Search Results (810)

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

Cucumber, a high-yielding crop commonly grown in facility environments, is particularly susceptible to nitrogen (N) deficiency due to its rapid growth and high nutrient demand. This study used cucumber as its experimental subject and established a spectral dataset of leaves under four nutritional conditions, normal supply, nitrogen deficiency, phosphorus deficiency, and potassium deficiency, aiming to develop an efficient and robust method for quantifying N in cucumber leaves using Raman spectroscopy (RS). Spectral data were preprocessed using three baseline correction methods—BaselineWavelet (BW), Iteratively Improve the Moving Average (IIMA), and Iterative Polynomial Fitting (IPF)—and key spectral variables were selected using 4-Dimensional Feature Extraction (4DFE) and Competitive Adaptive Reweighted Sampling (CARS). These selected features were then used to develop a N content prediction model based on Partial Least Squares Regression (PLSR). The results indicated that baseline correction significantly enhanced model performance, with three methods outperforming unprocessed spectra. A further analysis showed that the combination of IPF, 4DFE, and CARS achieved optimal PLSR model performance, achieving determination coefficients (R²) of 0.947 and 0.847 for the calibration and prediction sets, respectively. The corresponding root mean square errors (RMSEC and RMSEP) were 0.250 and 0.368, while the residual predictive deviation (RPDC and RPDP) values reached 4.335 and 2.555. These findings confirm the feasibility of integrating RS with advanced data processing for rapid, non-destructive nitrogen assessment in cucumber leaves, offering a valuable tool for nutrient monitoring in precision agriculture. Full article

Educational institutions are facing a crisis characterized by the need to address diverse learning styles and vocational aspirations, exacerbated by ongoing financial pressures. To navigate these challenges effectively, there is an urgent need to innovate educational practices and learning environments, ensuring they are adaptable and responsive to the evolving needs of students and the workforce. The adoption of the Industry 5.0 framework offers a promising solution, providing a holistic approach that emphasizes the integration of human creativity and advanced technologies to transform educational institutions into resilient, human-centric, and sustainable learning environments. In this context, this article presents a transdisciplinary methodology that integrates Asset Management (AM) with Social Innovation (SI) through Design Thinking (DT) to co-design Educational Facilities 5.0 with stakeholders. The application of the proposed approach in an AgroLab case study—a food and agricultural laboratory—demonstrates how the methodology enables the definition of an Educational Facility 5.0 and generates AM Design Knowledge to support informed decision-making in the subsequent design, implementation, and operation phases. Following DT principles—where knowledge emerges through iterative experimentation and insights from practical applications—this article also discusses the role of SI and DT in AM, the role of Large Language Models in convergent processes, and a vision for Educational Facilities 5.0. Full article

Light-emitting diodes (LEDs) in agricultural systems mainly contribute their capacity to create a precise and constant light spectral environment. However, the potential of LED in crop production was underestimated. LEDs serve not only as efficient artificial light sources for plant growth, but are also a good tool for enhancing biomass production with limited energy consumption. This article reviewed innovative applications of LED in facility agriculture, e.g., plant factory, and greenhouse. Compared to conventional application of LED, innovative lighting strategies such as intermittent lighting, night break, continuous lighting, alternate lighting, dynamic lighting, and end-of-day (EOD) far-red provided by LED light can elevate the production efficiency effectively. However, the scientific explanation of the above lighting strategies remains to be clearly revealed, providing theoretical support for the further optimization of conducting parameters. This review summarizes the physiological effects of different lighting strategies on crop cultivation and illustrates their future application in facility agriculture, aiming to provide novel methods for elevating the energy utilization efficiency and lowering the cost in facility agriculture using artificial light. Full article

Low-concentration N₂O (≤5%) emissions from agricultural fields and waste treatment facilities in China reach 7.333 × 10⁵ t annually, making them a significant but inadequately controlled contributor to global warming. Agricultural wastes were selected as precursors to prepare biochar, including pecan shell (SH), poplar sawdust (JM), wheat straw (XM), and corn straw (YM), which were subsequently acid-modified with 0.1 mol L⁻¹ HCl. The objectives were (i) to quantify the enhancement in N₂O capture achievable by acid treatment, (ii) to elucidate the underlying chemisorption mechanism, and (iii) to identify the most efficient feedstock for practical deployment. Acid modification increased the oxygen content, specific surface area, and the number of hydroxyl and carboxyl groups on the biochar surface. Both modified and unmodified biochar followed the pseudo-second-order kinetic model (R² ≥ 0.960), indicating chemisorption-dominated processes. The adsorption performance ranked as XM > JM > SH > YM, with XM exhibiting the highest adsorption capacity (26.000 mol/kg unmodified, 43.088 mol/kg modified, 65.72% increase). The Langmuir model provided a better fit for N₂O adsorption, suggesting dynamic multilayer heterogeneous adsorption. The findings demonstrate that acid-modified biochar derived from agricultural waste is a scalable, economical, and environmentally friendly adsorbent for mitigating low-concentration N₂O emissions. Full article

