Greenhouse Model Research Articles

The Influence of Mountain Height and Distance on Shape Factor of Wind Load of Plastic Tunnel

Due to their soft structure and covering material, plastic greenhouses are vulnerable to wind disasters, causing large-scale damage and huge economic losses. The wind load of greenhouses depends on the surface wind pressure distribution, which is different for greenhouses located in valleys from those in plain areas. To study the wind pressure distribution law for various regions of greenhouses built in valleys, mountain and greenhouse models have been built by Computational Fluid Dynamics, in which the length direction of the greenhouse is perpendicular to the valley and the wind direction is parallel to the valley. In the analysis, the verified turbulence model and grid division method are both introduced, and the effect of the height and distance of mountains is considered. According to the distribution law of wind pressure, the greenhouse’s surface is partitioned, and the variation law of the shape factor of wind load on a plastic tunnel is analyzed. Then, the calculation model for the shape factor of the wind load on the greenhouse located in a valley is proposed. The conclusions show that: (a) When the wind inflow direction angle is parallel to the valley, the distribution pattern of wind pressure on the surface of the greenhouse is similar to that on the plain regardless of the distance and height of the mountains, while the values of the wind pressure are greatly affected by the mountain height and distance. The distance between mountains has greater influence than the effect of mountain height. (b) The shape factor of wind load on the suction area of the greenhouse decreases as the distance of mountains increases, while the shape factor on the pressure area of the greenhouse increases with the increase in the distance. It can be seen that the valley effect is non-negligible. The narrower and deeper the valley, the greater the wind pressure effect. (c) When the ratio of the distance between the foot of the mountain and the greenhouse d to the height of the mountain H is less than 5, i.e., d/H < 5, the ratio of the distance to the height has a significant impact on the shape factor of wind load on the greenhouse. When d/H is close to 10, the shape factor of the wind load in the valley area is close to that in the plain area, and the effect of the ratio between the height and the distance is negligible. (d) The proposed calculation model can be used to calculate the effect of mountain height and distance on the shape factor of wind load. The research results can be used in the wind resistance design of plastic greenhouses in valley areas, and can also provide some data support for the revision of the greenhouse structural load code.

The Greenhouse Model of Nursing Home Care: A Scoping Review.

The study aimed to comprehensively review and assess evidence-based outcomes of the Greenhouse model. We systematically reviewed, assessed, and reported on relevant literature using the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines for the scoping review. We identified qualitative or quantitative studies that met our inclusion criteria from PubMed, Medline, CINAHL, and EBSCOhost. The review yielded 41,515 articles published between January 2015 and December 2022; eleven articles met the inclusion criteria and were included in the analysis. The emerging themes were organizational culture, clinical outcomes, and business effects. The Greenhouse model offers a favorable organizational culture with opportunities to enhance clinical and business outcomes. The scoping review was registered in Prospero: CRD42023389048.

Electrocatalytic CO2 Reduction to Ethylene: From Advanced Catalyst Design to Industrial Applications.

The value-added chemicals, monoxide, methane, ethylene, ethanol, ethane, and so on, can be efficiently generated through the electrochemical CO2 reduction reaction (eCO2 RR) when equipped with suitable catalysts. Among them, ethylene is particularly important as a chemical feedstock for petrochemical manufacture. However, despite its high Faradaic efficiency achievable at relatively low current densities, the substantial enhancement of ethylene selectivity and stability at industrial current densities poses a formidable challenge. To facilitate the industrial implementation of eCO2 RR for ethylene production, it is imperative to identify key strategies and potential solutions through comprehending the recent advancements, remaining challenges, and future directions. Herein, the latest and innovative catalyst design strategies of eCO2 RR to ethylene are summarized and discussed, starting with the properties of catalysts such as morphology, crystalline, oxidation state, defect, composition, and surface engineering. The review subsequently outlines the related important state-of-the-art technologies that are essential in driving forward eCO2 RR to ethylene into practical applications, such as CO2 capture, product separation, and downstream reactions. Finally, a greenhouse model that integrates CO2 capture, conversion, storage, and utilization is proposed to present an ideal perspective direction of eCO2 RR to ethylene.

