Introduction
The development of mechanization and machine technology can have positive and negative effects on the economic, social, and environmental conditions of a region. Conflicts in these areas complicate the selection and optimization of sustainable mechanization systems. One of the basic questions in the selection of a sustainable agricultural mechanization system is how and with what methodology would it be possible to propose the closest mechanization model that will overcome the simultaneous contradictions between the three pillars of sustainability; taking into account the natural and technical limitations in agricultural production. What is the appropriate approach considering the economic, environmental, and social aspects? The current research aims to provide a framework for an optimal mechanization model to achieve the goals of agricultural sustainability so that it can be implemented and applied practically. It is possible to provide a model that addresses the conflicting economic, social, and environmental aspects by quantitatively optimizing the level of mechanization.
Materials and Methods
In this study, a framework is applied whereby contradictory goals of agricultural sustainability can be achieved simultaneously. After selecting the indices and data collection, by combining Shannon entropy and TOPSIS, the similarity index was obtained for each objective. The similarity indices and values of the Benefit-Cost Ratio calculated for each system were considered as coefficients of three objective (economic, social, and environmental) functions in multi-objective optimization. The multi-objective optimization model was applied to achieve sustainable mechanization patterns and was solved using the NSGA-II algorithm. For framework validation, paddy production mechanization systems in the Ramhormoz region located in southwestern Iran were analyzed with constraints: land, water, and machinery. The five mechanization systems of paddy production included puddled transplanted, un-puddled transplanted, water seeded, dry seeded, and, no-till.
Results and Discussion
Pareto-optimal solutions of different scenarios with water and machine constraints showed that this framework cannot only meet the sustainable goals, but also the optimal allocation of mechanization systems is identified and the effect of different scenarios under different constraints can be examined. The sustainability goals between the no-tillage and planting with puddling systems are highly contradictory. The no-tillage system has the highest score in the environmental aspect and the lowest score in the social and economic aspects. This modern system was developed in Ramhormoz three years ago and has faced technical, economic, and social challenges ever since. The cultivated area using this system was 43 hectares in 2019. Despite the speed and ease of planting with this system, and its direct environmental benefits, the possibility of fungal outbreaks is raised due to the pre
Agriculture is a cornerstone of many developing economies, providing food, income, and employment for millions of people. It is also projected to play a vital role in feeding a global population of 9.1 billion people by 2050. However, there are growing concerns about the environmental impact of agriculture, particularly in arid and semi-arid regions like Iran. Managing water and fertilizer usage in agriculture is crucial to ensuring food security and sustainability. However, conducting field experiments to assess the interaction of all factors involved is expensive and time-consuming. This research focuses on optimizing maize production in Kerman province, a region where maize is a major crop. The research is motivated by the need to improve resource management in Iran, where water and fertilizer resources are limited. The APSIM model is used to determine the best management scenario for maize production in Kerman province. APSIM is a crop growth simulation model that can be used to predict the impact of different management practices on crop yield, water use efficiency, and nutrient use efficiency. The use of APSIM in this research provides a cost-effective and time-efficient alternative to conducting extensive field experiments. The results of this research will contribute to the development of sustainable and efficient agricultural practices in Kerman province and similar regions. These regions are characterized by resource constraints, such as limited water and fertilizer availability. The research aimed to simulate the effect of management parameters (planting date and irrigation) on Crop yield and subsequently achieve the optimal management scenario.
Automatic Detection of Plant Cultivation Rows Robot using Machine Vision (Cas...J. Agricultural Machinery
Introduction
Nowadays, machine vision systems are extensively used in agriculture. The application of this technology in the field can help preserve agricultural resources while reducing manual labor and production costs. In the field of agricultural automation, accurately detecting crop rows is recognized as a crucial and challenging issue for weed identification and the automatic guidance of machines. Therefore, it is necessary to explore practical solutions to optimize this process. Hence, the purpose of this study is the precise identification of basil cultivation rows to enable the automatic navigation of robots in the cultivation field.
Materials and Methods
In the first stage of this research, six images from each growth period of basil plants (third, fourth, and fifth week) were taken and weeds were removed from the area between the crop rows using three different methods of area opening, dimensional removal, and masking. In the next stage, six images of crop rows without weeds were examined by performing image processing operations and implementing several routing algorithms, namely, Hough transform, wavelet transform, Gabor filter, linear regression, and an additional algorithm proposed in this study. The output of each of these algorithms was compared with the ideal path identified by the user. For this purpose, after capturing an image, green areas were extracted from it by performing the segmentation process. By applying each of the routing algorithms to the image, plant cultivation lines were identified and their equations were determined. Finally, the performance of the designed robot was evaluated using the most appropriate routing algorithm.
Results and Discussion
Examining the performance of three different methods of weed removal in three periods of plant growth (third, fourth, and fifth week) showed that during this interval, the masking method had the lowest error rate compared to the ideal path and the shortest average operation time of 1.64 seconds, followed by the dimensional removal and the area opening methods. Comparing the routes detected by different routing algorithms with the ideal routes and according to the results of the t-test at 5% probability level, the order of the studied routing methods from the most superior is as follows: the proposed algorithm, Gabor filter, linear regression, Hough transform and wavelet transform algorithm. Overall, the proposed algorithm had the highest rate of adaptation to the ideal path (with an average error of 3.65 pixels) and the shortest operation time (4.79 seconds) and was selected as the most appropriate routing algorithm and the performance of the designed robot was evaluated using it.
Conclusion
A reliable crop row detection algorithm can reduce production costs and preserve the environment. In this study, the masking method was used for removing weeds from the images. The new proposed routing algorithm has superior performance when compared with common routing algorithms s
Maize (Zea mays L.) is one of the most important cereals after wheat and rice in the tropical and temperate regions of the world. Also, its mean production is 8 ton ha-1. Moreover, the total area of under cultivation is 132572 hectares in Iran. Crop simulation models can play an important role in improving agricultural production systems in many developing countries. Crop models can simulate plant growth processes and grain yield instead of conducting several years of field experiments. On the other hands, crop simulation models should be calibrated and evaluated with independent data sets under different climatic conditions. Therefore, the purpose of this research was evaluation of the APSIM model for simulation of growth, development and yield of maize hybrids in Kerman province under different amounts of nitrogen.
Identifying and Prioritizing the Key Factors Affecting the Efficient Maintena...J. Agricultural Machinery
Introduction: With the emergence of new automation and mechanized technologies in the production and processing of agricultural products in Iran, which aim to accelerate the food supply process, adopting appropriate management models in the field of maintenance becomes inevitable. This is crucial to maintain and enhance the operational reliability of agricultural machinery, tools, and equipment. Furthermore, proper management of various physical assets in the agricultural industry, including operation and maintenance, is one of the most important requirements. This is due to their crucial role in ensuring readiness and high availability during the seasons of planting, cultivating, and harvesting agricultural products. These needs differ from that of other continuous production processes.
Materials and Methods: To achieve an efficient model in the field of maintenance, the following steps have been investigated:
a) Reviewing and identifying the most important criteria and sub-criteria driving the maintenance management. This is based on the previous literature and the experts’ opinion.
b) Evaluating and prioritizing the main criteria and the interactions between their sub-criteria using the Best-Worst Method (BWM).
c) Providing improved solutions for maintenance management of Iranian agro-industries.
We decided to employ BWM because, compared to similar methods, it (i) provides more reliable pairwise comparisons, (ii) reduces the possible anchoring bias that may occur during the weighting process by respondents, (iii) is the most data-efficient method, and (iv) provides multiple optimal solutions which increase flexibility when accessing the best weight point. The process of weighting by BWM is summarized in five steps:
1) Determine a set of evaluation criteria identified by the experts or decision-makers.
2) Identify the most important (Best) and the least important (Worst) criteria according to the experts or decision-makers, each of which may have their own Best and Worst.
3) Determine the preference of the Best criterion over all the other criteria using a number from 1 to 9 (where 1 represents equal importance and 9 represents extremely more important).
4) Determine the preference of all the decision criteria over the Worst criterion.
5) Compute optimal weights.
Results and Discussion: According to the preliminary surveys, the most important criteria in the excellence maintenance model were identified as “organizational management”, “human-related factors”, and “organizational aspects”, respectively. The results of the BWM revealed that sub-criteria such as "top management support," "fund allocation and inventory resource management," and "appropriate maintenance strategies" had the greatest impact on maintenance management in agro-industries, with global weights of 0.108, 0.075, and 0.067, respectively. Additionally, these findings were compared to previous research conducted in the field of agricultural and production system maintenance
During the 1950s and 1960s, the green revolution led to a dramatic increase in global food and fodder production to eliminate hunger and boost food security. This production enhancement was accompanied by an intensified agricultural and chemical input consumption and increased cultivated area and mechanization. Although yield per unit area has improved in most crops, concerns about food security for the world's rising population are still significant. Guaranteeing food security in the future will necessitate a shift in management approaches to boost output, agroecosystem sustainability, and stability and reduce the environmental harm caused by agriculture. The first step to achieving sustainability and ecological intensification in agricultural systems is to have a comprehensive agroecological analysis of agricultural systems in each region. Hence, the complete evaluation and analysis of agroecological features according to their type in each region is necessary for establishing an optimal management technique. After analyzing the present state of each region's shared ecosystems, the optimal strategy for boosting production stability must be devised and implemented.
Introduction
Sugarcane is one of the strategic products of Khuzestan province, which is cultivated in 10 active agro-industrial sites and covers an area of about 110,000 hectares of irrigated farms in the province. Sugarcane harvesting, like most crops, is done by special sugarcane harvesters. Due to the life of machines and also the amount of heavy machine operations in each season of sugarcane harvest, the loss is inevitable. On the other hand, in Khuzestan province, due to lack of studies, there is little information in this area. Therefore, the aim of this study is to investigate the extent of losses during sugarcane harvesting operations, taking into account factors such as cultivars, age of sugarcane, and reaping speed of the Astaf 7000 model. The study will be conducted at the sugarcane agro-industrial site of Dehkhoda in 2021.
The relationship between economic development and the environment is known as one of the most important issues facing societies. If in the context of sustainable development, economic and environmental activities are considered together, the environment and economic development are two complementary factors and, as a result, it will lead to ecological balance. In this case, economic activities will not disturb this balance. Presently, the imperative of safeguarding the environment and attaining sustainable development has ascended to a prominent position on the agendas of diverse societies, Iran included. This commitment is underscored by the execution of comprehensive economic, social, and cultural initiatives aimed at fostering long-term ecological resilience and balanced societal progress. Therefore, to preserve the environment and meet the goals of sustainable development, as well as to guide and rationally manage plans and projects, especially in the agricultural sector, serious measures should be taken. Therefore, this study was carried out to evaluate the operational, environmental, and eco-efficiency of the major agricultural products of the irrigation and drainage networks of Gotvand.
The irrigation and drainage network of Gotvand is located in the southwest of Iran in Khuzestan province. This network is designed to irrigate lands located in three regions of Gotvand, Aghili, and Dimcheh, enclosed between two rivers, Karun and Lor. According to the official statistics of government organizations, the consumption of fertilizers and chemical poisons in the lands covered by this network is 3.6 times the average limit in Iran. The excess irrigation water in this network is returned to the rivers by the built-in drains and causes water pollution downstream of the network. Therefore, considering that environmental protection is one of the most important aspects of sustainable development, it is very important to investigate the effects of the use of pesticides and chemical fertilizers in agriculture and to introduce solutions to improve the efficiency of the environment in the study area.
