Introduction

Cucumis sativus, a prominent horticultural crop, holds significant importance in India’s farming sector and everyday cuisine. Extensively cultivated in regions such as Karnataka, Andhra Pradesh, Tamil Nadu, Maharashtra, and Uttar Pradesh, India is among the leading global producers of Cucumis sativus. This vegetable flourishes in warm climates with well-aerated soils and reliable irrigation, often grown as a short-cycle crop under open-field conditions or in controlled environments. Its adaptability to varied agricultural methods makes it an essential component of India’s vegetable output¹. Renowned for its exceptional water content (approximately 94%), Cucumis sativus is a hydrating and cooling dietary option. With only 15 calories per 100 grams, it is a low-calorie food enriched with nutrients such as vitamins C and K, potassium, magnesium, and antioxidants like flavonoids and beta-carotene. The fiber content aids digestion, while the high water content supports hydration and improves skin vitality. Additionally, silica present in Cucumis sativus contributes to enhanced skin firmness and joint flexibility². From a health perspective, Cucumis sativus offer notable benefits due to their anti-inflammatory and antioxidant attributes, helping to mitigate oxidative damage and lowering the risks of chronic disorders such as heart illness, diabetes, and cancers. Their mild diuretic action promotes detoxification and assists in regulating blood pressure. Moreover, Cucumis sativus derivatives are widely utilized in cosmetic products for their cooling, soothing, and anti-aging properties³. As a result, Cucumis sativus serve not only as a valuable agricultural product in India but also as a significant element of nutrition and holistic health. Although Cucumis sativus offers numerous health advantages, it is highly perishable, with its availability often restricted by seasonal and geographic factors. To overcome these challenges and prolong its usability, preservation techniques like dehydration are vital. Drying not only ensures a consistent supply of Cucumis sativus throughout the year but also retains their essential nutrients. The primary objectives of drying are to extend shelf life and minimize post-harvest wastages, which are key to ensuring food security and reducing waste. A key approach to extending the shelf life of a specimen is by reducing its moisture content to below 11% on a wet basis. Reaching this wet threshold is essential to prevent deterioration and preserve the product’s quality for a prolonged period. These standards act as important benchmarks for maintaining the ideal moisture levels in dehydrated food items, helping to enhance their durability and preserve their nutritional value⁴.

Preservation methods play a crucial role in maintaining the nutritional integrity of vegetables after harvest⁵. Among these, greenhouse drying has emerged as an eco-friendly and sustainable solution⁶. This technique is particularly effective in reducing the environmental impact of the drying process while ensuring the quality and nutritional value of food products, making it an ideal choice for long-term preservation⁷. A natural-mode greenhouse dryer was first developed for drying vermicelli products of varying sizes, providing a more eco-friendly alternative to the OSD method⁸. Another greenhouse dryer was created for drying ginger and turmeric in natural and forced convection modes, where heat absorption within the dryer caused the ginger and turmeric temperature to exceed that of the surrounding air⁹. The implementation of a mixed-mode greenhouse dryer, which combines both natural and forced convection drying methods, has been shown to accelerate the drying process for red pepper and grape, with forced airflow significantly reducing the overall drying time compared to natural airflow. Optimizing the use of greenhouse dryers can also contribute to reducing carbon dioxide emissions¹⁰. In a constructed setup, the item undergoing drying is enclosed within a framework encased by a transparent cover that shields it from contaminants. The cover absorbs sunlight, raising the temperature of the internal air in the greenhouse, which facilitates moisture extraction from the item¹¹.

Recent progress in solar-powered drying systems for greenhouses has been investigated by numerous scientists, who have employed various types of covering materials to improve the performance of the drying units. When transparent glass is utilized as the covering in a natural greenhouse dryer, the drying period for pepper is shortened by 30%. Adding a non-transparent northern wall and dark PVC coverings on the ground minimized heat dissipation in both natural and forced greenhouse dryer configurations. Enhanced energy transmission has been noted when ginger has been dried using a forced greenhouse dryer system¹². To dehydrate bitter melon samples, a natural greenhouse dryer with a roof-shaped plastic cover was designed, featuring a sheet with a depth of 0.0015 meters. In comparison to the OSD method, the forced convection greenhouse dryer demonstrated a higher convective heat transfer coefficient¹³. Cassava chips was dehydrated utilizing a natural convection drying system with a plastic cover, employing transparent glass with a thickness of 0.005 meters as the glazing material, which resulted in a 30% reduction in drying time¹⁴. The effectiveness of the greenhouse drying technique for dehydrating mint leaves has been evaluated and contrasted with the OSD technique, utilizing ten statistical models to analyze the drying kinetics¹⁵. Likewise, ten statistical models have been applied to examine and describe the moisture removal operation of handmade papers in greenhouse dryer, with the Midilli-Kucuk model providing the best fit to the empirical results¹⁶. These models play an important part in understanding the drying behaviour of food products in greenhouse dryer under different time conditions, aiding in the enhancement of drying process predictions. Items dried in greenhouse dryer generally show superior quality compared to those dried through conventional methods.