Green House and Ḥalāl Budget Allocation for Sustainable Household Finance Realization

This research aims first to describe household budget allocation and the realization of sustainable financial management in the household, both formulations of the greenhouse model and ḥalāl allocation budget in realizing sustainable finance for households in Indonesia. The research method used is a library study approach with secondary data sources. Data was obtained from BPS, OJK and observations in villages where the community allocated a budget for greenhouses and environmental health. The collected data was analyzed using Ibn Khaldūn's thoughts on Trade and Social Change. The results of this research are as follows: first, budget allocation considers the sources of income they have; households tabulate their needs and make a percentage budget allocation. In this budget allocation, not everything is used for consumption but also for savings and righteous charity activities. The realization of sustainable financial management is carried out using the greenhouse model and ḥalāl budget allocation. Greenhouses are realized by the community participating in waste banks, Sustainable Food House Areas or Climate Resilient Integrated Service Post (Postaklim). Through this, community economic empowerment occurs. Second, the greenhouse model collaborates with the ḥalāl budget allocation model so that there is no waste in household expenditure because sustainable finances in the household do not only talk about current financial existence but also financial existence in the future.

A hierarchical optimization strategy in the intelligent ecological control of the greenhouse downy mildew

In a low-cost greenhouse, where there are few actuators to regulate the climate, increasing yield and preventing crop diseases are contradictory processes because pathogens and hosts stay in a similar ecological niche. Under given weather conditions, the environmental range for crop growth and disease control must be carefully balanced. The aim of this paper is to develop an accurate optimal control algorithm for disease ecological control and explore its contribution in the application of intelligent downy mildew prevention in a low-cost solar greenhouse. The proposed hierarchical optimization control strategy is compared with four common management methods in order to evaluate its impact on crop growth and disease prevention. The results show that the hierarchical optimization control strategy reaches the best balance between disease prevention, accumulated temperature promotion, and low temperature stress risk reduction without using an additional heating system. Moreover, an event-based PID controller is applied to the system considering the energy conservation aspect, which decreases the vents movements areas by 16%, while the control error is only increased by 1.9%. On the whole, this paper provides a solution for low-cost greenhouses about the joint use of greenhouse modelling, disease early warning and environment control, looking for promoting the green production in greenhouse environments by considerably reducing the disease occurrence and use of pesticides.

The energy efficiency of a solar greenhouse for biomass drying

Solar energy is a renewable, inexhaustible and clean source, it is becoming the main target of several applications, both domestic or industrial, cutting costs on electrical and thermal demands when compared with conventional sources. In the case of solar chamber, which makes use of incident solar radiation, it creates a favorable microclimate for drying inputs for reducing humidity to prevent the spread of biodegradable agents, on agricultural, forestry, and other products. With the objective to verify the energy efficiency of a prototype of the Greenhouse model, a solar chamber was built, where energy data and environmental variables were daily monitored in the drying process. For the determination of energy efficiency the ratio between converted energy into heat by the received energy was used. It was found that the chamber presented a daily energy gain of 220141,7 kJ, a daily thermal efficiency of 13,96% and up to 3 pm in 24,19%. The percentage difference in this efficiency is attributed to the chamber structure, which transmits and absorbs a higher percentage of solar energy during the day, but at night due to its transmissibility, emissivity properties, in addition to small structural failures that favor greater energy losses.

Heat Recovery Potential in a Semi-Closed Greenhouse for Tomato Cultivation

This study first presents the development and the experimental validation of a numerical model of a semi-closed greenhouse using a dynamic thermal simulation. The second objective was to identify the influential parameters on the indoor climate and to calculate the heating demand of the greenhouse. The model reproduced the behavior of a full-scale experimental greenhouse in Carquefou (France). The comparison with experimental measurements recorded over an entire season of tomato cultivation validated the numerical model. The result of the simulated energy consumption was 310 kWh/m2/year with a relative error of 3.5%. The parametric study identified that the evapotranspiration power and ventilation rate were the most influential input variables, accounting for 50% and 32%, respectively, of the heating demand. The most sensitive output variable was indoor humidity. The presence of a thermal buffer zone all around the greenhouse reduced the energy consumption by 48%, and thermal/shading screens reduced it by 30%. The final objective was to assess the amount of heat recovery potential over the year and each week, depending on the energy storage strategy. Around 43 kWh/m2/year can be recovered over the year, leading to a potential energy savings of 24%.

