Research Article
Post-harvest technologies
E. Barzanouni; H. Sadrnia; F. Sohbatzadeh; S. Khodavaisy
Abstract
IntroductionPenicillium Digitatum (PD) and Penicillium italicum diseases pose significant economic challenges to citrus fruit production across the globe. The primary aim of this research is to investigate the synergistic effects of low concentrations of H2O2 solution combined with transient spark discharge ...
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IntroductionPenicillium Digitatum (PD) and Penicillium italicum diseases pose significant economic challenges to citrus fruit production across the globe. The primary aim of this research is to investigate the synergistic effects of low concentrations of H2O2 solution combined with transient spark discharge plasma on the inactivation of PD. Additionally, assess the chemical and physical properties. Ultimately, this approach can be presented as an eco-friendly solution for rinsing citrus fruits on an industrial scale.Materials and MethodsThe Penicillium digitatum (PD) isolate (ATCC 24692) was obtained from the Tehran Molecular Mycology Laboratory and cultured on Sabouraud Dextrose Agar medium at pH 5.6 and 27°C for 7 days. The initial concentration of spores in the solution was determined using a UV absorption spectrophotometer, set to 0.1 at a wavelength of 420 nm, and the concentration of spores was approximately equivalent to 106 spores per milliliter (Palou et al., 2002). In this study, the plasma reactor had a point-to-plane geometry. The high-voltage needle electrode was placed above a Petri dish filled with a microbial solution combined with H2O2, while the grounded electrode was immersed in the solution. The distance between the tip of the needle electrode and the surface of the solution was 15 mm. Solutions of 0.05%, 0.1% and 0.5%v/v H2O2 (35% soluble in water) were added to the microbial solution before plasma treatment. The final volume of the solution was 5 ml and exposure times were 2.5, 5, 10, and 15 minutes. The reactor was fed with an air flow of 2 l/min. A transient spark discharge was generated, characterized by a discharge voltage of approximately 18 kV, short durations of less than 100 ns, and high current pulses exceeding 1A, with a repetition frequency ranging from 0.5 to 10 kHz. After treatment, H2O2, NO2‾, and NO3‾ as the main long-lived species in plasma-activated solution are measured. Also, physical factors such as electrical conductivity and pH were measured. Data Analysis performed using SAS 9.4 software. Results and DiscussionWith increasing plasma treatment time and H2O2 concentration, the log reduction increased across all treatments. The combination of 0.1 and 0.5% H2O2 solution with plasma resulted in complete inactivation of P. digitatum within just 15 minutes. In plasma-treated solutions, regarding chemical properties, the concentrations of H2O2, NO2‾, and NO3‾ increased linearly with the treatment time. Furthermore, the electrical conductivity increased linearly, with a notable acceleration in the treated 0.5% H2O2 solution, reaching 373µS cm-1. Additionally, pH value dropped from an initial value of 6.95, using distilled water as a control, to a low of 2.14 for plasma treated with 0.5% H2O2 after 15 min of exposure.ConclusionThe combined treatment was more effective than the isolated use of hydrogen peroxide solution. H2O2 enhances the effectiveness of plsma sterilization without requiring additional power input. Consequently, the synergistic application of atmospheric pressure plasma and H2O2 proved to be a promising method for the inactivation of PD. The findings indicate that reactive oxygen species (ROS) significantly contribute to the inactivation of PD cells, as well as the concentration of H2O2. Finally, the combination of H2O2 solution at 0.1 and 0.5% with cold plasma presents an environmentally friendly method for sanitizing citrus fruits.Acknowledgment This work was supported by the Ferdowsi University of Mashhad [Grant number 48527]. The authors greatly appreciate the technical support from Mazandaran University in Iran, particularly from the Department of Atomic and Molecular Physics.
Research Article
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
L. Behrooznia; M. Khojastehpour; H. Hosseinzadeh-Bandbafha
Abstract
IntroductionPomegranate has gained global popularity due to its high vitamin content and antioxidant properties, attracting fans worldwide. The processing of pomegranate into various products, including pomegranate juice, has become a thriving industry. However, this processing requires significant energy ...