The literature review highlights a limited understanding of the drying kinetics of Cucumis sativus. To address this gap, this study introduces a straightforward DLSGD under both natural and forced convection, aiming to evaluate its effectiveness in moisture removal. The research objectives include developing and enhancing a greenhouse dryer by incorporating a drip lock glazing sheet to optimize the drying process. In this study, Cucumis sativus was selected as the plant material. The samples were sourced from a local farm and authenticated based on botanical characteristics. The plant material was assigned the Boucher number Sp. Pl. 1012/1753, serving as a reference for identification and traceability in the study. Additionally, experimental observations will compare the efficiency of OSD and DLSGD under both convection conditions. The study will also examine drying kinetics by measuring moisture content, moisture ratio, and drying rates to achieve the safest moisture level in the shortest possible time. Furthermore, eleven mathematical models will be utilized to identify the most accurate drying model for each technique, using statistical matrices such as R², RMSE, and χ². Lastly, the research will investigate the nutritional retention of essential components like carbohydrates, vitamin C, and calcium in Cucumis sativus, assessing the impact of different drying methods on nutrient preservation and overall drying effectiveness.

Material and Methods

DLSGD system

A DLSGD, designed with a 1.2 m × 1.2 m floor area and a 1 m height, enclosed with drip lock glazing sheet of 0.001 m thick to capture solar radiation. This setup developed for Cucumis sativus drying in both natural and forced convections. In natural convection, the dryer uses natural solar energy and a tactically positioned roof vent to facilitate airflow, enabling drying without mechanical support. In forced convection, a fan working at 1.2 m/s improves air movement inside the dryer. These design features ensure effective air movement and maximize solar energy absorption. Figure 1 presents a schematic of the DLSGD built for this drying operation. The dryer was intentionally oriented in an east–west direction to optimize sunlight exposure. For both OSD and DLSGD processes, 2 kg Cucumis sativus samples were placed in trays. Cucumis sativus pieces were uniformly sliced to a thickness of 0.005 m for consistency during drying. The drying experiments took place from 08:00 to 17:00 hours in May 2024. To prevent moisture reabsorption overnight, sealed plastic covers have been utilized to store the dried Cucumis sativus. The goal was to achieve a safest moisture content suitable for storage, ensuring the dried product’s quality and extending its shelf life by efficiently using solar irradiation in the DLSGD system.

Figure 1: (a) Schematic representation of designed DLSGD and (b) Developed experimental DLSGD system Click here to view Figure

The examination utilized the HR83 Halogen moisture analyzer to determine the initial water content of the Cucumis sativus. Solar irradiance has been measured with a solarimeter that can gauge values up to 1500 W/m², with a precision of ±5%. Temperature readings were taken using infrared thermocouples, which provide a precision of ±1.5°C and could be measured up to 100°C. Wind velocity in the experimental environment was evaluated with the Benetech anemometer, which has a measurement range from 0 to 30 m/s. These specialized and accurate tools supplied reliable data on important ecological parameters, enabling a complete assessment of the drying conditions for Cucumis sativus in both the OSD and DLSGD devices.

Uncertainty analysis

The reliability of the data could be affected by dimensions measured errors during the drying operation like precision, calibration, and interpretation inaccuracies. Temperature, air velocity, mass, and solar irradiation are independent variables in the Cucumis sativus dehydrating process, while moisture content and drying rate are dependent variables¹⁷. Let Y₁, Y₂, Y₃, …, Y_n represent the independent parameters, each linked to uncertainties signified by X₁, X₂, X₃, …, X_n. These uncertainties in the independent variables impact the accuracy and precision of the observations in the drying operation. The dependent outcome, Y, is influenced by these independent parameters, and its uncertainty is termed by Y_U in Equation (1)¹⁸. The uncertainties in both the observed and computed variables are provided in Table 1.

