Xanthoceras sorbifolium Bunge, belonging to the Sapindaceae family, has been one of the most potential promising woody oil species in northern China. X. sorbifolium can play the important ecological roles, including desert greening, windbreak, and sand fixation, also providing for the edible and medicinal value among plant resources. Furthermore, X. sorbifolia can be used as nature food for health protection and disease prophylaxis in recent years, such as for tea, due to its high concentration of unsaturated fatty acids, especially neuroprotective nervonic acid. The leaves and buds of X. sorbifolium also share the nourishing ingredients and bioactive substances, including amino acids, proteins, soluble sugars, polyphenols, flavonoids, and saponins. In this study, a full-factor design was adopted with five levels of steeping temperature and seven levels of steeping time. Nutritional quality of the tea infusions was evaluated under 35 combinations. A systematic investigation was conducted to fully clarify the influence of brewing conditions on the quality of the tea infusions with the Xanthoceras sorbifolium bud green tea (XBT). Fuzzy A fuzzy membership function was used to screen the optimal brewing parameters. The aroma and taste of the tea infusions with XBT were characterized by gas chromatography-ion mobility spectrometry, electronic nose, and electronic tongue. The results showed that the content of tea polyphenols in the tea infusions of XBT first increased, then decreased, and finally tended to be stable, with the extension of steeping time. While the contents of total free amino acids, flavonoids, and caffeine generally showed a trend of first increasing and then decreasing. At the same time, a higher brewing temperature was conducive to the dissolution of soluble sugar components. Fuzzy The fuzzy membership function also showed that the long-term brewing (360, 720 min) was not conducive to the overall quality of the tea infusions, while short brewing time (5 min) together with low temperature (50, 60 ℃) failed to fully dissolve the nutrients in the tea infusions of XBT. Three optimal combinations of steeping parameters were obtained: 70 ℃ for 60 min, 90 ℃ for 30 min, and 80 ℃ for 30 min. A total of 60 volatile organic compounds and 13 key aroma substances were detected in the tea infusions. 2-methylbutyraldehyde and 3-methylbutyraldehyde jointly contributed to the roast aroma of tea infusions, while both octanal and hexanal contributed to the fresh fruit aroma of the tea infusions, and pentanal contributed to the grassy aroma of the tea infusions. The brewing conditions of 70 ℃ for 60 min and 80 ℃ for 30 min were more benefits beneficial to the retention of aroma substances in the tea infusions, thereby reducing the bitterness and astringency. According to the nutritional quality, taste, and aroma, the optimal combination of 80 ℃ for 30 min was recommended as the daily drinking brewing for XBT. The finding can also provide a theoretical basis for the subsequent processing of tea beverages. In short, the bud can be expected to serve as a tea products for the high economic value of Xanthoceras sorbifolium.

Kitchen waste (KW) composting often suffers from prolonged processing time and strong odor emissions due to the high moisture content and complex organic composition of the substrate. This study aimed to elucidate how inoculation with an immobilized bacterial consortium (IBC) regulates the microbial community, co-occurrence network structure, and metabolic functions in a KW composting system, thereby improving composting efficiency and mitigating odor generation. A composting system inoculated with an IBC composed of six functional bacterial strains was established, with a non-inoculated treatment serving as control. The physicochemical parameters of the compost, including temperature, moisture content, pH, and germination index (GI), were continuously monitored throughout the 15-day process. Bacterial community composition and succession were analyzed via 16S rRNA gene sequencing. Co-occurrence networks were constructed for different composting phases to reveal changes in microbial interactions. Functional Annotation of Prokaryotic Taxa (FAPROTAX) was applied to predict metabolic pathways related to carbon, nitrogen, and sulfur cycling. Partial Least Squares Path Modeling (PLS-PM) was used to explore causal relationships among physicochemical conditions, microbial community structure, network complexity, metabolic functions, and composting efficiency. The IBC treatment sustained a longer and more stable thermophilic phase than the control, accelerating compost maturity, with the GI reaching 88.89% on day 15 compared to 58.89% in the control. Inoculation