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IntroductionPomegranate has gained global popularity due to its high vitamin content and antioxidant properties, attracting fans worldwide. The processing of pomegranate into various products, including pomegranate juice, has become a thriving industry. However, this processing requires significant energy and chemicals—most of which are derived from fossil fuels. The combustion of these fuels releases harmful gases, contributing to global warming, environmental damage, and health risks. The costs tied to these environmental burdens are often overlooked, neglecting the principles of environmental sustainability. Therefore, it is vital to assess the monetary value of the environmental impacts throughout the entire life cycle of pomegranate juice production. This research aims to investigate the costs imposed on society, including the social costs of carbon emissions, damage costs from air pollution, and costs associated with environmental prevention measures related to processing pomegranate juice. Feel free to ask for further changes or adjustments.Materials and MethodsThis study focuses on assessing the environmental impact and associated costs generated during the processing of pomegranate juice in Mashhad, Iran, from 2022 to 2023. The research examines the case study of Saman Bazar Razavi Co. to conduct an environmental impact cost assessment. The study begins by evaluating the environmental impacts associated with the pomegranate juice production process using a life cycle assessment (LCA) approach. The costs related to these impacts are then estimated by multiplying the impact amounts with predetermined monetary coefficients. The study adopts a system boundary that extends from the arrival of the fruit at the factory to the departure of the packaged juice, defining a 160g pack of pomegranate juice as the functional unit (FU). SimaPro software, version 9, is utilized for analyzing the environmental impacts. The evaluation of environmental impact costs encompasses three categories: social costs of carbon emissions, damage costs from air pollution, and costs for environmental prevention measures. Carbon dioxide emissions are considered to assess social costs, while five other gases—nitrogen oxides, particulate matter, sulfur dioxide, volatile organic compounds, and ammonia vapor—are included in investigating air pollution damage costs. Furthermore, the calculation of environmental prevention costs takes into account seven impact categories: global warming, photochemical oxidation, respiratory inorganic effects, human toxicity, ecotoxicity, eutrophication, and acidification.Results and DiscussionHere’s the edited text with corrections marked: The investigation reveals that the production of pomegranate juice emits approximately 0.12 kg CO2 eq of carbon, with a social cost of $0.0062 per functional unit. The primary contributors to carbon emissions are natural gas and electricity. Furthermore, the evaluation of air-polluting gases indicates a total cost of $0.021 for air pollution damage. Among the five considered gases, ammonia vapor, sulfur dioxide, and nitrogen oxides incur the highest damage costs. The assessment of environmental prevention costs demonstrates a total calculated cost of $0.026, with the impact categories of global warming and acidification making the most substantial contributions of 59% and 28%, respectively. This finding suggests that the majority of costs for preventing damage in pomegranate juice production should be focused on mitigating the effects of global warming. The consumption of natural gas and electricity during the pomegranate juice production process is the main source of carbon dioxide emissions and global warming. Additionally, in terms of acidification, the contributions of pomegranate, electricity, apple, natural gas, and sugar are noteworthy. Based on these findings, it is evident that the resources used in pomegranate juice processing, derived from fossil fuels, have the most significant impact on environmental damage. Therefore, one practical method to prevent the creation of these pollutants is the utilization of alternative bioproducts produced from biomass. Considering the substantial amount of pomegranate waste generated after juice processing,which is often not utilized; these wastes can be effectively employed to produce bioenergy, such as biogas. This approach not only prevents waste disposal but also offers economic and environmental benefits.ConclusionThis article provides an overview of the environmental impacts and associated costs of pomegranate juice production in Mashhad. Using the life cycle assessment approach, the study calculates the environmental impacts per functional unit (a 160g juice pack) and estimates the corresponding costs. The results indicate that the social cost of carbon emissions, the total damage costs of air pollution, and the total environmental prevention costs per functional unit are $0.0062, $0.021, and $0.026, respectively. These costs should be allocated to mitigating the environmental damage caused by pomegranate juice production in the region.AcknowledgmentsThe authors express their gratitude to Ferdowsi University of Mashhad for funding this research (Grant No. 54189).
