assess the performance of a dryer. It consists of energy, exergy, environmental, and economic analysis (Hao et al., 2020; Mugi & Chandramohan, 2022; Pandey et al., 2021). Energy analysis can provide options for energy savings, determine optimum process conditions, and identify energy losses (Aviara et al., 2014; Sansaniwal et al., 2018). Meanwhile, exergy analysis can determine the ‘quality’ of energy and the sustainability of a dryer system, hence signifying its importance in accompanying energy analysis and developing a sustainable dryer (Aman et al., 2022; Andharia et al., 2021; Kalogirou et al., 2016). Environmental analysis plays an important role in solar drying systems, including evaluating the amount of CO2 mitigated and emitted from the solar drying system. Prioritizing a clean and environment-friendly drying process is desirable to reduce gas emissions and help minimize environmental challenges (Jiakui et al., 2023; Srinivasan & Muthukumar, 2021). Lastly, economic analysis enables forecasting the possibility of actual benefits over the expenses during the lifetime of a solar drying system, which is critical since a bigger solar dryer requires larger capital expenditure. Moreover, economic analysis is essential for good decision-making, especially in the current times when the market is very competitive. (Abbas et al., 2019; Fudholi et al., 2015a, 2015b; Srivastava et al., 2021).

Although 4E analyses are often conducted simultaneously, they are independent parameters by nature and not directly related to each other. Therefore, it cannot reveal the real behaviour of the dryer system. Hence, additional parameters that link those analyses must be evaluated to obtain a complete and accurate understanding of a drying system. In other thermal system studies, other “E” analysis parameters exist, such as energoeconomic, exergoeconomic, and enviroeconomic (referred to as “additional 3E” analysis for convenience). Energoeconomic analysis is a mix between energy and economic analysis and provides extra information about the cost-effective design of a system from the energy standpoint. (Sreenath, Sudhakar, & AF, 2021). Exergoeconomic analysis, also known as the exergy costing principle, utilizes exergy analysis to determine the price of exergy output and exergy destruction of a unit and the whole system (Thangavelu et al., 2021). Lastly, enviroeconomic analysis is a combination of environmental and economic analysis that identifies the options for reducing the environmental impact of a system and is mainly performed based on the price of CO2 produced by a system (Gaur & Tiwari, 2014). Since the energy, exergy, and environmental constraints are being incorporated into economic analysis, they can give in-depth perceptions for enhancing the environmental impact and cost-effectiveness of a dryer, making them valuable for proper and careful decision-making (Lamidi et al., 2019; Yousef & Hassan, 2020). Hence, combining the additional 3E analysis with the existing 4E analysis is imperative to obtain an accurate and complete understanding of a thermal system. The additional 3E provides a multi-dimensional way to assess the system, namely connecting the technical or performance aspect and the economic aspect.

Product quality is another indicator that arises when designing a solar dryer system besides the performance parameters, as it determines the product’s marketability. However, balancing quality and performance parameters is difficult due to conflicting drying parameters or operating conditions. For example, freeze-drying (Salazar et al., 2018) and vacuum drying (Schulze et al., 2014) can produce dried products with good quality parameters. Still, their operating costs are exceedingly high due to the higher energy demand. Therefore, assessing performance and quality parameters in drying studies can provide information about balancing both parameters and finding the optimum operating conditions. Quality parameters can be categorized into physical, chemical, and nutritional, depending on the dried product (Deng et al., 2021; Hii et al., 2019).

To the best of the authors’ knowledge, literature about energoeconomic, exergoeconomic, and enviroeconomic analysis on drying applications is scarce. Information about 7E analysis on drying systems and in-depth explanation of quality aspects of solar-dried products are also limited. Furthermore, a combination of 7E and quality (Q) analysis on a solar dryer system has yet to be evaluated. It is expected that performing the 7E + Q analysis will give a complete understanding of the solar dryer system from the performance, economic, and product quality standpoint, thus providing a balanced view and better information for decision-making regarding the dryer operation. Therefore, this article will provide a comprehensive review of the additional 3E analysis and quality parameters of solar-dried products. The concept of 7E + Q analysis as a new assessment tool for solar dryers will be presented in detail. The structure of the review article is presented as follows. First, the energoeconomic, exergoeconomic, and enviroeconomic parameters and their applications in thermal systems will be explained. After that, the impact of solar drying on the quality parameters of various products will be reviewed. Next, the importance of 7E analysis on solar drying systems will be discussed. Finally, the 7E + Q analysis for solar dryers will be introduced, and the conclusion will be presented.