In the past decade, agricultural biogas plants have become one of the key tools driving the energy transition in rural areas. Nevertheless, their development in Poland still lags behind that in Western European countries, suggesting the existence of barriers that go beyond technological or regulatory issues. This study aims to examine how Polish farmers perceive the risks and expected benefits associated with investing in biogas plants and which of these perceptions influence their willingness to invest. The research was conducted in the second quarter of 2025 among farmers planning to build micro biogas plants as well as owners of existing biogas facilities. Geographic Information System (GIS) tools were also used in selecting respondents and identifying potential investment sites, helping to pinpoint areas with favorable spatial and environmental conditions. The findings show that both current and prospective biogas plant operators view complex legal requirements, social risk, and financial uncertainty as the main obstacles. However, both groups are primarily motivated by the desire for on-farm energy self-sufficiency and the environmental benefits of improved agricultural waste management. Owners of operational installations—particularly small and medium-sized ones—tend to rate all categories of risk significantly lower than prospective investors, suggesting that practical experience and knowledge-sharing can effectively alleviate perceived risks related to renewable energy investments. Full article

Accurate counting of cucumber flowers using intelligent algorithms to monitor their sex ratio is essential for intelligent facility agriculture management. However, complex greenhouse environments impose higher demands on the precision and efficiency of counting algorithms. This study proposes a dual-area counting algorithm based on an improved YOLOv8n-Track (YOLOv8n-T) and ByteTrack cascaded framework. This method accomplishes the cucumber flower counting task by detecting flower targets, tracking them frame-by-frame, and validating the count through dual-area counting. The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. By integrating the ByteTrack tracking algorithm with a dual-area counting strategy, the robustness of flower counting in dynamic environments is strengthened. Experimental results show that the improved YOLOv8n-T achieves mAP and F1 scores of 86.9% and 82.1%, surpassing YOLOv8n by 3% and 2.6%, respectively, with a 0.3 G reduction in model parameters. The integrated framework achieves a detection accuracy of 82.4% for cucumber flower counting. This research provides a new method for monitoring cucumber flower sex ratios in facility agriculture, promoting the development of intelligent agricultural management. Full article

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

This paper presents the results of laboratory tests on the intensity of mass and heat exchange in a polytunnel, with a focus on the synergy between the polytunnel and a stone accumulator. The subject of study was a standard polytunnel made of double polythene sheathing. In the process of selecting the appropriate working conditions for such a polytunnel, the characteristic operating parameters were modeled and verified. They were related to the process of mass and energy exchange, which takes place in regular controlled-environment agriculture (CEA). Then, experimental tests of a heat accumulator on a fixed stone bed were carried out. The experiments were carried out for various accumulator surfaces ranging from 18.7 m² to 74.8 m², which was measured perpendicularly to the heat medium. To standardize the results obtained, the analysis included the unit area of the accumulator and the unit time of the experiment. In this way, 835 heat and mass exchange events were analyzed, including 437 accumulator charging processes and 398 discharging processes from April to October, which is a standard period of polytunnel use in the Polish climate. During the tests, internal and external parameters of the process were recorded, such as temperature, relative humidity, solar radiation, wind speed and air flow speed in the accumulator system. Based on the parameters, a set of empirical relationships was developed using mathematical modeling. This provided the foundation for calculating heat gains as a result of its storage in a stone accumulator and its discharging process. The research results, including the developed dependencies, not only fill the scientific gap in the field of heat storage, but can also be used in engineering design of polytunnels supported by a heat storage system on a stone bed. In addition, the proposed methodology can be used in the study of other heat accumulators, not only in plant production facilities. Full article