Table 1: Uncertainties in the observed and computed variables

Drying kinetics

The starting moisture level of the Cucumis sativus was measured at 94% employing a Halogen moisture analyzer, regulated to a drying temperature of 120°C. The moisture content of the specimens during the drying process was calculated throughout the day using Equation (2) in % wet basis. This wet basis calculation monitored changes in moisture content over the course of the drying process^19,20:

where  and  represent the initial and final masses of the sample during the drying process, respectively in kg, while 𝑚 denotes the total mass of the Cucumis sativus sample (2 kg). The drying process is finalized once the Cucumis sativus achieves a moisture level close to 11.5%.

The drying rate is a vital parameter for assessing the efficiency of the drying process. It is determined using Equation (3) in kg/hr, which quantitatively measures the speed at which the drying process occurs and the effectiveness of reaching the target moisture content for storage. This metric is crucial for analyzing and relating various drying techniques, providing key insights into the overall effectiveness of the drying system²¹.

The moisture ratio is a critical parameter for assessing and comparing the performance of greenhouse dryers. It is mathematically defined by Equation (4), offering a quantitative representation of the moisture level in relation to the solid mass of the sample²². This parameter serves as a key metric for analyzing and benchmarking the effectiveness of various dehydrating techniques and systems in Cucumis sativus drying processes²³:

Here, MC_it represents the instantaneous moisture content, MC_e denotes the equilibrium moisture content, and MC_i refers to the initial moisture content in % wet basis.

Statistical Analysis

The constants of the model were determined and the curve-fitting process was executed using the Excel Solver tool to evaluate the mathematical models for Cucumis sativus drying. Nonlinear regression analysis was conducted for the eleven models presented in Table 2. Key evaluation parameters, such as the coefficient of determination (R²), Root Mean Square Error (RMSE), and reduced chi-square (χ²), were employed to assess the fitting quality of each model²⁴. The model that exhibited the maximum R² and the minimum RMSE and χ² values was identified as the most suitable. Equations (5), (6), and (7) were applied to calculate the R², RMSE, and χ² values, respectively. These metrics play a crucial part in determining the precision and reliability of the mathematical models describing the drying behavior of Cucumis sativus under the specified experimental conditions²⁵.

Where, n and m represent the number of observations and the constants of the mathematical model, respectively. M_Re ,  M_Rf and M_Rfm correspond to the empirical, forecasted, and mean forecasted moisture ratios.

Table 2: Mathematical models for understanding the drying behaviour of Cucumis sativus^26,27

Nutritional analysis

The drying of food products can greatly affect their nutritional value, influenced by variables like pre-treatment techniques, drying temperature, and storage conditions²⁸. To reduce nutrient degradation, methods like reducing moisture removal durations, using minimal temperatures, and controlling oxygen exposure during preservation can be applied^29,30. In this study, these issues were tackled by incorporating drip lock glazing sheet material. The goal was to reduce nutrient loss and decrease drying times for Cucumis sativus in both natural and forced convection drying conditions. This method represents a pro-forced approach to improve the quality of the dried samples while preserving the nutritional content of the Cucumis sativus by optimizing the drying process. The analytical methods used for measuring the nutritional content of food samples are discussed further. The mineral composition, including calcium and iron, has been analyzed using an atomic absorption spectrophotometer, following modified standard procedures as outlined in the referenced methodology³¹. The Kjeldahl method has been employed for protein measurement³². The equations and methodologies used for determining ash content and carbohydrate content were adopted from the references cited in ³¹ and ³⁴, respectively. The ascorbic acid (vitamin C) concentration in fresh and dehydrated Cucumis sativus samples was determined using a modified titration method³³.

Results

Experimental results

Experimental assessments have been performed to evaluate the performance of DLSGD configurations and OSD in removing moisture from Cucumis sativus slices. Observations were carried out under both natural and forced airflow scenarios. A comprehensive error assessment was conducted on the collected parameters, verifying that all equipment readings were within permissible limits, ensuring data accuracy. Figure 2 illustrates the daily fluctuations in solar energy levels over eight consecutive days in May 2024, measured between 08:00 and 17:00 hours. The mean solar energy intensity was approximately 649.2 W/m². Peak solar intensity of 980.6 W/m² was recorded at 13:00 hour on 05 May 2024. To maintain the target moisture level and prevent humidity absorption from the environment, the dehydrated specimens were stored securely in sealed containers at the conclusion of every session. The drying experiments were repeated daily to ensure uniformity and facilitate cross-comparison of outcomes among various sessions. Natural and forced airflow approaches, alongside the OSD technique, were executed concurrently under equivalent environmental parameters. This methodology enabled a detailed evaluation of the drying approaches and supported an in-depth comparison of their performance.