Research Article
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. Zangeneh; M. Rouhi Farajabad
Abstract
Introduction To successfully provide and distribute agricultural services throughout the supply chain and enhance efficiency in this sector, selecting the right locations for service centers is a crucial and complex challenge. One of the ways to develop rice mechanization infrastructure is to establish ...
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Introduction To successfully provide and distribute agricultural services throughout the supply chain and enhance efficiency in this sector, selecting the right locations for service centers is a crucial and complex challenge. One of the ways to develop rice mechanization infrastructure is to establish rice seedling banks. A rice seedling bank is a specialized facility dedicated to the large-scale industrial production of rice seedlings, utilizing seedling trays to optimiz space, resources, and labor. The primary aim of this research is to identify the most suitable location for establishing a rice seed bank by employing multiple-criteria decision-making (MCDM) methods.Materials and MethodsThe present research was conducted in Fuman County, Guilan Province, Iran. The main objective of identifying a location for the seedling bank in the studied area is to minimize transportation costs for the seedling trays while selecting a site with the greatest potential for successfully establishing the seedling bank. To achieve this, we analyzed the location criteria for the seedling bank at the district level during the early stages of the research. The selection criteria for identifying a suitable district include several factors, such as the number of farmers, land leveling, area under cultivation, the number of agricultural machines, the level of mechanized transplanting and harvesting, and the number of seed banks in each district. Subsequently, the best village in the district, chosen in the prior step, was evaluated using several key criteria: total cultivated area, number of farmers, cultivated area per farmer, and total distance from other villages within the district. Shannon's entropy method was employed to estimate the weight and rank for the location criteria in both stages. The districts were ranked using the Fuzzy VIKOR method, while the TOPSIS method was used to prioritize villages within the selected district.Results and DiscussionAccording to the results of the Fuzzy VIKOR method, among the five studied districts in Fuman County, Lulaman rural district stands out as the best location for establishing a seedling bank. Furthermore, based on the results obtained from the TOPSIS method, Khoshknudhan-e Bala village is identified as the most favorable site for establishing a seedling bank within the Lulaman district, among the fifteen alternatives considered. The VIKOR model excels in ranking alternatives due to its ability to generate ideal positive and negative maps, making it particularly well-suited for location and spatial analysis. By utilizing this model, we can assess not only the locations themselves but also evaluate how each alternative measures up against both positive and negative ideals. In contrast, other models lack this capability, as they merely identify the optimal location without providing a comprehensive understanding of each alternative's standing.ConclusionThe purpose of this research is to provide a suitable algorithm for locating a seedling bank in Fuman County. Given the numerous influencing factors and available options, the integration of the VIKOR MCDM model with fuzzy numbers to identify the most suitable district, followed by the TOPSIS MCDM model to determine the best village, yielded promising results. The findings indicate that several factors play a crucial role in identifying the optimal location for the seedling bank. However, integrating all these elements through traditional methods—such as manual map analysis—proves impractical due to the sheer volume of data involved. Furthermore, neglecting these factors in site selection leads to substantial waste of material resources, energy, and environmental resources. Overall, the results of the Fuzzy VIKOR analysis revealed that Khoshknudhan-e Bala village in the Lulaman district is the best option for establishing a seedling bank in Fuman County.
Research Article
Precision Farming
R. Fathi; M. Ghasemi-Nejad Raeini; S. Abdanan Mehdizadeh; M. Taki; M. Mardani Najafabadi
Abstract
IntroductionInnovative technologies, such as smart sprayers, are pivotal catalysts for modernizing the agricultural sector and play an indispensable role in providing food for human consumption. Without the utilization of these technologies and the implementation of proper input management, it is predicted ...