significantly reshaped the bacterial community structure and enhanced deterministic assembly processes, guiding microbial succession toward functional guilds specialized in organic degradation and nutrient transformation. The inoculated compost exhibited greater network complexity, characterized by increased node and edge numbers, higher average degree, and reduced path length and network diameter, indicating stronger microbial connectivity and synergistic metabolic cooperation. Functional prediction showed that carbon cycling was dominated by chemoheterotrophy and aerobic chemoheterotrophy, both increasing over time, while fermentation functions gradually declined. In the nitrogen cycle, nitrite respiration and dissimilatory ammonification were most active during the early phase, but nitrogen fixation became dominant in the later cooling and maturation stages. Sulfur respiration pathways were markedly suppressed in the inoculated group, implying the inhibition of reductive sulfur metabolism and reduced potential for odor emission. PLS-PM analysis further demonstrated that microbial inoculation reversed the relationship between physicochemical properties and bacterial community from negative to positive, promoting the enrichment of core functional taxa. The relationship between community structure and metabolic function shifted from diversity-driven to functional taxa-driven patterns. Although the direct effect of network complexity on composting efficiency declined, it indirectly enhanced system functionality through improved robustness and cooperative stability. The immobilized bacterial consortium effectively optimized the composting physicochemical environment, reconstructed microbial interaction networks, and reinforced functional coupling among key taxa. These integrated effects accelerated organic matter degradation, shortened the composting period, and reduced odor emissions. The study provides new ecological insights into the microbial regulatory mechanisms of KW composting and supports the development of efficient, low-emission, and sustainable biotechnological strategies for organic waste recycling.

To address the feed arching phenomenon that occurs during the feeding process of beef cattle and to satisfy the individualized feeding requirements of beef cattle, a roller-brush type supplementary feeding and pushing robot was designed in this study, which consists of a roller-brush pushing device, a screw-type supplementary feeding device, and an Ackermann chassis. The structural design of the feeding screw and the pushing roller brush was completed, and the motion behavior of feed particles was analyzed. In order to investigate the influence of the motion parameters of the supplementary feeding and pushing robot on the feeding and pushing performance, a simulation analysis of the robot’s motion process was carried out based on the EDEM-RecurDyn coupling method. First, the contact parameters among total mixed ration (TMR) particles as well as between the feed and the mechanical components were determined. Subsequently, dynamic models of the supplementary feeding device and the pushing device were respectively constructed in RecurDyn, and a flexible mesh was generated for the roller brush. Finally, a feed particle model was built in the EDEM software, and the device models were imported to complete the coupled simulation. In the study of feeding performance, the screw rotation speed and the robot’s travelling speed were taken as experimental factors, while feeding uniformity and feeding efficiency were used as evaluation indicators. In the study of pushing performance, the roller brush rotation speed, the roller brush deflection angle, and the robot’s travelling speed were taken as experimental factors, and the pushing rate and pushing efficiency were used as evaluation indicators. Single-factor and orthogonal experimental methods were adopted for the simulation tests. The simulation results showed that when the screw rotation speed of the supplementary feeding and pushing robot was 160 r/min, the robot travelling speed was 0.68 m/s, the roller brush rotation speed was 450 r/min, and the roller brush deflection angle was 40°, the feeding uniformity exceeded 96%, the feeding efficiency reached 120.6 kg/min, the pushing rate was 98.25%, and the pushing efficiency was 418.94 kg/min. Prototype tests were carried out under these optimal parameters, and the obtained results were as follows: feeding uniformity greater than 93%, feeding efficiency of 135.8 kg/min, pushing rate of 97.90%, and pushing efficiency of 311.90 kg/min. The designed robot exhibits good working performance and can meet the auxiliary feeding requirements of small- and medium-scale cattle barns.