Figure 2: Variations of solar irradiance with drying hours Click here to view Figure

Figure 3 illustrates the daily patterns of ambient air temperatures and wind speeds recorded between 08:00 and 17:00 hours. On 02 May 2024, the maximum air temperature reached 36.9°C around 14:00 hour. The temperature ranged between 25°C and 37°C, exhibiting a direct correlation with solar radiation rising with increased solar intensity and declining as it decreased. Wind speeds fluctuated between 1.03 m/s and 7.19 m/s, with an average value of 3.91 m/s. For the forced convection experiments, a consistent wind velocity of 1.2 m/s was applied to study the drying behavior of the Cucumis sativus slices.

Figure 3: Variations of atmospheric air temperature and wind velocity with drying hours Click here to view Figure

Drying kinetics

The initial moisture content of Cucumis sativus, measured at 94%, was reduced to a preservation target of below 11.5% over varying durations depending on the drying method. The OSD process required 8 days to achieve a moisture content of 11.5%. In comparison, the DLSGD system operating under forced convection achieved a moisture content of 11.4% in 4.5 days, while the natural convection mode of the DLSGD system reached 11.05% in 5.7 days. These findings underscore the superior efficiency of greenhouse drying, particularly in forced convection mode, for rapidly lowering the moisture content of Cucumis sativus. The selection of drip-lock glazing material played a crucial role in optimizing the drying process, enhancing the overall efficiency of the system. Forced convection in the DLSGD system accelerated moisture reduction due to improved heat transfer facilitated by enhanced air circulation. This faster drying process not only preserves higher nutritional content by reducing the product’s exposure to heat and air but also extends shelf life by minimizing moisture levels more effectively, thereby preventing microbial growth and spoilage^35,36. Figure 4 provides a graphical representation of the gradual decrease in moisture content over time across various dehydration techniques, including OSD and DLSGD under both natural and forced convection modes.

Figure 4: Moisture content of the Cucumis sativus in DLSGD and OSD with drying hours Click here to view Figure

The choice of glazing material significantly affects both the drying rate and the dryer inside air temperature. Larger heat transfer rates result in faster drying. Figure 5 provides a visual comparison of drying rate variations over several days for DLSGD in both natural and forced convection modes, as well as for OSD. Experimental findings reveal the following average drying rates: 0.0221 kg/hr for OSD, 0.0379 kg/hr for DLSGD under forced convection, and 0.0303 kg/hr for DLSGD under natural convection. Among these, the DLSGD system operating in forced convection mode exhibits the highest drying rate. This can be attributed to the enhanced air movement generated by the fan, which improves heat transfer efficiency, and the glazing material, which effectively increases the internal temperature of the greenhouse dryer. During the initial hours of the first day, the drying rate is notably higher across all methods due to the rapid removal of surface moisture from the sample. However, as drying progresses, the rate steadily decreases, aligning with observations in prior research studies³⁷.

Figure 5: Drying rate of the Cucumis sativus in DLSGD and OSD with drying hours Click here to view Figure

Figure 6 illustrates the temporal variation of moisture content in Cucumis sativus samples based on observed results. A final moisture level of roughly 0.12 was attained after 4.5 days using the DLSGD setup with forced airflow, 5.7 days with natural airflow, and 8 days using the OSD approach. These variations highlight the differing effectiveness of the drying techniques in achieving target moisture levels within specified timeframes. In the early stages, surface moisture is quickly eliminated, driven predominantly by evaporation. As drying advances, the moisture removal rate declines, shifting to the internal movement of moisture toward the surface, supported by thermal energy. This leads to a consistent decline in moisture levels throughout the drying period. Of all methods, the OSD process shows the slowest rate of moisture loss, while greenhouse drying methods, particularly those employing forced airflow, demonstrate superior drying effictiveness.

