Life Cycle Research Articles

Comparative analysis of storage compound metabolism in the embryo and endosperm of Cakile maritima seeds.

Seed production plays an essential role in the life cycle of angiosperms. Within the Brassicaceae family, which includes species that have successfully colonized a wide range of habitats, seed maturation has been extensively studied in the model plant Arabidopsis thaliana and several agronomically important species. In this study, we investigate this developmental process in Cakile maritima, a wild halophytic member of the Brassicaceae that thrives along sandy coastlines from the Arctic to the Mediterranean. This species is also widely used as a model for studying salt tolerance mechanisms. By independently analyzing the different zygotic tissues of the seed, namely, the embryo and the endosperm, we demonstrate that, quantitatively, the embryo is the main site of storage compound accumulation. Notably, the biochemical composition of these reserves differs substantially between the zygotic tissues. Approximately half of the fatty acids in the endosperm consist of omega-7 monounsaturated fatty acids, which are largely absent in the embryo. By contrast, the embryo shows a stronger induction of omega-9 and polyunsaturated fatty acid biosynthesis pathways compared to the endosperm, reflecting tissue-specific regulation of fatty acid metabolism genes. Furthermore, seeds collected from different ecological niches along a latitudinal gradient reveal that environmental temperature significantly affects the composition of seed reserves, particularly the proportion of polyunsaturated fatty acids in the embryo. Together, these findings underscore the metabolic diversity and adaptative potential of C. maritima, providing valuable insights into seed development, environmental plasticity, and oil composition within the Brassicaceae.

Phytochemical profiling and antioxidant capacity of Achillea Santolina at different phenological stages.

In the present study, the phytochemical quantity and quality as well as the antioxidant capacity of Achillea santolina at different growth stages including vegetative, flowering, and fruit set were investigated. The leave methanolic extraction of harvested plants at the flowering stage showed the highest phenolic and flavonoids content. The content and composition of A. santolina essential oil was varied depending on the plant development stage. The highest essential oil content (0.3% v/w) was obtained in the harvested aerial parts at the flowering stage followed by fruit set and vegetative stages. According to results of GC-FID and GC-MS, oxygenated monoterpenes represented by 1,8-cineole, α-thujone, and camphor were the predominant compounds in the A. santolina essential oil, which comprised 69.63-88.61% of the total oil composition. The essential oil quality of A. santolina was varied during the growing season and the observed variation was related to the differences in concentrations of main compounds and occurrence of minor constituents. An ascending and descending trend respectively was found regard to monoterpene and sesquiterpene contents during the growing life cycle of A. santolina and the highest ratio of these compounds was obtained at the fruit set stage. The total phenol content and antioxidant capacity of A. santolina essential oils gradually increased during the plant growth period that reached a maximum value at the fruit set stage. According to obtained results, appropriate harvesting stage can be chosen based on application purpose regards to essential oil quantity or quality. The results suggests that the flowering and fruit set stages can be considered as suitable sources of highest essential oil content and antioxidant potential, respectively.

Boosting energy storage performance of ZnCoTe@NiCoSe2 with core-shell structure as an efficient positive electrode for fabrication of high-performance hybrid supercapacitors.

Transition metal chalcogenides are promising compounds in electrochemistry with different applications including energy conversion/storage devices due to their stability, different oxidation states, and highly active surface areas. In this work, ZnCoTe nanorods coated with NiCoSe2 as the shell have been synthesized by a two-step method. ZnCoTe@NiCoSe2 has an excellent specific capacity of 240 mAh g-1 at a current density of 2A g-1 in a three-electrode system containing 3M KOH electrolyte solution, which is much superior to each of the core and shell components of the constructed electrodes. Furthermore, a remarkable cycle life of 94% is obtained at a current density of 10A g-1 after 5000 cycles, suggesting its long-term stability. The hybrid supercapacitor consists of ZnCoTe@NiCoSe2 and activated carbon as the positive and negative electrodes, respectively. In addition, ZnCoTe@NiCoSe2//AC (HSC device) showed 580W kg-1 power density at an energy density of 57 Wh kg-1. Additionally, the device retained 90% of its initial capacitance after 5000 cycles. Eventually, considering the excellent electrical conductivities and large numbers of active sites, transition metal chalcogenides have been utilized as efficient electrodes for supercapacitor applications. This work introduces a method for the incorporation of zinc into the telluride matrix, which modulates the electronic structure, enhances intrinsic electrical conductivity, and increases the density of electroactive sites. Moreover, the engineered core-shell architecture of ZnCoTe@NiCoSe₂ provides a synergistic combination of high electrical conductivity, abundant active sites, and a well-organized hierarchical structure. These integrated features significantly boost charge storage performance and overall efficiency of the supercapacitor device.

