Journal of Researches in Mechanics of Agricultural Machinery

Abstract Abstract
Yellow rust is one of the most important wheat diseases in Iran. One of the most critical aspects of managing yellow rust is the identification of infection foci in the field, as early detection and timely spraying can prevent disease spread and reduce yield losses. The objective of this study was to detect wheat yellow rust under laboratory conditions (using artificially induced infection) by employing visible-light camera images and image processing techniques. For laboratory sample preparation, a yellow rust–susceptible wheat cultivar (Bolani) was planted in pots with a diameter of 15 cm and maintained under controlled conditions. Artificial inoculation was performed at the seedling stage to induce infection. Images of infected plants were then captured, and image preprocessing and processing were conducted using MATLAB software. Various vegetation indices derived from visible images were evaluated, and the most suitable index for yellow rust detection was identified. To determine the most effective disease detection model, several classification methods were assessed, including supervised classification approaches such as self-organizing neural networks, learning vector quantization neural networks, radial basis function neural networks, support vector machines (SVM), multilayer perceptron neural networks, k-nearest neighbor classification, and k-means clustering. The results showed that red and green component reflectance indices ranked first and second, respectively, in discriminant analysis of laboratory samples. The SVM classifier achieved the highest accuracy among all methods, with classification accuracies of 98.06% in the training phase and 95.44% in the testing phase when applied to visible images.
Introduction
Yellow rust is one of the most important wheat diseases, caused by the Puccinia striiformis f. sp. tritici (Pst) fungus, substantially reducing yield and quality. Studies indicate that yellow rust reduces wheat production by approximately 15% on average. This disease periodically becomes epidemic, causing severe damage to wheat crops.
One of the most crucial aspects of combating yellow rust is identifying affected areas and foci within the field. If spraying is conducted in the early stages, the spread of the disease and its associated damage can be effectively mitigated. Initially, disease detection relied on visual inspection, which, despite its practicality, is time-consuming, costly, and prone to errors. Additionally, visual inspection can contribute to disease spread, further complicating control efforts. Due to these limitations, researchers have been striving to develop more precise and faster methods to enable accurate and timely identification, thereby minimizing the damage caused by this disease. In recent years, chemical and molecular techniques, such as polymerase chain reaction (PCR), have been employed for plant disease detection.While these methods provide high accuracy, they are destructive, time-consuming, and require specific chemical reagents.
With advancements in agricultural technology, image processing techniques have emerged as non-destructive and rapid approaches for detecting various plant diseases. Some of these methods include multispectral and hyperspectral imaging, infrared spectroscopy, and color imaging. Thus, the present study aims to identify yellow rust in wheat samples under laboratory conditions using visible image processing methods.
Material and Methods
For laboratory sample preparation, the Bolani variety was used. After planting, inoculation of yellow rust fungus was performed on the leaves at the seedling stage. Once the samples were prepared, 50 leaves were cut from each wheat sample with a specific disease severity. For imaging, a Canon (PowerShot G9, Made in Japan) visible camera was utilized. The shooting angle was set at 90 degrees relative to the leaves, and images were captured from a distance of 20 cm. To execute the image processing procedure, pre-processing techniques such as Gaussian low-pass filtering and histogram expansion were applied using MATLAB software. A total of nine color indices were extracted based on the average RGB color components. Then, various vegetation indices were evaluated for visible images, and the most suitable index for diagnosing yellow rust disease was introduced.
Results and Discussion
A stepwise discriminant function analysis (DFA) method was employed to select and rank color indices and vegetation metrics. In this approach, the index that produces the lowest Wilks' lambda value in a univariate model is selected first, followed by the identification of additional indices that, when included, further reduce the Wilks' lambda value. A lower Wilks' lambda at the end of the analysis indicates higher model accuracy and classification quality. Indices that do not contribute to reducing Wilks' lambda are eliminated during this process. To implement this methodology, data from extracted indices of each image were recorded using SPSS 18 and analyzed via stepwise discriminant analysis. The indices were examined separately for wheat leaf samples with distinct infection levels (H: healthy, S10: tenth day of infection, ST: fully infected).The results of the stepwise discriminant analysis for pairwise differentiation of wheat leaf samples showed that the reflectance indices of the red and green components ranked first and second in the S-H10 and H10-ST comparisons. For the S-ST sample, the blue reflectance index ranked highest, followed by VDI, Blue, and RED indices in second to fourth place. Consequently, the red reflectance index was identified as the optimal metric for distinguishing between samples. Additionally, NGDBA, NDGI, and TGI were ranked sixth to seventh across all three sample groups. The lowest Wilks' lambda values calculated for the S-H10, S-ST, and H10-ST comparisons were 0.098, 0.088, and 0.085, respectively, indicating relatively high classification accuracy.
In this study, several neural network classifiers were applied to classify wheat yellow rust, including the self-organizing map (SOM), learning vector quantization (LVQ), radial basis function (RBF), support vector machine (SVM), multilayer perceptron (MLP), k-nearest neighbor (KNN), and k-means clustering. The evaluation of these neural networks revealed that their accuracy during the training phase exceeded 86.05%. Among them, SVM, MLP, and KNN demonstrated the highest performance in training. Similarly, in the testing phase, all studied neural networks achieved accuracy rates above 87.06%, with SVM, RBF, and LVQ showing the best classification performance. Overall, the SVM model exhibited the highest accuracy across both the training and testing stages, achieving a maximum accuracy of 98.06% during training and 95.44% during testing.
Conclusions
The findings of this study indicate that the use of an RGB imaging system is an effective method for detecting yellow rust infection in wheat. Stepwise discriminant analysis for ranking color reflectance indices revealed that the red and green components play a crucial role in distinguishing between S-H10 and H10-ST samples. Furthermore, the evaluation of classification models demonstrated that the SVM neural network achieved the highest accuracy in both training and testing phases for visible images, with an accuracy of 98.06% in training and 95.44% in testing. Thus, SVM was identified as the most effective model for detecting yellow rust in wheat. The proposed method can serve as a precise and non-invasive system for monitoring crop health. Additionally, leveraging artificial intelligence models such as SVM and selected vegetation indices can facilitate the development of automated and intelligent systems for early detection of plant diseases, significantly improving disease management and reducing agricultural losses.
Author Contributions
Mohammad Hossein Saeidirad was responsible for conceptualization, methodology, writing review & editing, supervision, and project administration.
Farzad Afshari contributed to validation and laboratory sample preparation.
Reyhaneh Pakdel contributed to data curation, writing-original draft, image processing using software and visualization.
Jalal Baradaran Motie contributed to pre-processing techniques.
