Sustainable Production Systems Research Articles

PENDAMPINGAN PETERNAK KAMBING PADA WILAYAH PENYANGGA PERUSAHAAN PTPV VII KABUPATEN LAMPUNG TENGAH

In the context of rural economic development, it is important to implement a social innovation collaborative model with social agents (industry, government, NGOs, and other organizations), where farmers take collective action to build a sustainable agricultural production system. Using the INRM (Integrated Natural Resource Management) method, the FEB Unila Community Service Team developed an Inclusive Social Business Model that encourages local farmer groups to collaborate on economic and social development activities through goat farming. INRM is a method of development-oriented research that aims to simultaneously reduce poverty, increase food security, and achieve environmental protection. The result of the community service is the formation of a livestock farmer group organization which is expected to become a local institution that plays the role of the Inclusive Social Business Model, encouraging sustainable economic and social programs to increase the income of farmers particularly, and the community of Mekar Jaya Village in general.

Energy and Protein Requirements of Growing Lambs in Colombian Highlands

Determining the nutritional requirements of lambs is necessary to formulate balanced rations and contribute to sustainable sheep production systems. However, limited information is available regarding the nutritional requirements of growing lambs in the Colombian highlands. Twenty-two Romney Marsh males were used. Initially, four lambs were slaughtered at 20 kg body weight (BW). The remaining 18 lambs were distributed into two groups, according to BW (light: 20 BW and heavy: 30 kg BW). Lambs were randomly allocated into one of three different nutritional schemes, according to voluntary intake (no restriction, and 25 and 50% restriction). All the animals received a totally mixed ration. When a voluntary-fed lamb gained 10 kg BW, the two other lambs restricted to 25 and 50% were slaughtered and dissected into components to determine protein and gross energy concentration. Energy and protein accumulation were analyzed through regression analysis. The net energy for maintenance was 82.3 kcal/kg BW0.75, while the energy efficiencies for maintenance and gain were 0.72 and 0.29, respectively. Crude protein for maintenance was 1.78 g/kg BW0.75, and the nitrogen efficiencies for maintenance and gain were 0.41 and 0.27, respectively. The maintenance requirement of energy was greater, while protein was similarly related to values reported in the literature; however, the efficiency of energy and protein use was lower in growing lambs. These results suggested that estimating energy and nitrogen requirements for growing lambs must be adjusted in Colombian highland conditions.

Comparison of robot concepts for new sustainable crop production systems

In recent decades the agricultural intensification led to a landscape simplification, where once heterogeneous landscapes turned into more monocultured cropping regions. The main driver behind it was to be able to use larger and more powerful agricultural machinery in order to increase productivity and specially to decrease labor costs. With the advent of robots in combination with new methods of AI it is obvious that this is not only a new step of automated mechanization. New robotic systems open up new opportunities of how to cultivate crop plants. Different robotic concepts with different properties are discussed and how these might contribute to achieve the indisputably needed improvements in sustainable and environmental-friendly crop production systems. In a performed case study, it is demonstrated that even if larger robotic solutions when operated in isolation still can achieve higher area outputs, smaller and often specialized robotic systems can achieve a substantially improved work quality in the use case of seeding.

Assessment of techno-economic analyzes of grid-connected nuclear and PV/wind/battery/hydrogen renewable hybrid system for sustainable and clean energy production in Mersin-Türkiye

The main novelty in the presented paper is that it presents an energy analysis for a hybrid system that integrates nuclear power plants with wind/solar power plants for sustainable and clean energy production. In addition, excess energy is used to produce hydrogen. A techno-economic feasibility assessment is performed to ensure continuous electricity supply for hourly and peak residential load requirements in Mersin located in Türkiye. In the first stage of the study, suitable areas and sizes for solar and wind energy for energy production were determined with ArcGIS and Multi-Criteria Decision-Making methodologies. In the second stage, six scenarios were investigated in terms of electricity production, and excess energy was used for hydrogen production. The results brought out that more electricity was produced than the city's electricity consumption (5395 GWh) in all 6 scenarios considered. The maximum electricity production at a rate of 11900 GWh/yr and the maximum hydrogen at a rate of 132675 tons was produced in Scenario 4 with the cost of energy (0.31 $/kWh) and cost of hydrogen (12.6$/kgH2). In this scenario, the percentages of solar, wind and nuclear energy in total production 1 %, 12 %, and 87 %, respectively. According to the results, it was concluded that 236621 tons of carbon emissions were reduced when the city's energy needs were met according to the 6 scenarios in this study.

