Search Results (303)

Continuous and accurate biomass measurement is a critical enabler for control, decision making, and optimization in modern plant production systems. It supports the development of plant growth models for advanced control strategies like model predictive control, and enables responsive, data-driven, and plant state-dependent cultivation. Traditional biomass measurement methods, such as destructive sampling, are time-consuming and unsuitable for high-frequency monitoring. In contrast, image-based estimation using computer vision and deep learning requires frequent retraining and is sensitive to changes in lighting or plant morphology. This work introduces a low-cost, load-cell-based biomass monitoring system tailored for vertical farming applications. The system operates at the level of individual growing trays, offering a valuable middle ground between impractical plant-level sensing and overly coarse rack-level measurements. Tray-level data allow localized control actions, such as adjusting light spectrum and intensity per tray, thereby enhancing the utility of controllable LED systems. This granularity supports layer-specific optimization and anomaly detection, which are not feasible with rack-level feedback. The biomass sensor is easily scalable and can be retrofitted, addressing common challenges such as mechanical noise and thermal drift. It offers a practical and robust solution for biomass monitoring in dynamic, growing environments, enabling finer control and smarter decision making in both commercial and research-oriented vertical farming systems. The developed sensor was tested and validated against manual harvest data, demonstrating high agreement with actual plant biomass and confirming its suitability for integration into vertical farming systems. Full article

Indoor horticulture requires a substantial quantity of electricity to meet crops extended photoperiodic requirements for optimal photosynthetic rate. Simultaneously, global electricity costs have grown dramatically in recent years, endangering the sustainability and profitability of indoor vertical farms and/or modern greenhouses that use artificial lighting systems to accelerate crop development and growth. This study investigates the growth rate and physiological development of cherry tomato plants cultivated in a pilot indoor vertical farm at the Agricultural University of Athens’ Laboratory of Farm Structures (AUA) under continuous and disruptive lighting. The leaf physiological traits from multiple photoperiodic stress treatments were analyzed and utilized to estimate the plant’s tolerance rate under varied illumination conditions. Four different photoperiodic treatments were examined and compared, firstly plants grew under 14 h of continuous light (C-14L10D/control), secondly plants grew under a normalized photoperiod of 14 h with intermittent light intervals of 10 min of light followed by 50 min of dark (NI-14L10D/stress), the third treatment where plants grew under 14 h of a load-shifted energy demand response intermittent lighting schedule (LSI-14L10D/stress) and finally plants grew under 13 h photoperiod following of a load-shifted energy demand response intermittent lighting schedule (LSI-13L11D/stress). Plants were subjected also under two different light spectra for all the treatments, specifically WHITE and Blue/Red/Far-red light composition. The aim was to develop flexible, energy-efficient lighting protocols that maintain crop productivity while reducing electricity consumption in indoor settings. Results indicated that short periods of disruptive light did not negatively impact physiological responses, and plants exhibited tolerance to abiotic stress induced by intermittent lighting. Post-harvest data indicated that intermittent lighting regimes maintained or enhanced growth compared to continuous lighting, with spectral composition further influencing productivity. Plants under LSI-14L10D and B/R/FR spectra produced up to 93 g fresh fruit per plant and 30.4 g dry mass, while consuming up to 16 kWh less energy than continuous lighting—highlighting the potential of flexible lighting strategies for improved energy-use efficiency. Full article