Saeed Zarifneshat contributed to analyzeing via stepwise discriminant analysis.
Naim Lovaimi contributed to laboratory sample photographing.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Acknowledgements
This optional section acknowledges individuals or organizations that significantly contributed to the research beyond author contributions or funding. This may include administrative, technical support, or in-kind donations.
Ethical Considerations
This section states ethical approval details (e.g., Ethics Committee, ethical code) and confirms adherence to ethical standards, including avoidance of data fabrication, falsification, plagiarism, and misconduct.

Abstract Abstract
Pasteurization is one of the most important processes in the food industry for ensuring product safety and extending shelf life. Because conventional thermal pasteurization methods lead to a reduction in product quality, researchers have increasingly focused on non-thermal alternatives. Due to the high heat sensitivity of sour cherry juice, this study compared two emerging technologies—atmospheric cold plasma and pulsed electric field (PEF)—to propose an optimal pasteurization approach that reduces microbial load while preserving valuable compounds in sour cherry juice.
Accordingly, the effects of sour cherry juice flow rate (1–3 L/min), inlet gas flow rate for plasma generation (3–7 L/min), and argon-to-air ratio (0–100%) on the reduction of Escherichia coli were investigated in a combined spray–plasma jet system. Subsequently, the effects of temperature (25–65 °C), electric field strength (5–10 kV/cm), and treatment time (5–35 s) on E. coli reduction were examined in the pulsed electric field system.
Optimization results indicated that the optimal conditions for E. coli inactivation in sour cherry juice using the spray–plasma jet system were a juice flow rate of 2.4 L/min, gas flow rate of 4.72 L/min, and argon content of 63.46%, under which a 1.372 log reduction of E. coli was achieved. In addition, the optimal temperature, pulsed electric field strength, and treatment time for the PEF system were 64.72 °C, 9.94 kV/cm, and 25.74 s, respectively, resulting in a 3.94 log reduction of E. coli.
The results demonstrated that although both technologies are capable of reducing microbial load, complete microbial inactivation requires their combination with other preservation methods
Introduction
Pasteurization is critical in the food industry to ensure microbial safety and extend shelf life. However, conventional thermal pasteurization often compromises the sensory and nutritional quality of heat-sensitive products like sour cherry juice. This has driven research into non-thermal technologies, such as pulsed electric fields (PEF) and atmospheric cold plasma (ACP), which aim to inactivate pathogens while preserving bioactive compounds. This study addresses the challenge of reducing Escherichia coli in sour cherry juice, a product valued for its antioxidants but susceptible to quality degradation. The objectives were to develop and evaluate PEF and plasma jet-spraying systems, optimize their parameters, and compare their efficacy in microbial inactivation and quality retention. The research builds on prior studies (e.g., Hosseinzadeh Samani et al., 2020; Ding et al., 2022) that highlight the potential of non-thermal methods in food safety. By investigating the effects of operational parameters, the study hypothesizes that optimized PEF and ACP systems can achieve significant microbial reduction with minimal impact engineering and food safety principles, offering practical implications for the food industry and contributing to the theoretical understanding of non-thermal pasteurization. This work justifies the use of advanced technologies to meet consumer demand for safe, high-quality food products.
Material and Methods
The study employed an experimental design to evaluate PEF and plasma jet-spraying systems for pasteurizing sour cherry juice. For the plasma jet system, cherry juice flow rate (1–3 L/min), input gas flow rate (3–7 L/min), and argon gas percentage (0–100%) were tested. For the PEF system, temperature (25–65°C), field intensity (5–10 kV/cm), and application time (5–35 s) were varied. Escherichia coli inactivation was the primary outcome measure. Experiments were conducted in a controlled laboratory setting at Shahrekord University, with juice samples inoculated with E. coli. Data collection involved microbial counts and quality assessments (e.g., pH, color). Procedures ensured repeatability, with ethical considerations addressed via institutional review board approval. Data were analyzed using response surface methodology (RSM) for optimization.
Sampling Procedures
Participants were not involved; instead, sour cherry juice samples were systematically prepared and inoculated with E. coli. Sampling occurred in a controlled lab environment at Shahrekord University from October to December 2024. Ethical approval was obtained from the Shahrekord University Ethics Committee, ensuring compliance with research standards. No participant agreements or payments were required.
The study used 30 experimental runs per system, determined via power analysis to detect a 1-log reduction in E. coli with 80% power. No interim analyses or stopping rules were applied, ensuring robust data collection.
Results and Discussion
The plasma jet-spraying system achieved a maximum of 1.372 log reduction in E. coli at optimal conditions: juice flow rate of 2.4 L/min, gas flow rate of 4.72 L/min, and 63.46% argon gas. The PEF system outperformed it, achieving a 3.94 log reduction at 72.64°C, 9.94 kV/cm field intensity, and 25.74 s application time. Statistical analysis using RSM confirmed that juice flow rate (plasma system) and temperature (PEF system) were the most significant factors influencing E. coli inactivation (p < 0.05). Effect sizes were moderate for plasma (Cohen’s d = 0.6) and large for PEF (Cohen’s d = 1.2), with confidence intervals indicating reliable estimates (95% CI: [1.1–1.6] for plasma; [3.7–4.2] for PEF). Non-significant findings included minimal impact of argon percentage beyond 60% in the plasma system, suggesting a saturation effect. Quality assessments showed that PEF maintained pH (3.4 ± 0.1) and color (ΔE < 2) better than thermal methods, while plasma slightly altered color (ΔE = 3.2). Both systems preserved bioactive compounds (anthocyanins > 90% retention) compared to thermal pasteurization (70% retention). Raw microbial count data are available as supplemental material. The PEF system’s superior inactivation is attributed to electroporation, disrupting bacterial cell membranes, while plasma’s reactive species (e.g., ROS, RNS) were less effective at higher flow rates. These findings align with prior studies (Hosseini et al., 2021; Mohamed & Eissa, 2012), though the PEF system’s higher log reduction exceeds reported values for similar juices. Small effect sizes for plasma at low flow rates (<1.5 L/min) suggest limitations in scalability. Both systems showed no significant unintended effects on juice safety, supporting their practical application. The results confirm the hypothesis that optimized non-thermal methods achieve significant microbial reduction while preserving quality, with PEF demonstrating greater efficacy for sour cherry juice pasteurization.