CFD Model Verification and Aerodynamic Analysis in Large-Scaled Venlo Greenhouse for Tomato Cultivation

To address the challenges of climate change and food security, the establishment of smart farm complexes is necessary. While there have been numerous studies on the productivity and environmental control of individual greenhouses, research on greenhouse complexes is considerably limited. Conducting environmental studies during the design phase of these complexes poses financial constraints and practical limitations in terms of on-site experiments. To identify potential issues that may arise when developing large-scale greenhouse complexes, it is possible to utilize modeling techniques using computational fluid dynamics (CFD) to assess environmental concerns and location issues before constructing the facilities. Consequently, simulating large-scale CFD models that incorporate multiple greenhouses and atmospheric conditions simultaneously presents significant numerical challenges. The objective of this study was to design and verify the 3D CFD model for a large-scale Venlo greenhouse, where acquiring field data before construction is not feasible for designing a greenhouse complex. The verification of the CFD models was conducted using the improved grid independence test (GIT) and wall Y+ approaches. The findings revealed that a grid resolution of 0.8 m and a first-layer height of 0.04 m were suitable for developing large-scale greenhouse models, resulting in a low Root Mean Square Error (RMSE) of 3.9% and a high coefficient of determination (R2) of 0.968. This process led to a significant reduction of 38% in the number of grid cells. Subsequently, the aerodynamic characteristics and regional ventilation efficiency were analyzed in a 3D greenhouse model for developing a new large-scale greenhouse complex.

The Need to Reframe Nursing Homes as Community Hubs

This JAMA Forum discusses reforms to traditional nursing homes, including the Green House model, community-focused nursing homes, and integrating nursing home services and facilities into the community.

An overview of innovative living arrangements within long-term care and their characteristics: a scoping review

BackgroundWithin long-term care, a culture change (e.g. focus on increasing autonomy in everyday life) is leading to the development of innovative living arrangements for older adults. Insight into characteristics of innovative living arrangements, which are described as an alternative to regular nursing homes, is lacking. This review aims to provide an overview of innovative living arrangements and to describe their defining characteristics.MethodsA scoping review was performed following the framework of Arksey and O’Malley. The preferred reporting items for systematic reviews and meta-analyses with extension, for scoping reviews (PRISMA-ScR) was also followed. The databases PubMed, PsycInfo, CINAHL, and Web of Science were searched. Articles, published between 2012 and 2023 were included when they presented an innovative living arrangement as an alternative to regular nursing homes. A thematic analysis was performed, describing the physical, social, and organizational environment of the innovative living arrangements.ResultsFifty-six articles were identified describing seven types of distinct innovative living arrangements: small-scale living, the green house model, shared housing arrangements, green care farms, dementia villages, group homes, intergenerational living, and an ‘other’ category. The themes included supporting autonomy and creating a small-scale and/or homelike environment, which were emphasized in most innovative living arrangements. Other themes, such as involvement of the community, focus on nature, integration of work tasks, and involvement of family members, were emphasized in a subsection of the described living arrangements. Twenty-eight articles reported on the effects of the innovative living environment on residents, family members, or staff members. Most articles (N = 22) studied resident-related outcomes, focusing mainly on quality of life and aspects of daily life.ConclusionMore insight into the mechanisms of the social and organizational environments is needed, which may lead to greater transparency and homogeneity regarding the description of living arrangements. This review shows that more knowledge is needed about the potential key elements of innovative living arrangements, especially related to their social and organizational environment. This may provide a better guide for developers within long-term care.

Thermal Environment Analysis of Selected Polyethene Cladded Single-Span Greenhouse Shapes Models Towards Cooling Needs

Greenhouse energy management is one of the most significant factors of consideration in greenhouse agriculture. Besides implementing energy supply systems to the facility, energy-saving measures must also be taken into consideration. To address the issue of energy demand by greenhouses in a tropical environment, three greenhouse models were developed to simulate their thermal environments utilizing the Transient Systems Simulation Program (TRNSYS 18) as a building energy simulation (BES) platform. The proposed models were used to examine the impact of greenhouse design parameters; roof shape, orientation, covering (polyethene), and ventilation, on their temperature, relative humidity (RH), vapour pressure deficit (VPD), and cooling load. It was found that the most suitable roof design and orientation was the split-gable roof design with the ventilation switched on and 0o (E-W) orientation that had the lowest mean temperature of 24.12 oC and the least cooling demand of 454.59W. While the tunnel greenhouse had the highest cooling load of 21.30 kW. The split-gable greenhouse had. Also, the RH and VPD in the split-gable greenhouse with ventilation were within the acceptable ranges of 50-75% and 0.8 and 1.1 kPa, respectively, for successful greenhouse crop production. The developed models can aid greenhouse farmers in knowing the cost-benefit of a greenhouse before venturing into greenhouse agriculture in the tropical regions.