Urban agriculture (UA) is emerging as a promising strategy for sustainable food production in response to growing environmental pressures. Indoor vertical farming (IVF), combining Controlled Environment Agriculture (CEA) with Building-Integrated Agriculture (BIA), enables efficient resource use and year-round crop cultivation in urban settings. This study assesses the environmental performance of a prospective IVF system located on a university campus in Portugal, focusing on the integration of photovoltaic (PV) energy as an alternative to the conventional electricity grid (GM). A Life Cycle Assessment (LCA) was conducted using the Environmental Footprint (EF) method and the LANCA model to account for land use and soil-related impacts. The PV-powered system demonstrated lower overall environmental impacts, with notable reductions across most impact categories, but important trade-offs with decreased soil quality. The LANCA results highlighted cultivation and packaging as key contributors to land occupation and transformation, while also revealing trade-offs associated with upstream material demands. By combining EF and LANCA, the study shows that IVF systems that are not soil-based can still impact soil quality indirectly. These findings contribute to a broader understanding of sustainability in urban farming and underscore the importance of multi-dimensional assessment approaches when evaluating emerging agricultural technologies. Full article

Accurate pig counting is crucial for precision livestock farming, enabling optimized feeding management and health monitoring. Detection-based counting methods face significant challenges due to mutual occlusion, varying illumination conditions, diverse pen configurations, and substantial variations in pig densities. Previous approaches often struggle with complex agricultural environments where lighting conditions, pig postures, and crowding levels create challenging detection scenarios. To address these limitations, we propose EAPC-YOLO (enhanced adaptive pig counting YOLO), a robust architecture integrating density-aware processing with advanced detection optimizations. The method consists of (1) an enhanced YOLOv8 network incorporating multiple architectural improvements for better feature extraction and object localization. These improvements include DCNv4 deformable convolutions for irregular pig postures, BiFPN bidirectional feature fusion for multi-scale information integration, EfficientViT linear attention for computational efficiency, and PIoU v2 loss for improved overlap handling. (2) A density-aware post-processing module with intelligent NMS strategies that adapt to different crowding scenarios. Experimental results on a comprehensive dataset spanning diverse agricultural scenarios (nighttime, controlled indoor, and natural daylight environments with density variations from 4 to 30 pigs) demonstrate our method achieves 94.2% mAP@0.5 for detection performance and 96.8% counting accuracy, representing 12.3% and 15.7% improvements compared to the strongest baseline, YOLOv11n. This work enables robust, accurate pig counting across challenging agricultural environments, supporting precision livestock management. Full article

Background: Reliable and non-invasive methods for assessing welfare in poultry are essential for improving evidence-based welfare monitoring and advancing management practices in commercial production systems. The iris-to-pupil (IP) ratio, previously validated by our group in primates and cattle, reflects autonomic nervous system balance and may serve as a physiological indicator of stress in laying hens. This study evaluated the utility of the IP ratio under field conditions across diverse commercial layer housing systems. Materials and Methods: In total, 296 laying hens (Lohmann Brown, n = 269; White Leghorn, n = 27) were studied across four locations in Canada housed under different systems: Guelph (indoor; pen), Spring Island (outdoor and scratch; organic), Ottawa (outdoor, indoor and scratch; free-range), and Toronto (outdoor and hobby; free-range). High-resolution photographs of the eye were taken under ambient lighting. Light intensity was measured using the light meter app. The IP ratio was calculated using NIH ImageJ software (Version 1.54p). Statistical analysis included one-way ANOVA and linear regression using GraphPad Prism (Version 5). Results: Birds housed outdoors had the highest IP ratios, followed by those in scratch systems, while indoor and pen-housed birds had the lowest IP ratios (p < 0.001). Subgroup analyses of birds in Ottawa and Spring Island farms confirmed significantly higher IP ratios in outdoor environments compared to indoor and scratch systems (p < 0.001). The IP ratio correlated weakly with ambient light intensity (r² = 0.25) and age (r² = 0.05), indicating minimal influence of these variables. Although White Leghorn hens showed lower IP ratios than Lohmann Browns, this difference was confounded by housing type; all White Leghorns were housed in pens. Thus, housing system but not breed was the primary driver of IP variation. Conclusions: The IP ratio is a robust, non-invasive physiological marker of welfare assessment in laying hens, sensitive to housing environment but minimally influenced by light or age. Its potential for integration with digital imaging technologies supports its use in scalable welfare assessment protocols. Full article