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IntroductionInnovative technologies, such as smart sprayers, are pivotal catalysts for modernizing the agricultural sector and play an indispensable role in providing food for human consumption. Without the utilization of these technologies and the implementation of proper input management, it is predicted that environmental impacts will worsen in the future. Attaining sustainable production, while implementing programs to ensure food security, presents a considerable challenge for researchers and policymakers worldwide. In this research, the performance of a fixed-rate orchard sprayer was evaluated. Employing various equipment, the sprayer was then upgraded to a variable-rate sprayer, and its performance was reevaluated and compared to the fixed-rate model.Material and MethodsThis research comprehensively evaluated a fixed-rate orchard sprayer and subsequently upgraded it to a variable-rate sprayer for further assessment. The primary components of the developed variable-rate sprayer, consists of an ON-OFF solenoid valve, a digital camera for imaging purposes, an ultrasonic sensor, a flow meter, and a control circuit. The necessary modifications were implemented on a fixed-rate turbine sprayer. The development of the variable-rate sprayer was devided into two distinct phases. The initial phase involved determining the canopy volume and acquiring the necessary information pertaining to the spraying target, specifically the tree. The subsequent phase focused on decision-making and control of the spraying rate, thereby facilitating variable-rate application. Upon laboratory examination of the samples, spectroscopic results were obtained, and the total concentration of the pesticide solution was calculated across different sections of a one-hectare orange orchard. An investigation into the sedimentation of pesticide solution was conducted across different treatments in two spraying modes namely, variable-rate and fixed-rate and at three distinct speeds: low (1.6 km hr-1), medium (3.2 km hr-1), and high (4.8 km hr-1) resulting in six treatments.Results and DiscussionThe comparative analysis of average pesticide deposition on trees revealed a significant difference between the two spraying modes; variable-rate and fixed-rate. All indicators demonstrate that the type of sprayer and the spraying speed significantly influence changes in pesticide deposition across different treatments. However, the interaction effect of the type of sprayer and the speed of spraying did not significantly impact the amount of pesticide deposition on the trees and the total consumption of pesticide per hectare. The results indicated that neither the type of sprayer, nor the speed of spraying, nor their interaction had a significant effect on the spraying quality index. Furthermore, the numerical median diameter and volume median diameter were not significantly different across the treatments.The maximum pesticide consumption savings in the variable-rate spraying mode was 46%, achieved at a speed of 1.6 km hr-1. The maximum efficiency was 70% in the variable-rate spraying mode, occurring at a speed of 3.2 km hr-1. The lowest amount of pesticide deposition on the canopy of trees was observed in the variable-rate spraying method at the speed of 4.8 km hr-1 (1303 L ha-1), and the highest amount of deposition occurred in the fixed-rate spraying at the speed of 1.6 km hr-1 (2121 L ha-1). The highest amount of pesticide release in the air was also calculated in the fixed-rate spraying mode with a speed of km hr-1 (241 L ha-1) and the lowest value was calculated in the variable-rate spraying mode with a speed of 3.2 km hr-1.ConclusionEmerging technologies, such as smart sprayers, play a crucial role in increasing the productivity of the agricultural sector. If these technologies are not utilized, the challenges related to the sustainability of production will increase in the future. One of the critical operations in the production of agricultural products is the spraying phase. In this research, a fixed-rate sprayer was upgraded to a variable-rate sprayer, both sprayers were evaluated, and the results of this evaluation were then used to compare the two spraying systems. The results revealed that because the amount of the pesticide sprayed is controlled in real time by canopy volume detection in the variable-rate sprayer, in the best case (speed 1.6 km hr-1), it reduced pesticide consumption by 46% and reached 70% efficiency. In all the studied treatments, both the type of sprayer and the speed of spraying significantly affected changes in pesticide deposition. However, the interaction between the type of sprayer and the speed of spraying did not have a significant effect on the amount of pesticide deposition on trees or total pesticide consumption per hectare. There was no significant difference in the coverage percentage of the pesticide deposition on the target in different treatments, and the best spraying quality occurred in variable rate spraying with a speed of 4.8 km hr-1.By using a variable-rate sprayer, while saving on the costs of chemical pesticide consumption and spraying, toxic emissions that cause environmental pollution will also be reduced. Future research should focus on developing a variable-rate system based on independent nozzles, allowing for real-time control of each individual nozzle's spraying.