Evaluating the effectiveness of participatory science dog teams to detect devitalized Spotted Lanternfly (Lycorma delicatula) egg masses

The spotted lanternfly (Lycorma delicatula, SLF) is an invasive planthopper first detected in the United States in 2014, with initial sightings in Pennsylvania. SLF poses a serious threat to agriculture, particularly targeting grapevines, hops, and ornamental plants, resulting in substantial annual economic losses. Due to its life cycle, the early detection and removal of egg masses are the most effective strategies for preventing long-distance dispersal. However, visual detection by humans is time-consuming and inefficient. Detection dogs have demonstrated high accuracy in locating SLF egg masses and differentiating them from environmental distractors. Despite their effectiveness, the number of dogs available through governmental channels is insufficient to meet demand. This study evaluated whether community scientist dog-handler teams could meet standardized detection criteria using SLF egg masses. Teams from across the U.S. were recruited and trained using devitalized egg masses, with oversight provided by local trainers. Following a 3- to 6-month independent training period, team performance was assessed through an odor recognition test and a field trial. Dogs demonstrated a sensitivity of 82% in controlled testing and 58% in field conditions. These results provide proof of concept; community scientist dog teams could play a significant role in protecting their local environments and agriculture from invasive species.

A natural allele of the transcription factor gene TaMYB-D7b is a genetic signature for phosphorus deficiency in wheat

Abstract Phosphorus (P) and nitrogen (N) deficiencies are major yield-limiting factors for wheat (Triticum aestivum) production worldwide, particularly in the acidic soils of the southern Great Plains of North America. In this study, we report that the transcription factor gene TaMYB-D7 is responsible for a major quantitative trait locus controlling purple leaf color. The wheat cultivar ‘2174’ showed purple coleoptiles regardless of P status, whereas ‘Jagger’ did not, even under P limitation. The two cultivars differed by one amino acid in TaMYB-D7: Gly-50 in TaMYB-D7b (encoded by the 2174 allele) and Ser-50 in TaMYB-D7a (encoded by the Jagger allele). We used genome editing to inactivate all three TaMYB7 homoeologs in cv. 2174. The resulting edited wheat plants did not accumulate purple pigments throughout their life cycle, validating the functions of TaMYB-7Db associated with the purple phenotype. In the TaMYB7-edited plants, chalcone synthase 2-like (TaCHSL2), which may be involved in anthocyanidin biosynthesis and metabolism, was dramatically downregulated, suggesting that TaMYB7 induces its transcription. We also discovered that the expression of TaMYB7 and TaCHSL2 was upregulated by P but downregulated by N. Lastly, we developed a Kompetitive Allele Specific PCR (KASP) marker to facilitate the genotyping of TaMYB-D7b, which can be used for marker-assisted breeding. Our results provide insight into nutrient use efficiency in wheat.

Cost Efficiency Evaluation of Ceramic Fiber, Glass Fiber, and Basalt Fiber-Reinforced Asphalt Mixtures

The performance of SBS (Styrene Butadiene Styrene) modified asphalt mixtures can be enhanced through the addition of fibers including basalt, ceramic, and glass. This study investigates whether a reduced SBS content of 3%, combined with 0.3% fiber reinforcement can match or exceed the performance of a traditional 7% SBS mixture. A comparative analysis was carried out by examining both performance efficiency and life cycle costs across ceramic, basalt, and glass fiber-reinforced mixtures. Maintenance requirements for each scenario were factored into the life cycle analysis. To assess structural integrity, 3D finite element simulations were conducted using the Burger’s logit model while focusing on fatigue and rutting damage. Findings indicate that basalt and ceramic fiber mixtures deliver better asphalt mixtures, thereby outperforming the 7% SBS mix by requiring fewer maintenance interventions. However, due to the higher cost of ceramic fiber mixtures at 831 Eur/m3, basalt fiber emerges as the more cost-effective option, achieving a performance efficiency gain of 20% with reduced costs at 532 Eur/m3. Among the fiber-reinforced variants, glass fiber showed the least improvement in performance, with a difference in 11% and 13% when compared to ceramic fiber and basal fiber, respectively.