Light quality and biostimulants regulate alkaloid biosynthesis and promote plant growth, but their combined effects on vindoline (VDL) and catharanthine (CAT) production in Catharanthus roseus remain underexplored. This study investigated the impact of different LED spectra and an arbuscular mycorrhizal fungi-based biostimulant (BS) on VDL and CAT production in indoor-grown C. roseus. After a 60-day pretreatment under white LEDs, plants were exposed to eight treatments: white (W, control), red (R), blue (B), and red-blue (RB) light, and their combinations with BS. Samples were collected before treatments (T0) and 92 days after pretreatment (T1). No mycorrhizal development was observed. VDL was detected in both roots and leaves, with higher levels in roots. R produced significantly higher mean concentrations of both VDL and CAT than W. BS significantly increased mean concentrations and total yields of both alkaloids than the untreated condition. The combination of R and BS produced the highest mean concentrations and total yields of VDL and CAT. In particular, it resulted in a significantly higher mean concentration and total yield of VDL compared to sole W. Total yields increased from T0 to T1, primarily due to a substantial rise in root yield. In conclusion, combining R and BS proved to be the most effective strategy to enhance VDL and CAT production by maximizing their total yields, which also increased over time due to greater root contribution. This underscores the importance of combining targeted treatments with harvesting at specific stages to optimize alkaloid production under controlled conditions. Full article

This study evaluates the effects of dietary lipid levels on growth performance, hematological health, and muscle composition of juvenile Arapaima gigas. We tested five isonitrogenous diets (451.7 g kg⁻¹ of crude protein) with increasing lipid levels (6%, 10%, 14%, 18%, and 22%). A total of 600 juvenile A. gigas (80.0 ± 10.5 g; 21.8 ± 1.0 cm) were distributed into 20 tanks (500 L; n = 4; 30 fish per tank) in an indoor open system. The fish were fed to apparent satiety four times daily for 60 days. As dietary lipid levels increased, all growth parameters and lipid content in both the whole body and muscle declined. The diet containing 6% lipids resulted in the maximum final weight, weight gain, feed intake, and the lowest feed conversion rate. However, a maximum lipid level of up to 10.26%, with a gross energy-to-protein ratio of 10.15 kcal g⁻¹ in the diet, as determined through polynomial regression analysis, can be used for juvenile A. gigas without significantly affecting weight gain. Diets with high lipid content (18% and 22% lipids) resulted in the lowest survival rates, highest feed conversion rates, lowest condition factor, visible skeletal protrusions, scale depigmentation, and impaired blood biochemistry. The content of eicosapentaenoic acid, docosahexaenoic acid, n-3, and the n-3:n-6 ratio increased in the muscle lipid fraction (mg g⁻¹ of total lipids) in response to higher dietary lipid levels; however, this does not represent an overall improvement in the meat quality, since the total lipid content in the muscle (g of lipid per 100 g of muscle) was reduced due to impaired growth in fish fed high-lipid diets. Notably, the experimental diets also differed in fatty acid composition, which may have influenced some of the physiological and compositional responses observed. Diets with 6% lipids are recommended to provide optimal growth performance, and a maximum dietary lipid level of up to 10.26% is advised to ensure successful A. gigas farming without impairing weight gain. Full article