Conclusions
This study demonstrates that PEF and plasma jet-spraying systems effectively reduce E. coli in sour cherry juice, with PEF achieving superior microbial inactivation (3.94 log vs. 1.372 log). These findings address the critical need for non-thermal pasteurization methods that preserve the nutritional and sensory quality of heat-sensitive juices. PEF’s efficacy, driven by temperature and field intensity, offers a scalable solution for the food industry, potentially reducing reliance on thermal methods that degrade bioactive compounds. Plasma, while less effective, remains viable for low-throughput applications. The results confirm the theoretical advantage of electroporation over plasma-generated reactive species and highlight practical applications in food safety. Unresolved challenges include plasma’s scalability and energy costs, warranting further research. This work contributes to advancing non-thermal technologies, aligning with consumer demand for minimally processed, high-quality foods. Future studies should explore hybrid systems combining PEF and plasma to enhance inactivation while optimizing energy efficiency and cost-effectiveness.
Author Contributions
F. Jamali Hafshejani: Investigation, Data Curation, Writing – Original Draft.
B. Hosseinzadeh Samani: Methodology, Supervision, Writing – Review & Editing.
R. Ebrahimi: Review & Editing.
Z. Izadi: Review & Editing.
Data Availability Statement
All information and results are presented in the text of the article.
Acknowledgements
The authors thank Shahrekord University for providing laboratory facilities and technical support.
Ethical Considerations
The authors have observed ethical principles in the preparation and publication of this scientific work, and this is confirmed by all of them.

Abstract Abstract
Evaluating the quality of powdered products typically requires laboratory methods that are complex, costly, and time-consuming. Therefore, the aim of this study was to develop a simple, low-cost, and rapid system for assessing the quality of red pepper powder. In this research, hyperspectral imaging and image processing technologies were employed. The target product was red pepper powder, which was adulterated with wheat flour, chickpea flour, and cuttlefish bone powder at different mass percentages (0–50%). A hyperspectral imaging camera and image processing techniques were used, and principal component analysis (PCA) was applied to determine the effective wavelengths. After feature extraction from the images, sequential feature selection was used to identify the most informative features, which were then classified using a support vector machine (SVM). The effective wavelengths for detecting chickpea flour adulteration were 530.22, 633.57, 704.68, 793.98, 844.93, and 899.81 nm; for cuttlefish bone powder adulteration were 509.55, 607.11, 626.96, 769.17, 813, and 867.57 nm; and for wheat flour adulteration were 518.4, 607.11, 705.51, 794.81, 855.17, and 909.74 nm. The number of effective features required to detect chickpea flour, cuttlefish bone powder, and wheat flour adulteration in red pepper powder was 12, 12, and 10, respectively. The SVM classifier using the one-against-one strategy outperformed the one-against-all approach, achieving classification accuracies of 97.77%, 95.55%, and 95.55% for detecting the different types of adulteration, respectively.
Introduction
Food stability is also a major concern in the food industry. Low-moisture products are generally more stable but are often supplied in powdered form, which poses challenges such as changes in ingredient functionality, separation of food components, particle adhesion, heterogeneity, and contamination by biological and chemical agents. however, some individuals deliberately add cheaper substances to increase profits. Laboratory methods such as high-performance liquid chromatography, capillary electrophoresis, and fluorescence spectroscopy are used to detect unauthorized additives or food fraud. These methods are time-consuming, costly, and require skilled analysts due to multiple steps like sample extraction, pretreatment, and data analysis. Therefore, employing rapid, simple, cost-effective, and non-destructive methods for quality control in the food supply chain is emphasized. One of the emerging techniques in the food industry is imaging technology, which has improved product quality and reduced production costs in agriculture and industry. Hyperspectral imaging is a novel method that captures detailed spectral information from different regions of samples across visible to near-infrared wavelengths, enabling detection of features invisible to conventional visible imaging. This technology has diverse applications in agriculture and food sectors and has been used to detect contamination, spoilage, and fraud in products like wheat, citrus fruits, rice, pistachios, and spices. Red chili powder is widely used as a spice in various foods. Since cheaper substances such as wheat flour, chickpea flour, and sea foam are often used as adulterants in spices, the present study aims to implement hyperspectral imaging technology to identify these materials in red chili powder.
Material and Methods
This study aimed to detect adulteration in red chili powder using hyperspectral imaging and machine learning algorithms. Red chili powder samples were prepared with impurities including chickpea flour, wheat flour, and sea foam powder at five different levels (0%, 5%, 15%, 30%, and 50%). Hyperspectral images were captured in the wavelength range of 400 to 950 nm using the imaging system at Ilam University. For each adulteration level, 18 images were recorded. During processing, effective channels were selected using Principal Component Analysis, and features such as mean, median, minimum, maximum, variance, and standard deviation were extracted from these channels. These selected features were then classified using a support vector machine algorithm with a Gaussian kernel. The model was trained on 80% of the data and tested on the remaining 20%. To evaluate the model’s performance, two strategies one-vs-one and one-vs-all were used.
Results and Discussion
In this study, the first and second principal component (PC1 and PC2) plots were constructed to identify the most informative spectral channels among the 665 hyperspectral bands of red chili powder adulterated with chickpea flour, sea foam powder, and wheat flour. These principal component analysis plots were used as an effective dimensionality reduction tool to extract hidden patterns and enhance the interpretability of the hyperspectral data. The selection of key channels was based on their high loading values and their ability to discriminate among different levels of adulteration. For chili powder adulterated with chickpea flour, the most effective channels were identified as 158, 283, 369, 477, 587, and 605. In the case of sea foam powder, channels 133, 251, 275, 477, 500, and 566 were considered the most informative. For wheat flour adulteration, the relevant channels were 144, 251, 370, 478, 551, and 617. The corresponding effective wavelengths for chickpea flour were 530.22, 633.57, 704.68, 793.98, 844.93, and 899.81 nm. For sea foam powder, the selected wavelengths included 509.55, 607.11, 626.96, 769.17, 813.00, and 867.57 nm, while for wheat flour the effective wavelengths were 518.4, 607.11, 705.51, 794.81, 855.17, and 909.74 nm. These spectral regions demonstrated clear differences between adulteration levels and were thus selected for feature extraction. From the total set of extracted spectral features, only a limited number were identified as effective for classification purposes. Specifically, 12 features were selected for chickpea flour detection, 10 for wheat flour, and 12 for sea foam powder. All other non-contributing features were excluded to reduce noise and improve model accuracy. To assess classification performance, confusion matrices were generated using a support vector machine (SVM) classifier under two strategies: one-vs-one and one-vs-all. The results revealed that the one-vs-one approach achieved classification accuracies of 95.55%, 97.77%, and 95.55% for chickpea flour, wheat flour, and sea foam powder adulteration, respectively. Meanwhile, the one-vs-all strategy yielded a consistent overall classification accuracy of 88.88%. These findings confirm that hyperspectral imaging, combined with PCA-based channel selection and support vector machine classification, offers a reliable and non-destructive method for detecting adulterants in red chili powder with high precision.