Validation of a methodology to automatically classify design stage 3D models into activity units using PointNet and PointNet++ algorithms

ABSTRACT A design model comprises the elemental units of a structure. These elements should be extracted and classified into detailed components to use this model during the construction life cycle. However, owing to the increasing scale and complexity of construction projects, the complexity and level of detail of design models have increased significantly due to the growing scale of construction projects, along with the number of components they contain. Therefore, an efficient method to accurately classify the detailed components of the design model should be devised. We used PointNet and PointNet++ to automatically classify construction activity units of bridge design models. The accuracies of these methods for the automatic classification of abutment, pier, and bridge design models were validated, reaching 0.9 ~ 1.0, 1.0, and 0.69 ~ 0.99, respectively. The proposed automatic classification approach may enable the reuse of design models throughout the construction life cycle.

Research on the Carbon Footprint of Rural Tourism Based on Life Cycle Assessment: A Case Study of a Village in Guangdong, China

In the context of China’s “dual carbon” goals and rural revitalization strategy, scientifically assessing the carbon footprint of rural tourism is essential for promoting the sustainable development of the tourism sector. This study presents the first case analysis of the rural tourism carbon footprint in Guangdong Province, using Village B as a representative example. A tourism carbon footprint model for village B was developed using the life cycle assessment (LCA) method. Based on empirical survey data, the tourism carbon footprint of Village B in 2024 was estimated at 7731.23 t, with a per capita carbon footprint of 38.656 kg/p/a. Among the contributing sectors, transportation accounted for the largest share (85.18%), followed by catering (6.93%) and accommodation (5.10%). As an ecotourism-oriented rural destination, Village B exhibited a relatively low carbon footprint from recreational activities. To facilitate the low-carbon transition of rural tourism in the study area and accelerate progress toward the “dual carbon” targets, it is recommended to optimize public transport infrastructure, promote green mobility, enhance the energy efficiency of rural dining and accommodation, and raise awareness of low-carbon tourism.

Legacy Datasets and Their Impacts: Analysing Ecoinvent’s Influence on Wool and Polyester LCA Outcomes

Accurate and transparent Life Cycle Assessment (LCA) datasets are essential for reliable sustainability evaluations, particularly in the complex and varied textile industry. Historically, the ecoinvent database has been a foundational source for LCA studies in the textile sector. This paper critically examines the limitations of the ecoinvent v3.7 dataset, which is widely used in academic research, industry tools, and policymaking. While newer versions, such as v3.11, released in 2024, have addressed many issues, including enhanced geographical representation and updated emission profiles for chemicals, this study emphasises the historical implications of earlier data versions. By comparing the cradle-to-gate Global Warming Potential (GWP) of wool and polyester jumpers, this research reveals how aggregated and outdated data underestimated the polyester’s environmental impact while overestimating that of wool. These discrepancies have shaped fibre certification, eco-labelling, and consumer perceptions for years. Understanding the legacy of these datasets is vital for re-evaluating past LCA-based decisions and guiding future assessments toward greater regional relevance and transparency.

On-Orbit Life Prediction and Analysis of Triple-Junction Gallium Arsenide Solar Arrays for MEO Satellites

This paper focuses on the triple-junction gallium arsenide solar array of a MEO (Medium Earth Orbit) satellite that has been in orbit for 7 years. Through a combination of theoretical and data-driven methods, it conducts research on anti-radiation design verification and life prediction. This study integrates the Long Short-Term Memory (LSTM) algorithm into the full life cycle management of MEO satellite solar arrays, providing a solution that combines theory and engineering for the design of high-reliability energy systems. Based on semiconductor physics theory, this paper establishes an output current calculation model. By combining radiation attenuation factors obtained from ground experiments, it derives the theoretical current values for the initial orbit insertion and the end of life. Aiming at the limitations of traditional physical models in addressing solar performance degradation under complex radiation environments, this paper introduces an LSTM algorithm to deeply mine the high-density current telemetry data (approximately 30 min per point) accumulated over 7 years in orbit. By comparing the prediction accuracy of LSTM with traditional models such as Recurrent Neural Network (RNN) and Feedforward Neural Network (FNN), the significant advantage of LSTM in capturing the long-term attenuation trend of solar arrays is verified. This study integrates deep learning technology into the full life cycle management of solar arrays, constructs a closed-loop verification system of “theoretical modeling–data-driven intelligent prediction”, and provides a solution for the long-life and high-reliability operation of the energy system of MEO orbit satellites.