2 Energoeconomic, exergoeconomic, and enviroeconomic analyses on various thermal systems

2.1 Energoeconomic analysis

This analysis aims to measure the impact of energy usage of a thermal system on the economic aspect, i.e., the cost associated with the energy usage. Gaur and Tiwari (2014) conducted an energoeconomic analysis of semitransparent and opaque photovoltaic (PV) modules for four different types of solar cells. They defined the energoeconomic parameter (Ren) as the ratio of energy loss rates (Len, kWh) with net present value (NPV, $), respectively, as shown in Eq. 1. In this case, the low value of energoeconomic parameter is preferred. They found that higher thermal efficiency of the module will translate to lesser energy loss and lower value of energoeconomic parameter.

$$ R_{en} = \frac{{L_{en} }}{NPV} $$
(1)

Ozturk and Dincer (2020) investigated the energy loss ratio (energoeconomic parameter) of a solar-assisted tea dryer and found that the energoeconomic parameter of the dryer was 76.45 MJ/$. They discovered that higher reference temperature led to a lower value of energoeconomic parameter, which is desirable. Meanwhile, Shoeibi et al. (2021) compared the energoeconomic parameters of water-cooled and air-cooled solar still. In this study, they defined the energoeconomic parameter as the ratio of energy produced by solar still per year (Een,out, kWh/year) and the total uniform annual cost (UAC, $/year) of the solar still, as depicted in Eq. 2. In this case, a high value of this parameter is preferred. They reported that water-cooled solar still had a higher energoeconomic parameter (2.62 kWh/$) compared to air-cooled (2.31 kWh/$), due to the much higher annual energy output and lower production cost.

$$ R_{en} = \frac{{E_{en,out} }}{UAC} $$
(2)

Sreenath et al., (2021a, 2021b) compared the energoeconomic parameter of a land-based solar PV power plant from five locations in Malaysia. The energoeconomic parameters were in the range of 0.0147 – 0.1473 kWh/$ without including the greenhouse gas (GHG) revenue and 0.0111 – 0.065 kWh/$ including the GHG revenue. The location with the highest daily solar radiation and air temperature had the lowest energoeconomic parameter, due to higher system efficiency and energy generation. In another work by Sreenath et al., (2021a, 2021b), they investigated the energoeconomic parameter of PV power plants in seven airport sites in India. The energoeconomic parameter varied between 78.63 and 192.22 MWh/mil $ if GHG revenue was excluded and 42.64–68.30 MWh/mil $ when GHG revenue was included. The lowest energoeconomic parameter belonged to the Dehradun airport, which has the highest energy generation and lowest energy loss among other locations.

Yousuf et al. (2022) assessed the energoeconomic parameter of a 50 MW wind energy system for eight locations in Pakistan. Among them, the three best locations (Sujawal, Sanghar, and Umerkot) were selected. Excluding the GHG credit, the energoeconomic parameter of the wind farm was 4.03, 7.36, and 8.95 GWh/mil$, respectively, whereas when the GHG credit is considered, the value decreased to 1.87, 2.76, and 3.08 GWh/mil$, respectively. The Sujawal region had the highest wind power density, highest power generation, and the lowest cost of electricity production, which translates into low energoeconomic parameter value.

2.2 Exergoeconomic analysis

Exergoeconomic analysis combines exergy aspects with economic constraints to provide information that cannot be accessed through conventional exergy or economic analysis. An exergoeconomic analysis of a gas engine–driven heat pump drying system for three different medicinal plants was carried out by Gungor et al. (2012). The Specific Exergy Costing (SPECO) principle was used, in which the exergy unit of each material and energy stream has an assigned cost value. The exergoeconomic properties used to assess the system performance were the exergoeconomic factor (fk) and relative cost difference (rk), as shown in Eq. 3 and 4. Zk is the hourly levelized cost of investment of equipment k ($/h), CD,k is the exergy cost rate of destruction of equipment k ($/h), and ηk is the exergy efficiency of equipment k. They reported that the highest exergy destruction cost rates were observed during the drying of T. vulgaris, likely due to lower drying rate and exergy efficiency than the other two medicinal plants. All exergoeconomic factor values were higher than 20%, indicating that the costs of exergy destruction were low. A higher temperature difference between the system and ambient conditions will increase the exergy destruction, which leads to a higher exergy cost, lower exergoeconomic factor, and a higher relative cost difference.

$$ f_{k} = \frac{{\dot{Z}_{k} }}{{\dot{Z}_{k} + \dot{C}_{D,k} }} $$
(3)
$$ r_{k} = \frac{{1 - \eta_{k} }}{{\eta_{k} }} + \frac{{\dot{Z}_{k} }}{{\dot{C}_{D,k} }} $$
(4)

Ganjehsarabi et al. (2014) conducted an exergoeconomic analysis of a heat pump tumbler dryer using the SPECO method. The exergoeconomic factor, relative cost difference, and exergoeconomic parameter (Rex, kW/$) were determined. The exergoeconomic parameter is defined as the ratio of component exergy destruction rate (ExD,k, kW) and the purchased equipment cost (PEC, $), as shown in Eq. 5. They reported that the compressor had the highest exergy destruction rate (0.85 kW) while the condenser had the highest exergy destruction cost rate (0.17 $/h). The highest exergoeconomic factor belonged to the compressor unit (76.34%), whereas the condenser had the highest relative cost difference (4.78). From the results, it can be implied that the investment cost of the compressor unit was too high as it has the highest exergoeconomic factor. Meanwhile, the exergoeconomic factor of the condenser unit was the lowest, indicating high exergy destruction cost. Meanwhile, increasing the air mass flow rate will increase the exergy destruction, resulting in a higher value of the exergoeconomic parameter, which is not desirable.

$$ R_{ex} = \frac{{Ex_{D,k} }}{PEC} $$
(5)