Synthesis of g-C3N4 decorated with ZIF-8 and CuFe2O4 as a highly efficient and magnetically separable photocatalyst for degradation of tetracycline

In this study, for the first time a magnetically recoverable zeolitic imidazolate framework-8 (ZIF-8) / graphite carbon nitride (g-C3N4)/ cooper ferrite (CuFe2O4) nanocomposite was prepared through a fast and simple wet impregnation procedure. The magnetic behavior of the ZIF-8/g-C3N4/CuFe2O4 heterostructure was used for the easy recovery of the nanocomposite by an external magnet. After studying the structural, crystallinity, magnetic, and photophysical properties of the as-syntesized sample, its application was investigated for the enhanced photodegradation of tetracycline under visible light illumination. The band gap energies for ZIF-8, g-C3N4, and CuFe2O4 were obtained 5.1 eV, 2.8 eV, and 1.3 eV, respectively. After combination of ZIF-8, g-C3N4, and CuFe2O4, the band gap energy was obtained to 2.4 eV, which indicate the improvement of photocatalytic activity of ZIF-8/g-C3N4/CuFe2O4 nanocomposite. Among the as-synthesized photocatalyst samples, the ZIF-8/g-C3N4/CuFe2O4 showed an excellent photocatalytic activity (99.15 %) for degradation of tetracycline within 65 min irradiation of visible light, solution pH of 5 and photocatalyst dosage of 0.75 g/L. The rate constant of the ZIF-8/g-C3N4/CuFe2O4 is almost 13.1, 9.9, and 15.6 times higher than that of ZIF-8, g-C3N4, and CuFe2O4, respectively. The ZIF-8/g-C3N4/CuFe2O4 heterojunction showed the effective degradation activity for four consecutive cycles, which exhibited its excellent reusability and stability. Moreover, the free radical quenching tests confirmed that holes, and hydroxyl radicals were the main reaction species for degradation of tetracycline. Altogether the preparation of novel ZIF-8/g-C3N4/CuFe2O4 provides an promise avenue for the development of high potential magtenticaly photocatalytic systems for sustainable tetracycline production with remarkable efficiencies.

Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives

The aim of this position paper is to identify a specific focus and the major challenges related to the human-centered artificial intelligence (HCAI) approach in the field of Industry 5.0 and the circular economy. A first step towards the opening of a line of research is necessary to aggregate multidisciplinary and interdisciplinary skills to promote and take into consideration the different aspects related to this topic, from the more technical and engineering aspects to the social ones and the repercussions in terms of sustainability. The proposal and vision of this preliminary work is to identify and discuss a suitable field for such interaction. This field has been identified, specifically, within additive manufacturing (AM) in the context of Industry 5.0. Additive manufacturing (AM), is a disruptive opportunity for more sustainable production systems that can be better optimized with AI, becoming an ideal platform for interconnection between different levels of application and integration of HCAI concepts, and at the same time able to prove them. In this context, two prospective areas with a high application impact of HCAI are those of AM-oriented supply chain and product customization in the AM field, enabled by a plethora of recently emerging technologies such as the internet of things, cloud and edge computing, and next-generation networks (5G). The paper concludes with the challenges HCAI poses to public policymakers, who face significant policy challenges in regulating artificial intelligence, and addressing the socioeconomic and technological impacts. Decision-makers are required to address these challenges by adopting some tentative policy recommendations.

Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives

The aim of this position paper is to identify a specific focus and the major challenges related to the human-centered artificial intelligence (HCAI) approach in the field of Industry 5.0 and the circular economy. A first step towards the opening of a line of research is necessary to aggregate multidisciplinary and interdisciplinary skills to promote and take into consideration the different aspects related to this topic, from the more technical and engineering aspects to the social ones and the repercussions in terms of sustainability. The proposal and vision of this preliminary work is to identify and discuss a suitable field for such interaction. This field has been identified, specifically, within additive manufacturing (AM) in the context of Industry 5.0. Additive manufacturing (AM), is a disruptive opportunity for more sustainable production systems that can be better optimized with AI, becoming an ideal platform for interconnection between different levels of application and integration of HCAI concepts, and at the same time able to prove them. In this context, two prospective areas with a high application impact of HCAI are those of AM-oriented supply chain and product customization in the AM field, enabled by a plethora of recently emerging technologies such as the internet of things, cloud and edge computing, and next-generation networks (5G). The paper concludes with the challenges HCAI poses to public policymakers, who face significant policy challenges in regulating artificial intelligence, and addressing the socioeconomic and technological impacts. Decision-makers are required to address these challenges by adopting some tentative policy recommendations.

Border row effects improved the spatial distributions of maize and peanut roots in an intercropping system, associated with improved yield.

Border row effects impact the ecosystem functions of intercropping systems, with high direct interactions between neighboring row crops in light, water, and nutrients. However, previous studies have mostly focused on aboveground, whereas the effects of intercropping on the spatial distribution of the root system are poorly understood. Field experiments and planting box experiments were combined to explore the yield, dry matter accumulation, and spatial distribution of root morphological indexes, such as root length density (RLD), root surface area density (RSAD), specific root length (SRL), and root diameter (RD), of maize and peanut and interspecific interactions at different soil depths in an intercropping system. In the field experiments, the yield of intercropped maize significantly increased by 33.45%; however, the yield of intercropped peanut significantly decreased by 13.40%. The land equivalent ratio (LER) of the maize-peanut intercropping system was greater than 1, and the advantage of intercropping was significant. Maize was highly competitive (A = 0.94, CR=1.54), and the yield advantage is mainly attributed to maize. Intercropped maize had higher RLD, RSAD, and SRL than sole maize, and intercropped peanut had lower RLD, RSAD, and SRL than sole peanut. In the interspecific interaction zone, the increase in RLD, RSAD, SRL, and RD of intercropped maize was greater than that of intercropped peanut, and maize showed greater root morphological plasticity than peanut. A random forest model determined that RSAD significantly impacted yield at 15-60 cm, while SRL had a significant impact at 30-60 cm. Structural equation modeling revealed that root morphology indicators had a greater effect on yield at 30-45 cm, with interactions between indicators being more pronounced at this depth. These results show that border-row effects mediate the plasticity of root morphology, which could enhance resource use and increase productivity. Therefore, selecting optimal intercropping species and developing sustainable intercropping production systems is of great significance.

Comparative 1H NMR-Based Metabolomics of Traditional Landrace and Disease-Resistant Chili Peppers (Capsicum annuum L.).

Chili peppers (Capsicum annuum L.) are economically valuable crops belonging to the Solanaceae family and are popular worldwide because of their unique spiciness and flavor. In this study, differences in the metabolomes of landrace (Subicho) and disease-resistant pepper cultivars (Bulkala and Kaltanbaksa) widely grown in Korea are investigated using a 1H NMR-based metabolomics approach. Specific metabolites were abundant in the pericarp (GABA, fructose, and glutamine) and placenta (glucose, asparagine, arginine, and capsaicin), highlighting the distinct physiological and functional roles of these components. Both the pericarp and placenta of disease-resistant pepper cultivars contained higher levels of sucrose and hexoses and lower levels of alanine, proline, and threonine than the traditional landrace cultivar. These metabolic differences are linked to enhanced stress tolerance and the activation of defense pathways, imbuing these cultivars with improved resistance characteristics. The present study provides fundamental insights into the metabolic basis of disease resistance in chili peppers, emphasizing the importance of multi-resistant varieties to ensure sustainable agriculture and food security. These resistant varieties ensure a stable supply of high-quality peppers, contributing to safer and more sustainable food production systems.