A Review of Remote Sensing and GIS in Agronomic Decision-Making

Agronomical research benefits greatly from the use of remote sensing. Understanding the agronomic parameters has been made possible by the evaluation of agricultural crop canopies. Crop classification, yield assessment, and crop monitoring all heavily rely on remote sensing. Agronomical research requires the use of remote sensing since the field is extremely susceptible to changes in soil, climate, and other physico-chemical factors. Strong seasonal patterns are observed in the agricultural production system monitoring in relation to the crops' biological life cycle. Each of these elements varies greatly in both space and time. Furthermore, because of unfavourable growth circumstances, agricultural yield might fluctuate quickly. Observing of agricultural systems have to be adhered to promptly. Remote sensing is an essential tool for timely monitoring and giving a precise picture of the agriculture industry because of its high visit frequency and exceptional precision. Sustainable agriculture management requires a spatiotemporal analysis of all the factors influencing the agricultural industry. The assessment and management of agricultural activities heavily relies on remote sensing and other cutting-edge methods like geographical information systems and global positioning systems. These technologies have numerous multifaceted uses in agriculture, including yield estimation, weather forecasting, crop acreage estimation, crop growth monitoring, soil moisture estimation, soil fertility evaluation, crop stress detection, disease and pest infestation detection, drought and flood condition monitoring, precision agriculture to preserve the sustainability of agricultural systems and boost national economic growth.

AI Liability Along the Value Chain: Lessons from the Liability of Suppliers of Components in Product Liability Law

Abstract Though it is common to think of AI systems as a singular tool, AI systems are often developed and deployed in a value chain that involves numerous components and actors. The AI life cycle has at least three stages: programming, fine-tuning, and implementation. Different actors can participate in these stages or sell and supply key components, such as pre-labeled data. Consequently, when harm occurs and an AI system is involved, allocating liability among these different actors and stages poses difficult questions. This Article begins to address this question by drawing on existing tort doctrine on the liability of suppliers of raw materials and components in product liability law. In doing so, it identifies principles that can inform courts, regulators, and technologists on whether and when the different participants in the AI value chain should be held liable for harm involving an AI system. It argues that several factors should be considered when facing AI liability cases. These include the relative expertise of the different actors, the moment in the AI lifecycle where it may be most efficient to adopt safety measures, the context of the AI system’s deployment, whether AI component suppliers should foresee specific uses and risks, and the level of participation of each AI actor in the outcome that causes harm.

Integrating Noise Pollution into Life Cycle Assessment: A Comparative Framework for Concrete and Timber Floor Construction

Despite the well-documented health risks of noise pollution, its impact remains overlooked mainly in life cycle assessment (LCA). This study introduces a methodological innovation by integrating both traffic and construction noise into the LCA framework for concrete construction, providing a more holistic and realistic evaluation of environmental and health impacts. By combining building information modeling (BIM) with LCA, the method automates material quantification and assesses both environmental and noise-related health burdens. A key advancement is the inclusion of health-based indicators, such as annoyance and sleep disturbance, quantified through disability-adjusted life years (DALYs). Two scenarios are examined: (1) a comparative analysis of concrete versus timber flooring and (2) end-of-life options (reuse vs. landfill). The results reveal that concrete has up to 7.4 times greater environmental impact than timber, except in land use. When noise is included, its contribution ranges from 7–33% in low-density regions (Darwin) and 62–92% in high-density areas (NSW), underscoring the critical role of local context. Traffic noise emerged as the dominant source, while equipment-related noise was minimal (0.3–1.5% of total DALYs). Timber slightly reduced annoyance but showed similar sleep disturbance levels. Material reuse reduced midpoint environmental impacts by 67–99.78%. Sensitivity analysis confirmed that mitigation measures like double glazing can cut noise-related impacts by 2–10% in low-density settings and 31–45% in high-density settings, validating the robustness of this framework. Overall, this study establishes a foundation for integrating noise into LCA, supporting sustainable material choices, environmentally responsible construction, and health-centered policymaking, particularly in noise-sensitive urban development.