Current tomato harvesters rely primarily on external color as the sole indicator of ripeness. However, this approach often results in premature harvesting, leading to insufficient lycopene accumulation and a suboptimal nutritional content for human consumption. Such limitations are especially critical in controlled-environment agriculture (CEA) systems, where maximizing fruit quality and nutrient density is essential for both the yield and consumer health. To address that challenge, this study introduces a novel, multimodal harvest readiness framework tailored to nutrient film technology (NFT)-based smart farms. The proposed approach integrates plant-level stress diagnostics and fruit-level phenotyping using wearable biosensors, AI-assisted computer vision, and non-invasive physiological sensing. Key physiological markers—including the volatile organic compound (VOC) methanol, phytohormones salicylic acid (SA) and indole-3-acetic acid (IAA), and nutrients nitrate and ammonium concentrations—are combined with phenomic traits such as fruit color (a*), size, chlorophyll index (rGb), and water status. The innovation lies in a four-stage decision-making pipeline that filters physiologically stressed plants before selecting ripened fruits based on internal and external quality indicators. Experimental validation across four plant conditions (control, water-stressed, light-stressed, and wounded) demonstrated the efficacy of VOC and hormone sensors in identifying optimal harvest candidates. Additionally, the integration of low-cost electrochemical ion sensors provides scalable nutrient monitoring within NFT systems. This research delivers a robust, sensor-driven framework for autonomous, data-informed harvesting decisions in smart indoor agriculture. By fusing real-time physiological feedback with AI-enhanced phenotyping, the system advances precision harvest timing, improves fruit nutritional quality, and sets the foundation for resilient, feedback-controlled farming platforms suited to meeting global food security and sustainability demands. Full article

Pork accounts for 34% of global meat consumption, following poultry and beef. Intensive pig farming has expanded to meet increasing demand, but space constraints and poor environmental conditions can negatively affect pig welfare. This study aimed to investigate pigs’ spatial preferences in response to environmental factors in an experimental pig barn. Six 60-day-old Yorkshire pigs were observed for 60 days. Indoor temperature (IT), relative humidity (IRH), and CO₂ concentration (ICO₂) were measured hourly, and pig positions were recorded using an RGB 2D-IP camera. Pearson correlation analysis was performed using SPSS. IT ranged from 14.3 °C to 25.1 °C, IRH from 78.9% to 96.5%, and ICO₂ from 1038 to 1850 ppm. A strong negative correlation was found between IT and IRH (r = −0.89), while IT and ICO₂ were uncorrelated (r = −0.01). Pigs showed a clear preference for sections with lower IT, supporting previous findings on thermal preference. Structural features, such as two-wall enclosures, also influenced stay frequency. These results suggest that optimizing barn structure and improving ventilation and manure management can support thermal comfort and improve welfare in intensive pig farming systems. Full article

Countries worldwide have implemented regulations on the green coverage ratio of new buildings to address the urban heat island effect. For example, Taipei City mandates that the green coverage rate of new buildings must be between 40% and 70%, while Singapore requires a green coverage rate of 100% or higher. Consequently, building greening is now a regulatory requirement rather than a preference. This study focuses on developing an indoor light-emitting-diode (LED) hydroponic inverted planting system to utilize ceiling space for expanding green areas in buildings. The light source of this system is suitable for both plant growth and daily lighting, thereby reducing electricity costs. The watertight planting unit does not require replenishment of the nutrient solution during a planting cycle for small plants, which can reduce water consumption and prevent indoor humidity. The modular structure allows various combinations, enabling interior designers to create interior ceiling scapes. Additionally, it is possible to grow aromatic plants and edible vegetables, facilitating the creation of indoor farms. Consequently, this system is suitable for high-rise residential buildings, office buildings, underground shopping malls, and indoor areas with limited or no natural light. It is also applicable to hospitals, clinics, wards, and care centers, where indoor plants alleviate psychological stress and enhance mental and physical health. Full article