Satellite remote sensing can identify the irrigation information, because of its rapid and wide-area observation. However, only a single source is often extracted from remote sensing data. Spatial and temporal resolution cannot fully meet the requirement for the high-accuracy and dynamic identification of irrigation information at the regional scale, especially for the strong spatial heterogeneity of agricultural activities in the complex terrain. In this study, a remote sensing framework was developed to identify the irrigation information using drought index analysis and spatiotemporal fusion. The Guanzhong Region was also taken as the study area. The temperature vegetation dryness index (TVDI) was selected as the identification index after correlation analysis between drought indices and soil moisture. Elevation correction with fusion optimization was introduced to characterize the variation in the soil moisture. Its spatiotemporal fusion accuracy was also enhanced under complex terrain conditions. Subsequently, the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) was used to fuse high-spatial-resolution Landsat imagery and high-temporal-resolution MODIS data for the high-spatiotemporal-resolution TVDI time series. Spring irrigation information in the Guanzhong Region in 2024 was identified using the threshold method with precipitation data. The results showed that the correlations between the remote sensing drought indices and soil moisture at the 10-20 cm depth were generally higher than those with soil moisture at the 0-10 cm depth. Elevation topographic correction effectively reduced the influence of terrain on land surface temperature. There was a strong correlation between TVDI and soil moisture. Furthermore, the elevation-corrected TVDI showed a strong negative correlation with soil moisture at the 10-20 cm depth, with the maximum correlation coefficient of −0.77 during the spring crop growth period. Normalized difference vegetation index (NDVI) and land surface temperature (LST) were fused for the higher accuracy of TVDI than the strategy of first calculation and then fusion. R² and RMSE values of 0.76 and 0.07 for the former, whereas 0.44 and 0.13 for the latter, respectively. The validation showed that the overall accuracy was 90.8% for the identification in the Donglei Phase II irrigation district, with a Kappa coefficient of 0.80. The mean error was 15.1% and 14.3%, respectively, for accumulated and actual irrigated areas in the irrigation districts. Regional identification results indicated that the spring irrigation was mainly concentrated from March to April, with the irrigation frequency ranging from one to two times. Irrigated areas were distributed in the relatively flat Weihe Plain, with a spatial pattern characterized by broader irrigation extent and higher irrigation frequency in the eastern and western parts. While the central part exhibited relatively lower irrigation intensity. The spatial distribution and irrigation frequency of spring irrigation were dominated by regional topography, water supply, and cropping structure. The finding can provide a strong reference to identify the regional-scale irrigation information and water resources under complex terrains.

Due to the poor mass transfer, long reaction time, and severe material back mixing in conventional stirring reactions, the microfluidic reaction system, with the advantages of enhanced mass transfer, fast reaction speed, and mitigated substrate inhibition, has received attention. Natural wood is a cheap, renewable, and earth-abundant material, which is regarded as the ideal model for monolithic reactors due to the existing 3D hierarchical structures. Carbonized wood with superior electrical conductivity, chemical and mechanical stability, and tunable multifunctionality endows it as a monolithic reactor object to synthesize advanced materials for multiple purposes. This study constructed a carbonized monolithic microreactor for the continuous-flow catalytic synthesis of ethyl cinnamate, using the basswood column with a natural three-dimensional microchannel structure, which was carbonized in a nitrogen atmosphere at 700 ℃. The peristaltic pump tube is used to connect the metal coil and the carbonized monolithic microreactor in turn. The peristaltic pump sends the reaction liquid to the metal coil, and the oil bath pan heats the metal coil to preheat the reaction liquid. Subsequently, the reaction liquid enters the carbonized monolithic microreactor, and the oil bath circulation device heats the reactor to ensure the reaction temperature. The results indicate that the length and diameter of carbonized-wood columns were reduced from 200 and 40 mm to 165 and 29.6 mm, respectively, due to the pyrolysis of lignin, hemicellulose, and cellulose at elevated temperature. The resulting material not only preserves the well-aligned microchannel topology of the original wood, but also exhibits significantly enhanced properties, including high chemical stability, robust mechanical strength, and exceptional mass and heat transfer performance—laying a solid foundation for efficient continuous-flow catalytic processes. SEM characterization demonstrated the regular and hierarchical porous structures of carbonized column with abundant tubular channels (5-50 µm in diameter) in the wood growth direction and micro-sized pores (0.5-1 µm) inside tubular channels. The micro-sized pores on the tubular channels allowed the liquid substrates to enter the adjacent channels and generate fluid disturbance for improved mass transfer and enhanced catalytic capacity. Then, 