Optimizing fenugreek (Trigonella foenum-graecum L.) oil yield and compositions in intercropping through growth-promoting bacteria and mycorrhiza

IntroductionBiofertilizers and intercropping are two main components in sustainable production systems.Materials and methodsA two-year (2020–2021) study was conducted in East Azarbaijan, Iran, to evaluate the effects of arbuscular mycorrhizal fungi (AMF), growth-promoting bacteria (GPB) and chemical fertilizer (CF) on fenugreek (Trigonella foenum-graecum L.) (F) oil yield and compositions in intercropping with Moldavian balm (Dracocephalam mobdavica L.) (MB). The cropping patterns included MB sole cropping, fenugreek sole cropping (F) and replacement intercropping ratios consisted of Moldavian balm : fenugreek (MB:F (1:1)), MB:F (2:2) and MB:F (4:2) and additive intercropping of MB:F (100:50).ResultsFor both years, among the intercropping patters, the highest seed and oil yields were obtained in MB:F (100:50) intercropping pattern treated with CF and AMF+GPB. In all cropping patterns except MB:F (4:2), the highest anthocyanin, total flavonoid, and mucilage contents were observed in plants received AMF+GPB. At all treatments, the linoleic, oleic, and linolenic acid were the main components of fenugreek oil. In MB:F (1:1), (2:2), (4:2), and (100:50) intercropping patterns, the linoleic acid content in AMF+GPB treatment, increased by 9.45%, 6.63%, 15.20%, and 7.82%, respectively, compared with sole fenugreek. The highest total land equivalent ratio (LERT) values were obtained in 2021 and MB:F (100:50) intercropping pattern treated with CF (1.70) and AMF+GPB (1.63).ConclusionsIn general, it could be concluded that MB:F (100:50) intercropping pattern treated with AMF+GPB improved the oil yield and unsaturated fatty acid contents of fenugreek compared with sole cropping and could be recommended in sustainable production systems.

New procedure for designing an innovative biomass-solar-wind polygeneration system for sustainable production of power, freshwater, and ammonia using 6E analyses, carbon footprint, water footprint, and multi-objective optimization

The correct management of renewable polygeneration systems is a highly effective approach that can not only help expand renewable energy systems but also ensure sustainable production. In the present work, a new procedure for designing renewable polygeneration systems is introduced. In this procedure, the management of polygeneration systems is discussed from various aspects, including climatic change, techno-economic and environmental conditions, layout design, ecological sustainability, and the sociological approach to polygeneration systems in a practical form. As a case study, an innovative biomass-solar-wind polygeneration system to produce power, ammonia, and freshwater for Ahvaz in Iran was designed and evaluated according to the developed procedure. The integration of multi-effect distillation and humidification-dehumidification desalination has been employed for freshwater production. For ammonia production, syngas produced in the gasification unit and nitrogen obtained from the air separation unit were utilized. Power production has been achieved using a combination of the hydrogen-ammonia Brayton cycle, the supercritical carbon dioxide cycle, and the organic Rankine cycle. The designed system was evaluated using energy, exergy, exergoeconomic, exergoenvironmental, emergoeconomic, emergoenvironmental, carbon footprint, and water footprint analyses. The layout design of the proposed system and the sociological study of the system from a systemic approach have enhanced the visibility of its application. Additionally, the investigation of biomass fuel variations and combinations according to climate, along with optimization and dynamic analyses, are key measures that allow for a more comprehensive evaluation of the system from various management perspectives. The results show that the proposed system is capable of producing 523.34 m3/day freshwater, 10.1 MW of power, and storing 17.75 ton/day of ammonia in optimal state. The energy and exergy efficiency of the polygeneration system in the optimal state is 29.97% and 13.12%. The total cost rate and total environmental impact rate of the entire system in this case are equal to 0.48 $/s and 19.79 mPts/s, respectively. Meanwhile, the defined renewable system has an ecological sustainability index of 1.76.