In order to meet the increasing demands of the growing population, it is essential to boost rice production. This not only ensures food security but also helps maintain environmental well-being. To achieve these goals, it is crucial for crop management research to focus on increasing rice yields while minimizing water usage. In Iran, particularly in the Rudbar region, recognizing the significance of rice cultivation in agriculture is of utmost importance. To improve rice field management, various aspects such as water and soil resource management, pest and disease control, nutrition management, sales and marketing strategies, human resources and social capital management, as well as technical and agricultural improvements need to be addressed. Therefore, the aim of the present study was to identify more effective methods for managing the rice fields in Rudbar county, Iran. Materials and Methos Initially, the researchers conducted a comprehensive analysis of available national and international databases to gather background information for the study. This analysis aimed to establish an initial list of components that could contribute to improving the management of rice fields. The statistical population of the study consisted of all 850 rice farmers in Rudbar City. Using the Karjesi-Morgan table, a statistical sample size of 265 participants was estimated, which corresponded to the size of the population. Eventually, 252 questionnaires were collected after distributing them to the participants, resulting in an 88% response rate. The opinions of faculty members from Tehran University's Department of Agricultural Management and Development were sought to assess the content validity of the questionnaire which was finally confirmed. To assess the reliability or internal consistency of the questionnaire, Cronbach's alpha coefficient was calculated for each of its components. All coefficients were found to be above 0.7, indicating good reliability of the study tool. The data obtained from the questionnaires was subjected to statistical analysis using the LISREL 8.8 software. A confirmatory factor analysis model was applied to examine the data. The reliability of the indicators loaded on each structure was evaluated using the t statistic. Indicators with values exceeding the critical limit of 1.96 were considered to have the required precision for measuring the relevant structure. Additionally, significant factor loadings were determined by extracting values greater than 0.5 from the factor loadings. It is important to note that Cronbach's alpha (with values higher than 0.7) was utilized to assess the reliability of the constructs.
Agriculture is a cornerstone of many developing economies, providing food, income, and employment for millions of people. It is also projected to play a vital role in feeding a global population of 9.1 billion people by 2050. However, there are growing concerns about the environmental impact of agriculture, particularly in arid and semi-arid regions like Iran. Managing water and fertilizer usage in agriculture is crucial to ensuring food security and sustainability. However, conducting field experiments to assess the interaction of all factors involved is expensive and time-consuming. This research focuses on optimizing maize production in Kerman province, a region where maize is a major crop. The research is motivated by the need to improve resource management in Iran, where water and fertilizer resources are limited. The APSIM model is used to determine the best management scenario for maize production in Kerman province. APSIM is a crop growth simulation model that can be used to predict the impact of different management practices on crop yield, water use efficiency, and nutrient use efficiency. The use of APSIM in this research provides a cost-effective and time-efficient alternative to conducting extensive field experiments. The results of this research will contribute to the development of sustainable and efficient agricultural practices in Kerman province and similar regions. These regions are characterized by resource constraints, such as limited water and fertilizer availability. The research aimed to simulate the effect of management parameters (planting date and irrigation) on Crop yield and subsequently achieve the optimal management scenario.
Automatic Detection of Plant Cultivation Rows Robot using Machine Vision (Cas...J. Agricultural Machinery
Introduction
Nowadays, machine vision systems are extensively used in agriculture. The application of this technology in the field can help preserve agricultural resources while reducing manual labor and production costs. In the field of agricultural automation, accurately detecting crop rows is recognized as a crucial and challenging issue for weed identification and the automatic guidance of machines. Therefore, it is necessary to explore practical solutions to optimize this process. Hence, the purpose of this study is the precise identification of basil cultivation rows to enable the automatic navigation of robots in the cultivation field.
Materials and Methods
In the first stage of this research, six images from each growth period of basil plants (third, fourth, and fifth week) were taken and weeds were removed from the area between the crop rows using three different methods of area opening, dimensional removal, and masking. In the next stage, six images of crop rows without weeds were examined by performing image processing operations and implementing several routing algorithms, namely, Hough transform, wavelet transform, Gabor filter, linear regression, and an additional algorithm proposed in this study. The output of each of these algorithms was compared with the ideal path identified by the user. For this purpose, after capturing an image, green areas were extracted from it by performing the segmentation process. By applying each of the routing algorithms to the image, plant cultivation lines were identified and their equations were determined. Finally, the performance of the designed robot was evaluated using the most appropriate routing algorithm.
Results and Discussion
Examining the performance of three different methods of weed removal in three periods of plant growth (third, fourth, and fifth week) showed that during this interval, the masking method had the lowest error rate compared to the ideal path and the shortest average operation time of 1.64 seconds, followed by the dimensional removal and the area opening methods. Comparing the routes detected by different routing algorithms with the ideal routes and according to the results of the t-test at 5% probability level, the order of the studied routing methods from the most superior is as follows: the proposed algorithm, Gabor filter, linear regression, Hough transform and wavelet transform algorithm. Overall, the proposed algorithm had the highest rate of adaptation to the ideal path (with an average error of 3.65 pixels) and the shortest operation time (4.79 seconds) and was selected as the most appropriate routing algorithm and the performance of the designed robot was evaluated using it.
Conclusion
A reliable crop row detection algorithm can reduce production costs and preserve the environment. In this study, the masking method was used for removing weeds from the images. The new proposed routing algorithm has superior performance when compared with common routing algorithms s
Maize (Zea mays L.) is one of the most important cereals after wheat and rice in the tropical and temperate regions of the world. Also, its mean production is 8 ton ha-1. Moreover, the total area of under cultivation is 132572 hectares in Iran. Crop simulation models can play an important role in improving agricultural production systems in many developing countries. Crop models can simulate plant growth processes and grain yield instead of conducting several years of field experiments. On the other hands, crop simulation models should be calibrated and evaluated with independent data sets under different climatic conditions. Therefore, the purpose of this research was evaluation of the APSIM model for simulation of growth, development and yield of maize hybrids in Kerman province under different amounts of nitrogen.
Identifying and Prioritizing the Key Factors Affecting the Efficient Maintena...J. Agricultural Machinery
Introduction: With the emergence of new automation and mechanized technologies in the production and processing of agricultural products in Iran, which aim to accelerate the food supply process, adopting appropriate management models in the field of maintenance becomes inevitable. This is crucial to maintain and enhance the operational reliability of agricultural machinery, tools, and equipment. Furthermore, proper management of various physical assets in the agricultural industry, including operation and maintenance, is one of the most important requirements. This is due to their crucial role in ensuring readiness and high availability during the seasons of planting, cultivating, and harvesting agricultural products. These needs differ from that of other continuous production processes.
Materials and Methods: To achieve an efficient model in the field of maintenance, the following steps have been investigated:
a) Reviewing and identifying the most important criteria and sub-criteria driving the maintenance management. This is based on the previous literature and the experts’ opinion.
b) Evaluating and prioritizing the main criteria and the interactions between their sub-criteria using the Best-Worst Method (BWM).
c) Providing improved solutions for maintenance management of Iranian agro-industries.
We decided to employ BWM because, compared to similar methods, it (i) provides more reliable pairwise comparisons, (ii) reduces the possible anchoring bias that may occur during the weighting process by respondents, (iii) is the most data-efficient method, and (iv) provides multiple optimal solutions which increase flexibility when accessing the best weight point. The process of weighting by BWM is summarized in five steps:
1) Determine a set of evaluation criteria identified by the experts or decision-makers.
2) Identify the most important (Best) and the least important (Worst) criteria according to the experts or decision-makers, each of which may have their own Best and Worst.
3) Determine the preference of the Best criterion over all the other criteria using a number from 1 to 9 (where 1 represents equal importance and 9 represents extremely more important).
4) Determine the preference of all the decision criteria over the Worst criterion.
5) Compute optimal weights.
Results and Discussion: According to the preliminary surveys, the most important criteria in the excellence maintenance model were identified as “organizational management”, “human-related factors”, and “organizational aspects”, respectively. The results of the BWM revealed that sub-criteria such as "top management support," "fund allocation and inventory resource management," and "appropriate maintenance strategies" had the greatest impact on maintenance management in agro-industries, with global weights of 0.108, 0.075, and 0.067, respectively. Additionally, these findings were compared to previous research conducted in the field of agricultural and production system maintenance
During the 1950s and 1960s, the green revolution led to a dramatic increase in global food and fodder production to eliminate hunger and boost food security. This production enhancement was accompanied by an intensified agricultural and chemical input consumption and increased cultivated area and mechanization. Although yield per unit area has improved in most crops, concerns about food security for the world's rising population are still significant. Guaranteeing food security in the future will necessitate a shift in management approaches to boost output, agroecosystem sustainability, and stability and reduce the environmental harm caused by agriculture. The first step to achieving sustainability and ecological intensification in agricultural systems is to have a comprehensive agroecological analysis of agricultural systems in each region. Hence, the complete evaluation and analysis of agroecological features according to their type in each region is necessary for establishing an optimal management technique. After analyzing the present state of each region's shared ecosystems, the optimal strategy for boosting production stability must be devised and implemented.
Introduction
Sugarcane is one of the strategic products of Khuzestan province, which is cultivated in 10 active agro-industrial sites and covers an area of about 110,000 hectares of irrigated farms in the province. Sugarcane harvesting, like most crops, is done by special sugarcane harvesters. Due to the life of machines and also the amount of heavy machine operations in each season of sugarcane harvest, the loss is inevitable. On the other hand, in Khuzestan province, due to lack of studies, there is little information in this area. Therefore, the aim of this study is to investigate the extent of losses during sugarcane harvesting operations, taking into account factors such as cultivars, age of sugarcane, and reaping speed of the Astaf 7000 model. The study will be conducted at the sugarcane agro-industrial site of Dehkhoda in 2021.
The relationship between economic development and the environment is known as one of the most important issues facing societies. If in the context of sustainable development, economic and environmental activities are considered together, the environment and economic development are two complementary factors and, as a result, it will lead to ecological balance. In this case, economic activities will not disturb this balance. Presently, the imperative of safeguarding the environment and attaining sustainable development has ascended to a prominent position on the agendas of diverse societies, Iran included. This commitment is underscored by the execution of comprehensive economic, social, and cultural initiatives aimed at fostering long-term ecological resilience and balanced societal progress. Therefore, to preserve the environment and meet the goals of sustainable development, as well as to guide and rationally manage plans and projects, especially in the agricultural sector, serious measures should be taken. Therefore, this study was carried out to evaluate the operational, environmental, and eco-efficiency of the major agricultural products of the irrigation and drainage networks of Gotvand.
The irrigation and drainage network of Gotvand is located in the southwest of Iran in Khuzestan province. This network is designed to irrigate lands located in three regions of Gotvand, Aghili, and Dimcheh, enclosed between two rivers, Karun and Lor. According to the official statistics of government organizations, the consumption of fertilizers and chemical poisons in the lands covered by this network is 3.6 times the average limit in Iran. The excess irrigation water in this network is returned to the rivers by the built-in drains and causes water pollution downstream of the network. Therefore, considering that environmental protection is one of the most important aspects of sustainable development, it is very important to investigate the effects of the use of pesticides and chemical fertilizers in agriculture and to introduce solutions to improve the efficiency of the environment in the study area.
