https://best.basu.ac.ir/ Biosystems Engineering and Sustainable Technologies en daily 1 Mon, 01 Dec 2025 00:00:00 +0330 Mon, 01 Dec 2025 00:00:00 +0330 https://best.basu.ac.ir/article_6275.html This review article provides a comprehensive analysis of wheat losses across the supply chain, from pre-harvest to post-harvest stages, and explores strategies to mitigate these losses to enhance global food security and sustainability. Wheat, a vital cereal crop, faces significant quantitative and qualitative losses due to factors such as pests, diseases, inefficient agricultural practices, inadequate storage, and environmental challenges. In developing countries, losses are predominantly concentrated at the farm level due to limited access to modern technologies and infrastructure, while developed countries experience higher losses during the consumption phase. The review highlights the importance ofadopting advanced technologies and sustainable practices to reduce losses. Mechanized harvesting, when properly calibrated, can minimize grain shedding and breakage, while modern storage solutions like expanded metal silos and controlled-environment systems can prevent spoilage and pest infestations. Solar-powered drying methods and biodegradable packaging materials offer environmentally friendly alternatives to traditional practices. Pre-harvest interventions, such as cultivating high-yielding and pestresistant seed varieties, optimizing planting practices, and improving soil health, are also critical for reducing losses at the source. Furthermore, the review emphasizes the need for integrated approaches, including farmer education, policy support, and cross-sector collaboration, to address wheat losses effectively. By implementing evidence-based solutions tailored to local contexts, stakeholders can enhance food availability, reduce economic pressures, and promote environmental sustainability. This review serves as a roadmap for minimizing wheat losses, ensuring a resilient and efficient supply chain, and contributing to global food security for future generations. https://best.basu.ac.ir/article_6277.html Contemporary agriculture faces a dual challenge: meeting the food demands of a growing population while mitigating its environmental footprint. Conventional farming machinery, despite its vital role in boosting productivity, contributes to irreversible ecological damage through greenhouse gas emissions and soil compaction. In this context, electric agricultural robots emerge as a transformative solution, offering three key advantages: eliminating direct pollutant emissions, significantly reducing carbon footprints, and optimizing energy consumption. These advanced technologies enable precise, controlled operations that maintain soil structure and microbial ecosystems while ensuring long-term agricultural sustainability. Critical operational parameters such as working speed and depth have been identified as decisive factors in energy efficiency—their optimization could mark a turning point in harmonizing high yields with sustainable practices. This technological shift not only addresses current environmental challenges but also establishes a new paradigm for agricultural mechanization, charting a sustainable future for the industry. A robot pulling a rotivator was simulated in MATLAB version R2022b software, and all the forces applied to the robot and rotivator were applied. To get the answer closer to reality, the soil was considered variable. The goal is to find the best working mode of the robot that has the lowest energy consumption. The highest amount of energy consumption was observed at high speeds (10 km/h). By increasing the depth of the rake from 5 to 10 cm, energy consumption increased by 19% on average. The largest amount of energy loss was included in the pseudo-made set of tires. About 40 to 45 percent of the total losses in the simulation set are assigned to tires. The findings showed that the depth of work has a greater effect on losses than the speed of movement. The intensity of the operation significantly affects the battery losses. In the lightest mode, the battery loss was 1.2 Wh/km and in the heaviest mode, the battery loss increased to 6.1 Wh/km. In general, it can be concluded that the robot should be used at a low depth and at low speeds in order to have the lowest amount of energy consumption. Less use of energy and renewable resources is essential to achieve sustainable development. https://best.basu.ac.ir/article_6388.html Long-term driving of Off-Road Vehicles increases the risk of damage to some organs of humans, such as the spinal column or digestive system. Whereas seat suspensions are used in heavy-duty off-road vehicles, adjusting the parameters of them is crucial. Recently, non-gradient optimization methods have been focused on by researchers to tune