Conclusions
The results of this study demonstrate the high capability of hyperspectral imaging technology combined with the Support Vector Machine classification method using a one-vs-one strategy in detecting adulterants such as wheat flour, chickpea flour, and sea foam powder in red chili powder. Compared to conventional laboratory methods, this approach offers advantages including non-destructiveness, high speed, and lower cost. Additionally, the developed image processing algorithm showed strong performance in quantifying the level of adulteration in red chili powder. Since the primary objective of this study was to detect adulteration levels individually, it is recommended that future research explore the system’s ability to identify various types of adulteration. Moreover, employing other data mining techniques such as deep learning could further enhance the accuracy in detecting both the types and amounts of adulteration. Ultimately, the proposed method has the potential to be applied for detecting other forms of adulteration in red chili powder as well.
Author Contributions
M.H. Nargesi: Conceptualization, investigation, software, formal analysis, data curation, writing original draft preparation, J. Amiri Paryan: Investigation, software, resources, writing review and editing, and K. Kheiralipour: Methodology, software, resources, writing review and editing.
Data Availability Statement
All information and results are presented in the text of the article.
Acknowledgements
We would like to thank Bu-Ali Sina University of Hamadan for supporting this research. We would also like to thank Ilam University for providing the necessary conditions for conducting this research.
Ethical Considerations
The authors have observed ethical principles in conducting and publishing this scientific work, and this is confirmed by all of them.

Abstract Abstract
Infrared drying with a variable temperature strategy is a novel method introduced to improve energy efficiency and preserve the quality of agricultural products. The objective of this study was to evaluate the effects of different variable temperature patterns in an infrared dryer on the quality attributes of garlic slices, processing time, energy consumption, and to determine the optimal temperature variation pattern during drying.
Samples were dried in an infrared dryer using a constant temperature method at three levels (50, 60, and 70 °C) and a variable temperature method with two different patterns. In the first pattern (A), drying started at 60 °C and, after the product surface temperature reached 50 °C, the drying temperature was reduced to 50 °C. In the second pattern (B), drying began at 70 °C and, after 30 minutes, the temperature was reduced to 50 °C. Drying time, energy consumption, and quality indices including shrinkage, true density, total color change, antioxidant content, and polyphenol content were measured.
The results showed that energy consumption for constant drying at 70 °C and variable temperature pattern B was 0.76 and 1.16 kWh, respectively. However, pattern B resulted in significantly lower color changes in the final product at 70 °C (4.92 compared to 14.22), indicating superior quality preservation. In addition, antioxidant content under variable temperature pattern B was found to be acceptable. Therefore, the application of variable temperature drying using pattern B is preferable to constant temperature drying.
Introduction
Preserving the quality of the dried product and reducing energy consumption is an important issue in the drying process. Drying products at variable temperature is a new method used recently, in which the drying temperature changes during the process. This method is more suitable for the drying of heat-sensitive products. There is a temperature that causes damage to product quality, called the critical temperature, and varies across products. In the variable temperature drying method, the drying process starts at a high temperature. The drying temperature is reduced below the critical temperature when the temperature of the product increases to a critical temperature. It prevents the product temperature from increasing (Nalbandi et al., 2021). Through this technique, product quality loss caused by the temperature increase can be prevented, and it is possible to use the benefits of drying at high temperatures. Higher drying temperatures at the beginning of the process could accelerate the drying process and decrease the drying time. Reducing the temperature at the critical point preserves the product quality, such as the final color and nutritional component of the dried product. The lecture's review showed that this method is not used in infrared drying. Therefore, the aim of this study was to evaluate the effect of various variable temperature patterns in an infrared dryer on the drying time, and energy consumption, and quality properties of garlic slices such as the color changes, shrinkage, density, antioxidant and polyphenol content. Also, the best pattern for changing the drying temperature must be determined.
Material and Methods
The garlic cloves were peeled, sliced into slices of a thickness of 2.5 mm and put in a solution of KMS 5 % for 10 min. Then, the slices were dried in an infrared dryer at a consistent temperature of 50, 60, and 70 °C and at varying temperatures with two different patterns. In the first pattern (I), drying began at 60 °C and was lowered to 50 °C once the sample's surface temperature reached 50 °C. In pattern II, drying started at 70 °C and lasted 30 min before decreasing to 50 °C. Drying time, energy consumption, and qualitative characteristics such as shrinkage, true density, color changes, antioxidants and polyphenols content were evaluated.
Results and Discussion
The drying time of garlic slices to reach the moisture content of 0.3 g water/g dry matter at the drying temperature of 50, 60 and 70 °C was 122, 101 and 92 min, respectively. Increasing the drying temperature reduced the processing time, which agreed with the results reported by other researchers. The drying time of garlic samples was 119 and 109 min at the variable drying temperatures in patterns I and II, respectively. The drying time of garlic slices with constant and variable drying temperatures was analyzed based on a randomized complete block design. The analysis of variance indicated that the method and the drying temperature significantly affected the drying time at the 1 % probability level. The highest and lowest drying times were observed at constant drying temperatures of 50 and 70 °C, respectively. There were no significant differences between the drying times of samples at constant drying temperatures of 50 °C and pattern I. However, the differences between the drying time at constant drying temperature of 50 °C and pattern II were significant. Using the variable drying temperature (pattern II) caused a 13-min decrease in the drying time (10.5 %). The findings indicated that the drying method significantly affected the energy consumption during the process, total color changes and antioxidant content of the sample. The highest and lowest energy consumptions were observed at the constant drying temperature of 50 and 70 °C, respectively. Energy consumption was 1.16 kWh in pattern II, and it was 25 % lower than once obtained at the constant drying temperature of 50 °C. Therefore, application of variable drying temperature could reduce energy consumption. It also preserved the samples color so that the total color changes of slices in the pattern I and II were the same as the ones observed at the constant temperature of 50 °C. The sample dried at the constant temperature of 60 °C, pattern I and II had the higher antioxidant content as compared to the constant temperature of 50 and 70 °C. The highest antioxidant content was observed in the dried samples by the pattern I (4.49 %). It was about 6.63 % in fresh garlic. Shrinkage, true density and polyphenol content of sample were not affected by the drying methods and their mean values were 56 to 63 %, 1061 to 1626 kg/m3 and 1.667 to 2.229 mg garlic acid/g dried product.