Ozturk and Dincer (2020) conducted an exergoeconomic analysis of a solar-assisted tea dryer. They defined the exergoeconomic parameter as the ratio between exergy loss (Exloss, MJ) and the capital cost (Ccap, $), as shown in Eq. 6. The exergy loss ratio i.e., exergoeconomic parameter of the system was 72.63 MJ/$. They observed that a higher inlet air mass flow rate leads to a higher exergy loss ratio (exergoeconomic parameter), whereas a higher reference temperature will decrease the exergoeconomic parameter. Singh et al. (2020) studied the exergoeconomic performance of each component from a batch-type solar-assisted heat pump dryer applied for banana chips. They reported that from all of the main components of the dryer (compressor, condenser, expansion device, evaporator, and drying chamber), the exergoeconomic factor varied between 0.1395 and 0.8076 during heat pump drying, while during solar-assisted heat pump drying, the value varied between 0.2053 and 0.8595. The drying chamber had the highest exergoeconomic factor while the expansion device had the lowest value. Thus, operating the heat pump dryer with the assistance of solar energy is better as the exergy losses and the exergy destruction costs are lower. Atalay and Cankurtaran (2021) investigated the exergoeconomic of a large-scale solar dryer with thermal energy storage applied for strawberries. The exergoeconomic factor was 0.507, 0.658, 0.786, 0.937, 0.98, and 0.991 for the fans, energy storage medium, heat exchanger, drying cabin, fittings, and solar air collectors. Meanwhile, the exergoeconomic parameter for each component (defined as the ratio of exergy loss to the purchased equipment cost) was 0.266, 0.184, 0.068, 0.042, 0.102, and 0.073 MW/$. It can be implied that the fans had the highest exergy loss and exergy destruction cost, indicating that improving the exergy efficiency of the said equipment is required. Akdeniz et al. (2022) investigated the exergoeconomic performance of a jet-fueled turbofan of an aircraft engine. The cost rate of exergy destruction, exergoeconomic factor, and relative cost difference of the turbofan engine subcomponents varied between 4.148 and 344.328 $/h, 10.708–92.753%, and 3.35–180.212%, respectively. Meanwhile, for the entire turbofan engine system, the value was 560.119 $/h, 34.494%, and 683.772%, respectively.

$$ R_{ex} = \frac{{EX_{loss} }}{{C_{cap} }} $$
(6)

Al-Hamed and Dincer (2022) investigated the exergoeconomic performance of a carbon-capturing system powered by solar energy integrated with oxy-combustion for a combined power cycle. Aside from the exergoeconomic factor, the cost per unit exergy of fuel (cF,k, $/kJ) and product (cP,k, $/kJ) and the exergy destruction cost rate (CD,k, $/s) were assessed, with Eq. 7 – 9 showing the formula used. C is the cost rate ($/s), Ex is the exergy rate (kW), Exdest is the exergy destruction rate (kW), F stands for fuel, P stands for product, and k is the component measured. In the base case condition, the overall exergy destruction cost rate was 3.4 $/s while the overall exergoeconomic factor was 7.43%. The results indicate that the overall exergy destruction cost rate of the system was indeed high. Hence, the exergy efficiency must be increased. Analysis with varying operating conditions showed that the exergoeconomic factor increased when fluid temperature entering and exiting the solar collector increased.

$$ c_{F,k} = \frac{{C_{F,k} }}{{Ex_{F,k} }} $$
(7)
$$ c_{P,k} = \frac{{C_{P,k} }}{{Ex_{P,k} }} $$
(8)
$$ C_{D,k} = c_{F,k} Ex_{dest,k} $$
(9)

2.3 Enviroeconomic analysis

In this analysis, environmental aspects will be integrated with the economic analysis, where the cost of greenhouse gas emissions will be calculated, promoting a more environmentally-friendly design and operation (Jiakui et al., 2023). Shahsavar and Rajabi (2018) investigated the enviroeconomic performance of an air-based BIPV/T system. They defined the enviroeconomic parameter (ZCO2, $) as the amount of CO2 mitigation (ϕCO2, ton) times the carbon price (zCO2, $/ton CO2), as shown in Eq. 10. They discovered that the enviroeconomic parameter increased with the increase of airflow rate, channel length, and channel width, whereas increasing the channel depth will decrease the parameter instead. Meanwhile, Saini et al. (2017) studied the enviroeconomic of five different PV modules integrated with a greenhouse solar dryer. The CO2 emission was 141.73, 116.48, 85.51, 82.35, and 40.96 kg/year for c-Si, p-Si, a-Si, CdTe, and CIGS PV modules respectively, whereas the net CO2 mitigation over the system’s lifetime was 108.35, 103.16, 80.21, 87.71, and 92.37 tons, respectively. Meanwhile, the enviroeconomic parameter was 1083.54, 1031.58, 802.10, 877.12, and 923.68 $ for five PV modules. Although the c-Si type has the highest enviroeconomic parameter and net CO2 mitigation, the carbon emission of the CIGS type is the lowest due to its simpler manufacturing, making this type a viable choice when reducing greenhouse gases is a primary concern.

$$ Z_{{CO_{2} }} = \phi_{{CO_{2} }} z_{{CO_{2} }} $$
(10)