In order to meet the increasing demands of the growing population, it is essential to boost rice production. This not only ensures food security but also helps maintain environmental well-being. To achieve these goals, it is crucial for crop management research to focus on increasing rice yields while minimizing water usage. In Iran, particularly in the Rudbar region, recognizing the significance of rice cultivation in agriculture is of utmost importance. To improve rice field management, various aspects such as water and soil resource management, pest and disease control, nutrition management, sales and marketing strategies, human resources and social capital management, as well as technical and agricultural improvements need to be addressed. Therefore, the aim of the present study was to identify more effective methods for managing the rice fields in Rudbar county, Iran. Materials and Methos Initially, the researchers conducted a comprehensive analysis of available national and international databases to gather background information for the study. This analysis aimed to establish an initial list of components that could contribute to improving the management of rice fields. The statistical population of the study consisted of all 850 rice farmers in Rudbar City. Using the Karjesi-Morgan table, a statistical sample size of 265 participants was estimated, which corresponded to the size of the population. Eventually, 252 questionnaires were collected after distributing them to the participants, resulting in an 88% response rate. The opinions of faculty members from Tehran University's Department of Agricultural Management and Development were sought to assess the content validity of the questionnaire which was finally confirmed. To assess the reliability or internal consistency of the questionnaire, Cronbach's alpha coefficient was calculated for each of its components. All coefficients were found to be above 0.7, indicating good reliability of the study tool. The data obtained from the questionnaires was subjected to statistical analysis using the LISREL 8.8 software. A confirmatory factor analysis model was applied to examine the data. The reliability of the indicators loaded on each structure was evaluated using the t statistic. Indicators with values exceeding the critical limit of 1.96 were considered to have the required precision for measuring the relevant structure. Additionally, significant factor loadings were determined by extracting values greater than 0.5 from the factor loadings. It is important to note that Cronbach's alpha (with values higher than 0.7) was utilized to assess the reliability of the constructs.
Evaluation and Optimization of Energy and Environmental Indicators Using Life...J. Agricultural Machinery
Introduction: Environmental crises and resource depletion have adversely affected environmental resources and food security in the world. Therefore, with the global population growth in the coming years and the rising need to produce more food, attention must be given to environmental issues, energy consumption, and sustainable production. The purpose of this study is to evaluate the pattern of energy consumption, environmental impacts, and optimization of the studied energy indicators in dairy cattle breeding industrial units in Khuzestan province, Iran.
Materials and Methods: This research was conducted in Khuzestan province, located in the southwest of Iran. Energy indicators including energy ratio, energy efficiency, specific energy, and net energy were used to determine and analyze the relationships between the output and input energy. Additionally, the life cycle assessment methodology was used to assess the environmental impact. Life cycle assessment includes a goal statement, identification of inputs and outputs, and a system for assessing and interpreting environmental impacts, and can be a good indicator for assessing environmental issues related to production. The life cycle assessment method used in this study was CML-IA baseline V3.05, which includes the four steps of (1) selecting and classifying impact categories, (2) characterizing effects, (3) normalizing, and (4) weighting. Overall, 11 impact groups were studied. The Data Envelopment Analysis (DEA) method with the Anderson-Peterson model was used for optimization. This method identifies the most efficient production unit and makes it possible to rank all of the farms in the region. In this study, each production unit (farm) was considered a decision-making unit (DMU), and its production efficiency was determined based on two models. Namely, the Charnes, Cooper, and Rhodes (CCR) model also known as Constant Return to Scale (CRS), and the Banker, Charnes, and Cooper (BCC) model also known as Variable Return to Scale (VRS).
Results and Discussion: The results showed that the input and output energies per cow per day were 173.34 and 166 MJ, respectively. Livestock feed and electricity accounted for 65.47% and 27.2% of the input energy, respectively, while the oil used for tiller-scraper lubrication of fertilizer collection accounted for only 0.01%, making it the lowest input energy. Energy efficiency, specific energy, and net energy were calculated as 0.95, 0.13 kg MJ-1, 7.51 MJ kg-1, and -7.20 MJ per cow, respectively. In the abiotic depletion impact group, animal feed, machinery, and livestock equipment had the highest environmental impacts. The results showed that animal feed had the highest environmental emissions in all impact groups except for abiotic depletion of fossil fuels where electricity had the greatest effect. CRS model determined that 7 units were efficient; with an average efficiency of 0.78. In the BCC model, 20 production units were calculated as highly efficient,
Balancing Time and Cost in Resource-Constrained Project Scheduling Using Meta...J. Agricultural Machinery
Agricultural production involves a series of tasks including tillage, planting, and harvesting, which must be done at the right time for each region and type of product. Failing to complete these tasks on time can lead to a decrease in yield. Farmers may wrongly attribute this to factors such as infertile land, pests, diseases, and uneven rainfall distribution. However, this decrease in yield may not always be evident or tangible. To avoid such losses and unforeseen expenses, it is crucial to plan agricultural mechanization projects using the principles of project control. Agricultural projects, like industrial projects, must be carried out in the correct order and at the right time to achieve optimal results. Given the limited availability of resources for mechanization projects, it is imperative to meticulously plan activities to ensure that they are carried out on time and with maximum utilization of resources. To address these challenges, researchers have used meta-heuristic methods in project control, such as the colonial competition algorithm, which has been proven effective in solving the issue of scheduling projects with limited resources. The algorithm has been tested across various industrial activities and projects, and its performance in scheduling the Resource-Constrained Project Scheduling Problem (RCPSP) has been validated by researchers globally.
On the field and in the paddy milling factory dryer losses have always been challenging issues in the rice industry. Different forms of losses in brown rice may occur depending on the field and factory conditions. To reduce the losses, proper management during pre-harvest, harvesting, and post-harvest operations is essential. In this study, different on-field drying and tempering methods were investigated to detect different forms of brown rice losses
Nitrogen (N) is one of the main limiting factors in agroecosystems all around the world. However, high application rates of N fertilizers would lead to negative environmental consequences. Reduction of N fertilizers consumption decreases production costs and environmental pollution. Therefore, N efficiency to be enhanced due to the high N fertilizer cost and required measures to prevent the waste of N. Cultivation of diverse crop cultivars with higher resources absorption and utilization efficiency is one of the major approaches in sustainable agriculture that would result in the effective use of natural and chemical inputs and reduce significantly the environmental risks. Quchan City is one of the potato production poles in Khorasan Razavi province. In this region, large amounts of N fertilizers annually are consumed in the potato agroecosystem. Therefore, the potato of the present study was evaluating N uptake and utilization efficiency, and finally, N uses efficiency in the potato agroecosystem of Quchan.
Design of a Harvester for Harvesting of the Leaves and Stems of Plants in Cul...J. Agricultural Machinery
The world today is facing the issue of population growth, which will result in food shortages. One way to supply food to this growing population is to facilitate the production of agricultural products to meet the growing demand. Medicinal plants are an important product of the agricultural sector. In Iran, manual harvesting reduces the productivity of these crops, and the use of manual harvesting poses challenges related to available manpower. The costs and time required for manual harvesting are additional obstacles. Given the importance of developing medicinal plants, designing and constructing a mechanized machine for harvesting them could improve the harvesting process.
Modeling and Fabrication of a Robot for Sowing in a Seedling Tray (Case Study...J. Agricultural Machinery
Adopting new technologies for crop growth has the characteristics of improving disaster resistance and stress tolerance, ensuring stable yields, and improving product quality. Currently, the cultivation of seed trays relies on huge labor power, and further mechanization is needed to increase production. However, there are some problems in this operation, such as the difficulty of improving the speed of a single machine, seedling deficiency detection, automatic planting, and controlling the quality, which need to be solved urgently. To solve these problems, there are already some meaningful attempts. Si et al. (2012) applied a photoelectric sensor to a vegetable transplanter, which can measure the distance between seedlings and the movement speed of seedlings in a seedling guide tube, to prevent omission transplantation. Yang et al. (2018) designed a seedling separation device with reciprocating movement of the seedling cup for rice transplanting. Tests show that the structure of the mechanical parts of the seedling separation device meets the requirements of seed movement. The optimization of the control system can improve the positioning accuracy according to requirements and achieve the purpose of automatic seedling division. Chen et al. (2020) designed and tested of soft-pot-tray automatic embedding system for a light-economical pot seedling nursery machine. The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%. The successful tray embedding rate was 100% and the seed exposure rate was less than 1% with a linear velocity of the conveyor belt of 0.92 m s-1. The experiment findings agreed well with the analytical results.
Despite the sharp decline in Iran's water resources and growing population, the need to produce food and agricultural products is greater than ever. In the past, most seeds were planted directly into the soil, and many water resources, especially groundwater, were used for direct seed sowing and plant germination. One way to reduce the consumption of water, fertilizers, and pesticides is to plant seedlings instead of direct seed sowing. Therefore, the purpose of this study was dynamic modeling and fabrication of seed planting systems in seedling trays.
The growing importance of energy resources in the formation and growth of economic processes, as well as the need to exploit these resources based on environmental considerations and sustainable economic development, the issue of energy saving as an important issue in all economic infrastructures, including industry. Global warming, declining crop yields, climate change and acid rain are the result of fossil fuel consumption. Hence, in recent years, there has been a growing global emphasis on renewable energy across both developed and developing nations. The primary objective is to decrease reliance on conventional energy sources, mitigate environmental pollution, and attain sustainable energy practices.
Simulation of Natural Frequencies of Orange Fruit Using Finite Element MethodJ. Agricultural Machinery
The growing consumer demand for high-quality products has led to the development of new technologies for assessing the quality of agricultural products. Iran is the 9th largest orange producer in the world. Every year, large quantities of agricultural products lose their optimal quality due to mechanical and physical damage during various operations such as harvesting, packaging, transportation, sorting, processing, and storage. This study is performed to identify the natural frequencies and vibration modes of the Thomson orange fruit using finite element modal analysis by ANSYS software. In addition, physical properties including mass, volume, density, and principal dimensions were measured, and mechanical properties were determined using Instron Texture Profile Analysis. The dynamic behavior of the orange fruit was simulated using the pendulum impact test. Afterward, the obtained impact was applied to the orange fruit by force gauge and three-axis accelerometer sensors in both polar and equatorial directions. The three-dimensional geometric model of the orange fruit was drawn in the ANSYS software. After meshing and applying the boundary conditions, the first 20 modes and corresponding natural frequencies were obtained. Since the objective of this study was to identify the natural frequencies of the orange fruit, it was considered to have free movement and rotation in space. The results showed that the natural frequencies of orange fruit are in the range of 0 to 248.41 Hz. Knowledge of the texture characteristics and dynamic behavior of horticultural products is essential for the design and development of agricultural machinery. Furthermore, the design and development of agricultural machinery are directly related to the biological properties of agricultural products.
In the pursuit of a resilient and progressive agricultural system, the incorporation of diverse fertilizers is deemed essential. This practice not only enhances product quality but also aids in cost reduction. However, over-reliance on a specific type of input can inadvertently lead to unintended repercussions. The unrestricted utilization of chemical fertilizers, for instance, can precipitate adverse outcomes such as imbalanced pH levels, the accumulation of heavy elements, soil structure deterioration, and environmental contamination. Conversely, organic fertilizers, while environmentally friendly, often release nutrients at a slower rate, potentially disrupting optimal plant growth. To attain a balanced and sustainable agricultural approach, the combined application of organic and chemical fertilizers is advocated. Moreover, harnessing the biological potential inherent in soil ecosystems, including beneficial microbial communities encompassing bacteria and fungi, emerges as a promising avenue in cultivating sustainable agriculture. Acknowledging the adverse impact of late-season heat stress on wheat production in Khuzestan and recognizing the significance of reducing chemical fertilizer usage while augmenting organic and biological fertilizers to foster ecological health, this experiment undertakes the exploration of the effects of a synergistic approach. Specifically, it delves into the combined utilization of nitrogen and compost fertilizers, complemented by the incorporation of plant growth-promoting rhizobacteria. This endeavor aims to shed light on how this combined strategy operates within the context of terminal heat stress, assessing its influence on the physiological attributes and yield of the wheat cultivar Chamran 2.