96.5% of cinnamic acid conversion was reached with the molar ratio of cinnamic acid to ethanol at 1:20, the catalyst addition of concentrated H₂SO₄ (98 wt%) being 30 % of the mass of cinnamic acid, the reaction temperature of 100 ℃, substrate flow rate of 5 mL/min and the outlet pressure at 0.2 MPa. Under the continuous-flow reaction mode, a carbonized-wood monolithic microreactor induced a maximum TOF of 42.4 h⁻¹ for the catalyst of sulfuric acid, which was 11.7-22.3 times higher than that in batch-mode reaction. This carbonized monolithic microreactor exhibited excellent mechanical strength (4 538 N in load, 31.2 MPa in compressive strength, 3839 MPa in elastic modulus) and acid-base tolerance, which could maintain over 90% of cinnamic acid conversion after 10 consecutive runs. The microchannel reactor was subjected to immersion tests in both acidic and alkaline solutions of varying concentrations for 24 hours. After drying, its structural morphology remained fully intact, demonstrating exceptional resistance to corrosive chemical environments. These properties ensure long-term chemical stability under continuous operation, structural integrity against collapse or deformation caused by reactive fluid flow under process conditions. Besides, it can also be used for the efficient preparation of various flavor esters, such as ethyl acetate (93.5%), hexyl hexanoate (95.7%), iso-amyl p-methoxycinnamate (87.6%), ethyl hexanoate (78.9%), ethyl butyrate (92.0%), and cinnamic acid methylester (92.4%). Hence, the research developed a carbonized-wood monolithic microreactor with basswood as raw material, which was filled into a metal casing after elevated temperature carbonization. The reactor exhibited high mass and heat transfer efficiency, presented good mechanical properties, and acid and alkali resistance. The finding can provide a potential strategy for the efficient synthesis of flavor esters by combining continuous flow reaction and acid catalysis, in industrial applications in the field of food and cosmetics.

Sinohyriopsis cumingii is one of the economically important freshwater mussels in the pearl aquaculture industry. Phenotypic traits of S. cumingii can be expected to evaluate the individual growth performance. Germplasm resources are identified to implement precise genetic breeding. However, conventional manual measurements cannot fully meet the scalability and applicability of the large-scale production in intelligent aquaculture, due to their labor-intensive, time-consuming, and highly susceptible to subjective errors. In this study, an improved measurement was proposed for the non-destructive, rapid, and accurate acquisition of phenotypic parameters using YOLOv8n, termed YOLOv8n-CBM. 1) An integrated phenotypic measurement for S. cumingii was constructed to combine the dynamic transmission, machine vision, and digital image processing. The system comprised a conveyor device, a high-precision industrial camera, and an image processing module. The mussel samples were automatically transported into the imaging area, thus enabling standardized image acquisition and high-throughput phenotypic measurement under continuous dynamic conditions. 2) Three targeted improvements were implemented in the original YOLOv8n network architecture, according to the characteristics of mussel images. In the backbone network, four convolutional block attention modules (CBAM) were embedded after each C2f block to enhance the extraction of contour edges and local features of mussel samples, while effectively suppressing irrelevant background interference. In the neck network, the bidirectional feature pyramid network (BiFPN) was introduced to strengthen bidirectional fusion of multi-scale features for the targets of different sizes and postures. Meanwhile, the original C2f module was replaced with a multi-scale dilated attention (MSDA) module to expand the network’s receptive field for the local fine-grained and global contextual information. Finally, the key phenotypic parameters were extracted, including shell length, full height, shell height, and radial rib length of the buttock angle, according to the geometric relationship between rotated bounding boxes and biological key points. A series of experiments was conducted on a dataset of 50 manually annotated S. cumingii samples with diverse sizes and postures. The results show that the mean average precision (mAP50-95) of the YOLOv8n-CBM model reached 98.2%, indicating the rotated object detection performance over the original YOLOv8n model. The average localization deviation of biological key points was less than 2.0 mm, indicating the high precision in feature detection. The mean absolute errors (MAE) of shell length, full height, shell height, and radial rib length of the buttock angle were 1.51, 1.08, 1.019, and 1.998 mm, respectively. In all groups stratified by different shell lengths and full heights, the measurement errors of YOLOv8n-CBM were consistently lower than those of the original YOLOv8n model, with the maximum absolute error within 2.879 mm. Measurement accuracy and robustness were effectively improved with diverse morphologies and postures. In conclusion, the reliable technical approach was used to realize the rapid, accurate, and non-destructive acquisition of phenotypic traits in S. cumingii. Shellfish growth evaluation and genetic breeding can be expected to support the transition of the pearl industry from empirical farming to data-driven and intelligent aquaculture. The findings can also offer a valuable reference for phenotypic measurement in the molluscan species.