Coupling life cycle audition and operation research methods to achieve sustainable rapeseed production system

Coupling life cycle audition and operation research methods to achieve sustainable rapeseed production system

The LTAR cropland common experiment in the Lower Mississippi River Basin.

The Lower Mississippi River Basin-Long-Term Agroecosystem Research Site (LMRB-LTAR) encompasses six states from Missouri to the Gulf of Mexico and is coordinated by the USDA-ARS National Sedimentation Laboratory, Oxford, MS. The overarching goal of LTAR is to assess regionally diverse and geographically scalable farming practices for enhanced sustainability of agroecosystem goods and services under changing environment and resource-use conditions. The LMRB-LTAR overall goal is to assess sustainable row crop agricultural production systems that integrate regional environmental and socioeconomic needs. Primary row crops in the region include soybeans, corn, cotton, rice, and sugarcane with crop rotations influenced by commodity crop price and other factors. The field-scale common experiment (CE) includes four row crop farms (26-101 ha) established in 2021 and 2023. Three fields are managed with alternative practices, including reduced tillage, cover crops, and automated prescription irrigation, and three fields are managed with prevailing farming practices, consisting of conventional tillage, no cover crop, and nonprescription irrigation. Treatment effects on crop productivity, soil quality, water use efficiency, water quality, and carbon storage are assessed. Research from the LMRB CE will deliver outcomes linked to overarching LTAR network goals, including innovative agricultural systems, strengthened partnerships, data management technologies, and precision environmental tools.

Innovative fertilizers with added plant extracts in the cultivation of Valeriana officinalis and Raphanus sativus and in the control of Botrytis and powdery mildew

Research objective: The main objective of this article is to report the results obtained from the use of innovative fertilisers with added plant extracts in agriculture. In particular, this article will deal with two important topics: i) study of the effect of innovative fertilisers on the biomass of vegetable plants; ii) possible control on mortality due to diseases such as Botrytis and powdery mildew. The information reported in this research work can support the design of cultivation systems in which agricultural sustainability is fundamental due to the presence of plant extracts as an alternative to synthetic plant protection products. Materials and Methods: The plants were grown in pots under controlled conditions; 30 seedlings per thesis, divided into 3 replications of 10 plants each, were planted in early January 2024. The plants used in the trial were Valeriana officinalis L. and Raphanus sativus. The five experimental groups in cultivation were: i) group control, irrigated with water and previously fertilised substrate; ii) group with Aktigen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iii) group with Lifegen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iv) group with QI-gen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); v) Group with Ecklonia maxima (EK): (peat 70% + pumice 20%), irrigated with water and previously fertilised substrate, (3 ml per plant once a week). On 5 May 2024, plant height, number of leaves, primary root length (mm), biomass of the aerial and root system, and number of dead plants (Botrytis and powdery mildew) were recorded. Results and Discussion: The experiment showed that the use of innovative fertilisers enriched with plant extracts can indeed significantly improve the vegetative and root growth of Valeriana officinalis L. and Raphanus sativus. All treatments showed a significant improvement over the untreated control and the commercial Ecklonia maxima treatment for the agronomic parameters analysed, but the Qi-gen treatment was significantly the best for increasing vegetative and root biomass. Improvements were also found in plant height, leaf number and root length. The trial also revealed the significant effect on Botrytis control of the product Aktigen and on powdery mildew of the product Lifegen, in fact they reduced the mortality of Valeriana officinalis and Raphanus sativus seedlings. Conclusions: A number of scientific studies have shown that the application of biofertilizers can improve plant growth, productivity, quality, and tolerance to biotic and abiotic stresses. Because of their multiple properties, they have become increasingly important as advanced agricultural techniques in global agriculture. This type of product, which includes natural substances, will contribute significantly to ecologically and economically sustainable agricultural production systems in the coming years, as well as serving as the foundation for large-scale sustainable agriculture in the future.