Detection of Different Percentages of Palm in Corn Oil with the Help of an El...J. Agricultural Machinery
The use of corn oil in diets is due to its positive effects on cardiovascular and immune systems. Corn oil is composed of 99% triacylglycerol, with 59% unsaturated fatty acids and 13% saturated fatty acids. Of the unsaturated fatty acids, 24% contain a double bond. Because of this composition, corn oil can be a good alternative to other oils high in saturated fatty acids, as it reduces blood cholesterol levels.
This study employed an electrical nasal system to detect the amount of palm oil present in corn oil. The properties extracted from the signals obtained by the device were processed using principal component analysis, artificial neural networks, infusion, and response surface methods. The results were then compared to find the best method for detecting palm oil levels in corn oil.
Global warming directly affects agricultural production and food security (Ainsworth & Ort, 2010). Temperature controls the rate of plant metabolic processes that ultimately affect biomass production and grain yield (Hay & Walker, 1981). Although farmers are not able to control the climatic conditions, management and changes in factors such as irrigation, soil, crop varieties, activities, and technologies used in the cultivation of crops can reduce the harmful effects of climate change (Moradi et al., 2014). One of the reliable approaches to studying the effects of climate change on agricultural production is using crop growth models. The present study was conducted to simulate the effects of climate change on phonological stages and yield of maize and to investigate the possibility of mitigating the negative effects of climate change on maize by changing the sowing date and selecting suitable cultivars as management strategies for adaptation to climate change in Kermanshah region.
The excessive use of chemical fertilizers is a leading cause of environmental pollution in the agriculture sector. Therefore, optimizing fertilizer application is a crucial approach to boost production while minimizing environmental harm. On the other hand, application of chemical fertilizers along with manure can be considered as the proper management system that led to reduce the amount of chemical fertilizers and adverse effects on environment and also improve nutrition for plants. Response-surface methodology is a powerful tool to optimize production resources which decreases cost and time of the experiments by reducing number of them. Therefore, the aim of the study was optimization of chemical fertilizers of nitrogen and phosphorus along with manure application in fodder maize production.
The excessive use of chemical fertilizers is a leading cause of environmental pollution in the agriculture sector. Therefore, optimizing fertilizer application is a crucial approach to boost production while minimizing environmental harm. On the other hand, application of chemical fertilizers along with manure can be considered as the proper management system that led to reduce the amount of chemical fertilizers and adverse effects on environment and also improve nutrition for plants. Response-surface methodology is a powerful tool to optimize production resources which decreases cost and time of the experiments by reducing number of them. Therefore, the aim of the study was optimization of chemical fertilizers of nitrogen and phosphorus along with manure application in fodder maize production.
The development process of organic cultivation in Iran is not favorable because the average growth rate of organic agriculture development from 2008 to 2019 according to FAO statistics in 2021 is equal to -0.47% and this is while foods contaminated with various substances Chemicals have an unpleasant effect on the general health of society. According to the statistics of 2021, 600 million people in the world, i.e. 1 out of every 10 people, will get sick after eating food. Since any change in the use of chemicals in agriculture should be based on the behavior of farmers, the purpose of this study is to investigate the behavioral intention to produce organic pistachio production among 5200 pistachio growers in Ardakan county, Yazd province, using the Decomposed Theory of Planned Behavior (DTPB) analysis.
Analysis of Workspace and Kinematics of Robot Manipulator for Product Handlin...J. Agricultural Machinery
Robots have been used for material handling for many years, and their applications have greatly expanded with the integration of intelligent technologies. While numerous researchers have proposed various robots for this field, it is crucial to design customized configurations that are suitable for agricultural farms. However, research in our country has been limited to a few mobile agricultural robots. The main focus of this paper is to design and model workspaces and analyze the kinematics of manipulators in agricultural settings.
In recent decades, the need for increased food production has resulted in the expansion of intensified agriculture practices characterized by high consumption of inputs, thereby reducing agricultural sustainability. The agricultural sector's contribution to the world's energy consumption, ecological footprint, and greenhouse gas emissions has grown substantially. Emissions of greenhouse gases have negative ecological effects, including climate change, global warming, and diminished sustainable development. In this sector, energy analysis and greenhouse gas emissions in ecosystems are the most common methods for assessing sustainability. This study was conducted to evaluate the sustainability of canola agroecosystems by analyzing energy consumption, carbon footprint, and greenhouse gas emissions.
Evaluation of Two Types of Cotton Pickers in Terms of the Functionality and Q...J. Agricultural Machinery
Cotton, as one of the most widely used products in various industries, has always been considered by leading countries in agriculture. The applications of this plant range from the food industry to the military industry, as well as the textile and animal nutrition industry. It is predicted that by 2025, the area under cotton cultivation in the world will reach more than 33 million hectares (FAO, 2017). Based on the growing population, it is necessary to use machines in industries and other sectors to accelerate production and increase efficiency. Cotton is no exception to this rule. The use of a machine can play an effective role in reducing harvest costs and decreasing losses from frost and early fall rainfall by enabling timely harvesting.
Experimental Study and Mathematical Modeling of Hydrogen Sulfide Removal from...J. Agricultural Machinery
Introduction
Anaerobic bacteria break down organic materials like animal manure, household trash, plant wastes, and sewage sludge during the anaerobic digestion process of biological materials and produce biogas. One of the main issues in using biogas is hydrogen sulfide (H2S), which can corrode pipelines and engines in concentrations between 50 and 10,000 ppm. One method for removing H2S from biogas with minimal investment and operation costs is biofiltration. Whether organic or inorganic, the biofilter's bed filling materials must adhere to certain standards including high contact surface area, high permeability, and high absorption. In this study, biochar and compost were used as bed particles in the biofilter to study the removal of H2S from the biogas flow in the lab. Afterward, kinetic modeling was used to describe the removal process numerically.
Material and Methods
To remove H2S from the biogas, a lab-sized biofilter was constructed. Biochar and compost were employed separately as the material for the biofilter bed. Because of its high absorption capacity and porosity, biochar is a good choice for substrate and packed beds in biofilters. The biochar pieces used were broken into 10 mm long cylindrical pieces with a diameter of 5 mm. Compost was used as substrate particles because it contains nutrients for microorganisms. Compost granules with an average length of 7.5 mm and 3 mm in diameter were used in this study. For the biofilter reactor, each of these substrates was put inside a cylinder with a diameter of 6 cm and a height of 60 cm. The biofilter's bottom is where the biogas enters, and its top is where it exits. During the experiment, biogas flowed at a rate of 72 liters per hour. Mathematical modeling was used to conduct kinetic studies of the process to better comprehend and generalize the results. This method involves feeding the biofilter column with biogas that contains H2S while the biofilm is present on the surface of the biofilter bed particles. The bacteria in the biofilm change the gaseous H2S into the harmless substance sulfur and store it in their cells. The assumptions that form the foundation of the mathematical models are: the H2S concentration is uniform throughout the gas flow, the gas flow is constant, and the column's temperature is constant at a specific height.
Results and Discussion
In the beginning, biochar was used as a substrate in the biofilter to test its effectiveness, and the results obtained for removing H2S from the biogas were acceptable. H2S concentration in biogas was significantly reduced using biochar beds. It dropped from 300 ppm and 200 ppm to 50 ppm where the greatest H2S concentration reduction was achieved. The level of Methane in the biogas was not significantly impacted by the biofilter. This is regarded as a significant outcome when taking into account the goal which is producing biogas with a high concentration of methane. The H2S elimination effectiveness was 94% with the biochar bed and
Maize is one of the most important cereal crops worldwide, providing staple food for people globally. Counting maize tassels provides essential information about yield prediction, growth status, and plant phenotyping, but traditional manual approaches are expensive and time-consuming. Recent developments in technology, including high-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs) and advanced machine-learning techniques such as deep learning (DL), have been used to analyze genotypes, phenotypes, and crops.
In this study, we modified the YOLOv5s single-stage object detection technique based on a deep convolutional neural network and named it MYOLOv5s. We incorporated BottleneckCSP structures, Hardswish activation function, and two-dimensional spatial dropout layers to increase tassel detection accuracy and reduce overfitting. Our method's performance was compared with three state-of-the-art algorithms: Tasselnetv2+, RetinaNet, and Faster R-CNN. The results obtained from our proposed method demonstrate the effectiveness of MYOLOv5s in detecting and counting maize tassels.
Simulation of Heat and Mass Transfer in a Refractance Window Dryer for Aloe v...J. Agricultural Machinery
Drying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the drying process. However, this approach consumes time and cost, with a significant amount of energy resources. By harnessing available software and leveraging technological advancement to develop a general model for drying food under varying initial conditions, the drying process can be significantly optimized.
Evaluation of the Energy Efficiency of a Solar Parabolic Collector Equipped w...J. Agricultural Machinery
With increasing the world's population, the demand for supply water resources is also increasing. Nevertheless, climate change has severely impacted the accessibility of fresh water resources. Consequently, researchers have been focusing on producing drinkable water from seas and oceans. Iran, with its significant levels of solar radiation and access to open water from the north and south, is an ideal country for fresh water production. Using solar water desalination systems is a reliable and cost-effective solution for producing drinking water from salt water sources. The purpose of this research is to enhance the performance of the solar water desalination system by using the latent heat storage system and a solar tracking system. In this experimental setup for fresh water production, water was used as the working fluid, while a parabolic collector functioned as the source of thermal energy.
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Evaluation and Optimization of Energy and Environmental Indicators Using Life...J. Agricultural Machinery
Introduction: Environmental crises and resource depletion have adversely affected environmental resources and food security in the world. Therefore, with the global population growth in the coming years and the rising need to produce more food, attention must be given to environmental issues, energy consumption, and sustainable production. The purpose of this study is to evaluate the pattern of energy consumption, environmental impacts, and optimization of the studied energy indicators in dairy cattle breeding industrial units in Khuzestan province, Iran.
Materials and Methods: This research was conducted in Khuzestan province, located in the southwest of Iran. Energy indicators including energy ratio, energy efficiency, specific energy, and net energy were used to determine and analyze the relationships between the output and input energy. Additionally, the life cycle assessment methodology was used to assess the environmental impact. Life cycle assessment includes a goal statement, identification of inputs and outputs, and a system for assessing and interpreting environmental impacts, and can be a good indicator for assessing environmental issues related to production. The life cycle assessment method used in this study was CML-IA baseline V3.05, which includes the four steps of (1) selecting and classifying impact categories, (2) characterizing effects, (3) normalizing, and (4) weighting. Overall, 11 impact groups were studied. The Data Envelopment Analysis (DEA) method with the Anderson-Peterson model was used for optimization. This method identifies the most efficient production unit and makes it possible to rank all of the farms in the region. In this study, each production unit (farm) was considered a decision-making unit (DMU), and its production efficiency was determined based on two models. Namely, the Charnes, Cooper, and Rhodes (CCR) model also known as Constant Return to Scale (CRS), and the Banker, Charnes, and Cooper (BCC) model also known as Variable Return to Scale (VRS).