Farmland shelterbelts can be represented as typical narrow linear features in remote sensing imagery. However, the significant challenges remain in accurate segmentation, due to their strong global contextual dependencies and weak local features. In this study, a semantic segmentation model, named MFF-Net, was proposed to accurately and rapidly extract cultivated land and shelterbelts. Multi-feature fusion block (MFFB) and spatially gated fusion mechanism (SGFM) were also adaptively integrated with three complementary approaches: the long-range dependency modeling using a mamba-like linear attention (MLLA) operator, the local detail perception in convolutional networks, and the frequency-domain edge enhancement via fast Fourier transform (FFT). The feature representation was effectively balanced when segmenting elongated objects. Furthermore, a task- oriented super-resolution preprocessing was introduced into the network. This front-end step was designed to reconstruct high-resolution images. Thereby, the textual details were enhanced to sharpen the boundaries of subtle features, like shelterbelts. Superior input was provided for the subsequent segmentation model. A series of experiments was performed on the self-constructed dataset of the farmland shelterbelt. The results demonstrate that the superior performance of MFF-Net was achieved in the precision rates of 96.42% for cropland and 82.83% for shelterbelts, with a mean intersection over union (mIoU) of 83.45%, thus outperforming a range of advanced models, including RS³Mamba, DC-Swin, DeepLabV3+, and SegMAN. Ablation studies validated the effectiveness of each component within the multi-feature fusion. Frequency-domain features via FFTFormer contributed to a 2.80% increase in the shelterbelt IoU, indicating the enhanced boundary discrimination. The spatially gated fusion mechanism (SGFM) further boosted the overall mIoU by 1.71%, indicating the adaptive balance on the contribution rates from different feature domains. Compared with a baseline model, the full MFFB was improved mIoU of 5.14%. Super-resolution preprocessing was integrated with the highly effective auxiliary strategy. Taking 4x upsampled images as the input, there was a remarkable 6.61% increase in shelterbelt IoU and a 2.47% gain in overall mIoU. The difficulties with segmenting narrow targets were effectively mitigated to augment their pixel-width and edge clarity. A complete technical pipeline was established from pixel-level segmentation to vectorization and application. Accurate area estimation was achieved with average relative errors of 7.50% for cropland and 6.76% for shelterbelts, compared with the national survey data. An application analysis of shelterbelt closure degree was also made on individual farmland plots. The 91.95% of the plots met the national standard requirement (≥0.75). In conclusion, the MFF-Net model can be expected to effectively segment the narrow linear features in complex landscapes. Synergistic fusion of global, local, and frequency-domain features was combined with task-oriented super-resolution enhancement. This research can provide a robust technical pathway for the precise monitoring and dynamic evaluation of farmland shelterbelt networks in ecological conservation.