Energy performance assessment of photovoltaic greenhouses in summer based on coupled optical-electrical-thermal models and plant growth requirements

Photovoltaic (PV) greenhouses are widely used to regulate internal irradiance and air temperature to create optimal climatic conditions for plant growth. Therefore, comprehensive multidomain energy models of PV greenhouses are more likely needed to improve the system performance. However, few studies investigate optical-electrical-thermal characteristics and PV greenhouse evaluation indicators based on crop growth requirements. The aim of this work is to develop coupled optical-electrical-thermal models to assess the energy performance of the PV greenhouse with different PV roof coverage ratios during the summer months. In addition, the models of photosynthetically active radiation (PAR) and net photosynthetic rate (PN) are presented based on the irradiance and temperature of the PV greenhouse to evaluate the dynamic response of crops to interior climate conditions. The models are validated with experiments on the PV greenhouse in Kunming, with a total area of 26.25 m2. The electricity supply and demand systems include PV modules (3.285 kWp), a battery bank (24 kWh), an air–water heat pump (AWHP), and spray combined with fan cooling. Two cooling scenarios are analysed and compared by varying the PV module coverage ratio. Scenario 1 (S.1) is AWHP cooling, and scenario 2 (S.2) is spray combined with fan cooling. The optimum interior temperature and PAR of the PV greenhouse are 22 °C and 300 μmol·m−2·s−1, respectively. The simulations indicate that if the proportion of the PV layout on the greenhouse roof is greater than 20%, the year-round PAR inside the greenhouse will be below the threshold value of 550 μmol·m−2·s−1 at which the strawberry PN is saturated. For every 10% increase in PV roof coverage, the interior air temperature decreases by 0.02–0.56 °C corresponding to a daily cooling load reduction of 0.45–1.02 kWh/d, while the PV generation increases by 1.7–3.19 kWh/d and the maximum electricity consumption of S.1 and S.2 drops by 0.66 kWh/d and 0.52 kWh/d, respectively. Moreover, the high self-consumption-sufficiency balance (SCSB) values show that the PV and battery sizes are 2.22–2.78 kWp (40–50% coverage) and 15.72–15.75 kWh for S.1, and those in S.2 are 1.11–1.67 kWp (10–30% coverage) and 0.66–3.22 kWh. The coefficient of performance (COP) of the system reaches a maximum of 0.45–1.12 at 40% coverage in S.1 and 1.88–3.01 at 10–30% coverage in S.2. When the PV module coverage is 40% in S.1, the levelized costs of electricity (LCOE) and levelized costs of cooling (LCOC) are the lowest at 0.0760USD/kWhel and 0.0693USD/kWhc. Similarly, the lowest LCOE and LCOC of S.2 are 0.0306USD/kWhel and 0.0210USD/kWhc, as the PV module coverage is 30%. The study will be beneficial for applying photovoltaic modules, battery banks, and cooling technologies in the greenhouse, especially considering the dynamic crop response to internal climates and the energy performance assessment.

Greenhouses in space: from intention to implementation

April 12 is Cosmonautics Day, International Day of Human Space Flight. This is a memorable date dedicated to the flight of the first cosmonaut of the planet, Yuri Alekseevich Gagarin, who became a symbol of the earthlings' dream come true. The All-Russian Research Institute of Vegetable Breeding and Seed Production (Federal State Budgetary Scientific Institution Federal Scientific Vegetable Center (FSBSI FSVC)), like a number of other academic institutions, from the beginning of space exploration, got involved in the work to solve the problem of developing food for astronauts and continues research to this day. In the embodiment of the ideas of K.E. Tsiolkovsky and S.P. Korolev on the creation of space greenhouses received a number of significant achievements in the Federal Scientific Vegetable Center, Russian State Agrarian University – Moscow Timiryazev Agricultural Academy, Institute of Biochemical Physics N.M. Emanuel, SSC RF IBMP RAS and others. Varieties of vegetable crops have been created, tested and recommended for weightlessness conditions: radish, Chinese cabbage, dill, lettuce and other rapidly maturing plants. The variety of Chinese Vesnyanka cabbage has successfully passed biotechnical tests on the ground model of the Phytocycle-SD space conveyor greenhouse, during which good production and biochemical parameters were obtained. Russian scientists are conducting research on developing a technology for cultivating various vegetable plants under space flight conditions – in closed ecosystems (synergotrons), which can serve as the basis of life support systems during space flights, at space stations or in space habitats, where some conditions specific for ISS. Studies have been carried out to study tomato plants grown from seeds that have been under space flight conditions for a long time. As a result of the study, a statistically significant increase in the levels of ascorbic acid, polyphenols and carotenoids, the total antioxidant activity of tomato fruits compared to plants grown from control seeds (ground control) was found.