Research Article
Precision Farming
A. Ghaffarnezhad; H. Navid; H. Karimi
Abstract
IntroductionImproving field operations through precise spot planting rates depends on the accurate functioning of seed flow sensors within the working rows. Despite the availability of these sensors in the market, achieving measurement precision remains a challenge in their optimal design. Seed flow ...
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IntroductionImproving field operations through precise spot planting rates depends on the accurate functioning of seed flow sensors within the working rows. Despite the availability of these sensors in the market, achieving measurement precision remains a challenge in their optimal design. Seed flow sensors can be categorized into two primary types: optical and non-optical. Among these, optical sensors—particularly infrared sensors—are gaining popularity among researchers due to their distinct advantages, including simple circuit design, cost-effectiveness, and a strong correlation with seed flow. However, the accuracy of these sensors tends to diminish over time due to dust accumulation from planting operations and the effects of sunlight. In response to these challenges, researchers are actively exploring various solutions, employing diverse approaches such as the development of different algorithms and the utilization of alternative hardware configurations. Each research initiative aims to address specific challenges associated with these sensors, with the overarching goal of facilitating effective commercialization, optimizing resource use, and minimizing waste.Materials and MethodsTwo distinct algorithms, utilizing analog-to-digital converter and interrupt-based methodologies, were meticulously developed and thoroughly evaluated to determine the more effective method for monitoring. Correspondingly, unique circuits were engineered for each algorithm.To enhance the sensitivity of the sensor while simplifying the circuit's complexity and dimensions, the lm324 Op-Amp was used in the interrupt-based sensor circuit. Adjusting sensitivity was made feasible through a multi-turn potentiometer, enabling precise adjustment of the external interrupt within the microcontroller. On the other hand, the analog-to-digital converter-based circuit, without relying on the LM324 chip, provided a more straightforward and quieter configuration.The intricate nature of construction mandated the design of circuits using Altium Designer 17 software, which was then printed onto circuit boards. Both developed circuits featured the deployment of the STM32F103C8T6 microcontroller, renowned for its robust capabilities and cost efficiency.In the interrupt-based algorithm's development, the microcontroller's external interrupt was used, selecting its sensitivity to detect both rising and falling edges. This strategic configuration ensured comprehensive scanning of all receivers by the analog-to-digital converter upon any interruption in the infrared sensors. Given the singular passage of seeds in precision seeding, each pass was counted as a single seed.At the start of the planting operation and upon reaching the end of each planting row, the microcontroller employed a micro-switch to sample the output of the infrared sensor, which were then used to execute further calculations based on those samples. Throughout the planting process, the microcontroller continuously performed sensor scanning and promptly converted the sensor outputs into binary values based on defined thresholds. Then, it counted the seeds based on the predetermined counting thresholds for the number of passes.The efficacy of these developed algorithms and sensors underwent rigorous testing encompassing hybrid corn seeds, popcorn, soybean, and mung bean. The evaluation was conducted on an 11-meter-long conveyor belt platform, tested at three different speeds: 4, 7, and 10 km h-1, through five distinct iterations. This comprehensive evaluation ensured the robustness and reliability of the algorithms across diverse seed types and varying operational conditions.Results and DiscussionTest results indicate that interrupt-based sensors demonstrate impressive seed counting capabilities; however, they may encounter issues such as susceptibility to dust and the need for manual recalibrations. Moreover, these sensors exhibited acceptable performance across various crops, including corn and soybeans. Nonetheless, variations in seed characteristics could affect counting accuracy. Additionally, simultaneous seed passage through the sensor under certain conditions posed challenges, diminishing the sensor's precision. On the other hand, sensors employing analog-to-digital algorithms showed promising performance. They offer enhanced adjustability compared to their interrupt-based counterparts, showcasing adaptability to diverse conditions. In summary, each sensor type has its strengths and weaknesses. Sensors that utilize analog-to-digital converter algorithms may offer superior performance in varied scenarios due to their advanced features and adaptable configurations.ConclusionThis study developed and tested two seed counting algorithms: one based on interruption and the other utilizing an analog-to-digital converter. Both algorithms effectively counted seeds larger in diameter than the distance between adjacent LEDs with remarkable accuracy. However, due to their reliance on infrared optical components, both were susceptible to dust generated during planting operations. The algorithm utilizing the analog-to-digital converter demonstrated a notable advantage. Its ability to adjust the threshold either at the start of planting or at the end of each crop row provided a distinct edge over the interruption-based algorithm. Consequently, the analog-to-digital converter-based algorithm was selected as the superior choice for this research.AcknowledgmentThe authors express appreciation for the financial support provided by the University of Tabriz.
