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This research investigates how the integration of land consolidation and agricultural mechanization can enhance the technical efficiency, energy consumption, and environmental sustainability of paddy cultivation compared to conventional farming practices. Our primary objective is to assess whether consolidated and mechanized farming systems result in higher productivity and lower energy use, while also reducing environmental impacts such as greenhouse gas emissions, water consumption, and soil erosion. Conventional farming methods, characterized by fragmented land holdings, often lead to inefficiencies and environmental harm. By merging smaller plots into larger, contiguous fields, we aim to boost farming efficiency and facilitate the adoption of agricultural machinery. This study will analyze three distinct cultivation scenarios: i) conventional fragmented fields relying on manual labor, ii) integrated fields utilizing manual labor, and iii) integrated fields employing mechanization. We will evaluate key technical indicators, including crop yield, labor productivity, and crop quality, alongside energy consumption metrics like fuel and electricity usage. Furthermore, will assess the environmental implications of each scenario, focusing on greenhouse gas emissions, water usage, and soil erosion. The findings from this research will enhance our understanding of the combined effects of land consolidation and mechanization in paddy farming. Additionally, the insights gained will provide valuable guidance for policymakers and farmers, promoting sustainable practices in paddy cultivation that support food security while minimizing negative environmental impacts. This investigation aims to distinguish itself by examining the synergistic potential of land consolidation and mechanization, rather than considering them in isolation as has been done in previous studies.

This study proposes using input-output analysis to improve energy use efficiency and assess environmental indicators in soybean and peanut farming. The research findings show that soybean production consumes 43170.20 MJ ha−1 of total energy and yields 40417.28 MJ ha−1 of output energy, while peanut production requires 28677.36 MJ ha−1 of total energy and produces 28677.36 MJ ha−1 of output energy. The LCA results indicate that on-farm emissions are associated with production inputs for both soybean and peanut systems, with diesel fuel and chemical fertilizers being the main contributors. Soybean farming shows higher levels of diesel fuel pollutants due to reduced usage, while peanuts have a higher prevalence of contaminants associated with diesel fuel. Using ICA to calculate optimized energy consumption results in 36672.77 MJ ha−1 for soybean production and 23485.45 MJ ha−1 for peanut production, leading to energy savings of 6075.33 MJ ha−1 and 5191.91 MJ ha−1, respectively. Additionally, the environmental impact category quantities for ICA analysis of soybean and peanut production reveal the resources per ton for soybean production to be 111.25 USD2013 and for peanut production to be 45.43 USD2013 in terms of energy use. The use of ICA demonstrates potential in maximizing energy efficiency and evaluating environmental indicators in soybean and peanut farming. By optimizing resource allocation and decision-making processes, ICA can help farmers reduce energy consumption and minimize environmental impact, ultimately leading to more sustainable and eco-friendly farming practices that benefit both the environment and the agricultural industry. Further research and implementation of ICA in farming practices have the potential to significantly improve energy efficiency and environmental sustainability in the soybean and peanut farming industry.

Energy use efficiency is a measure of how efficiently energy is used in an agricultural production system. It considers the amount of energy inputs required to produce a given output, such as a unit of cumin or fennel. The province of Qazvin, Iran was selected for the study of the cultivation of medicinal plants in 2022. A life cycle assessment (LCA) is a comprehensive analysis of the environmental impact of a product or process throughout its entire life cycle, from raw material extraction to disposal. It considers the environmental impact of various stages, including production, transportation, use, and disposal, and assesses the impact on categories such as climate change, water use, and land use. The present study investigates energy use and environmental impacts of cumin and fennel production. The results showed that fennel had higher productive energy and that its energy output was 18206.04 MJ ha-1. The highest consumption of inputs, which was over 40%, was related to nitrogen fertilizers. The negative addition of net energy indicates that more care should be taken in medicinal plant farms as to how energy inputs, especially chemical fertilizers and diesel fuel, are consumed. LCA is a suitable instrument to investigate and quantify the environmental effects of agricultural products and food industries. The effects of environmental emissions of medicinal plant production were calculated as an important part of human health. The weighting results showed that the human health category has more environmental emissions for both crops