CFD Simulation Study on the Cooling Characteristics of Shading and Natural Ventilation in Greenhouse of a Botanical Garden in Shanghai

Botanical garden greenhouses typically use solar radiation as an important heat source and meanwhile provide light for plants to survive. However, in the summertime, when the solar radiation is too strong, overheating will occur in the greenhouse and natural ventilation assisted with shading is used to cool it down. The modulation strategy of shading is very important not only to indoor temperature but also to the growth of plants. In order to determine the control strategy of the shading area in the design and installation stage, a CFD model of an exhibition greenhouse in Shanghai is established. During summer conditions, under the worst-case scenario of a windless day, the minimum shading area needed under different outdoor comprehensive temperatures is studied, and the correlation curve is fitted to guide the control of the shading to maintain appropriate thermal conditions. The decrease in indoor temperature under different shading areas is also explored when the outdoor comprehensive temperature is 34 °C. The annual carbon emission reduction of the greenhouse is about 500 t CO2, by adopting shading and natural ventilation. This study provides a reference value for shading control and energy saving and emission reduction of a botanical garden greenhouse.

Evaluation of CFD and machine learning methods on predicting greenhouse microclimate parameters with the assessment of seasonality impact on machine learning performance

For cleaner and sustainable greenhouse crops production, it is essential to successfully manage the needs and resources. Thus the prediction of the greenhouse microclimate, especially the temperature and relative humidity is of great interest. The research done in this area is, however, still limited, and a number of machine learning techniques have not yet been sufficiently exploited. The objective of this paper is to evaluate two greenhouse modeling techniques (machine learning (Artificial Neural Networks (ANN), Support Vector Machine (SVM), Bagging trees (BG) and Boosting trees (BT)) and Computational Fluid Dynamics (CFD) methods and assess the impact of the seasonal changes on machine learning performances. The study was carried out in a commercial greenhouse located in Agadir, Morocco, and the experimental data were collected during October and March. Results show that all predictive models are capable of predicting the inside air temperature (Tin) and relative humidity (Rhin) of the greenhouse with a quite good precision (R>0.98, nRMSE<7%). However, the time required by machine learning models was much more less than the one required by CFD model. For this reason, machine learning models were selected for further analysis and assessment of seasonality impact on their performances. The analysis and assessment of seasonality impact on Machine learning models prove their efficiency in predicting Tin and Rhin with a good agreement. A “combined data” model, built from experimental data of the two months, is tested and proved its efficiency in predicting Tin and Rhin of March and October separately and at the same time (R>0.98, nRMSE <9%).

Energy-Saving Control Algorithm of Venlo Greenhouse Skylight and Wet Curtain Fan Based on Reinforcement Learning with Soft Action Mask

Due to the complex coupling of greenhouse environments, a number of challenges have been encountered in the research of automatic control in Venlo greenhouses. Most algorithms are only concerned with accuracy, yet energy-saving control is of great importance for improving economic benefits. Reinforcement learning, as an unsupervised machine learning method with a framework similar to that of feedback control, is a powerful tool for autonomous decision making in complex environments. However, the loss of benefits and increased time cost in the exploration process make it difficult to apply it to practical scenarios. This work proposes an energy-saving control algorithm for Venlo greenhouse skylights and wet curtain fan based on Reinforcement Learning with Soft Action Mask (SAM), which establishes a trainable SAM network with artificial rules to achieve sub-optimal policy initiation, safe exploration, and efficient optimization. Experiments in a simulated Venlo greenhouse model show that the approach, which is a feasible solution encoding human knowledge to improve the reinforcement learning process, can start with a safe, sub-optimal level and effectively and efficiently achieve reductions in the energy consumption, providing a suitable environment for crops and preventing frequent operation of the facility during the control process.