these parameters, such as spring constant, damper coefficient, and seat pan mass. Current work represents the application of two Meta-Heuristic techniques (Gravitational Search (GSA)and Fire Hawk Optimization Algorithms (FHOA)) to minimize transmitted vibration from the cabin floor to the seat pan. According to the GSA, the amplitude of seat displacement is around 2×10-5 (m). Moreover, the first peak is reached at 0.95×10-5 at 8Hz. In addition, according to the FHOA, the magnitude of output via FHOA optimum parameters is 0.8× 10-5, in the time domain. On the other hand,in the frequency domain, the first peak is gotten 4.2×10-6. So, it shows that the performance of passive seat suspension, which is adjusted with GSA, is more enhanced in comparison to FHOA. In conclusion, the outcomes of optimization via simulation show that GSA has a better performance compared to FHOA, and the seat suspension tuned by that can diminish the vibration with notable diminishment. https://best.basu.ac.ir/article_6389.html  This paper is a case study on auditing energy and water used in greenhouse-grown cucumber production. The study has been done under real conditions in Hamedan a western province of Iran with harsh winters. Here, all the procedures of production from land preparation to harvest and finally the removal of residues were recorded. The fruit produced per square meter of covered area was 10.07 kg m-2. Moreover, the parameters of energy consumption, energy output, net energy gain, specific energy, energy productivity, and energy use efficiency were 5.05 MJ, 18,560 MJ, -5.03 MJ, 217.60 MJ kg-1, 0.0046 kg MJ-1, and 0.0037, respectively. Water productivity was also 39.42 kg m-3. The indicators obtained in this study showed the effect of surrounding environmental parameters on the performance in comparison with the literature. Additionally, it is estimated that to provide solar-based electricity for this greenhouse, roughly 110 square meters of solar panels are required. https://best.basu.ac.ir/article_6464.html A mesophilic co-digestion of sugarcane straw and sewage sludge with long hydraulic retention time in lab-scale reactors has been studied. Anaerobic biodegradability was examined in a biochemical methane potential (BMP) testing apparatus using 500 ml bottles. Both the design of the experiment method and the I-optimal mixture design were used as a mixed design strategy to systematically optimize the substrate composition ratios and elucidate the possible synergistic effects for an anaerobic co-digestion system. A reduced cubic model was created by Design-Expert software as a function of substrate composition ratios. The model was experimentally validated by the ANOVA method. Based on the observations, all linear impacts and interactions between substrates showed synergistic effects on the biogas production rate. The optimum proportions of the feedstock were 0.28% (w/w) of Primary sludge (A), 48.98% (w/w) of Secondary sludge (B), and 50.73% (w/w) of sugarcane straw (C). Also, according to the aforementioned optimum proportions, cumulative biogas reaches the maximum level of 8.581 L during 150 days. https://best.basu.ac.ir/article_6465.html Farm soil density affects the energy consumption of agricultural machinery and implements, root growth, and thus crop yield. Pre-compaction stress is one of the most important criteria for assessing soil compaction. The purpose of this study was to investigate the compaction behavior of a crop soil with sandy, clayey, and loamy textures during two tests of plate sinkage and compactness and They were simulated with Mohr-Columb and Drucker-Prager numerical models to evaluate the stress distribution and displacement in the depth and width of different soil layers and to predict soil compaction stress. During the experimental tests, the stress-displacement diagram of the soil compaction tests was drawn, and the pre-compression stress was determined by the Alexandro and Eral method from the plate subsidence test. The results showed that Drager-Prager and Mohr-Columb models with 99 and 98% explanation coefficient, respectively, were in good agreement with the data obtained from experimental experiments. The study of stress distribution and displacement in soil depth showed that the amount of stress and displacement in the layers close to the loading plate increased more, and the amount of stress and displacement decreased by moving to deeper layers. The simulation results also showed that the amount of stress across each layer of soil decreased with distance from the center of the loading axis. In the high-depth plate sinkage test, the depth stress distribution is almost fixed and negligible, while in the plate sinkage test and enclosed compaction (together), the amount of depth stress in the soil was fixed and stable. This indicates that the soil is compacted.