Enhancing Waste-to-Energy Conversion Efficiency and Sustainability Through Advanced Artificial Intelligence Integration

Artificial intelligence (AI) has emerged as a pivotal tool in optimizing waste-to-energy conversion technology, addressing critical environmental issues while promoting sustainable energy sources. This study delves into the multifaceted role of AI in enhancing the efficiency and effectiveness of waste-to-energy processes. By leveraging AI, significant improvements can be achieved in automated waste sorting, process monitoring, and energy production forecasting. The integration of AI into these domains not only streamlines operations but also enhances the accuracy of data management, analysis, and processing. This results in a more efficient conversion of waste into energy, mitigating adverse environmental impacts and fostering sustainable energy practices. The research highlights the practical applications of AI in optimizing the entire waste-to-energy workflow, underscoring its potential to revolutionize this sector. Moreover, the study addresses the inherent challenges and discusses future prospects for AI implementation in waste-to-energy technologies. Through comprehensive analysis and case studies, the findings reveal that AI can significantly contribute to reducing environmental footprints and promoting a circular economy. This exploration provides valuable insights into how AI-driven innovations can lead to more sustainable and efficient waste management and energy production systems, paving the way for future advancements in this critical field.

Effects of Agrivoltaics on the Microclimate in Horticulture

Chilean agriculture must adapt to climate change as droughts are already affecting the country and water availability is expected to further decline. In this context, Agrivoltaics (AV) systems, that install photovoltaic (PV) panels over crops and thus provide shading and an altered microclimate could enhance the resilience of agriculture in semi-arid zones. We compare data measured under an AV system with a reference measurement to quantify the effects of AV on microclimate in horticulture in the Metropolitan Region of Santiago, Chile. Data on irradiation, air temperature, air humidity, and wind speed allow us to compute potential evapotranspiration (PET). We observe a reduction of Global Horizontal Irradiation (GHI) under the AV system of 42%. Mainly, as a result of the decreased GHI, we derive a diminution in PET of 31%, quantifying the potential to lower the water demand of crops and thus irrigation. Measured soil moisture is on average 29% higher under the AV system compared to the reference condition, hence validating PET computations. Also, we find a more moderate climate with slightly stabilized air temperature and lower soil temperatures. Our results give a glimpse of the effects of installing PV panels over horticulture crops concerning the challenges of Chilean agriculture. AV systems have the potential to increase water availability by lowering irrigation demand and protecting crops from the effects of extreme irradiation, such as sunburn and heat stress. Thus, AV could foster the transformation of agriculture towards sustainable production systems. The documented effects should be verified over longer periods with different crops to understand the impact of AV within seasonal and interannual climatical variation and the diversity of Chilean agriculture.

Enhancing the efficacy of humidifier-dehumidifier desalination in humid regions through the use of an absorption refrigeration cycle (an economic and experimental investigation)

This experimental study investigates the performance of a novel humidifier-dehumidifier (HDH) desalination system integrated with a vapor absorption refrigerator (VAR) and photovoltaic (PV) panels for humid regions. The effects of air mass flow rate (m˙a) and inlet air temperature on key performance indicators were evaluated. Increasing m˙afrom 0.0039 kg/s to 0.0071 kg/s led to a 73 % increase in freshwater output, a 35 % increase in Coefficient of Performance (COP), a 100 % increase in Gain of Output Ratio (GOR), and a 75 % increase in Recovery Ratio (RR), but a 20 % decrease in dehumidifier efficiency. The maximum freshwater production rate of 870 g/h and a GOR of 1.4 were obtained at m˙a= 0.0071 kg/s and inlet air temperature of 50 °C, representing a 117 % increase compared to the lowest temperature and flow rate tested. The cost of freshwater for solar and electric operation modes was 0.075 and 0.094 USD/kg, respectively. The system's novelty lies in the integration of HDH desalination with a VAR and PV system, enabling continuous freshwater production even under cloudy or nighttime conditions. The findings demonstrate the potential of the proposed system for sustainable freshwater production in humid areas.