Zuhur and Ceylan (2019) conducted an enviroeconomic analysis of a concentrated PV/T collector for winter application. They reported that with CO2 mitigation of 0.6 kg CO2/h, up to 1 ¢/h of savings achieved due to prevention of CO2 production (i.e., enviroeconomic parameter) can be obtained. Moreover, using concentrators increased the enviroeconomic parameter by about 50%. Arslan and Aktas (2020) investigated the enviroeconomic parameter of an infrared-convective solar dryer powered by a solar photovoltaic thermal collector for mint and fresh apples. During drying with the air mass flow rate of 0.0455 and 0.0364 kg/s, the enviroeconomic parameter was found to be 3.39 and 2.33 euro/h. This indicates that drying at a higher air mass flow rate is environmentally safer and saved more environmental costs. Meanwhile, Chopra et al. (2021) compared the enviroeconomic performance of a solar water heating system with and without thermal energy storage (TES). In this study, the enviroeconomic parameter is calculated from both energy and exergy standpoints. Based on the energy approach and with varying water flow rates between 0.13 and 0.46 L/min, the enviroeconomic parameter varied between 310.3 and 401.17 $/lifetime on the system with TES and 215.08–289.521 $/lifetime on the system without TES. Meanwhile, from the exergy standpoint, the value varied between 95.7 and 114.79 $/lifetime and 70.57–89.42 $/lifetime for systems with and without a TES unit. The results showed that the solar water heater with the TES unit is a better choice.

Pal et al. (2021) assessed the enviroeconomic performance of four different types of modified solar still. From the energy standpoint, the enviroeconomic parameter varied between 24.6 and 32.16, 47.04–57.92, 37.48–4.95, and 74.37–96.45 euros for single slope, double slope, single slope multi-wick, and double slope multi-wick solar still, respectively. Meanwhile, from the exergy approach, the value varied between 1.3 and 1.65, 1.18–1.5, 1.5–2.8, and 1.42–2.2 euros for four solar still types. Therefore, double slope multi-wick modified solar still is the best choice. Moreover, they also discovered that higher water depth would decrease the enviroeconomic parameter, likely due to less energy and exergy output obtained. Meanwhile, Abo-Elfadl et al. (2021) compared the enviroeconomic performance of a flat and a newly designed tubular absorber on single and double solar air heaters. For the flat absorber, the enviroeconomic parameter varied between 172.6 and 484.4 $/year, whereas the value varied between 398.3 and 578 $/year for the tubular absorber. Therefore, the tubular absorber performed better in terms of achieving higher benefits from CO2 reduction. Moreover, the double-pass solar air heater with a higher air mass flow rate gave the highest enviroeconomic parameter.

3 Summary

Table 1 summarizes some important findings about the additional 3E analysis. Based on the reviews, the additional 3E parameters can reveal the direct connection between energy, exergy, or environmental parameters and the economic aspect. Such connections cannot be obtained through the conventional 4E analysis. For example, the exergoeconomic factor can directly correlate the exergy destruction (or exergy loss) and the system’s total cost, resulting in a concrete value that represents both exergy and economic aspects. Another benefit of implementing additional 3E analysis is that it can greatly assist in optimizing the thermal system and provide more accurate results. This is because one does not need to optimize, for example, the energy and economic aspect separately, as the energoeconomic parameter includes both aspects, making the process easier and faster. The implementation of additional 3E analysis is important in the drying of food and agricultural products since it provides additional information on the performance parameters concerning the economic aspect, which is arguably the most important factor for small-medium enterprises (SMEs) in rural areas. This allows the user to make better decisions about whether to replace certain dryer components, improve their performance, or change the type of dryer or food product to avoid low profitability (Atalay & Cankurtaran, 2021; Ge et al., 2022). Hence, conducting the additional 3E analysis alongside the conventional 4E analysis is critical to determine the true behaviour of the thermal system.

Table 1 Important findings and benefits of the additional 3E analysis
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4 Quality analysis of solar dried products

4.1 Physical properties

The moisture reduction of material during drying will change its appearance and physical attributes. Being one of the easiest to notice, colour changes on dried products are mainly caused by the browning reaction, which may be enzymatic or non-enzymatic. Mennouche et al. (2017) found that during indirect solar drying of dates, the total colour change increased from 1.34 to 4.97 when the drying temperature increased from 50 to 65 °C, indicating that higher temperature will further degrade the dates’ colour. They also discovered a darkening phenomenon during drying at 65 °C. During mint drying, Eltawil et al. (2018) reported that the solar dryer system had lower total colour changes (0.208–0.747) than open sun drying (0.173–0.983). Pankaew et al. (2020) discovered that chilli dried using a greenhouse dryer integrated with phase change material (PCM) could produce chilli with dark golden colour, which is preferable, whereas open sun drying’s result was a bit lighter. Kushwah et al. (2021) found that the reduction of garlic’s yellow colour in open sun drying was more severe than in solar dryers due to continuous solar radiation exposure. Meanwhile, Sharma et al. (2021) reported that the colour changes of turmeric dried using a hot-air dryer were slightly higher (9.56–15.85) compared to the direct solar dryer (9.12–14.59).