Figure 6: Moisture ratio of the Cucumis sativus in DLSGD and OSD with drying hours Click here to view Figure

Mathematical model analysis

A regression analysis has been conducted on twelve different models, as detailed in Table 2, to identify the most suitable model for describing the thin-layer drying behavior of Cucumis sativus. The evaluation criteria focused on selecting the model with the maximum R² value and the minimum RMSE and χ² values. All models showed a strong correlation with the empirical observations. The findings indicated that the Two-term model provided the best representation of Cucumis sativus drying under OSD, with parameters R² = 0.982679, RMSE = 0.033165, and χ² = 0.001619, as outlined in Table 5. For DLSGD, the Midilli and Kucuk model emerged as the most accurate under both natural and forced convection conditions, achieving R² = 0.997452, RMSE = 0.014567, and χ² = 0.000263 for natural convection (Table 3), and R² = 0.997685, RMSE = 0.013751, and χ² = 0.000226 for forced convection (Table 4). To further validate this model, the error analysis of predicted versus actual moisture ratios over drying hours in the DLSGD forced convection was performed. Most error values were near zero, confirming the high accuracy of predictions. Changes in air temperature and initial moisture content of the sample were identified as key factors influencing the observed deviations in moisture ratio during the drying operation. The mathematical equations that best describe the drying behaviour of Cucumis sativus slices in the DLSGD system under natural convection, forced convection, and OSD are presented as Equations (8), (9), and (10), respectively. These equations represent the optimal models derived from regression analysis, reflecting the drying kinetics for each drying method.

Table 3: Results of mathematical models of drying behaviour of the Cucumis sativus in DLSGD during natural mode

Table 4: Results of mathematical models of drying behaviour of the Cucumis sativus in DLSGD during forced mode.

Table 5: Results of mathematical models of drying behaviour of the Cucumis sativus in OSD

Nutritional analysis

A comprehensive assessment of the nutritional composition was performed to examine the nutritional attributes of Cucumis sativus subjected to drying under different settings, including OSD and DLSGD with both natural and forced airflow. The key nutritional elements evaluated were carbohydrates, vitamin C, calcium, and other essential nutrients³⁸. Each measurement was repeated three times (n = 3) to ensure consistency and reproducibility of the results. The mean values of each parameter are presented in Figure 7. Cucumis sativus dried through the DLSGD with forced airflow showed an increased carbohydrate concentration compared to those dried utilizing alternative coating techniques. On the other hand, the protein levels were marginally lower in the forced convection setting than in the natural convection setting, due to the elevated temperatures within the DLSGD affecting protein stability. Vegetables typically contain a considerable amount of calcium, and its preservation was more significant under the DLSGD with forced airflow compared to natural convection and OSD, with calcium playing a role in the firmness of the vegetable tissue. In contrast, iron preservation was superior in the natural convection mode compared to the forced convection mode. Nevertheless, the iron concentration in DLSGD under forced airflow surpassed that in OSD. The reduction in iron levels is attributed to heat and atmospheric exposure. Vitamin C, being sensitive to heat, is better preserved at lower drying temperatures and smaller durations. The retention of vitamin C was superior in DLSGD with forced convection relative to OSD. The mineral content, indicated by ash levels, was higher in DLSGD with natural convection than in other drying techniques. Nutrient variations after drying with OSD and DLSGD under different modes are visually represented in Figure 7.

Figure 7: Variation of nutritional content under OSD and DLSGD scenarios Click here to view Figure

Discussion

The experimental results from this study indicate that the Drip Lock Sheet Greenhouse Dryer (DLSGD) with forced convection offers significant advantages over traditional Open Sun Drying (OSD) and DLSGD with natural convection for drying Cucumis sativus. The forced convection mode demonstrated the shortest drying duration, achieving the target moisture level of 11.5% within 4.5 days, compared to 5.7 days for natural convection and 8 days for OSD. The accelerated drying process observed in forced convection mode can be attributed to the enhanced heat transfer facilitated by the increased airflow. This aligns with previous research indicating that forced convection significantly reduces drying times by improving moisture removal efficiency. From a drying kinetics perspective, the Midilli and Kucuk model emerged as the best fit for DLSGD, while the Two-Term model was most appropriate for OSD. The high R² values and low RMSE and χ² values confirmed the accuracy of these models in predicting the moisture removal process^15,16. These findings reinforce the importance of selecting the appropriate mathematical model to describe drying behaviors accurately, as previously suggested by studies on greenhouse drying applications for other agricultural products. The superior fit of the Midilli and Kucuk model for DLSGD suggests that incorporating additional parameters such as moisture diffusivity and non-linear drying behavior improves the model’s reliability for greenhouse drying conditions.