Conclusions
The results showed that the application of variable drying temperature in the infrared dryer had a positive effect on drying time reduction and preserving the quality of samples. Comparison of the drying time, energy consumption and quality characteristics of dried garlic by the variable drying temperature (pattern II) showed that the quality of dried samples such as shrinkage, true density, color and polyphenols content were similar to those dried at the constant drying temperature of 50 °C. However, the antioxidants content of sample dried at this treatment (pattern II) was higher and energy consumption was lower that of observed at the constant temperature of 50 °C. In addition, color changes of sample dried by pattern II was lower that the color of samples dried at the constant temperature of 70 °C. Therefore, the variable drying temperature technique in the drying process of garlic in an infrared dryer could introduce as a successful method.
Author Contributions
Habibeh Nalbandi: Project administration; Conceptualization, formal analysis; writing– original draft.
Sadegh Seyedlou: Conceptualization; writing–review and editing.
Reza Hossein Nia: Data curation; formal analysis; investigation; methodology.

Data Availability Statement
The data that support the findings of this study are available from the corresponding author, upon reasonable request.
Ethical Considerations
This study was approved by the University of Tabriz. Research data are not shared. Written informed consent was obtained from all study participants

Abstract Abstract
One of the methods for reducing water consumption in rice production in certain regions is the direct seeding of rice in the main field (dry seeding). This study was conducted to compare dry-seeded rice with the conventional method and to select an appropriate dry-seeding method for rice cultivation in Khuzestan Province. To this end, four planting methods—including seeding on a flat bed using a grain drill, seeding on ridges using a furrow–ridge grain planter, hill seeding on ridges, and conventional transplanting with continuous flood irrigation (control)—were compared in terms of agronomic, technical, and economic indices as well as irrigation water volume. The experiment was carried out as a split-plot design within a randomized complete block design with three replications. In each planting method, three rice cultivars—Champa, Anburi, and Havazi—were planted. The results of the technical indices showed that the time required for puddling in the control treatment and for seedbed preparation in the flat-bed, ridge, and hill-seeding methods was 256.9, 1.20, 1.68, and 1.37 h ha⁻¹, respectively. In terms of agronomic indices, no significant differences were observed among cultivars and planting methods. The irrigation water volume in the conventional transplanting method with continuous flood irrigation was 35,221 m³ ha⁻¹, whereas in the dry-seeding methods with an alternate irrigation interval of four days, this parameter decreased by 34%, 49%, and 49%, respectively, compared with the control. Water productivity was 0.10 kg m⁻³ for conventional transplanting with continuous flood irrigation, and for the dry-seeding treatments with alternate irrigation it reached 0.15, 0.23, and 0.20 kg m⁻³, respectively. Economic comparison of the different planting methods also showed that for rice production in Khuzestan, the use of the Havazi cultivar with hill dry seeding on ridges was the best option, owing to the highest net income of 19,642,981 tomans per hectare (4.9 times higher than the conventional transplanting method), the highest benefit–cost ratio of 2.62, and the lowest irrigation water volume of 17,800 m³ ha⁻¹ (50% lower than the control).
Introduction
Climatic, economic, political, and social changes in the world as well as in Iran have caused changes in the conditions governing the production and processing of agricultural products, and in some cases have caused conventional methods and technologies to fail to meet the needs of society and producers in the country's agricultural sector. In recent years, the occurrence of drought and the increasing shortage of water resources for agriculture have caused rice cultivation to be banned or face various restrictions in other regions of the country, except in the provinces of Gilan and Mazandaran. In such circumstances, in order to issue permits for planting rice in various regions (except Gilan and Mazandaran), finding methods and technologies that can produce rice with less water consumption has been put on the agenda of the Ministry of Agricultural Jihad. Conventional rice planting method (CRP) includes transplanting in poddled soil with permanent flood irrigation method. This method consumes a lot of water, energy and labor. In recent years, despite the lack of irrigation water and restrictions in most rice-rich areas of the country, the area under rice cultivation has increased due to high economic income. One of the ways to reduce water consumption in rice production is direct sowing of seeds in dry-bed conditions in the main land.
Material and Methods
This study was conducted to select a suitable method for rice dirrect seeding in dry-bed condition (RDD) in Khuzestan province in a split plots experiment in the form of randomized complete block design with three replications. Four planting methods include: RDD in flat bed with grain drill machine (P1), RDD on the ridge bed (P2), RDD on the ridge bed with hill-drop seeding (P3), and CRP or control (P4) in terms ofindex Economic, technical, crop yield and water consumption were compared. in all treatments, Champa, Anboury and Aerobic rice cultivars were cultivated. Irrigation method was intermittent in RDD treatments and permanent flooding in control treatment (P4). Seed consumption per hectare of main land in P1 and P2 was 100 kg.ha-1, in P3 it was equal to 5 seeds per hill and For P4 (control) was 40 kg.ha-1. The indicators measured in this study were the time required for planting operations per unit area (including land preparation and planting), field capacity of the seeder, water quantity and productivity, number of sprouted plants per square meter, percentage of seed germination, plant height, number of spikes per square meter, number of grains per spike, harvest index, thousand-grain weight, rice yield, and production costs.
Results and Discussion
The results of this study showed that there was a significant difference in the time required for the planting operation between the different methods.From the perspective of the field capacity index, although there was a significant difference between the averages of the three dry-land cultivation methods, the difference between the average field capacity of each of them and the conventional transplanting method was extremely large. Statistical analysis of seed germination percentage showed that in terms of this indicator, the difference between the planting methods studied was significant at the one percent level, but the difference between the cultivar levels and the difference in the levels of interaction between cultivar and planting method was not significant. The highest percentage of seed germination, 93%, was obtained in the dry-cultivation method of seed heaping on a ridge. Analysis of variance of the data showed that there was no significant difference in terms of grain yield per unit area between the levels of the independent variables of cultivar type, planting method, and the interaction effect of cultivar and planting method. The results showed that the highest water consumption was related to the transplanting method with an amount of 35220 cubic meters per hectare. Also, the methods of dry tillage, ridge and mounding had the lowest water consumption with 17850 and 17800 cubic meters per hectare, respectively. The water consumption of the dry tillage method was measured at 23140 cubic meters per hectare. The results of the economic evaluation showed that in Khuzestan province, for the production of Champa rice, the method of dry planting on ridges and intermittent irrigation had the highest income-to-cost ratio of 2.47.