Dried materials are more fragile due to water loss, and the texture change may impact the acceptability of the product for the consumer. Lakshmi et al. (2019) found that curcuma dried in the mixed mode solar dryer required more force (7920.34 g) than indirect solar dryer and open sun drying, which may be caused by more efficient and uniform drying. Kondareddy et al. (2021) reported that the hardness of blood fruit dried using the solar dryer integrated with PCM was 613.73 ± 12.29 N, which was lower compared to open sun drying (937.97 ± 11.52 N) and tray drying at 60 °C (728.35 ± 15.29 N). They attributed lower crushing strength to a more stable and uniform drying process. Meanwhile, Roratto et al. (2021) conducted banana drying using a hybrid solar vacuum dryer. They found that the dryer was able to reduce the porosity, increase bulk density, and increase the maximum puncture of the banana, resulting in a denser material structure and lesser irregularities.

During drying, the moisture removal will create a pressure imbalance inside the material. This generates stress and contraction inside the material, leading to shrinkage, change of shape, and eventually cracking. Koua et al. (2019) discovered that the volume of cocoa beans dried using an indirect solar dryer decreased by 0.276 mm3 for every mm3 of moisture removed. They also found that low-temperature drying could reduce internal stresses and promote continuous shrinkage throughout drying. Seerangurayar et al. (2019) compared the shrinkage of dates dried using a greenhouse tunnel dryer and an indirect forced-convection solar dryer. The shrinkage in length, diameter, and volume of dates dried using the indirect solar dryer was 6.9–9.4%, 10.5–26.8%, and 25.3–51.3%, while in the greenhouse tunnel dryer, the values were 6.9–12.7%, 12.5–27.1%, and 28.5–53.5%. Iranmanesh et al. (2020) reported that the shrinkage of apples dried using a solar dryer with PCM varied between 78.94 and 82.23%. Apples dried at a higher airflow rate had the lowest shrinkage, indicating better quality retention.

4.2 Chemical properties

As a result of moisture reduction during drying, the dried material’s chemical compositions will change. A lot of chemical compounds degrade at a high temperature and prolonged drying time. Hence, the flavour and odour of food and agricultural products will also change, depending on the drying method. Barrientos et al. (2019) investigated the impact of solar drying on the various flavour and odour attributes of cocoa. They discovered that in 132 h of drying, the dairy, acid, and woody odours fluctuated, whereas the flavour attributes that changed were toasted, astringent, spicy, and acid. Moreover, due to water loss during drying, the concentration of ethereal extract and glucose increased, corresponding to a fatty and sweet flavour. Meanwhile, Murali et al. (2019) utilized a solar-electric hybrid dryer for mackerel drying and reported that the odour of fish dried using the solar hybrid dryer was less fishy than open sun drying. This might be caused by the lower amount of Thiobarbituric Acid (TBA) in the solar-dried sample, which is a compound that indicates the secondary lipid oxidation responsible for discoloration, rancid flavour, and off odours. Mongi and Ngoma (2022) investigated the changes of flavour in solar-dried mango. They found that no significant flavour changes were observed, mainly because solar drying was able to concentrate sugars, making the dried mango sweeter compared to the fresh mango. They also reported a decrease in fat content in the solar-dried samples, which is desirable as lipid oxidation will result in rancid and unpleasant flavours.

Most raw agricultural products have high water activity, which makes them vulnerable to microbial spoilage and mechanical damage. By decreasing water activity through drying, physical and chemical changes in the material will be minimized, ensuring good quality retention (Zhang et al., 2017). Dufera et al. (2021) reported that the water activity of solar-dried tomatoes ranged between 0.288 – 0.32. Therefore, the water activity values were within the safe range of microbial growth (water activity > 0.7) and not vulnerable to non-enzymatic browning (between 0.5 and 0.8). Meanwhile, Alfiya et al. (2022) reported that the water activity of Bombay duck dried using a solar LPG dryer was 0.596. Malakar et al. (2022) reported that the water activity of solar-dried beetroot is much lower (0.34) than open sun drying (0.55), indicating better performance by the solar dryer.

4.3 Nutritional properties

Inappropriate drying of agricultural products will result in high nutritional loss and reduced overall quality (EL-Mesery et al., 2022). In most agricultural products, a drying temperature higher than 60 ºC is unfavourable as rapid drying will cause the outer layer to dry quickly. As a result, the diffusion path will break, causing chemical compounds inside to leave (Barghi Jahromi et al., 2022). Good retention of nutritional components may increase the selling value of the product and retain its nutritional benefits (Takougnadi et al., 2020; Zafar et al., 2022).