Review of Crop Phenotyping in Field Plot Experiments Using UAV-Mounted Sensors and Algorithms

The phenotyping of field crops quantifies a plant’s structural and physiological characteristics to facilitate crop breeding. High-throughput unmanned aerial vehicle (UAV)-based remote sensing platforms have been extensively researched as replacements for more laborious and time-consuming manual field phenotyping. This review aims to elucidate the advantages and challenges of UAV-based phenotyping techniques. This is a comprehensive overview summarizing the UAV platforms, sensors, and data processing while also introducing recent technological developments. Recently developed software and sensors greatly enhance the accessibility of UAV-based phenotyping, and a summary of recent research (publications 2019–2024) provides implications for future research. Researchers have focused on integrating multiple sensing data or utilizing machine learning algorithms, such as ensemble learning and deep learning, to enhance the prediction accuracies of crop physiological traits. However, this approach will require big data alongside laborious destructive measurements in the fields. Future research directions will involve standardizing the process of merging data from multiple field experiments and data repositories. Previous studies have focused mainly on UAV technology in major crops, but there is a high potential in minor crops or cropping systems for future sustainable crop production. This review can guide new practitioners who aim to implement and utilize UAV-based phenotyping.

Techno-economic needs assessment for a sustainable novel solar panel production system

Techno-economic needs assessment for an automated solar panel production system is presented. Solar energy, a rapidly growing renewable energy source, has the potential to meet a significant portion of the world's energy needs. Solar panels, the key component of solar energy systems, there are produced in a major industry. Automated solar panel production systems offer the potential to increase production efficiency and reduce costs. The study outlines key factors necessary for successful establishment and operation of an automated solar panel production factory, including market analysis, financial projections, operational strategies, and sustainability initiatives. The market analysis through examination global trends in the solar energy market, identifying growth trends, potential competitors, and target customer segments. The study used a five-step methodology to assess needs, identifying major requirement such as the application of high-speed and precision manufacturing equipment, investment in reliable and efficient manufacturing processes, and development of cost-effective manufacturing methods. The study’s results highlight several key economic benefits of automated solar panel production, including increased production efficiency, reduced labor costs, and improved product quality. The findings are valuable to various stakeholders, including government officials, business leaders, and community members, informing decisions regarding solar industry development and new manufacturing facilities in specific regions. The paper recommends the use of eco-friendly manufacturing processes, utilization of recyclable materials, and adoption of energy-efficient automated technologies to minimize the carbon footprint of solar panel production.

Contamination and pesticide multiresidue analysis in cotton production systems in Benin

High quantity of chemical pesticides spraying in conventional cotton production systems may affect negatively natural ecosystems components. This study examined the contamination levels of soil in Benin's cotton production system in West Africa by residues of pesticides used in cotton farming. One hundred and fourteen soil samples from six conventional and organic cotton production systems were collected and analysed. Multi-class pesticide residues were extracted from the soil samples, and analysed using respectively modified QuEChERS extraction and LC–MS/MS chromatography methods. Results showed an overall soil contamination to emamectin benzoate (18.5 μg/kg), imidacloprid (116.3 μg/kg), profenofos (12.7 μg/kg), acetamiprid (10.8 μg/kg), triasophos (12.6 μg/kg), abamectin (14.3 μg/kg), and deltamethrin (10.4 μg/kg). Especially, emamectin benzoate was detected with a high contamination in Banikoara district (18.5 μg/kg). Nevertheless, these contaminations were not deemed threatening from a toxicological perspective. Soils in conventional cotton cultivation displayed lower organic matter levels but higher concentrations of pesticides, whereas soils in organic cotton cultivation were less degraded and contaminated. Consequently, it is imperative to conduct environmental risk assessments and monitor key pesticide metabolites to establish sustainable cotton production systems in Benin.