Nutritional analysis further demonstrated that drying method selection plays a crucial role in nutrient retention. DLSGD with forced convection preserved higher carbohydrate and calcium levels compared to OSD and DLSGD with natural airflow. However, vitamin C retention was superior in natural convection mode, likely due to the lower drying temperature, which minimizes heat-induced degradation³⁹. This trade-off between drying efficiency and nutrient preservation is a critical consideration for optimizing food drying processes. The findings align with prior studies that highlight the impact of drying temperature and duration on nutrient degradation, reinforcing the need for balance between efficiency and product quality. The choice of glazing material also played a significant role in drying efficiency. The drip lock glazing sheet effectively absorbed and retained heat, creating an optimal environment for moisture removal while preventing contamination from external factors. This design feature contributed to the superior performance of the DLSGD system compared to OSD, where exposure to environmental contaminants and fluctuations in solar radiation can lead to inconsistent drying rates and potential microbial growth.

Despite these advantages, certain limitations of the DLSGD system should be acknowledged. The reliance on solar irradiation means that drying efficiency may decrease during rainy or winter months, necessitating the integration of thermal energy storage or hybrid energy solutions for continuous operation.

Conclusion

This study introduced a DLSGD system to enhance the efficiency of food dehydration. Experiments were conducted to dry Cucumis sativus using both OSD and DLSGD under natural and forced convection. The findings led to several key conclusions. Firstly, the safest moisture content of under 11.5% was achieved in 4.5 days using DLSGD with forced airflow, compared to 5.7 days with natural convection and 8 days with OSD, demonstrating significant time savings. The drying rates were 0.0221 kg/hr for OSD, 0.0379 kg/hr for DLSGD with forced convection, and 0.0303 kg/hr for DLSGD with natural convection, with the forced convection method achieving the highest drying rate. From a mathematical modeling perspective, the Two-Term model best described the drying behavior in OSD, whereas the Midilli and Kucuk model was optimal for DLSGD under both convection modes, based on the highest R² and lowest RMSE and χ² values. Nutritional analysis indicated that carbohydrate retention was highest in DLSGD with forced convection, Vitamin C retention was superior in natural convection, and calcium retention was better in forced convection. Overall, DLSGD with forced convection emerged as the most effective drying method, ensuring faster drying, higher moisture removal rates, and improved carbohydrate retention. Additionally, the use of DLSGD provided a hygienic advantage, as the dried Cucumis sativus remained free from dust and contamination, enhancing the overall quality of the dehydrated product. The methods proposed here could be beneficial for professionals in food processing and agriculture, as they help in enhancing product quality, reducing drying hours, and lowering energy usage, thus promoting added sustainable food drying approach. A limitation of the proposed system is its reduced operational efficiency on rainy or winter times owing to insufficient solar irradiation for the moisture removal operation. Future research should explore the integration of energy storage solutions, such as thermal or phase change materials, to enhance the efficiency and sustainability of the drying process. These innovations could help maintain consistent drying conditions, reduce energy consumption, and improve overall performance. In future studies, detailed statistical analyses such as two-way or factorial ANOVA can be employed to better understand the interaction effects between drying and nutrient retention. This will allow for more precise identification of critical factors influencing drying performance and nutritional outcomes, ultimately aiding in developing optimized, data-driven drying protocols tailored for specific crops. Additionally, an economic evaluation is recommended to assess the cost-effectiveness of the DLSGD system in comparison to conventional drying methods. This analysis would provide valuable insights into operational expenses, energy savings, and the potential for large-scale implementation, ensuring both technical and financial viability.

Nomenclature:

χ²                     Chi-square

R²                    Coefficient of determination

DLSGD           Drip Lock Sheet Greenhouse Dryer

𝑚                      Mass of the sample (kg)

M_R                       Moisture ratio

OSD                Open Sun Drying

RMSE             Root Mean Square Error

Y_U                        Uncertainty

Acknowledgement

The author expresses sincere gratitude to the management of Sri Krishna College of Engineering and Technology, Coimbatore, for their continuous support and encouragement throughout this work.

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The author(s) do not have any conflict of interest.

Data Availability Statement

The manuscript incorporates all datasets produced or examined throughout this research study.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Permission to Reproduce Material from Other Sources

Not Applicable

Clinical Trial Registration

This research does not involve any clinical trials.

Author Contributions

• Madhankumar Seenivasan: Conceptualization, Methodology, Writing – Original Draft
• Velusamy Kolandasamy: Visualization, Supervision, Project Administration
• Senthilkumar Kandhampalayam Muthukrishnan: Analysis, Methodology
• Selvan Thottiapalayam Arumugam: Conceptualization, Methodology
• Viswanathan Arumuthu: Data Collection, Analysis, Writing – Review & Editing
• Rajesh Suresh: Conceptualization, Methodology, Resources, Writing – Original Draft

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