Reyes et al. (2019) conducted kiwifruit drying using a solar dryer integrated with PCM and found that higher moisture reduction and longer drying time led to further reduction of polyphenol content and antioxidant capacity. Moussaoui et al. (2021) utilized a hybrid solar-electric dryer for apple peel drying and reported that both phenolic and flavonoid content increased from 50 to 70 °C but decreased to a minimum value at 80 °C. Such an increase can be attributed to the breakdown of chemical bonds, thus allowing phenolic compounds to diffuse through the food matrix. Lakshmi et al. (2021) found that black pepper’s proximate contents (ash, fiber, carbohydrate, fat, and protein) increased during solar drying, but the highest increase was found on open sun drying. The antioxidant activity decreased from 54.22 μmol TE (Trolox Equivalent) per g sample on fresh samples to 45.69, 41.57, and 23.25 μmol TE/g sample for black pepper dried in mixed mode, indirect mode, and open sun drying, while TPC decreased from 38.47 mg GAE/g sample to 29.87, 30.11, and 18.35. Kondareddy et al. (2021) reported that the reduction of phenol and antioxidant activity during solar drying was fewer than open sun drying. The controllable nature of solar drying enabled systematic disruption of cell walls, gradually activating the oxidative enzyme.

Mohammed et al. (2020a) compared the conventional solar dryer (CSD) and improved indirect solar dryer (ISD) applied for mangoes and pineapples. The total acidity and phenols reduction was higher on open sun drying compared to both solar dryer types. ISD mode had a significantly higher number of proximate compositions. The vitamin A and C contents decreased during drying, but ISD had the smallest decrease than other drying modes. Mongi and Ngoma (2022) reported that solar dryers could retain more than 65% of the nutrients of mango, though fat and protein content had the highest decrease. Silva et al. (2021) conducted Spirulina drying using an indirect solar dryer and found that the phenolic content decreased by about 28% on average compared to the fresh Spirulina, but the values were still within the standards.

5 Summary

A summary of changes in quality parameters for solar-dried products is shown in Table 2. Generally, solar drying will cause irreversible changes in the dried material’s physical, chemical, and nutritional attributes. Hence, it is imperative to balance the performance and quality aspects of solar dryers to obtain optimum drying conditions while maintaining good product quality. From the reviews, it is found that operating the solar dryer in mild drying conditions (40 – 60 ºC) can minimize the dried product’s degradation. Moreover, several studies reported that the solar dryer can retain most of the useful nutritional compounds. In particular, indirect and mixed-mode solar dryers are the best combination to retain the product quality, the former being a good choice for photosensitive materials. Meanwhile, the latter allows for fast drying due to consistent solar radiation collection. These should be considered since a prolonged drying process, especially under high temperatures, will degrade the product quality.

Table 2 Changes of quality parameters in solar dried products
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6 Importance of 7E analysis in solar drying studies

Due to the useful information provided by additional 3E analysis, it would be beneficial to combine them with the already existing 4E analysis, thereby creating 7E analysis, a new assessment tool for the solar dryer systems. A comparison of 4E analysis and 7E analysis is shown in Table 3. It is clear that despite being more complex and requiring more effort, 7E analysis can reveal the connection between “E” parameters that cannot be obtained using only 4E analysis, namely the relation between technical / performance and the cost factors in the system (Yousuf et al., 2022). For example, conducting the exergoeconomic analysis will provide a direct connection between exergy loss and the cost of the system, thereby giving a new indicator that prompts exergy loss to be minimized so that less cost will be incurred. In this regard, the information on the system’s sustainability from exergy analysis is further strengthened by the inclusion of the economic aspect, making it a very useful parameter to assess. Unlike 4E analysis, 7E analysis allows qualitative assessment of the thermal system thanks to its multi-dimensional nature. Since the energy, exergy, and environmental aspects are assessed from an economic standpoint, the impact of the system’s performance on the cost or profit can be determined. This direct connection is critical, as it can provide a realistic view of the system, greatly assisting in how it can be improved and what specific parts could be changed. Moreover, optimization of the system becomes much easier and more accurate as 7E analysis provides a multi-dimensional view of the system. However, it is important that the energy, exergy, and environmental analysis are conducted properly and thoroughly to simplify the process of determining the additional 3E parameters. Exergoeconomic is the most complex among the additional 3E parameters, as it involves determining each component’s exergy loss and exergy cost. A proper exergy balance is critical to ensure accurate exergoeconomic calculations. Economic analysis must be performed in detail to support both energoeconomic and exergoeconomic analysis as they are often calculated for each component of the system. Nevertheless, additional 3E analysis is beneficial for decision-making and feasible to perform alongside 4E analysis to create a multi-dimensional assessment tool for thermal systems.