Results and Discussion: The results showed that the input and output energies per cow per day were 173.34 and 166 MJ, respectively. Livestock feed and electricity accounted for 65.47% and 27.2% of the input energy, respectively, while the oil used for tiller-scraper lubrication of fertilizer collection accounted for only 0.01%, making it the lowest input energy. Energy efficiency, specific energy, and net energy were calculated as 0.95, 0.13 kg MJ-1, 7.51 MJ kg-1, and -7.20 MJ per cow, respectively. In the abiotic depletion impact group, animal feed, machinery, and livestock equipment had the highest environmental impacts. The results showed that animal feed had the highest environmental emissions in all impact groups except for abiotic depletion of fossil fuels where electricity had the greatest effect. CRS model determined that 7 units were efficient; with an average efficiency of 0.78. In the BCC model, 20 production units were calculated as highly efficient,
Balancing Time and Cost in Resource-Constrained Project Scheduling Using Meta...J. Agricultural Machinery
Agricultural production involves a series of tasks including tillage, planting, and harvesting, which must be done at the right time for each region and type of product. Failing to complete these tasks on time can lead to a decrease in yield. Farmers may wrongly attribute this to factors such as infertile land, pests, diseases, and uneven rainfall distribution. However, this decrease in yield may not always be evident or tangible. To avoid such losses and unforeseen expenses, it is crucial to plan agricultural mechanization projects using the principles of project control. Agricultural projects, like industrial projects, must be carried out in the correct order and at the right time to achieve optimal results. Given the limited availability of resources for mechanization projects, it is imperative to meticulously plan activities to ensure that they are carried out on time and with maximum utilization of resources. To address these challenges, researchers have used meta-heuristic methods in project control, such as the colonial competition algorithm, which has been proven effective in solving the issue of scheduling projects with limited resources. The algorithm has been tested across various industrial activities and projects, and its performance in scheduling the Resource-Constrained Project Scheduling Problem (RCPSP) has been validated by researchers globally.
On the field and in the paddy milling factory dryer losses have always been challenging issues in the rice industry. Different forms of losses in brown rice may occur depending on the field and factory conditions. To reduce the losses, proper management during pre-harvest, harvesting, and post-harvest operations is essential. In this study, different on-field drying and tempering methods were investigated to detect different forms of brown rice losses
Nitrogen (N) is one of the main limiting factors in agroecosystems all around the world. However, high application rates of N fertilizers would lead to negative environmental consequences. Reduction of N fertilizers consumption decreases production costs and environmental pollution. Therefore, N efficiency to be enhanced due to the high N fertilizer cost and required measures to prevent the waste of N. Cultivation of diverse crop cultivars with higher resources absorption and utilization efficiency is one of the major approaches in sustainable agriculture that would result in the effective use of natural and chemical inputs and reduce significantly the environmental risks. Quchan City is one of the potato production poles in Khorasan Razavi province. In this region, large amounts of N fertilizers annually are consumed in the potato agroecosystem. Therefore, the potato of the present study was evaluating N uptake and utilization efficiency, and finally, N uses efficiency in the potato agroecosystem of Quchan.
Design of a Harvester for Harvesting of the Leaves and Stems of Plants in Cul...J. Agricultural Machinery
The world today is facing the issue of population growth, which will result in food shortages. One way to supply food to this growing population is to facilitate the production of agricultural products to meet the growing demand. Medicinal plants are an important product of the agricultural sector. In Iran, manual harvesting reduces the productivity of these crops, and the use of manual harvesting poses challenges related to available manpower. The costs and time required for manual harvesting are additional obstacles. Given the importance of developing medicinal plants, designing and constructing a mechanized machine for harvesting them could improve the harvesting process.
Modeling and Fabrication of a Robot for Sowing in a Seedling Tray (Case Study...J. Agricultural Machinery
Adopting new technologies for crop growth has the characteristics of improving disaster resistance and stress tolerance, ensuring stable yields, and improving product quality. Currently, the cultivation of seed trays relies on huge labor power, and further mechanization is needed to increase production. However, there are some problems in this operation, such as the difficulty of improving the speed of a single machine, seedling deficiency detection, automatic planting, and controlling the quality, which need to be solved urgently. To solve these problems, there are already some meaningful attempts. Si et al. (2012) applied a photoelectric sensor to a vegetable transplanter, which can measure the distance between seedlings and the movement speed of seedlings in a seedling guide tube, to prevent omission transplantation. Yang et al. (2018) designed a seedling separation device with reciprocating movement of the seedling cup for rice transplanting. Tests show that the structure of the mechanical parts of the seedling separation device meets the requirements of seed movement. The optimization of the control system can improve the positioning accuracy according to requirements and achieve the purpose of automatic seedling division. Chen et al. (2020) designed and tested of soft-pot-tray automatic embedding system for a light-economical pot seedling nursery machine. The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%. The successful tray embedding rate was 100% and the seed exposure rate was less than 1% with a linear velocity of the conveyor belt of 0.92 m s-1. The experiment findings agreed well with the analytical results.
Despite the sharp decline in Iran's water resources and growing population, the need to produce food and agricultural products is greater than ever. In the past, most seeds were planted directly into the soil, and many water resources, especially groundwater, were used for direct seed sowing and plant germination. One way to reduce the consumption of water, fertilizers, and pesticides is to plant seedlings instead of direct seed sowing. Therefore, the purpose of this study was dynamic modeling and fabrication of seed planting systems in seedling trays.
The growing importance of energy resources in the formation and growth of economic processes, as well as the need to exploit these resources based on environmental considerations and sustainable economic development, the issue of energy saving as an important issue in all economic infrastructures, including industry. Global warming, declining crop yields, climate change and acid rain are the result of fossil fuel consumption. Hence, in recent years, there has been a growing global emphasis on renewable energy across both developed and developing nations. The primary objective is to decrease reliance on conventional energy sources, mitigate environmental pollution, and attain sustainable energy practices.
Simulation of Natural Frequencies of Orange Fruit Using Finite Element MethodJ. Agricultural Machinery
The growing consumer demand for high-quality products has led to the development of new technologies for assessing the quality of agricultural products. Iran is the 9th largest orange producer in the world. Every year, large quantities of agricultural products lose their optimal quality due to mechanical and physical damage during various operations such as harvesting, packaging, transportation, sorting, processing, and storage. This study is performed to identify the natural frequencies and vibration modes of the Thomson orange fruit using finite element modal analysis by ANSYS software. In addition, physical properties including mass, volume, density, and principal dimensions were measured, and mechanical properties were determined using Instron Texture Profile Analysis. The dynamic behavior of the orange fruit was simulated using the pendulum impact test. Afterward, the obtained impact was applied to the orange fruit by force gauge and three-axis accelerometer sensors in both polar and equatorial directions. The three-dimensional geometric model of the orange fruit was drawn in the ANSYS software. After meshing and applying the boundary conditions, the first 20 modes and corresponding natural frequencies were obtained. Since the objective of this study was to identify the natural frequencies of the orange fruit, it was considered to have free movement and rotation in space. The results showed that the natural frequencies of orange fruit are in the range of 0 to 248.41 Hz. Knowledge of the texture characteristics and dynamic behavior of horticultural products is essential for the design and development of agricultural machinery. Furthermore, the design and development of agricultural machinery are directly related to the biological properties of agricultural products.
In the pursuit of a resilient and progressive agricultural system, the incorporation of diverse fertilizers is deemed essential. This practice not only enhances product quality but also aids in cost reduction. However, over-reliance on a specific type of input can inadvertently lead to unintended repercussions. The unrestricted utilization of chemical fertilizers, for instance, can precipitate adverse outcomes such as imbalanced pH levels, the accumulation of heavy elements, soil structure deterioration, and environmental contamination. Conversely, organic fertilizers, while environmentally friendly, often release nutrients at a slower rate, potentially disrupting optimal plant growth. To attain a balanced and sustainable agricultural approach, the combined application of organic and chemical fertilizers is advocated. Moreover, harnessing the biological potential inherent in soil ecosystems, including beneficial microbial communities encompassing bacteria and fungi, emerges as a promising avenue in cultivating sustainable agriculture. Acknowledging the adverse impact of late-season heat stress on wheat production in Khuzestan and recognizing the significance of reducing chemical fertilizer usage while augmenting organic and biological fertilizers to foster ecological health, this experiment undertakes the exploration of the effects of a synergistic approach. Specifically, it delves into the combined utilization of nitrogen and compost fertilizers, complemented by the incorporation of plant growth-promoting rhizobacteria. This endeavor aims to shed light on how this combined strategy operates within the context of terminal heat stress, assessing its influence on the physiological attributes and yield of the wheat cultivar Chamran 2.
Detection of Different Percentages of Palm in Corn Oil with the Help of an El...J. Agricultural Machinery
The use of corn oil in diets is due to its positive effects on cardiovascular and immune systems. Corn oil is composed of 99% triacylglycerol, with 59% unsaturated fatty acids and 13% saturated fatty acids. Of the unsaturated fatty acids, 24% contain a double bond. Because of this composition, corn oil can be a good alternative to other oils high in saturated fatty acids, as it reduces blood cholesterol levels.
This study employed an electrical nasal system to detect the amount of palm oil present in corn oil. The properties extracted from the signals obtained by the device were processed using principal component analysis, artificial neural networks, infusion, and response surface methods. The results were then compared to find the best method for detecting palm oil levels in corn oil.
Global warming directly affects agricultural production and food security (Ainsworth & Ort, 2010). Temperature controls the rate of plant metabolic processes that ultimately affect biomass production and grain yield (Hay & Walker, 1981). Although farmers are not able to control the climatic conditions, management and changes in factors such as irrigation, soil, crop varieties, activities, and technologies used in the cultivation of crops can reduce the harmful effects of climate change (Moradi et al., 2014). One of the reliable approaches to studying the effects of climate change on agricultural production is using crop growth models. The present study was conducted to simulate the effects of climate change on phonological stages and yield of maize and to investigate the possibility of mitigating the negative effects of climate change on maize by changing the sowing date and selecting suitable cultivars as management strategies for adaptation to climate change in Kermanshah region.
The excessive use of chemical fertilizers is a leading cause of environmental pollution in the agriculture sector. Therefore, optimizing fertilizer application is a crucial approach to boost production while minimizing environmental harm. On the other hand, application of chemical fertilizers along with manure can be considered as the proper management system that led to reduce the amount of chemical fertilizers and adverse effects on environment and also improve nutrition for plants. Response-surface methodology is a powerful tool to optimize production resources which decreases cost and time of the experiments by reducing number of them. Therefore, the aim of the study was optimization of chemical fertilizers of nitrogen and phosphorus along with manure application in fodder maize production.
The excessive use of chemical fertilizers is a leading cause of environmental pollution in the agriculture sector. Therefore, optimizing fertilizer application is a crucial approach to boost production while minimizing environmental harm. On the other hand, application of chemical fertilizers along with manure can be considered as the proper management system that led to reduce the amount of chemical fertilizers and adverse effects on environment and also improve nutrition for plants. Response-surface methodology is a powerful tool to optimize production resources which decreases cost and time of the experiments by reducing number of them. Therefore, the aim of the study was optimization of chemical fertilizers of nitrogen and phosphorus along with manure application in fodder maize production.