Holistic sidewall ventilation system (HSVS) is characterized by uniform temperature distribution in the poultry house. Yet two challenges remain: low air velocity at the front cross-section and suboptimal positions of recirculation zones in large-scale facilities. The airflow field is governed by the configuration and regulation of air inlets. In this study, the airflow distribution was optimized to enhance overall ventilation performance in HSVS poultry houses. The opening angles of local front inlets were also adjusted using field measurements and numerical simulations. A systematic analysis was implemented to explore the effects of inlet angles on the airflow field. A full-scale HSVS poultry house was selected as the research object, where 118 sidewall air inlets were divided into front, middle, and rear segments (40, 40, and 38 inlets, respectively). Two ventilation scenarios (with 3 and 4 operational fans) were evaluated, wherein the opening angles of the front inlets were adjusted within the range of 10° to 90°, whereas the middle and rear air inlets were kept at fixed angles to match the ventilation scenarios. Air velocity and pressure difference were continuously measured at 6 sensor points in the laying hen activity zone (1.5 m above the ground). Computational fluid dynamics (CFD) incorporated with the Reynolds-averaged Navier-Stokes (RNG) k-ε turbulence model was adopted to simulate the airflow field. The air velocity non-uniformity coefficient was employed as the evaluation metric to quantify the uniformity of airflow distribution. The results showed that different ventilation scenarios displayed an identical variation trend. The opening angle of the front air inlets reduced the static pressure difference between the inlets and the outdoors, while preserving a uniform distribution of pressure difference. The average pressure difference in the middle section of the poultry house was higher than that at the front end, with an average difference of (1.7±0.2) Pa. This discrepancy was also independent of both the inlet opening angle and the ventilation scenario. Meanwhile, air velocity increased with an increase in the opening angle of the front air inlets, indicating a negative correlation with pressure difference. Under the scenario with 3 operational fans, the maximum average air velocity in the front and middle segments reached (0.18±0.02) m/s (at 70°) and (0.30±0.06) m/s (at 90°), respectively; Under the scenario with 4 operational fans, these values were (0.25±0.04) m/s (at 90°) and (0.38±0.06) m/s (at 90°), respectively. Furthermore, the front inlet opening angle was adjusted to alleviate inadequate ventilation in the front section of the house, indicating a moderate improvement in air velocity in the middle section. The air velocity non-uniformity coefficient decreased consistently, as the inlet angle increased, thus dropping to below 0.30 at the angle of 70° or larger (0.24 for 3 fans and 0.30 for 4 fans at 70°). Subsequently, two optimal operating conditions were selected for further CFD simulation analysis. CFD simulation results showed that the front inlet angles enhanced the overall indoor air velocity, where the average air velocity at the front cross-section increased by 0.10 m/s. The optimal inlet angles effectively mitigated front ventilation dead zones for the airflow uniformity, indicating less unfavorable recirculation zones. The opening angle of the front air inlets was adjusted to 70° or larger for the weak ventilation zone at the front of HSVS poultry houses, indicating indoor airflow uniformity. Zoning regulation of air inlet angles can offer a cost-effective and efficient solution to enhance the ventilation performance of HSVS poultry houses. The finding can provide the theoretical basis and technical support for environmental control optimization in large-scale poultry houses. Future research can be expected to integrate the heat and mass exchange between hens and the environment in smart agriculture.

Accurate and rapid recognition is often required for the king oyster mushroom under dark and humid environments using machine vision. Particularly, the mushrooms can intertwine with mycelial networks after imaging. This study aims to accurately locate king oyster mushrooms under dark and damp environments. An identification framework of the king oyster mushroom was proposed using an infrared array. A test bench was established based on an infrared reflection module. Sensing distance and sensing space cross-sectional radius of the infrared reflection module were then measured under different electrical parameters. A numerical simulation was used to fit the relationship between electrical parameters and infrared sensing distances. A mathematical model was obtained for the infrared reflection under typical parameter conditions. The invisible infrared light was then visualized for mushroom identification, according to the sensing space model from the infrared reflection module. A detection gantry (including multiple linearly arranged infrared reflection modules) was placed over a tray. The tray moved at a constant speed. The output levels of the infrared reflection modules were sampled periodically by an STM32F103ZET6 controller. An information matrix was formed for the position and shape of the mushrooms within the tray area. The sensing information matrix was determined by the number of timed samplings and the infrared reflection modules. Simple matrix operations were performed on the single-connected regions