Table 3 Comparison of 4E and 7E analysis
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Though the additional 3E analysis is scarce in drying studies, some have attempted to do so. It is evident that they can connect energy, exergy, and environmental parameter directly with the economic aspect, thereby providing another point of view that cannot be obtained from the conventional 4E analysis alone (Arslan & Aktaş, 2020; Atalay & Cankurtaran, 2021; Ozturk & Dincer, 2020; Saini et al., 2017; Singh et al., 2020). Drying is an energy-intensive process, with the risk of wasted food products due to improper drying. Moreover, the food and agriculture sector also generate CO2 emissions during the farming or processing step. The energoeconomic and exergoeconomic parameters provide extra information on the cost-effective design of the system. Both parameters can determine the viability of a system in terms of profit generation (Sreenath, Sudhakar, & AF, 2021a Yousuf et al., 2022). Moreover, the exergoeconomic factor can assist in balancing the exergy loss and exergy cost of the whole system, promoting a more sustainable operation while still keeping the effort to minimize cost as much as possible. By determining the enviroeconomic parameter, the amount of savings obtained from mitigating CO2 can be known. Having a certain price for CO2 released into the atmosphere will discourage polluting energy sources such as coal and fossil fuel and promote the usage of renewable energy such as solar energy (Andharia et al., 2021; Gaur & Tiwari, 2014; Iorember et al., 2022). Due to its benefits, 7E analysis is a huge improvement over 4E analysis, making it a valuable assessment tool for drying studies. Since the additional 3E parameters can link the performance aspects to the economic aspect, it is critical to evaluate them, as designing a cost-effective drying system with good performance is quite challenging without a proper and robust assessment tool. This is important in the drying of agricultural products where economic aspects, product quality, and performance efficiency are prioritized. 7E analysis is able to provide more information on how the performance of each component of the drying unit will be reflected in the economic aspect. Thus, depending on the food product, profitability, and user priority, 7E analysis can assist the decision-making on which drying method should be chosen, or which existing dryer component should be improved or replaced. To conclude, 7E analysis is feasible to perform on food drying studies, as it provides a better and broader perspective of the dryer unit and directly connects the performance and economic aspects. However, to date, no studies on food and agricultural product drying have attempted to implement 7E analysis.

7 7E + Q analysis: implementation and future directions

A review of the quality parameters of solar-dried products has been presented in this article. Solar drying degrades the quality of dried products, though the impact varies depending on the product and the solar dryer type. Hence, it is difficult to balance quality and performance aspects (i.e., drying rate, energy, exergy parameters, etc.), as they conflict with each other. On one side, a fast drying process is preferred to save cost and increase the process efficiency, but doing so will compromise the quality parameters, especially for food products, since most of them cannot stand the intense heat for a long time (Mennouche et al., 2017; Reyes et al., 2019). Meanwhile, slow drying, especially at low temperatures, will ensure minimal degradation of quality parameters. However, this will incur more costs and more energy will be wasted (Akonor et al., 2016; Kondareddy et al., 2021; Koua et al., 2019). Often, quality aspects will be compromised for the effective and economical drying process. However, the bad quality of the product may also impact its marketability and sales, thereby affecting the economic aspect as well. This suggests that performance, economic, and product quality aspects are related, and must be equally considered when assessing the performance of a solar dryer.

Therefore, a new multi-dimensional assessment tool called the 7E + Q analysis will be introduced to solve this problem, and the methodology for 7E + Q in solar dryers is shown in Fig. 1. In this analysis, the energy, exergy, environmental, economic, energoeconomic, exergoeconomic, enviroeconomic, and quality analysis will be conducted simultaneously. This will provide a complete understanding of the drying system as the quality parameters are linked with the performance and economic aspects. Moreover, 7E + Q can connect the quality aspect with the multidimensional parameters (additional 3E), thereby providing new correlations of quality and performance parameters that otherwise cannot be obtained through conventional 4E analysis. Thanks to the 7E + Q analysis, it is possible to determine what and where changes should be made to the dryer system since both exergy and exergoeconomic analysis can determine the thermal performance and cost of each unit of the drying system (Atalay & Cankurtaran, 2021; A. Singh et al., 2020). Conducting the 7E + Q analysis will allow for easier adjustment of the drying system if a specific quality threshold is required or if any equipment limitations must be considered. Hence, despite being more complicated and requiring more time to perform, 7E + Q is a valuable assessment tool that will greatly assist in decision-making because it considers all aspects of the drying process. Additionally, due to the thorough and detailed information of the 7E + Q analysis, a more accurate optimization attempt can be carried out to determine the best operating conditions without compromising the performance, economic, or product quality aspect.

Fig. 1
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7E + Q analysis on solar drying system

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Due to their importance, it is beneficial to conduct the 7E and product quality analysis simultaneously to give an accurate and complete understanding of the behaviour of a solar dryer. Currently, there is no 7E + Q study on solar dryer systems, and the published 7E analysis papers were dedicated to solar still, solar power plants, and wind farms (Shoeibi et al., 2021; Sreenath, Sudhakar, & AF, 2021a; Yousuf et al., 2022). Therefore, this paper will be the first to propose the 7E + Q as a new assessment tool for solar dryer systems. Assessing every performance parameter possible is beneficial to improve the viability of solar dryer from the economic and performance standpoint and help provide better information on how to improve its competitiveness and attract more users. Any effort to modify and enhance the performance of solar dryers will result in increased investment costs, and an attempt should be made to balance both economic and performance aspects. This is where the energoeconomic, exergoeconomic, and enviroeconomic analysis can assist. Combined with the quality aspect, a more complete view of the dryer unit can be obtained, as performance, economic, and quality aspects are linked to each other. Future solar dryer research should focus on these parameters as they can reveal the real behaviour of the solar dryer system and help optimize the system. Therefore, implementing 7E + Q analysis for solar dryers is imperative for future studies since it links the performance, economic, and quality aspects. Addressing all of them is not an easy task. Thus, the 7E + Q analysis can help quantify to what extent both performance and quality aspects have been properly addressed.