Multi objective design optimization of residential buildings: energy consumption, life cycle cost and thermal discomfort based on NSGA-II

Multi objective design optimization of residential buildings: energy consumption, life cycle cost and thermal discomfort based on NSGA-II

Study on Multi-Dimensional Paths of Green Manufacturing and Sustainable Development in Indonesia's Automotive Industry

With its long industrial chain and high correlation, the automobile industry has a significant driving effect on the upstream and downstream economies. Promoting the construction of a green automobile manufacturing and management technology system is an important path for Indonesia to achieve coordinated development of economic growth and ecological protection. Based on the perspective of the entire life cycle of automobiles, this paper constructs a multidimensional model of the green manufacturing technology system from five dimensions: environmental carrying capacity, resource recycling, low-carbon energy substitution, economic cost optimization, and timeliness balance. Through a systematic analysis of the key technology systems required for the development of green automobiles, such as clean energy drive, lightweight design, and recycling remanufacturing, a localized implementation strategy is proposed. The study aims to provide a theoretical framework for Indonesia to reduce the carbon footprint of the automobile industry and enhance resource utilization efficiency, so as to help it enhance the international competitiveness of the manufacturing industry through green transformation, while alleviating the ecological and environmental pressures in the process of industrialization

Seed Mixes in Landscape Design and Management: An Untapped Conservation Tool for Pollinators in Cities

Urban green spaces are increasingly recognized as important habitats for pollinators, and wildflower seed mixes marketed as pollinator-friendly are gaining popularity, though their actual conservation value remains poorly understood. This study provides the first systematic screening of commercially available seed mixes in Portugal, evaluating their taxonomic composition, origin, life cycle traits, and potential to support pollinator communities. A total of 229 seed mixes were identified. Although these have a predominance of native species (median 86%), the taxonomic diversity was limited, with 91% of mixes comprising species from only one or two families, predominantly Poaceae and Fabaceae, potentially restricting the range of floral resources available to pollinators. Only 21 seed mixes met the criteria for being pollinator-friendly, based on a three-step decision tree prioritizing native species, extended flowering periods, and visual diversity. These showed the highest percentage of native species (median 87%) and a greater representation of flowering plants. However, 76% of all mixes still included at least one non-native species, although none is considered invasive. Perennial species dominated all seed mix types, indicating the potential for the long-term persistence of wildflower meadows in urban spaces. Despite their promise, the ecological quality and transparency of the seed mix composition remain inconsistent, with limited certification or information on species origin. This highlights the need for clearer labeling, regulatory guidance, and ecologically informed formulations. Seed mixes, if properly designed and implemented, represent a largely untapped yet cost-effective tool for enhancing the pollinator habitats and biodiversity within urban landscapes.

Allies or Enemies? The Power of Plant Hormones in Animals: Insights into Their Regulatory Roles

Phytohormones, representing a diverse group of molecules, are essential in orchestrating plant growth and development, ensuring the smooth progression of the entire life cycle from germination to senescence. Emerging research reveals that these compounds also exert biological effects in non-plant systems, including animals. Although some phytohormones can be harmful, their health-promoting potential is rapidly gaining attention. This has sparked a growing interest in exploring plant hormones as novel therapeutic agents, particularly in precision medicine. This review brings together a multidisciplinary team—plant physiologists, a pharmacist, and a medical doctor—to delve into the latest insight surrounding the health-related impacts of plant hormones on animal systems, with a particular emphasis on human health. We comprehensively analyze their effects, weighing both the benefits and potential risks. Key phytohormones—auxin, abscisic acid, cytokinins, jasmonates, ethylene, strigolactones, and gibberellins—are highlighted for their remarkable regulatory roles in animal physiology, with a special focus on their implications for human health. Our discussion reveals how phytohormones may help address critical health challenges, particularly those related to aging populations, including neurodegenerative diseases, diabetes, and cancers. These plant-derived molecules are emerging as promising candidates for future drug development and nutritional therapies. Hence, a deeper understanding of phytohormone action may not just revolutionize agriculture but also open new frontiers in medicine and human health.