The development process of organic cultivation in Iran is not favorable because the average growth rate of organic agriculture development from 2008 to 2019 according to FAO statistics in 2021 is equal to -0.47% and this is while foods contaminated with various substances Chemicals have an unpleasant effect on the general health of society. According to the statistics of 2021, 600 million people in the world, i.e. 1 out of every 10 people, will get sick after eating food. Since any change in the use of chemicals in agriculture should be based on the behavior of farmers, the purpose of this study is to investigate the behavioral intention to produce organic pistachio production among 5200 pistachio growers in Ardakan county, Yazd province, using the Decomposed Theory of Planned Behavior (DTPB) analysis.
Analysis of Workspace and Kinematics of Robot Manipulator for Product Handlin...J. Agricultural Machinery
Robots have been used for material handling for many years, and their applications have greatly expanded with the integration of intelligent technologies. While numerous researchers have proposed various robots for this field, it is crucial to design customized configurations that are suitable for agricultural farms. However, research in our country has been limited to a few mobile agricultural robots. The main focus of this paper is to design and model workspaces and analyze the kinematics of manipulators in agricultural settings.
In recent decades, the need for increased food production has resulted in the expansion of intensified agriculture practices characterized by high consumption of inputs, thereby reducing agricultural sustainability. The agricultural sector's contribution to the world's energy consumption, ecological footprint, and greenhouse gas emissions has grown substantially. Emissions of greenhouse gases have negative ecological effects, including climate change, global warming, and diminished sustainable development. In this sector, energy analysis and greenhouse gas emissions in ecosystems are the most common methods for assessing sustainability. This study was conducted to evaluate the sustainability of canola agroecosystems by analyzing energy consumption, carbon footprint, and greenhouse gas emissions.
Evaluation of Two Types of Cotton Pickers in Terms of the Functionality and Q...J. Agricultural Machinery
Cotton, as one of the most widely used products in various industries, has always been considered by leading countries in agriculture. The applications of this plant range from the food industry to the military industry, as well as the textile and animal nutrition industry. It is predicted that by 2025, the area under cotton cultivation in the world will reach more than 33 million hectares (FAO, 2017). Based on the growing population, it is necessary to use machines in industries and other sectors to accelerate production and increase efficiency. Cotton is no exception to this rule. The use of a machine can play an effective role in reducing harvest costs and decreasing losses from frost and early fall rainfall by enabling timely harvesting.
Experimental Study and Mathematical Modeling of Hydrogen Sulfide Removal from...J. Agricultural Machinery
Introduction
Anaerobic bacteria break down organic materials like animal manure, household trash, plant wastes, and sewage sludge during the anaerobic digestion process of biological materials and produce biogas. One of the main issues in using biogas is hydrogen sulfide (H2S), which can corrode pipelines and engines in concentrations between 50 and 10,000 ppm. One method for removing H2S from biogas with minimal investment and operation costs is biofiltration. Whether organic or inorganic, the biofilter's bed filling materials must adhere to certain standards including high contact surface area, high permeability, and high absorption. In this study, biochar and compost were used as bed particles in the biofilter to study the removal of H2S from the biogas flow in the lab. Afterward, kinetic modeling was used to describe the removal process numerically.
Material and Methods
To remove H2S from the biogas, a lab-sized biofilter was constructed. Biochar and compost were employed separately as the material for the biofilter bed. Because of its high absorption capacity and porosity, biochar is a good choice for substrate and packed beds in biofilters. The biochar pieces used were broken into 10 mm long cylindrical pieces with a diameter of 5 mm. Compost was used as substrate particles because it contains nutrients for microorganisms. Compost granules with an average length of 7.5 mm and 3 mm in diameter were used in this study. For the biofilter reactor, each of these substrates was put inside a cylinder with a diameter of 6 cm and a height of 60 cm. The biofilter's bottom is where the biogas enters, and its top is where it exits. During the experiment, biogas flowed at a rate of 72 liters per hour. Mathematical modeling was used to conduct kinetic studies of the process to better comprehend and generalize the results. This method involves feeding the biofilter column with biogas that contains H2S while the biofilm is present on the surface of the biofilter bed particles. The bacteria in the biofilm change the gaseous H2S into the harmless substance sulfur and store it in their cells. The assumptions that form the foundation of the mathematical models are: the H2S concentration is uniform throughout the gas flow, the gas flow is constant, and the column's temperature is constant at a specific height.
Results and Discussion
In the beginning, biochar was used as a substrate in the biofilter to test its effectiveness, and the results obtained for removing H2S from the biogas were acceptable. H2S concentration in biogas was significantly reduced using biochar beds. It dropped from 300 ppm and 200 ppm to 50 ppm where the greatest H2S concentration reduction was achieved. The level of Methane in the biogas was not significantly impacted by the biofilter. This is regarded as a significant outcome when taking into account the goal which is producing biogas with a high concentration of methane. The H2S elimination effectiveness was 94% with the biochar bed and
Maize is one of the most important cereal crops worldwide, providing staple food for people globally. Counting maize tassels provides essential information about yield prediction, growth status, and plant phenotyping, but traditional manual approaches are expensive and time-consuming. Recent developments in technology, including high-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs) and advanced machine-learning techniques such as deep learning (DL), have been used to analyze genotypes, phenotypes, and crops.
In this study, we modified the YOLOv5s single-stage object detection technique based on a deep convolutional neural network and named it MYOLOv5s. We incorporated BottleneckCSP structures, Hardswish activation function, and two-dimensional spatial dropout layers to increase tassel detection accuracy and reduce overfitting. Our method's performance was compared with three state-of-the-art algorithms: Tasselnetv2+, RetinaNet, and Faster R-CNN. The results obtained from our proposed method demonstrate the effectiveness of MYOLOv5s in detecting and counting maize tassels.
Similar to A Multi-Objective Optimization to Determine The Optimal Patterns of Sustainable Agricultural Mechanization Using NSGA-II Algorithm (20)
Simulation of Heat and Mass Transfer in a Refractance Window Dryer for Aloe v...J. Agricultural Machinery
Drying is one of the oldest methods of food preservation. To increase the efficiency of heat and mass transfer while maintaining product quality, the study of the drying process is crucial scientifically and meticulously. It is possible to conduct experimental tests, trial and error, in the drying process. However, this approach consumes time and cost, with a significant amount of energy resources. By harnessing available software and leveraging technological advancement to develop a general model for drying food under varying initial conditions, the drying process can be significantly optimized.
Evaluation of the Energy Efficiency of a Solar Parabolic Collector Equipped w...J. Agricultural Machinery
With increasing the world's population, the demand for supply water resources is also increasing. Nevertheless, climate change has severely impacted the accessibility of fresh water resources. Consequently, researchers have been focusing on producing drinkable water from seas and oceans. Iran, with its significant levels of solar radiation and access to open water from the north and south, is an ideal country for fresh water production. Using solar water desalination systems is a reliable and cost-effective solution for producing drinking water from salt water sources. The purpose of this research is to enhance the performance of the solar water desalination system by using the latent heat storage system and a solar tracking system. In this experimental setup for fresh water production, water was used as the working fluid, while a parabolic collector functioned as the source of thermal energy.
Design, Construction, and Optimization of Performance of Electrodynamic Spray...J. Agricultural Machinery
Due to the increasing need for agricultural products, protection of products against pathogens and preventing them from being wasted is important. Studies on droplet charging systems result in the reduction of chemical usage and an increase in the deposition of droplets on the target. Conventional sprayers used in Iran have numerous disadvantages such as drift, environmental pollution, lack of complete and homogeneous coverage of the spraying surface, phytotoxicity, and crop losses. Therefore, evaluation of new spraying methods and using a variety of electrical sprayers as alternatives to conventional spraying is essential. This study aims to design, construct, and optimize the performance of the electrodynamic head of an atomizer motorized knapsack sprayer, and study the effects of the angle of the target position, spraying distance, and wind speed on the performance of the electrodynamic sprayer.
Performance Evaluation of the UAV Sprayer in Controlling Brevicoryne Brassica...J. Agricultural Machinery
About 30% of the annual losses of agricultural products are caused by pests, diseases, and weeds. Spraying is currently the most common method of their control. At present, various manual and tractor-mounted sprayers are used for spraying. Manual spraying has very low work efficiency and is damaging as the spray might be applied irregularly and consumed by the labor or the product at poisonous levels. Tractor-mounted sprayers are more efficient than manual sprayers and require less labor. However, their use is associated with issues such as compacting the soil or crushing the product. In recent years, Unmanned Aerial Vehicle (UAV) sprayers have been used to spray farms and orchards. UAV spraying can increase the spraying efficiency by more than 60% and reduce the volume of spray used by 20-30%. Based on the capabilities of the UAV sprayer and the limitations of other current spraying methods, the purpose of this research is to evaluate the performance of the UAV sprayer in controlling Brevicoryne brassicae (L.) and compare the results with a turbo liner sprayer.
Rapid and Non-destructive Estimation of Apple Tree NPK Contents based on Leaf...J. Agricultural Machinery
Apple is one of the most frequently consumed fruits in the world. It is a source of minerals, fiber, various biological compounds such as vitamin C, and phenolic compounds (natural antioxidants). The amount of nutrients plays a significant role in the growth, reproduction, and performance of agricultural products and plants. Chemical inputs can be accurately managed by predicting these elements. Thus, timely and accurate monitoring and managing the status of crop nutrition is crucial for adjusting fertilization, increasing the yield, and improving the quality. This approach minimizes the application of chemical fertilizers and reduces the risk of environmental degradation. In crop plants, leaf samples are typically analyzed to diagnose nutrient deficiencies and imbalances, as well as to evaluate the effectiveness of the current nutrient management system. Therefore, the main aim of this study is to estimate the level of Nitrogen (N), Phosphorus (P), and Potassium (K) elements in the leaves of the apple tree using the non-destructive method of Visible/Near-infrared (Vis/NIR) spectroscopy at the wavelength range of 500 to 1000 nm coupled with chemometrics analysis.
Cold Plasma Technique in Controlling Contamination and Improving the Physiolo...J. Agricultural Machinery
Today, almost half of the total human food, especially in Asia, is directly supplied from grains, and nearly 70% of the cultivated area of the world, which is one billion hectares, is used for growing grains. Therefore, non-destructive methods must be found and developed to increase seed quality in agriculture and industry. Cold plasma is a novel and efficient method that can be used in the agricultural and food sectors for the inactivation of surface microorganisms and the excitation of seeds. This review presents a summary of the effectiveness of cold plasma treatment on the characteristics of four important cereal plants: wheat, rice, corn, and barley. The focus is on the effects of this treatment on seed germination, surface property changes, water uptake of seeds, growth parameters of root, shoot, and seedling length, biomass parameters, and metabolic activities. By examining the research conducted by the researchers, it can be seen that the cereal seeds treated with cold plasma had better germination power, water absorption, shoot length, growth efficiency, shoot and root weight, and metabolic activity. This review can provide insight into the promising trends in utilizing plasma as a method to decrease the prevalence of harmful plant diseases transmitted through seeds and reduce the dormancy of hard seeds.