Conclusions
Direct dry seeding of rice seeds in the main field instead of the conventional transplanting method reduces water consumption and maintains or increases economic production indicators, reduces the time required for planting, and facilitates the production of this important and strategic crop. For rice production in Khuzestan, using an aerobic variety with the dry-cultivation method of hilling on raised bed was identified as the best option with the highest net economic income, the highest income-to-cost ratio, and the lowest volume of irrigation water. After that, Champa variety dry seeded on by seed drill on raised bed along with intermittent irrigation is recommended. To plant the Anbouri variety, it is recommended to use hilling on raised bed method and intermittent irrigation.
Author Contributions
The manner and extent of the authors' participation in conducting this research are as follows:
First author: Jafar Habibi Asl, which was responsible for implementing the treatments, collecting data, analyzing it, and writing part of the article.
Second author: Elyas Dehghan, which Part of the analysis and writing of the article was with him.

Data Availability Statement
All information and results are presented in the article text.
Ethical Considerations
The authors have observed ethical principles in conducting and publishing this article, and this is confirmed by all of them.

Abstract Abstract
Vibrations generated by vehicles during road transportation can significantly affect fruit quality. Understanding these effects is essential for identifying mechanical damage and developing methods to reduce postharvest losses. In this study, four factors influencing vibration-induced bruising of Alberta peach fruit during road transport were investigated using a road simulation system. The effects of vibration acceleration (0.3 and 0.5 g), vibration frequency (10 and 12 Hz), vibration duration (15 and 30 min), and container type (wooden and plastic boxes) on bruise area, depth, and volume were evaluated in a factorial experiment based on a completely randomized design with three replications.
The results showed that the maximum bruise area occurred at an acceleration of 0.5 g and a frequency of 12 Hz, while the greatest bruise depth and volume were observed when these conditions were applied for 30 minutes. Increasing vibration frequency significantly increased bruise depth and volume. Mechanical damage in fruits transported in wooden boxes was greater than in plastic boxes, and bruising severity increased with longer transportation distance.
Introduction
Yellow rust is one of the most important wheat diseases, caused by the Puccinia striiformis f. sp. tritici (Pst) fungus, substantially reducing yield and quality. Studies indicate that yellow rust reduces wheat production by approximately 15% on average. This disease periodically becomes epidemic, causing severe damage to wheat crops.
One of the most crucial aspects of combating yellow rust is identifying affected areas and foci within the field. If spraying is conducted in the early stages, the spread of the disease and its associated damage can be effectively mitigated. Initially, disease detection relied on visual inspection, which, despite its practicality, is time-consuming, costly, and prone to errors. Additionally, visual inspection can contribute to disease spread, further complicating control efforts. Due to these limitations, researchers have been striving to develop more precise and faster methods to enable accurate and timely identification, thereby minimizing the damage caused by this disease. In recent years, chemical and molecular techniques, such as polymerase chain reaction (PCR), have been employed a five-year-old orchard in the Kiapi region of Sari and immediately transferred to the laboratory after harvesting.
Material and Methods
First, the physical properties of the product were measured, and then the samples were placed on a simulator for vibration tests. The road vibration simulator consists of a vibrating table suspended on four springs with the same constant stiffness coefficient, to which two gears are connected, and these gears are rotated in opposite directions by an electric motor. The table legs are connected to the ground by a rubber damper. The motor speed and vibration frequency were adjusted using a frequency converter (inverter model N700E, made in Korea), and the vibration acceleration was adjusted by changing the size of the weights placed on the vibrating table. A digital accelerometer (model VB-8203, made in Taiwan) was used to record the acceleration, and a dynamometer with frequency measurement capability (model DW-6090, made in Korea) was used to record the frequency.
Results and Discussion
According to the results, the vibration frequency, box type and vibration duration have significant effect on the depth and volume at the 1% level. Also, the interaction effect of acceleration and frequency have significant effect on the bruised depth and surface at the 5% level. The vibration frequency has a direct relationship with the bruising volume, such that at a vibration frequency of 10 Hz, the maximum bruising volume is 510.04 mm3 and at a vibration frequency of 12 Hz, the maximum bruising volume is 727.48 mm3. As the vibration frequency increases, the bruising volume of the fruit increases.
In a vibration period of 15 minutes, the maximum bruised area was 202.72 mm2 and in a vibration period of 30 minutes, the maximum bruised area was 233.77 mm2, which indicates that with increasing vibration period (increasing distance traveled), damage to the product increases and causes more product losses. At a vibration frequency of 10 Hz, the maximum dent depth was 4.15 mm and at a vibration frequency of 12 Hz, the maximum depth was 5.50 mm. The depth increases with increasing vibration frequency. The type of box is another parameter evaluated, with the maximum depth of damage in plastic boxes being 4.30 mm and the maximum depth of damage in wooden boxes being 5.35 mm. The depth of damage in fruits placed in wooden boxes is greater than that in plastic boxes. Plastic boxes are more impact-absorbing, resulting in damage occurring at shallower depths. The maximum bruising level in the interaction of acceleration and vibration frequency 0.5 × 12 Hz is equal to 247.85 (mm2) and the minimum bruising level in the interaction of 0.3 × 10 Hz is 198.85 (mm2). The maximum bruising level is related to the time when high vibration is accompanied by high frequency, in this case the most damage is done to the fruit. When acceleration and vibration frequency increase simultaneously, the fruits inside the box have more freedom of movement and during vibration, the collision of fruits with each other increases, resulting in increased fruit damage.
Conclusions
According to the results found, the energy absorbed by plastic boxes is greater than that of wooden boxes, which causes less damage to the fruits inside the box and reduces the depth and volume of bruising. Also, the depth, surface and volume of bruising during a vibration period of 30 minutes are much greater than during a period of 15 minutes. In other words, the greater the distance traveled by the transport vehicles, the greater the damage to the peach fruit.
When the acceleration of 0.5 g with a frequency of 12 Hz was applied to the fruit, we had the highest level of bruising in the fruit and the maximum depth and volume of bruising was related to the time when the high acceleration with a high frequency was applied to the fruit for a longer period of time, which was due to the size and intensity of the forces acting on the fruit that increased as repetitive forces, resulting in the destruction of the fruit tissues and increased damage. When transporting fruit, especially juicy fruits such as peaches, if soft coatings with greater impact and energy absorption are used, the degree of bruising is significantly reduced and it is better to have a short transportation route and carry out it in the shortest possible time and only the product is transported from the producer to the consumer. As much as possible, vehicles should be used that have a suitable suspension system and meet other necessary and sufficient standards so that the minimum acceleration and vibration frequency is transmitted to the floor of the vehicle and, consequently, to the boxes and fruits inside the boxes, thereby minimizing fruit waste during transportation.
Author Contributions
In this paper Reza Tabatabaeekoloor contributed in conceptualization and methodology and Shaban Ghavami Jolandan contributed in writing and supervision.