It is important to balance good agricultural practices, productivity, and environmental sustainability with climate change and the expanding global food demands. However, the agricultural sector contributes to greenhouse gas (GHG) emissions at about 19–29%. Most agricultural tools are driven by fossil fuels, which are the main source of GHG. In the Southeast Asian countries such as Malaysia, Indonesia, Thailand, and the Philippines, high emissions as a result of agricultural practices are still a major issue, as all of them utilize fossil fuels as a major energy source in the agricultural sector (R. Chopra et al., 2022; Liu et al., 2017). Moreover, the disparity between scheme smallholders and independent rural farmers is still profound in Southeast Asia, particularly in Indonesia. Independent farmers still suffer from a lack of knowledge about good agricultural practices and economic constraints (Jelsma et al., 2019; Sun et al., 2022). Being the country with the largest economy and highest population in Southeast Asia, Indonesia is committed to cutting greenhouse gas emissions by 2030 to 29% independently, and up to 38% with international cooperation and support under the 2015 Paris Agreement. Since then, the Indonesian Ministry of Energy and Mineral Resources has set up various regulations and policies on the implementation of renewable energy in Indonesia with a particular emphasis on tariffs in order to make renewable energy more competitive in comparison to fossil fuel (Mahmoody et al., 2021). Applying proper solar drying practices in the agricultural sector directly supports some of the Sustainable Development Goals (SDG) set by the United Nations, namely SDG 1 (no poverty), SDG 2 (zero hunger), SDG 7 (affordable and clean energy), SDG 8 (decent work and economic growth), and SDG 13 (climate action) (Liszbinski et al., 2023). Unlike the commonly used 4E analysis, the 7E + Q analysis introduced in this study can cover the aforementioned SDGs, as the product quality, system performance, economic aspect, and environmental impact are directly connected. Therefore, policymakers can consider 7E + Q as the standard assessment tool for solar dryers in the food and agricultural sector. However, communications between rural stakeholders, researchers, and policymakers are critical to ensure the proper knowledge and the conduct of 7E + Q analysis are shared properly. Government support is critical, mainly by providing the appropriate technology for solar drying and knowledge-sharing of proper solar drying practices in general and the 7E + Q analysis as well.

8 Conclusions

Solar drying is one of the most widely applied drying methods especially in rural areas, given its simplicity and versatility. Although 4E (energy, exergy, environmental, economic) analysis has seen wide application in solar dryer systems, they are one-dimensional by nature, meaning they cannot reveal the actual behaviour of the system. Therefore, this paper has reviewed the additional 3E analysis in various thermal systems. It is evident that they can provide a direct link between performance parameters (energy, exergy, environmental) and economic aspects in a multi-dimensional way. It is very useful for drying food and agricultural products since it can provide a better and broader view of economic and performance aspects since both tend to conflict with each other. Therefore, combining 4E with the additional 3E (thereby creating the 7E analysis) would be beneficial for solar dryers to determine the actual performance of the system and to help make a better decision on the solar drying process, whether to replace a dryer component, improve the efficiency of certain units, or even modify the design. The quality parameters of solar-dried products have been reviewed. The drying process will degrade the physical, chemical, and nutritional attributes of the dried product. Hence, a balance of performance, economic, and quality aspects must be obtained. However, this is not an easy task as the performance and quality parameters often conflict.

This paper has introduced the 7E + Q analysis and emphasized its importance as a new multi-dimensional assessment tool for solar dryers, which is essential to ensure proper food preservation through a proper drying process. Since the performance, economic, and quality aspects are equally considered, 7E + Q can provide better decision-making on what changes or upgrades should be implemented to the existing solar dryer. Moreover, optimization of solar dryers becomes easier as 7E + Q gives more information and correlates the quality, performance, and economic aspects simultaneously. Hopefully, the information presented in this paper could guide and assist researchers in designing and developing a solar dryer system carefully considering the performance, economic, and product quality aspects. In the future, studies of hybrid solar dryers should be focused on obtaining high energy and exergy efficiency, as this type of dryer may be the future of drying technology. 7E + Q analysis will be beneficial for the solar drying of food and agricultural products due to its detailed and thorough information. To date, no attempts have been made to conduct 7E + Q analysis on solar drying of food and agricultural products. It is expected that performing 7E + Q analysis may open up new possibilities to enhance the performance of solar dryer systems.

The agricultural sector still suffers from several drawbacks, such as over-reliance on fossil fuels and a lack of renewable energy usage. Moreover, rural independent farmers still suffer from economic constraints and a lack of knowledge about good agricultural practices. High emissions as a result of agricultural practices are still a major problem in Southeast Asia countries. Being the largest economy in the Southeast Asia, Indonesia has committed to greatly reducing its GHG emissions and as a result, has set up regulations and policies to promote the usage of renewable energy. Applying solar drying in food and agricultural products will support the Sustainable Development Goals. Unlike the one-dimensional 4E analysis, the 7E + Q analysis can cover all aspects of the SDGs involved. Therefore, policymakers may consider 7E + Q as a standard assessment tool for solar drying systems in the food and agricultural sector. However, communications between rural stakeholders, researchers, and policymakers are critical to ensure the proper knowledge and the conduct of 7E + Q analysis are shared properly. The government should support the necessary technology and knowledge-sharing of proper solar drying practices and the 7E + Q analysis as well.