Using Greenhouse Modelling to Identify the Optimal Conditions for Growing Crops in Northeastern Thailand

The most essential components in escort farming are the determination of airflow patterns and the distribution impact of microclimate temperature variables. The objective of this study is to use Computational Fluid Dynamics (CFD) models to ascertain the aerodynamic and thermal dynamics of protected agricultural greenhouses suitable for cultivation in tropical Northeastern crops of Thailand by defining differences in greenhouse layouts, specifically Gable Roof (GR), Curved Roof (CR), Saw tooth roof (SR), and Double roof (DR). The root means square error (RMSE) indicated that the factor determination of CFD modelling using the standard k−ε turbulence model was satisfactory. In addition, they found that, at a significance level of 0.05, the average temperature in the greenhouses was statistically distinct based on the form of the back of the house and the location of the air input and outflow.

Analytic model for calculation of soil temperature and heat balance of bare soil surface in solar greenhouse

This study establishes a soil temperature model of a solar greenhouse, which takes into account the soil water evaporation, solar radiation, thermal radiation and convective heat transfer on the soil surface. The model is utilized to obtain the mathematical function of soil temperature distribution according to solar radiation and air temperature in a solar greenhouse. The model is validated in two greenhouses with and without plants. Based on the model, the heat gain and loss of solar greenhouse soil are calculated. The results show that the heat accumulated by the greenhouse soil is mainly by absorbing solar radiation during the day and the heat lost by the greenhouse soil is mainly by water evaporation during the day and thermal radiation at night. Then, according to the small convective heat transfer between soil and air in the solar greenhouse, the solar-air temperature calculation equation is simplified, so that the simplified model can predict the soil temperature based on solar radiation and outdoor air temperature, which provides an important soil boundary condition for the solar greenhouse thermal model and CFD prediction. Finally, the evaporation coefficient is proposed to characterize the effect of water evaporation intensity on the soil temperature in a solar greenhouse. In this case, the average soil temperature increases by about 2℃ for every 0.1 decrease in evaporation coefficient.

Thermal environment model construction of Chinese solar greenhouse based on temperature–wave interaction theory

Chinese solar greenhouse (CSG) is an important energy-saving building to ensure the winter production of crops, but it still faces the problem of unbalanced supply and demand between actual thermal performance and crop temperature demand. The purpose of this study is to establish the relationship between greenhouse thermal environment simulation and thermal performance design and to put forward specific thermal performance requirements for the main heat storage components (walls) in the greenhouse design stage. Therefore, this study proposed a method to construct the thermal environment fluctuation model of Chinese solar greenhouse based on temperature-wave interaction theory. The method used dimensional analysis method to comprehensively analyze the related physical quantities of greenhouse thermal environment, explored the temperature fluctuation interaction among indoor air, energy storage wall and outdoor air, and constructed the thermal environment fluctuation model of Chinese solar greenhouse. Finally, the thermal environment fluctuation equation of Chinese solar greenhouse was established under the external climatic conditions in Xi'an, Shaanxi Province, and verified by the measured data of the experimental greenhouse. The experimental results show that the mean absolute error (MAE) between the predicted and measured indoor air temperature is 0.66 °C, the root mean square error (RMSE) is 1.04 °C, and the determination coefficient (R2) is 0.9956 (n = 2822). The model and equation accurately described the interaction between greenhouse internal components and the external greenhouse environment. The study put forward specific thermal performance design requirements for the main heat storage components (walls) in greenhouse, and also provided a new research method for the thermal environment model of Chinese solar greenhouse.

How To Identify The Quality Figs?

Fig production is carried out in a very limited number of countries in the world, and accordingly, the number of countries producing dried figs is quite low. In this study, a small scale tunnel type greenhouse model dryer was designed and manufactured. In this study, the process of drying figs with hot air was carried out by using a combination of uninsulated greenhouse and collector system. Sarılop fig variety was chosen as the food to be dried. The experiments were carried out in Aydın in August 2021. Drying parameters were determined for figs. In addition, the figs offered to the market throughout the province were examined, the practices that should be done to prevent drying damage in figs were determined, and the answer to the question of how to understand quality figs was sought. In the preparation of the study, the studies of the provincial directorate of agriculture, TÜİK reports, visual and printed documents were also examined.