Research Article
Precision Farming
A. Naderi Beni; H. Bagherpour; J. Amiri Parian
Abstract
IntroductionDetection of tree leaf diseases plays a crucial role in the horticultural field. These diseases can originate from viruses, bacteria, fungi, and other pathogens. If proper attention is not given, these diseases can drastically affect trees, reducing both the quality and quantity of yields. ...
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IntroductionDetection of tree leaf diseases plays a crucial role in the horticultural field. These diseases can originate from viruses, bacteria, fungi, and other pathogens. If proper attention is not given, these diseases can drastically affect trees, reducing both the quality and quantity of yields. Due to the importance of quince in Iran's export market, its diseases can cause significant economic losses to the country. Therefore, if leaf diseases can be automatically identified, appropriate actions can be taken in advance to mitigate these losses. Traditionally, the identification and detection of tree diseases rely on experts' naked-eye observations. However, the physical condition of the expert such as eyesight, fatigue, and work pressure can affect their decision-making capability. Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. This approach has significantly enhanced the classification and identification of diseases affecting plants and trees. This study employs a novel CNN algorithm alongside two pre-trained models to effectively identify and classify various types of quince diseases.Materials and MethodsImages of healthy and diseased leaves were acquired from several databases. The majority of these images were sourced from the Agricultural Research Center of Isfahan Province in Iran, supplemented by contributions from researchers who had previously studied in this field. Other supporting datasets were obtained from internet sources. This study incorporated a total of 1,600 images, which included 390 images of fire blight, 384 images of leaf blight, 406 images of powdery mildew, and 420 images of healthy leaves. Of all the images obtained, 70%, 20%, and 10% were randomly selected for the network's training, validation, and testing, respectively. Image flipping, rotation, and zooming were applied to augment the training dataset. In this research, a proposed convolutional neural network (CNN) combined with image processing was developed to classify quince leaf diseases into four distinct classes. Three CNN models, including Inception-ResNet-v2, ResNet-101, and our proposed CNN model, were investigated, and their performances were compared using essential indices including precision, sensitivity, F1-score, and accuracy. To optimize the models’ performance, the impact of dropout with a 50% probability and the number of neurons in the hidden layers were examined. Our proposed CNN model consists of an architecture with four convolutional layers, with 224 × 224 RGB images as input to the first layer, which has 16 filters, followed by additional convolutional layers with 32, 64, and 128 filters respectively. Activation functions of ReLU combined with max-pooling were used at each convolutional layer, and Softmax activation was applied in the last layer of the neural network to convert the output into a probability distribution.Results and DiscussionThree confusion matrices based on the test dataset were constructed for all the CNN models to compare and evaluate the performance of the classifiers. The indices obtained from the confusion matrices indicated that Inception-ResNet-v2 and ResNet-101 achieved accuracies of 79% and 72%, respectively. While all models exhibited promising efficiency in classifying leaf diseases, the proposed shallow CNN model stood out with an impressive accuracy of 91%, marking it as the most effective solution. The comprehensive results indicate that the optimized CNN model, featuring four convolutional layers, one hidden layer with 64 neurons, and a dropout rate of 0.5, outperformed the transfer learning models.ConclusionThe findings of this study demonstrate that our developed proposed CNN model provides a high-performance solution for the rapid identification of quince leaf diseases. It excels in real-time detection and monitoring, achieving remarkable accuracy. Notably, it can identify fire blight and powdery mildew with a precision exceeding 95%.