with zero values in the sensing information matrix. According to the morphologies of the king oyster mushroom, a double-cylinder rotary harvester was designed to calculate the position coordinates of the mushroom's center point relative to the tray. A servo motor drove a reducer, thus causing two coaxially arranged hollow cylinders to rotate relative to each other. Six blades evenly distributed below the cylinders were used to cut the king oyster mushroom in a planar motion. The harvester was fixed to a vertically moving linear module. The motion axes were arranged on an execution gantry, thereby driving the horizontal and vertical movements of the harvester. A king oyster mushroom harvesting device was developed, where the detection and execution gantries were sequentially placed on the tray. Taking king oyster mushrooms as the targets, five symmetrically distributed feature positions on the tray were selected for the identification and harvesting experiments. A series of experiments was conducted to verify the device. The time to solve for the mushroom center point coordinates was 3.5-4.5 ms using the information matrix, which was significantly less than the 40-50 ms required for mushroom image processing using machine vision. The high efficiency of the identification was obtained using the infrared array. Meanwhile, the deviation between the inner hole of the harvester and the mushroom cap center was controlled within 1.5-4.0 mm after the harvester was positioned on the mushroom. This gap met the operational quality requirements of mushroom harvesting robots. The harvesting success rate reached 100%, indicating the high positioning accuracy of the motion axis. The king oyster mushroom identification was developed using typical infrared reflection modules, whose cost was only 1/20 of the mainstream machine vision products. The outstanding efficiency and economic advantages were achieved in the strongly interfering substrate and mycelial networks. The findings can also provide a technical pathway for the edible king oyster mushroom harvesting under complex backgrounds.

Suburban rural areas of metropolitan regions can serve as the interface between urban and rural elements. Their rural settlements have posed challenges in recent years, such as idle and inefficient land use, scattered spatial layouts, and supply-demand mismatches in functions. Rural settlement consolidation can be expected to increasingly emphasize rural revitalization and territory-wide land consolidation. An accurate release of consolidation potential is often required for the precise alignment between land supply and development demand. Therefore, this study aims to assess the potential of rural settlements for the differentiated consolidation pathways in rural stock resources. A case study was taken of Jurong City, a suburb of the Nanjing metropolitan area. A "supply-demand assessment-type identification” framework was constructed using supply-demand theory. Supply–demand consolidation potential of rural settlements was also assessed using a one-class support vector machine (SVM) and machine learning. Furthermore, the precise pathways of land resource allocation were also explored at the village scale, according to the rural dominant function demands. The results show: 1) The theoretical consolidation potential of rural settlements was 8 490.19 hm², accounting for 61.51% of the settlement area. The willingness simulation model was validated with an accuracy of 87.81% and a recall rate of 95.48%, indicating high precision. The modeled willingness values ranged from 0.33 to 0.76 for administrative villages. Specifically, the villages with higher consolidation willingness were distributed in the southeastern region, including the Maoshan Scenic Area, Maoshan, Houbai, and Tianwang Town. The actual consolidation potential of rural settlements was 5441.91 hm² after correction, representing 39.42% of the rural settlement land. 2) The demand potential of rural revitalization ranged from 0.20 to 0.60, indicating a pattern of “higher in the west, lower in the east, with clustered distribution.” The number of medium-demand villages was the largest among all villages, totaling 100 (53% of all villages). 3) Four types of zones were identified for the supply-demand potential: priority consolidation, reserve regulation, demand-oriented, and stable control zone, accounting for 43, 35, 73, and 37 villages, respectively. 4) Four types of dominant functional demands were identified among the rural settlements, with the majority of balanced development villages. Most villages shared no dominant functional demand, resulting in a balanced functional profile with scattered spatial distribution. Potential zones were coupled with dominant functional demands. 12 consolidation types were derived at the village scale. Potential release pathways were summarized, such as “spatial reconstruction,” “precise guidance,” “flexible regulation,” and “micro-renewal,” thus enabling “one village, one strategy” precise intervention. Targeted consolidation measures were also proposed, such as “releasing potential through village reorganization” and “innovating dynamic land reservation supply.” Differentiated strategies were implemented to promote intensive and economical land use for the rural functions and spatial patterns. The findings can also provide a practical demonstration and reference to precisely match land supply with rural revitalization demands in the spatial units of metropolitan suburbs.