In alignment with the United Nations’ Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production) and 13 (Climate Action), this research explores the sustainable valorization of mangosteen peels into mangosteen peel powder (MPP), a value-added product with pharmaceutical properties. Mangosteen peels are an abundant agricultural waste in Thailand. This study evaluates six MPP production schemes, each employing different drying methods. Life Cycle Assessment (LCA) is utilized to assess the global warming potential (GWP) of these schemes, and the quality of the MPP produced is also compared. The results show that a combination of frozen storage and freeze-drying (scheme 4) has the highest GWP (1091.897 kgCO₂eq) due to substantial electricity usage, whereas a combination of frozen storage and sun-drying (scheme 5) has the lowest GWP (0.031 kgCO₂eq) but is prone to microbial contamination. Frozen storage without coarse grinding, combined with hot-air drying (scheme 6), is identified as the optimal scheme in terms of GWP (11.236 kgCO₂eq) and product quality. Due to the lack of an onsite hot-air-drying facility, two transportation strategies are integrated into scheme 6 for scenarios A and B. These transportation strategies include transporting mangosteen peels from orchards to a facility in another province or transporting a mobile hot-air-drying unit to the orchards. The analysis indicates that scenario B is more favorable both operationally and environmentally, due to its lower emissions. This research is the first to comparatively assess the GWP of different MPP production schemes using LCA. Furthermore, it aligns with the growing trend in international trade which places greater emphasis on environmentally friendly production processes. Full article

Agricultural production waste (APW) is characterized by pollution, increasing volume, spatial dispersion, and temporal and spatial variability in its generation. The improper handling of APW poses a growing risk to the environment and public health. This paper focuses on the planning of APW recycling networks, primarily analyzing the selection of temporary storage sites and treatment facilities, as well as vehicle scheduling and route optimization. First, to minimize the required number of temporary storage sites, a set coverage model was established, and an immune algorithm was used to derive preliminary site selection results. Subsequently, the analytic hierarchy process and fuzzy comprehensive evaluation method were employed to refine and determine the optimal site selection results for recycling treatment facilities. Second, based on the characteristics of APW, with the minimization of recycling transportation costs as the optimization objective, an ant colony algorithm was used to establish a corresponding vehicle scheduling route optimization model, yielding the optimal solution for recycling vehicle scheduling and transportation route optimization. This study not only improved the recycling efficiency of APW but also effectively reduced the recycling costs of APW. Full article

Global climate change has intensified the challenges of low-temperature, low-light, and high-humidity microclimates in North China’s greenhouses during winter, exposing the limitations of traditional controlled-environment agriculture (CEA) facilities. This study monitored air temperature, relative humidity, and light intensity in three greenhouse types—an externally insulated plastic greenhouse, soft-shell solar greenhouse, and brick-walled solar greenhouse—across three overwintering periods (pre-, mid-, post-) using high-precision sensors (monitoring period is from 1 October 2024 to 31 March 2025). A Comprehensive Evaluation Index (CEI) based on the entropy method was developed, integrating seven indicators (daily average temperature, temperature range, hours below 5 °C, average humidity, hours above 80% humidity, average light intensity, and light utilization efficiency) to systematically evaluate greenhouse microclimate regulation performance. Results showed that the brick-walled solar greenhouse exhibited superior thermal insulation, with nearly zero hours below 5 °C during mid-overwintering, while the soft-shell solar greenhouse achieved the highest light utilization efficiency (75.1–79.6%). The externally insulated plastic greenhouse exhibited the highest relative humidity (>80% for 13–19 h/day) but a poor thermal insulation performance. The CEI ranked the brick-walled solar greenhouse (0.86) and the soft-shell solar greenhouse (0.84) significantly higher than the externally insulated plastic greenhouse (0.39), with the relative humidity significantly negatively correlated with light indicators (P < 0.05), and the temperature and light indicators strongly correlated with the CEI (P < 0.01). Structural design and material innovation are critical for climate adaptation. Brick-walled and soft-shell solar greenhouses balance thermal and light performance, while the externally insulated plastic greenhouse faces structural limitations. The findings provide a scientific basis for greenhouse optimization and regional layout planning. Full article