Green Technology Innovations for Carbon Footprint Reduction in the Restaurant Industry: A Systematic Review

Abstract Restaurants contribute a significant carbon footprint (CF), with the food service sector responsible for 18% of food-related global CF. This impact arises from energy-intensive processes, carbon-intensive ingredient sourcing, inefficient waste management, and upstream and downstream supply chain activities. Notably, commercial kitchens exhibit carbon footprints 2–5 times greater than those of other commercial spaces. This review synthesizes recent empirical and theoretical literature on carbon footprint reduction strategies in restaurants, with emphasis on the application of life cycle assessment (LCA), IPCC methodologies, and material flow analysis (MFA) across diverse regional contexts. Green technologies such as the integration of solar, biogas, and biodiesel systems have been shown to reduce GHG emissions by 20–75%, while composting and food waste valorization can mitigate methane emissions by up to 30%. Menu-based interventions, including the substitution of beef with plant-based proteins and regionally sourced ingredients, offer substantial emissions reductions at the meal level. Despite these advances, the review identifies persistent challenges, including data inconsistency, underreporting of Scope 3 emissions, and limited adoption of standardized carbon accounting frameworks such as ISO 14064, PAS 2050. The findings highlight the need for harmonized assessment tools, integration of digital monitoring technologies, and cross-sector collaboration to enable consistent benchmarking and guide the sector toward carbon neutrality. This review provides a roadmap for advancing low-carbon transitions through operational, behavioral, and policy-driven interventions in the global restaurant industry. Graphical Abstract

Blind spots in elementary students’ perceptions regarding the food system: expanding Fonseca’s research on depictions of animal food production in Portuguese textbooks

Abstract This forum paper aims to expand the discussion on the representations of food systems from Fonseca’s research, which pointed to several neglected contexts regarding food systems in school textbooks. The main aim of the paper is to analyze elementary students’ representations to identify the presence or absence of socio-environmental issues in the drawings of the life cycle of food products, and how they dialog with Fonseca’s results. We propose the metaphor of blind spots as a theoretical and analytical construct to explain how some socio-environmental issues are not taken into account, whether consciously or unconsciously, to avoid the discomfort of some thorny issues related to the topic. After conducting a qualitative content analysis in 68 drawings by elementary students in two different school contexts, our results show that there are three main blind spots in the stories about food products: (a) a blind spot regarding food production, which involves the simplification or sugarcoating of how the food is produced; (b) a blind spot regarding food transformation, which ignores social and environmental issues related to the food industry; (c) a blind spot regarding waste management. Findings suggest the need to explore these blind spots as well as creating alternative educational imagery and actions that do not avoid the complexity and the discomfort of the topic, and which have the potential to enable educators and students to respond to socio-environmental issues.

Beneficial redox activity of halide solid electrolytes empowering high-performance anodes in all-solid-state batteries.

All-solid-state batteries receive ample attention due to their promising safety characteristics and energy density. The latter holds true if they are compatible with next-generation high-capacity anodes, but most highly ion-conductive solid electrolytes decompose at low operating potentials, leading to lithium loss and increased cell resistances. Here the dynamic stability of solid electrolytes that can improve all-solid-state battery performance is demonstrated. Halide electrolytes Li3YCl3Br3 and Li2ZrCl6, considered unstable at low potentials, are found to exhibit structurally reversible redox activity beyond their electrochemical stability windows, increasing compatibility with anodes and contributing to capacity without compromising ionic conductivity. The benefit of this dynamic stability window is demonstrated with cost-effective red phosphorus anodes, resulting in high reversible capacities (2,308 mAh g-1), high rate capacity retention (1,024 mAh g-1 at 7.75 mA cm-2) and extended cycle life (61% retention after 1,780 cycles). Furthermore, high areal capacity (7.65 mAh cm-2) and stability (70% retention after 1,000 cycles) are achieved for halide-based full cells with red phosphorous anodes. The beneficial redox activity of halide electrolytes greatly expands their application scenarios and suggests valuable battery design principles to enhance performance.