Research Article
Design and Construction
B. Abbasian; M. E. Khorasani Ferdavani; H. Zaki Dizaji
Abstract
IntroductionThis study investigated the development and evaluation of an automatic feeder control system for sugarcane planters. The primary objective was to address limitations in existing machines and enhance their performance by introducing precise control of cane feeding.Materials and MethodsThe ...
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IntroductionThis study investigated the development and evaluation of an automatic feeder control system for sugarcane planters. The primary objective was to address limitations in existing machines and enhance their performance by introducing precise control of cane feeding.Materials and MethodsThe automatic feeder control system was equipped with three types of sensors, including a Load Cell Sensor that directly measures the weight of sugarcane on the feeder table. This feature provides a real-time assessment of cane availability. The Hydraulic Oil Pressure Sensor monitored the pressure within the hydraulic system that drives the feeder mechanism. Variations in pressure served as an indirect measure of the force applied to the cane during the feeding process. The Ultrasonic Distance Sensor employed ultrasonic waves to estimate the distance between the sensor and the sugarcane pile. Nevertheless, some limitations concerning accuracy and response time were identified. A microcontroller served as the central processing unit, receiving sensor data and generating control signals to regulate the feeder mechanism. This allowed for automation and eliminated the need for a manual operator. The performance of the automatic feeder control system was evaluated against a manual control method operated by a human.Results and DiscussionThe evaluation focused on three key aspects: cane spillage, planting quality, and control stability. Cane Spillage: the amount of sugarcane inadvertently dropped during the planting process. Automatic control methods using a load cell and hydraulic oil pressure sensor reduced spillage similarly to manual control, averaging approximately 8.8 t ha-1. The ultrasonic sensor resulted in significantly lower spillage, achieving 7.4 t ha-1. However, its limited accuracy and responsiveness led to undesirable gaps between the planted canes. Planting Quality: The implementation of automatic control techniques utilizing load cells and hydraulic oil pressure sensors successfully ensured uniform spacing between planted canes, achieving results comparable to traditional manual methods. Due to its shortcomings, the ultrasonic sensor created gaps between the planted canes, undermining the overall quality of the planting process. Control Stability: The method utilizing hydraulic oil pressure sensors exhibited limitations in maintaining consistent control under varying operational conditions. This stemmed from temperature-dependent changes in oil viscosity, which affected the pressure readings and ultimately the control signal. Based on the evaluation results, the load cell control method emerged as the most favorable option for automatic feeder control. It delivered performance that matches manual control in terms of cane spillage reduction and planting quality, all while eliminating the need for an operator. The hydraulic oil pressure sensor method, although effective in some aspects, presented challenges due to oil viscosity variations. The ultrasonic sensor showed promise for reducing spillage; however, it ultimately fell short due to its inability to accurately and swiftly detect the availability of cane, resulting in gaps between planted canes. A separate assessment was carried out to compare manual cultivation with an automatic control method based on weight measurements using a load cell. This evaluation revealed significant differences (p < 0.01) in billet weight, the number of billets utilized, and one-sided gaps between the two methods. However, no significant difference was observed in terms of two-sided gaps.ConclusionThis study successfully designed and implemented an automatic feeder control system for sugarcane planters. The load cell control method emerged as the most effective solution, successfully eliminating the need for operators while ensuring high standards of planting quality and efficiency. Additional research could explore advancements in sensor technology and control algorithms to further enhance the performance of automatic feeder control systems.AcknowledgmentThe authors would like to express their gratitude to the Managing Director of Farabi Agro-Industrial Company and its staff, as well as the technical staff of Poya Sazan Sabz Avane Company, who cooperated in the preparation and evaluation stages of the system. Vice Chancellor for Research and Technology of Shahid Chamran University of Ahvaz, Iran: financial support under the special research grant number SCU.AA98.505.
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