This study aims to examine the energy use efficiency and conduct an environmental life cycle assessment (LCA) of the production of cumin and fennel using artificial intelligence (AI). The energy consumption for fennel and cumin is 34814.81 MJ ha−1 and 26214.17 MJ ha−1, respectively. The energy ratio for cumin is 0.66, indicating a substantial energy consumption per unit of output energy. Specifically, it takes 22.36 MJ of energy to produce 1 kg of cumin. Both crops exhibit a negative net energy balance. The results of the LCA analysis revealed three key findings when comparing the environmental emissions of cumin and fennel. Firstly, in the context of cumin cultivation, the environmental emissions related to human health were found to be 0.15 DALY. Secondly, there were no significant variations in the environmental emissions of medicinal plants when considering ecosystems. Finally, fennel production exhibited 237.77 USD2013 environmental publications in the resource category. It is worth noting that a substantial portion of the emissions in all three categories of medicinal plants can be attributed to direct emissions from crop cultivation. Additionally, nitrogen plays a significant role in emissions after the direct emissions occur. In comparison to fennel, cultivating cumin is recommended as it helps decrease environmental emissions and minimizes harm to water, air, and soil. The ANN model achieved a determination coefficient greater than 0.93 for four factors related to cumin cultivation in test mode. Similarly, the determination coefficient for output energy in fennel cultivation was found to be 0.852. However, the results indicate that the ANFIS test model outperformed the ANN model in terms of performance and accuracy. The ANFIS model exhibited an average detection coefficient of 0.95 for cumin cultivation and 0.93 for fennel cultivation, highlighting its superior performance compared to the ANN model. The application of AI techniques provides valuable insights into the production of cumin and fennel, facilitating informed decision-making towards more sustainable practices in the spice industry.

Abstract Water scarcity threatens human life and it is likely to be a main concern in the next century. In this work, a novel multigeneration system (MGS) is introduced and assessed with energy, exergy, and economic analyses. This MGS includes a gas cycle, multieffect distillation, an absorption refrigeration cycle, a heat recovery steam generator, and electrodialysis. Electrodialysis is integrated into this configuration to produce sodium hydroxide and hydrogen chloride from brine to prevent its release to the environment with harmful impacts. The other products are electricity, cooling, and demineralized water. For the evaluation of the proposed system, one computer code is provided in engineering equation solver software. For physical properties calculation, the library of this software is used. The MGS produces 614.7 GWh of electrical energy, 87.44 GWh of cooling, 12.47 million m3 of demineralized water, and 0.092 and 0.084 billion kg of sodium hydroxide and hydrogen chloride over a year. Energy and exergy evaluations demonstrate that the MGS energy and exergy efficiencies are 31.3% and 18.7%, respectively. The highest and lowest value of exergy destruction rate is associated with the combustion chamber and pump, respectively. The economic evaluation indicates that the net present value of this proposed system is 3.8 billion US$, while the internal rate of return and payback period, respectively, are 0.49 and 2.1 years.

The use of energy efficient in agriculture is one of the important factors to achieve sustainable production in agriculture. Considering the limited resources and the importance of preventing the loss of resources, it is necessary to evaluate investment projects from an economic point of view This study applying life cycle assessment (LCA) of paddy production in Khuzestan province of Iran were studied, LCA is a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service. In this study, energy indicators, economic analysis and LCA of paddy production in Khuzestan province of Iran were studied. Paddy production in this province was analyzed under three scenarios of multiple cultivation system including (Paddy-Transplantation System) PTS, (Paddy-Flooding System) PFS and (Paddy- Drying System) PDS. The highest total input (79069.80 MJ ha−1) and output (105400 MJ ha−1) energies are related to PTS method. PDS method has the lowest energy production and consumption. Diesel fuel and nitrogen fertilizers consume a lot of energy. Electricity and water showed 13 % of energy consumption in PFS method. Depending on the type of cultivation in PDS method, human labor has a large share of energy. The results of benefit to cost ratio showed of PTS method (6.60) shows the high profit of rice production from the amount of cost. Categories of damage to human health, ecosystems and resources were reported according to ReCiPe2016 method for paddy production. The resource impact category for PDS (114.76), PFS (111) and PTS (102.60) USD2013 is the highest to the lowest, respectively. The categories of human health damage for PTS, PFS and PDS methods were 0.041, 0.04 and 0.05 DALY, respectively. The resource category accounts for a significant portion of environmental emissions. Results of CExD showed the non-renewable, fossil form has a significant value in PTS (12980.06), PFS (14215.41) and PDS (14544.40) MJ ton–1, also that nitrogen fertilizer and the use of machinery and diesel fuel have the greatest impact on energy forms.

The influence of non-cognitive factors, including sin, on human knowledge has become a matter of question in epistemology in recent decades. Religious and mystical texts of different cultures throughout history have emphasized that humans' existential realms are deeply interconnected. Masnavi-ye-Ma'navi is an important text that discusses the influence of sin on human knowledge. In Rumi's view, sin affects the hereafter and also our existence and rational faculties in this world. Rumi's emphasis is on the daily sins, not the original sin. According to him, sins affect knowledge by causing a person to lose mental concentration due to the sense of guilt he or she experiences after sinning. In addition, he believes that the damage done to moral virtues after sinning affects intellectual virtues and, therefore, human knowledge. While Mawlana holds that sin is effective on all types of human knowledge, both our knowledge of Divine and non-Divine realms, his emphasis is on the effect of sin on our knowledge of God and self-knowledge.