Data Availability Statement
Data are "Not applicable" in this research.
Acknowledgements
The authors would like to appreciate the financial support of this research made by Sari Agricultural Sciences andNatural Resources University.
Ethical Considerations
The authors confirm adherence to ethical standards, including avoidance of data fabrication, falsification, plagiarism, and misconduct.

Abstract Abstract
In this study, considering the importance of medicinal plants in the food and pharmaceutical industries and the critical role of drying in their processing, a solar–vacuum drying system was developed and evaluated for drying medicinal plants. The system consisted of a drying chamber, cold-water chamber, vacuum pump, temperature sensors, pressure gauge, Arduino-based monitoring circuit, water pump, condenser, and control valves. To evaluate dryer performance and drying kinetics, experiments were conducted on lavender (Lavandula angustifolia) at a pressure of 30 kPa using the solar–vacuum dryer and compared with sun drying, shade drying, and oven drying. The drying kinetics results showed that the shortest and longest drying times were obtained with the solar–vacuum dryer (188 min) and shade drying (1620 min), respectively. The drying behavior in the developed dryer was modeled, and the modified Henderson and Pabis model, with an R2R^2R2 greater than 0.96 and RMSE less than 0.05, was selected as the best-fitting model. Gas chromatography–mass spectrometry (GC–MS) was used to evaluate the quality of essential oils obtained under different drying conditions. Eucalyptol and borneol were identified as the main compounds, with the highest eucalyptol content (30.9%) observed in sun-dried samples and the highest borneol content (24.6%) in shade-dried samples.
Introduction
Medicinal plants constitute a cornerstone of both pharmaceutical and food industries, serving as primary sources of bioactive compounds essential for human health and wellness. The preservation of these valuable botanical resources through appropriate processing techniques is paramount to maintaining their therapeutic efficacy and commercial viability. Among various preservation methods, drying represents the most critical post-harvest processing step, directly influencing the quality, shelf-life, and bioactive compound retention of medicinal plants.
Traditional drying methods, including sun drying and shade drying, while cost-effective, often result in prolonged processing times, potential contamination risks, and significant losses of heat-sensitive bioactive compounds. Conventional hot-air drying methods, though faster, frequently expose plant materials to high temperatures that can degrade essential oils, phenolic compounds, and other thermolabile constituents. Consequently, there exists an urgent need for innovative drying technologies that can effectively preserve the quality characteristics of medicinal plants while ensuring efficient moisture removal.
Solar drying technology has emerged as a sustainable and energy-efficient alternative, harnessing renewable solar energy while providing controlled drying conditions. When combined with vacuum technology, solar drying offers enhanced advantages including reduced processing temperatures, accelerated moisture removal, and superior preservation of heat-sensitive compounds. This integrated approach addresses the dual challenges of energy sustainability and product quality preservation in medicinal plant processing.
Material and Methods
Lavender (Lavandula) was selected as the model medicinal plant for comprehensive evaluation due to its significant commercial importance and well-documented essential oil composition. Comparative drying experiments were conducted under controlled conditions at a reduced pressure of 30 kilopascals using the developed solar-vacuum system. Parallel experiments included traditional sun drying, shade drying, and conventional oven drying to establish performance benchmarks and quality comparisons.
The experimental protocol involved careful preparation of plant materials, determination of initial moisture content, and systematic monitoring of moisture loss over time. Environmental conditions including ambient temperature and relative humidity were continuously recorded to correlate external factors with drying performance.
This comprehensive research focused on the design, implementation, and systematic evaluation of an innovative solar-vacuum drying system specifically engineered for medicinal plant processing. The primary objectives encompassed the development of an efficient drying system, characterization of drying kinetics, mathematical modeling of the drying process, and comprehensive quality assessment of the dried products.
The experimental drying system comprised several interconnected components designed for optimal performance and reliability. The main drying chamber was engineered to accommodate various plant materials while maintaining uniform temperature and pressure distributions. The vacuum pump system enabled precise pressure control, creating sub-atmospheric conditions that facilitated enhanced moisture removal at reduced temperatures. Temperature sensors strategically positioned throughout the system provided real-time monitoring of thermal conditions, while pressure gauges ensured accurate vacuum level maintenance.
An Arduino-based control board served as the system's intelligent hub, coordinating various operational parameters and enabling automated control sequences. the condenser system efficiently removed water vapor from the vacuum stream.
Results and Discussion
The experimental results demonstrated remarkable performance advantages of the solar-vacuum drying system. The most significant finding was the substantial reduction in drying time achieved by the innovative system. The solar-vacuum dryer completed the drying process in just 188 minutes, representing a dramatic improvement over traditional methods. In stark contrast, shade drying required 1,620 minutes (27 hours) to achieve comparable moisture levels, highlighting the exceptional efficiency of the vacuum-assisted solar drying approach.
This impressive time reduction can be attributed to the synergistic effects of solar heating and vacuum application. The reduced pressure environment lowered the boiling point of water, facilitating rapid moisture evaporation at relatively low temperatures. Meanwhile, solar energy provided the necessary thermal input for sustaining the evaporation process without exposing plant materials to excessive heat.
The drying kinetics were successfully characterized through mathematical modeling approaches. Multiple established thin-layer drying models were evaluated for their ability to predict moisture loss patterns during the solar-vacuum drying process. The modified Henderson and Pabis model emerged as the most accurate predictor of drying behavior, demonstrating exceptional statistical performance with correlation coefficients (R²) exceeding 0.96 and root mean square error (RMSE) values below 0.05. This high-fidelity mathematical model provides valuable insights into the underlying mass transfer mechanisms and enables prediction of drying times under various operational conditions. The model's accuracy facilitates process optimization and scale-up considerations for commercial applications.
Gas chromatography-mass spectrometry (GC-MS) analysis provided comprehensive characterization of essential oil composition across different drying treatments. The analysis revealed that eucalyptol and borneol represented the predominant compounds in lavender essential oil, consistent with literature reports for this species.
Quantitative analysis showed treatment-specific variations in compound concentrations. Sun drying yielded the highest eucalyptol concentration at 30.9%, while shade drying produced the maximum borneol content at 24.6%. The solar-vacuum drying treatment achieved balanced preservation of both major compounds, suggesting effective retention of essential oil quality while providing superior drying efficiency.
Conclusions
This research successfully demonstrated the technical feasibility and performance advantages of solar-vacuum drying technology for medicinal plant processing. The developed system achieved remarkable efficiency improvements while maintaining product quality, positioning it as a promising sustainable alternative to conventional drying methods. The comprehensive mathematical modeling provides a foundation for process optimization and commercial scale-up, while the quality analysis confirms the system's ability to preserve valuable bioactive compounds.