Modeling Soil Pressure-Sinkage Characteristic as Affected by Sinkage rate usi...J. Agricultural Machinery
Due to the numerous variables that may influence the soil-machine interaction systems, predicting the mechanical response of soil interacting with off-road traction equipment is challenging. In this study, deep neural networks (DNNs) are chosen as a potential solution for explaining the varying soil sinkage rates because of their ability to model complex, multivariate, and dynamic systems. Plate sinkage tests were carried out using a Bevameter in a fixed-type soil bin with a 24 m length, 2 m width, and 1 m depth. Experimental tests were conducted at three sinkage rates for two plate sizes, with a soil water content of 10%. The provided empirical data on the soil pressure-sinkage relationship served as the basis for an algorithm capable of discerning the soil-machine interaction. From the iterative process, it was determined that a DNN, specifically a feed-forward back-propagation DNN with three hidden layers, is the optimal choice. The optimized DNN architecture is structured as 3-8-15-10-1, as determined by the Grey Wolf Optimization algorithm. While the Bekker equation had traditionally been employed as a widely accepted method for predicting soil pressure-sinkage behavior, it typically disregarded the influence of sinkage velocity of the soil. However, the findings revealed the significant impact of sinkage velocity on the parameters governing the soil deformation response. The trained DNN successfully incorporated the sinkage velocity into its structure and provided accurate results with an MSE value of 0.0871.
A Finite Element Model of Soil-Stress Probe Interaction under a Moving Rigid ...J. Agricultural Machinery
Machinery traffic is associated with the application of stress onto the soil surface and is the main reason for agricultural soil compaction. Currently, probes are used for studying the stress propagation in soil and measuring soil stress. However, because of the physical presence of a probe, the measured stress may differ from the actual stress, i.e. the stress induced in the soil under machinery traffic in the absence of a probe. Hence, we need to model the soil-stress probe interaction to study the difference in stress caused by the probe under varying loading geometries, loading time, depth, and soil properties to find correction factors for probe-measured stress. This study aims to simulate the soil-stress probe interaction under a moving rigid wheel using finite element method (FEM) to investigate the agreement between the simulated with-probe stress and the experimental measurements and to compare the resulting ratio of with/without probe stress with previous studies. The soil was modeled as an elastic-perfectly plastic material whose properties were calibrated with the simulation of cone penetration and wheel sinkage into the soil. The results showed an average 28% overestimation of FEM-simulated probe stress as compared to the experimental stress measured under the wheel loadings of 600 and 1,200 N. The average simulated ratio of with/without probe stress was found to be 1.22 for the two tests which is significantly smaller than that of plate sinkage loading (1.9). The simulation of wheel speed on soil stress showed a minor increase in stress. The stress over-estimation ratio (i.e. the ratio of with/without probe stress) noticeably increased with depth but increased slightly with speed for depths below 0.2 m.
Optimization of the Mixing in a Gas-lift Anaerobic Digester of Municipal Wast...J. Agricultural Machinery
This research aims to optimize the mixing process in gas-lift anaerobic digesters of municipal sewage sludge since mixing and maintaining uniform contact between methanogenic bacteria and nutrients is essential. Wastewater municipal sludge sampling was performed at the Ahvaz West treatment plant (Chonibeh, Iran) during the summer of 2022. A Computational Fluid Dynamics (CFD) model was implemented to simulate, optimize, and confirm the simulation process using ANSYS Fluent software 19.0. The velocity of the inlet-gas into the digester was determined and a draft tube and a conical hanging baffle were added to the digester design. Different inlet-gas velocities were investigated to optimize the mixing in the digester. Furthermore, turbulence kinetic energy and other evaluation indexes related to the sludge particles such as their velocity, velocity gradient, and eddy viscosity were studied. The optimal inlet-gas velocity was determined to be 0.3 ms-1. The simulation results were validated using the Particle Image Velocimetry (PIV) method and the correlation between CFD and PIV contours was statistically sufficient (98.8% at the bottom corner of the digester’s wall). The results showed that the model used for simulating, optimizing, and verifying the simulation process is valid. It can be recommended for gas-lift anaerobic digesters with the following specifications: cylindrical tank with a height-to-diameter ratio of 1.5, draft tube-to-digester diameter ratio of 0.2, draft tube-to-fluid height ratio of 0.75, the conical hanging baffle distance from the fluid level equal to 0.125 of the fluid height, and its outer diameter-to-digester diameter of 2/3.
Investigating the Efficiency of Drinking Water Treatment Sludge and Iron-Base...J. Agricultural Machinery
In the quest for enhanced anaerobic digestion (AD) performance and stability, iron-based additives as micro-nutrients and drinking water treatment sludge (DWTS) emerge as key players. This study investigates the kinetics of methane production during AD of dairy manure, incorporating varying concentrations of Fe and Fe3O4 (10, 20, and 30 mg L-1) and DWTS (6, 12, and 18 mg L-1). Leveraging an extensive library of non-linear regression (NLR) models, 26 candidates were scrutinized and eight emerged as robust predictors for the entire methane production process. The Michaelis-Menten model stood out as the superior choice, unraveling the kinetics of dairy manure AD with the specified additives. Fascinatingly, the findings revealed that different levels of DWTS showcased the highest methane production, while Fe3O420 and Fe3O430 recorded the lowest levels. Notably, DWTS6 demonstrated approximately 34% and 42% higher methane production compared to Fe20 and Fe3O430, respectively, establishing it as the most effective treatment. Additionally, DWTS12 exhibited the highest rate of methane production, reaching an impressive 147.6 cc on the 6th day. Emphasizing the practical implications, this research underscores the applicability of the proposed model for analyzing other parameters and optimizing AD performance. By delving into the potential of iron-based additives and DWTS, this study opens doors to revolutionizing methane production from dairy manure and advancing sustainable waste management practices.
Dynamic Model of Hip and Ankle Joints Loading during Working with a Motorized...J. Agricultural Machinery
The main objective of this paper is to develop a seven-link dynamic model of the operator’s body while working with a motorized backpack sprayer. This model includes the coordinates of the sprayer relative to the body, the rotational inertia of the sprayer, the muscle moments acting on the joints, and a kinematic coupling that keeps the body balanced between the two legs. The constraint functions were determined and the non-linear differential equations of motion were derived using Lagrangian equations. The results show that undesirable fluctuations in the ankle force are noticeable at the beginning and end of a swing phase. Therefore, injuries to the ankle joint are more likely due to vibrations. The effects of engine speed and sprayer mass on the hip and ankle joint forces were then investigated. It is found that the engine speed and sprayer mass have significant effects on the hip and ankle forces and can be used as effective control parameters. The results of the analysis also show that increasing the engine speed increases the frequency of the hip joint force. However, no significant effects on the frequency of the ankle joint force are observed. The results of this study may provide researchers with insight into estimating the allowable working hours with the motorized backpack sprayers, prosthesis design, and load calculations of hip implants in the future.
Feasibility of Soil Texture Determination Using Acoustic Signal Processing of...J. Agricultural Machinery
Introduction
Precision agriculture is a modern approach to farming that ensures the crops and soil receive exactly what they need for optimum health and productivity. Precision agriculture offers the potential to automate and simplify the collection and analysis of information. It allows management decisions to be quickly made and implemented in small areas of larger fields. Measuring acoustic signals with a cone penetrometer is an advanced and inexpensive method that provides a lot of information about the soil within the shortest amount of time and with the lowest cost. The texture of the soil determines the percentage of the constituents of the mineral part of the soil such as sand, silt, and clay.
In this study, an acoustic penetrometer is developed to provide an accurate method for determining the soil texture. This system uses a microphone to record the sound produced by the cone-soil contact and correlates this data with the soil texture.
Materials and Methods
An acoustic cone penetrometer (ACPT) was designed to determine if there is a relationship between the sound produced at the cone-soil contact and soil particle size. Three types of cones with angles of 30, 45, and 60 degrees, diameter of 20.27 mm, and rod length of 300 mm according to ASAE standard S313.3 FEB1999ED (R2013) were used to determine the relationship between sound and soil texture and to choose the best angle. A microphone (20-20,000 Hz) suitable for fast dynamic responses was used to record the audio signals produced from the soil. Audio signals were stored online through the oscilloscope section of Matlab software. To create the controlled vertical movement of the cones, a mechanical mechanism with electronic controllers was designed. This mechanism can be connected to the rails of the soilbin available in Urmia University, Iran, and is made of a 5 hp electric motor with a gearbox, an inverter for controlling the rotational speed of the electric motor, and a digital ruler for recording vertical movement. Soil samples were tested in 19-liter bins.
Acoustic signals received from the microphone were processed in the time-frequency domain using wavelet transform. In this research, Daubechi function type 3 is used to analyze acoustic signals. It is not possible to use the processed acoustic signals directly for statistical analysis. Therefore, the relevant features should be extracted from them. From the 30 features of time domain signals, the most effective and main features include: SUM, Max, RMS, average, Var, kurtosis, and Moment4. They were ranked using the feature selection section of WEKA 3.9.2 software to avoid increasing the volume of calculations, increase processing speed, and reduce errors. The characteristic vector of the sub-signals of several different soil samples was analyzed to distinguish the soil type and constituents namely sand, silt, and clay.
Results and Discussion
The best type of cone was selected using WEKA software. The number of features in the
Fusion of Multispectral and Radar Images to Enhance Classification Accuracy a...J. Agricultural Machinery
Introduction
Remote sensing is defined as data acquisition about an object or a phenomenon related to a geographic location without physical. The use of remote sensing data is expanding rapidly. Researchers have always been interested in accurately classifying land coverage phenomena using multispectral images. One of the factors that reduces the accuracy of the classification map is the existence of uneven surfaces and high-altitude areas. The presence of high-altitude points makes it difficult for the sensors to obtain accurate reflection information from the surface of the phenomena. Radar imagery used with the digital elevation model (DEM) is effective for identifying and determining altitude phenomena. Image fusion is a technique that uses two sensors with completely different specifications and takes advantage of both of the sensors' capabilities. In this study, the feasibility of employing the fusion technique to improve the overall accuracy of classifying land coverage phenomena using time series NDVI images of Sentinel 2 satellite imagery and PALSAR radar imagery of ALOS satellite was investigated. Additionally, the results of predicted and measured areas of fields under cultivation of wheat, barley, and canola were studied.
Materials and Methods
Thirteen Sentinel-2 multispectral satellite images with 10-meter spatial resolution from the Bajgah region in Fars province, Iran from Nov 2018 to June 2019 were downloaded at the Level-1C processing level to classify the cultivated lands and other phenomena. Ground truth data were collected through several field visits using handheld GPS to pinpoint different phenomena in the region of study. The seven classes of distinguished land coverage and phenomena include (1) Wheat, (2) Barley, (3) Canola, (4) Tree, (5) Residential regions, (6) Soil, and (7) others. After the preprocessing operations such as radiometric and atmospheric corrections using predefined built-in algorithms recommended by other researchers in ENVI 5.3, and cropping the region of interest (ROI) from the original image, the Normalized Difference Vegetation Index (NDVI) was calculated for each image. The DEM was obtained from the PALSAR sensor radar image with the 12.5-meter spatial resolution of the ALOS satellite. After preprocessing and cropping the ROI, a binary mask of radar images was created using threshold values of altitudes between 1764 and 1799 meters above the sea level in ENVI 5.3. The NDVI time series was then composed of all 13 images and integrated with radar images using the pixel-level integration method. The purpose of this process was to remove the high-altitude points in the study area that would reduce the accuracy of the classification map. The image fusion process was also performed using ENVI 5.3. The support Vector Machine (SVM) classification method was employed to train the classifier for both fused and unfused images as suggested by other researchers.