As a globally important cash crop, the optimization of tomato yield and quality is strategically significant for food security and sustainable agricultural development. In order to address the problem of missing point cloud data on fruits in a facility agriculture environment due to complex canopy structure, leaf shading and limited collection viewpoints, the traditional geometric fitting method makes it difficult to restore the real morphology of fruits due to the dependence on data integrity. This study proposes an adaptive symmetry self-matching (ASSM) algorithm. It dynamically adjusts symmetry planes by detecting defect region characteristics in real time, implements point cloud completion under multi-symmetry constraints and constructs a triple-orthogonal symmetry plane system to adapt to multi-directional heterogeneous structures under complex occlusion. Experiments conducted on 150 tomato fruits with 5–70% occlusion rates demonstrate that ASSM achieved coefficient of determination (R²) values of 0.9914 (length), 0.9880 (width) and 0.9349 (height) under high occlusion, reducing the root mean square error (RMSE) by 23.51–56.10% compared with traditional ellipsoid fitting. Further validation on eggplant fruits confirmed the cross-crop adaptability of the method. The proposed ASSM method overcomes conventional techniques’ data integrity dependency, providing high-precision three-dimensional (3D) data for monitoring plant growth and enabling accurate phenotyping in smart agricultural systems. Full article

Planting tomatoes in enclosed facilities requires manual pollination assistance. Chemically-assisted pollination poses environmental pollution and food safety hazards. Contact vibration pollination is inefficient, ineffective, and prone to plant damage. This study developed a non-contact tomato pollination device based on pulse airflow, and conducted an experimental investigation on it. Firstly, a non-contact tomato pollination device based on pulse airflow was designed, based on the reciprocating motion of tomato flowers under the action of pulse airflow. Subsequently, this study took the coverage rate of pollen on the stigma as an indicator, and the optimal pulse airflow parameters were determined, which were a velocity of 1.22 m·s⁻¹, airflow angle of −19.69°, and pulse frequency of 25.64 Hz. Finally, comparative experiments were conducted between the pollination effect of tomatoes based on pulse airflow and other assisted pollination methods. The results show that tomato flowers produce a composite reciprocating vibration under the coupling effect of the inflorescence elastic force and the pulse airflow force, and the coverage of pollen on the stigma is 11.2% higher than assisted pollination using stable airflow. The use of a pulse airflow pollination method can increase the fruit setting rate by 13.21%, increase the weight per fruit by 11.46%, and increase the weight of fruits per bunch by 33.33%. Compared with chemically-assisted fruit setting, no chemical agents were used to ensure a fruit setting rate similar to chemical methods, and the number of seeds per fruit increased by 74.8. Compared with vibration pollination, it eliminated plant damage and increased the fruit setting rate by 4.45%, and improved efficiency by 18.6%. The results indicated that the pollination method based on pulse airflow is environmentally friendly, high-quality, and efficient. This study breaks through the theoretical and parameter limitations of traditional airflow pollination devices, and provides a theoretical base for the development of clean pollination equipment in facility agriculture. Full article

Elevated [CO₂] enhances light interception and carboxylation efficiency in plants. The combined effects of [CO₂] and photosynthetic photon flux density (PPFD) on stomatal morphology, leaf anatomy, and photosynthetic capacity in tomato seedlings remain unclear. This study subjected tomato seedlings (Solanum lycopersicum Mill. cv. Jingpeng No.1) to two [CO₂] (ambient [a[CO₂], 400 µmol·mol⁻¹] and enriched [e[CO₂], 800 µmol·mol⁻¹]) and three PPFD levels (L; low[Ll: 200 µmol·m⁻²·s⁻¹], moderate[Lm: 300 µmol·m⁻²·s⁻¹], and high[Lh: 400 µmol·m⁻²·s⁻¹]) to assess their interactive impacts. Results showed that e[CO₂] and increased PPFD synergistically improved relative growth rate and net assimilation rate while reducing specific leaf area and leaf area ratio. Notably, e[CO₂] decreased stomatal aperture (−13.81%) and density (−27.76%), whereas elevated PPFD promoted stomatal morphological adjustments. Additionally, Leaf thickness increased by 72.98% under e[CO₂], with Lm and Lh enhancing this by 10.79% and 41.50% compared to Ll. Furthermore, photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). While both e[CO₂] and increased PPFD Photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). Moreover, e[CO₂]-Lh treatment maximized total dry mass and seedling health index. Correlation analysis indicated that synergistic optimization of stomatal traits and leaf structure under a combination of e[CO₂] and increased PPFD enhanced light harvesting and CO₂ diffusion, thereby promoting carbon assimilation. These findings highlight e[CO₂]-Lh as an optimal strategy for tomato seedling growth, providing empirical guidance for precision CO₂ fertilization and light management in controlled cultivation. Full article