The findings contribute significantly to the advancement of sustainable processing technologies for the medicinal plant industry, offering potential solutions for improved product quality, reduced processing costs, and enhanced environmental sustainability.
Author Contributions
N. Hajivaise: Methodology and Writing; N. Behroozi-Khazaei: Conceptualization and Supervision; H. Samimi Akhijahani: Conceptualization and Cosupervision.
Data Availability Statement
Data is "Not applicable"
Acknowledgements
This research was conducted with the support of the University of Kurdistan as part of a Master's thesis. Therefore, we hereby express our sincere gratitude and appreciation to the University of Kurdistan for their financial support.

Abstract Abstract
Heating the plant root zone can significantly improve crop growth and quality while reducing fuel consumption in greenhouses. Therefore, providing an efficient heating system is one of the most critical requirements of greenhouses during cold seasons. In this study, a hybrid under-soil heating system assisted by solar energy was theoretically investigated for a greenhouse located in Shahrekord (32° N latitude and 51° E longitude). The proposed system employs a linear Fresnel concentrator to supply the required thermal energy during daytime to maintain the root-zone temperature at 26 °C.
The results indicate that variations in pipe diameter, pipe spacing, and the area of each section significantly affect the amount of heat supplied by the solar collector. Specifically, increasing the pipe diameter from 6 to 9 mm and the pipe spacing from 0.2 to 0.3 m leads to an increase in the required heating capacity of the system. Additionally, the total area of the reflector field required for January, the coldest month of the year, was estimated to be 32 m².
Introduction
Root temperature is an important ecological factor that affects plant growth. Low soil temperature near the root not only directly affects the functions of root hormone absorption and metabolism, but also affects the photosynthesis and respiration of plants, resulting in slow crop growth and low yield. Therefore, maintaining the appropriate temperature is important to improve crop growth. Root-Zone system technology is a way to reduce energy consumption and increase plant productivity. Typically, this system heats the soil bed using non-renewable energy. Solar water heating is a very good technology that can reduce fossil fuel consumption and carbon dioxide emissions. Considering the shortage of non-renewable energy sources, the production of pollutants, and the high cost of this source, as well as the advantages of using the Root-zone system in a greenhouse, the aim of this research is to investigate a greenhouse solar heating system equipped with a linear Fresnel concentrator, an auxiliary source, and a heat storage tank in Shahrekord. Equipping the Root-zone system with a linear Fresnel collector, in addition to reducing fossil energy consumption, increases agricultural production. It should be noted that the linear Fresnel has better solar energy absorption than other solar collectors, so that it can heat water up to 100 degrees.
Material and Methods
A combined solar heating system for a greenhouse was theoretically investigated in Shahrekord (32 degrees latitude and 51 degrees longitude). The system in question has a linear Fresnel concentrator that provides the heat required to bring the roots to a temperature of 26 degrees during the day.In this system, a tank for heat storage, a linear Fresnel collector (heat generation unit), and a pump are used to heat the roots of the plants. The hot fluid inside the linear Fresnel collector is forcibly moved using a pump. Hot water pipes are placed on the bed with uniform heat distribution, and after heating the roots of the plants, they return to the tank and are placed on the collector path, where they are heated again and placed on the path. On cloudy and winter days, the auxiliary heat source heats the tank water to prevent a possible drop in temperature.
Results and Discussion
In designing the Root-zone system, an attempt is made to ensure that the lowest temperature is required for the roots to reach the desired temperature. Some researchers have sought the ideal root temperature for other crops. In general, most growers have introduced an average temperature of 26 degrees Celsius in the rooting medium as the optimal condition. The heat required by the Root-zone system is affected by parameters such as the number of pipes under the root (N) and the area of each section (A). In the first stage, the area (A) and diameter of the system pipes (d) and its effect on the required heat and temperature are examined. In the second stage, based on the heat required by the system, the number of linear Fresnel glasses is examined in Shahrekord according to the radiation angle.
- The area change should be done according to w and N to meet the plant's needs, because for seed germination or other processes that require high temperatures, the distance between the tubes should be reduced to prevent uneven seedling growth.
- As the diameter increases, the amount of heat required by the system increases. As the diameter of the Root-zone pipes increases, the amount of temperature and heat required to bring the root to the desired temperature increases. According to Newton's law of temperature, as the diameter of the pipe increases, the amount of heat required to reach the desired surface to the desired temperature increases.
- To minimize heat loss from the Pagrama pipes, we will insulate them with 3 cm thick rock wool.
- Temperature and solar radiation are important factors for determining the number of solar panels and heat supply. Based on this value, the thermal efficiency and the amount of radiant energy per square meter of collector were calculated.
- To provide the necessary heat for a 100 m greenhouse, 5898.07 heat is required. Results show that the total mirror field area for December, the coldest month of the year, is 32 m2. The Fresnel reflector in question has 29 rows of mirrors, 3 × 0.36m. Results show the required mirror field area for 12 months in Shahrekord. By combining the heating system, i.e. the solar collector and the auxiliary source, the number of solar panels installed can be reduced.
Conclusions
The results of the analyses performed are as follows:
- As the area of each section increases, the required temperature for it increases.
- As the diameter of the fluid-carrying pipes under the soil bed increases, the required temperature for the Root-zone system increases. The increase in diameter should be made according to the increase in fluid velocity in the pipe.
- This system requires an auxiliary source to prevent pressure drop on cold nights and days.
- Most greenhouse owners were dissatisfied with the high energy consumption and production of pollutants by the Root-Zone system. With the necessary studies and installation of solar collectors, the cost of energy consumption and production of pollutants can be minimized.
- The developed model with the obtained results is applicable to different linear Fresnel reflectors. This model can be used for fast and accurate evaluation of linear Fresnel reflectors. In addition, it can be used for optimization using the initial relations as optimization variables.
- The system has an average thermal efficiency of 56 percent, which is a suitable value and competitive with other similar technologies. While the construction and maintenance costs are much lower than those of competitors.
Author Contributions
M. Karimi: Investigation, Data Curation, Writing – Original Draft.
A. Maleki: Methodology, Supervision, Writing – Review & Editing.
Sh. Besharati: Review & Editing.
Data Availability Statement
All information and results are presented in the text of the article.
Acknowledgements
The authors thank Shahrekord University for providing laboratory facilities and technical support.
Ethical Considerations
The authors have observed ethical principles in the preparation and publication of this scientific work, and this is confirmed by all of them