To evaluate the effectiveness of image fusion, Comm
Environmental Impact Assessment of Electricity Generation in Wind Power Plant...J. Agricultural Machinery
Introduction
The world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly in light of the pressing need to mitigate environmental impact and promote the use of renewable energy. The purpose of this research is to investigate and compare the environmental effects of electricity production from two wind power plants, Aqkand and Kahak, using wind turbines with a capacity of 2.5 megawatts for a period of three different lifetimes (20, 25, and 30 years).
Materials and Methods
The present study investigates the environmental effects of electricity generation during the life cycle of wind farms (Kahak and Aqkand) during the construction and operation of these power plants and the cumulative exergy demand index. The specifications of the wind turbines used in the current research are: turbine capacity of 2.5 MW, rotor diameter of 103 meters, rotor weight of 56 tonnes, three blades, each blade is 50.3 meters long and weighs 34.8 tonnes. The turbines are manufactured by Mapna and used in dry conditions. A functional unit of one kilowatt of electricity was selected and the data were analyzed in SIMAPRO software using IMPACT2002+ method with 15 midpoint indicators and four final indicators.
Results and Discussion
The results showed that the stage of raw materials and production has the highest impact on the creation of midpoint indicators, which is due to extraction, manufacturing, and production of parts such as steel casting using non-renewable energy and activities such as high-temperature welding. The total environmental index of Aqkand and Kahak wind power plants for 1 kWh of generated electricity was 5.84 and 4.45 μPt respectively, more than half of which belongs to the damage to human health category. The investigation of the ionizing radiation index showed that the use of diesel fuel in the installation phase resulted in the highest amount of emissions in both of the power plants, so the share of pollutant emissions in the raw materials and production phase is more than 40%, and in the installation phase due to diesel fuel consumption was more than 48%. The investigation of the eutrophication index showed that the raw materials and production stage accounted for more than 95% of the damage to the ecosystem quality category, and in the meantime, copper and electrical components had the highest amount of contribution to the raw materials and production stage. Additionally, diesel fuel accounted for the largest part of the result in the installation stage, and the transportation and maintenance stage included less than 1% of this result. The investigation of the renewable energy consumption index showed that the stage of raw materials and turbine production in the Aqkand power plant with a share of 68% and the Kahak power plant wi
Development and Field Evaluation of a Variable-Depth Tillage Tool Based on a ...J. Agricultural Machinery
Soil compaction can be naturally occurred or can be machinery-induced. Subsoiling is often applied to loosen soil compaction and decrease soil strength to levels that allow for root development and growth. Variable-depth subsoiling which modifies the physical properties of soil only where the tillage is required for crop growth has the potential to reduce labor, costs and fuel, and energy requirements. Since this study aimed to perform subsoiling operations with variable depth, the variable-depth tillage (VDT) tool was developed. A pneumatic multi-nozzles sensor has been used to simultaneously predict the depth of a soil layer in three depths (15, 30, and 45 cm), and send a signal to control the depth of the VDT tool. Evaluation of the VDT tool system was performed by two methods namely static and dynamic tests. In static evaluation, the system response time was measured to reach 95% of the proposed depths. The dynamic evaluation of the tool was accomplished in two steps in the field. The amount of fuel consumption and the travel distance of the tool tine to reach the desired operation depth were measured and compared with the common subsoiler (when the depth control was OFF). The average fuel consumption by using the variable-depth tillage tool decreased by 17.36% compared to the constant depth. Furthermore, the pneumatic sensor tine penetrated into the soil perfectly and sent the control signal to the control unit of the VDT tool in real-time, and the VDT tool loosened the soil at the exact depths sent by the sensor.
Experimental Investigation of Performance and Emissions of a Compression Igni...J. Agricultural Machinery
This study presents the effects of compressed natural gas fuel on a four-cylinder compression ignition engine. Compressed natural gas as the main fuel and diesel fuel as the igniter were used to investigate performance and emissions from the dual fuel engine. According to the engine speed and load, the amount of diesel fuel as igniter was adjusted using mechanical changes in the governor, while no ignition system was used. The engine experimental tests were performed at engine speeds of 1200, 1400, 1600, 1800 and 2000 rpm, using diesel fuel and dual fuel. These data were collected in the Engine Research Center of Tabriz Motorsazan Company and experimental runs were repeated three times. The maximum torque of the engine in diesel mode was 360 N m at 1400 rpm. Compared to the diesel mode, the dual fuel mode showed the maximum torque by 334 N m at 1600 rpm, which is about 26 N m less than that gained from the diesel mode. Considering emissions analysis at 2000 rpm, it is seen that the amount of NOX, HC, CO2 and CO emissions in the dual fuel mode was 20, 53, 16 and 86% more than diesel mode, respectively. However, O2 and soot showed the highest reduction at 2000 rpm for dual fuel mode by 51% and 69% respectively. This study indicated that there was a considerable enhancement in exhausted emissions when the injection of the diesel fuel as igniter was done mechanically. In this regard, control the amount and time of the igniter injection could likely be helped for better control of emissions. Therefore, further research on the modification of the diesel injection system as igniter or CNG injection system is needed towards reducing emissions.
In this study, an electronic system was built to determine the mass and volume of orange fruits from their dimensions using ultrasonic sensors. The system hardware parts include a metal box, three ultrasonic sensors, a load-cell sensor, an Arduino board, a memory card module, a voltage converter, a keypad, a display and a power adapter. A computer program was written to obtain data from ultrasonic sensors and determine the mass and volume of fruits using regression relationships in Arduino software. 100 samples of orange fruits (Dezful local variety) were picked randomly from a garden and various measurements were done to determine the main physical properties of fruits including three dimensions, mass (M), and volume (V). The system output values for mass and volume of orange fruits with their actual values had no significant difference at 1% probability level. The root mean square error (RMSE) in determining the oranges mass and volume by the system were 9.02 g and 10.90 cm3, respectively. In general, the proposed system performance was acceptable and it can be used for determining the mass and volume of orange fruits.
Cold Plasma: A Novel Pretreatment Method for Drying Canola Seeds: Kinetics St...J. Agricultural Machinery
Accurate investigation of kinetics and development of high-precision seed drying models will help better studying the drying process by identifying effective parameters. Present study investigates the application of cold plasma (CP), as a pretreatment process, in air drying of canola seeds. This may bring about some complication into the drying kinetics investigation. Canola seeds with an initial moisture content of 27.5±1% (dry basis) were exposed to CP for 0, 15, 30, and 60 s prior to fluidization by air at temperatures of 40, 50 and 60 °C in a pilot scale fluidized bed heated by a solar panel. The results showed a decreasing trend in drying time from 40 to 60 oC. The shortest drying time corresponds to samples dried at 60 oC with no CP pretreatment. The longest period however occurred for samples dried at 40 oC with 60 s of CP pretreatment. The greatest effect of CP on reducing the drying time was observed at temperatures of 40 and 50 °C at the CP exposure time of 15 and 60 s, respectively. A reasonably accurate study of drying kinetics was accomplished using the superposition method. Accordingly, using experimental data, curves correspond to different drying conditions were plotted and in two steps these were shifted to a reference curve to acquire a final drying curve. The curve then was fitted to a second-order equation, and was validated using the experimental data. The correlation coefficients, mean square error and mean absolute error were 0.99, 0.03, and 0.023, respectively.
The main purpose of this study was to provide a method for accurately identifying the position of cucumber fruit in digital images of the greenhouse cucumber plant. After balancing the brightness histogram of the desired image, it multiplies the image with a window containing the image of a cucumber fruit, which causes larger coefficients to be obtained in areas with suspected cucumber. By extracting these local maximums, clusters of initial points are obtained as possible windows of cucumber existence. Then, in order to accurately detect the location of the cucumbers, these points and areas around them are referred to a neural network that has been trained using a number of images including cucumber images, non-cucumber images and their optimal responses. The proposed method was implemented in the Simulink toolbox of MATLAB software. The proposed method was then simulated using this network structure and tested on 120 images obtained from a greenhouse by a digital camera. The areas obtained from this network led to the accurate detection of the location of the cucumbers in the image. The proposed method was then simulated and tested on 120 images. The proposed method had a low error and was able to detect high levels of cucumber fruit in the images. This detection took an average of 5.12 seconds for each image. The accuracy of the network in correctly identifying the position of the cucumber fruit in the images was 95.3%. This method had low error and was able to detect a high rate at a good time of cucumber fruits in discover images.
The present study aimed to examine the application of accurate and principle-based evaluation of a measuring instrument called the Form Tester in determining and detecting the wear phenomenon in the cylinder liner of agricultural tractors. For this purpose, a cylinder liner of the Perkins 4-248 engine (related to the Massey Ferguson 285 tractor) was manufactured by Keyhan Sanat Ghaem Company was used. The geometric parameters that were measured in this research included roundness, straightness, and concentricity of the cylinder liner. The evaluations on roundness and concentricity of cylinder liner were conducted in 12 circular positions with the same longitudinal distances. The straightness was measured in five lines with the same longitudinal distances in 90° around the cylinder liner environment. The results of the measurements were discussed and analyzed to evaluate the engine status along the functional path of the piston within the cylinder liner. The degree of deviation rate of the parameters indicated significant wear within the cylindrical liner. The wear rate in cross-sections at high and low dead points was significantly greater than that of the same cross-section in the vicinity of the midpoint of the piston movement path inside the cylinder, as well as the cross-sections near the high dead point. The results of this research provide feedbacks for engine designers to apply various changes to the engine and for maintenance and repair engineers to ensure the correct implementation as well as preventive and predictive repair and maintenance strategies.
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challenges ever since. The cultivated area using this system was 43 hectares in 2019. Despite the speed and ease
of planting with this system, and its direct environmental benefits, the possibility of fungal outbreaks is raised
due to the presence of wheat residues from previous cultivation and the warm and humid environment of
cultivation. Additionally, weed outbreaks caused by periodic irrigation have greatly affected the satisfaction and
profitability of this system, leading to the highest amount of pesticides consumed among the studied systems.
The results of multi-objective optimization of sustainable rice mechanization systems in Ramhormoz city
showed that the total surface area of optimal point systems is in the range of 2700 to 3200 hectares, which is
close to the area under rice cultivation in Ramhormoz (3310 hectares) and it indicates that the output of the
model is according to the applied restrictions and close to reality. The limitation of machinery and water has
made the two planting systems of un-puddled transplanting and dry-seeding better than other systems. Removing
only the machinery restriction can lead to an increase in the area under rice cultivation by about 700 hectares.
This means that the requirement for the development of sustainable rice cultivation in Ramhormoz is to
strengthen and support modern mechanized systems of no-tillage, dry-seeding, and planting with puddling, with
a focus on systems with less water consumption which are the systems with higher levels of mechanization.
Without water limitation, if the model is subject to the current machinery limitations, the optimal mechanization
systems are the more traditional ones such as transplanting without puddling and wet-seeding.
Conclusion
One of the most fundamental challenges in the development of mechanization is identifying systems that can
best balance the economic, social, and environmental aspects of sustainability and minimize environmental
damage whilst maximizing economic and social benefits. Using the framework for sustainable mechanization
will not only accomplish sustainable goals in identifying the optimum agricultural mechanization level, but it
will also allow researchers and implementers in the agricultural sector to examine the outcome of various
scenarios under different constraints. This framework can be used to find the optimal model for mechanization of
all stages of tillage, planting, harvesting, and post-harvest in diverse geographical areas.
Keywords: Agricultural mechanization, Multi-objective optimization, Optimal pattern, Sustainability