A prerequisite for the efficient utilization of water and fertilizer in the traditional ridge farming model in the black soil region of Northeast China is the precise elucidation of the small-scale temporal and spatial characteristics of rainfall infiltration and redistribution. However, the existing research findings have yet to fully satisfy this requirement. To investigate soil water infiltration and redistribution at different positions (ridge bed, ridge side, and furrow) before ridge closure in ridge-furrow crops within the black soil regions of Northeast China, indoor simulation experiments and field natural rainfall monitoring were conducted. The indoor test involved rainfall settings of 12, 16, 20, 24, and 30 mm with a rain intensity of 90 mm/h. Field monitoring recorded a natural rainfall intensity of 56 mm/h lasting 22.5 min, with cumulative rainfall reaching 21 mm (randomly measured), to analyze the process of soil water movement post-rainfall. Results indicated that under conventional ridge planting in black soil areas, prior to ridge bed coverage, the infiltration amounts for ridge bed, ridge side, and furrow under 16 mm rainfall conditions equaled the rainfall itself, with ratios close to 1:1:1, showing no significant redistribution of precipitation during infiltration. For rainfall levels of 20 mm, 24 mm, and 30 mm, the ratios of infiltration to rainfall at the ridge bed, ridge side, and furrow positions were 0.92:1.03:1.04, 0.90:1.03:1.06, and 0.89:1.04:1.09, respectively. When rainfall exceeded 20 mm, the infiltration-to-rainfall ratio was approximately 0.9 and 1.04, respectively. Approximately 10% of the rainfall on the ridge platform migrated to the ridge side via splash and runoff, increasing the water volume at the ridge side by about 4%. For rainfall less than 24 mm, the ridge bed, ridge side, and furrow reached a stable state after approximately 50 min of infiltration and redistribution. For rainfall between 24 mm and 30 mm, the ridge platform stabilized within 50 min, whereas the ridge side and furrow required longer stabilization times. These findings elucidate the spatial variation laws of small-scale rainfall infiltration, providing insights for enhancing soil water and fertilizer utilization efficiency. Full article

The production of duckweed (Lemnaceae) as a novel protein source could make a valuable contribution to human nutrition. The greatly reduced habitus of duckweed enables simple cultivation with extremely low space requirements, making this free-floating freshwater plant ideal for substrate-free and vertical cultivation in controlled environment agriculture. Of particular importance in the design of a plant-producing Indoor Vertical Farming process is the determination of light intensity, as artificial lighting is generally the most energy-intensive feature of daylight-independent cultivation systems. In order to make the production process both cost-effective and low emission in the future, it is, therefore, crucial to understand and mathematically describe the primary metabolism, in particular the light utilization efficiency. To achieve this, a growth model was developed that mathematically describes the combined effects of plant density and light intensity on the growth rate of Lemna minor L. and physiologically explains the intraspecific competition of plants for light through mutual shading. Furthermore, the growth model can be utilized to derive environmental and process parameters, including optimum harvest quantities and efficiency-optimized light intensities to improve the production process. Full article

Indoor farming presents a sustainable response to urbanization and climate change, yet optimizing light use efficiency (LUE) remains vital for maximizing crop yield and minimizing energy use. This study introduces an IoT-based framework for adaptive light management in controlled environments, using lettuce (Lactuca sativa L.) as a model crop due to its rapid growth and sensitivity to light spectra. The system integrates advanced LED lighting, real-time sensors, and cloud-based analytics to enhance light distribution and automate adjustments based on growth stages. The key findings indicate a 20% increase in energy efficiency and a 15% improvement in lettuce growth compared to traditional static models. Novel metrics—Light Use Efficiency at Growth stage Canopy Level (LUEP) and Lamp Level (LUEL)—were developed to assess system performance comprehensively. Simulations identified optimal growth conditions, including a light intensity of 350–400 µmol/m²/s and photoperiods of 16–17 h/day. Spectral optimization showed that a balanced blue-red light mix benefits vegetative growth, while higher red content supports flowering. The framework’s feedback control ensures rapid (<2 s) and accurate (>97%) adjustments to environmental deviations, maintaining ideal conditions throughout growth stages. Comparative analysis confirms the adaptive system’s superiority over static models in responding to dynamic environmental conditions and improving performance metrics like LUEP and LUEL. Practical recommendations include stage-specific guidelines for light spectrum, intensity, and duration to enhance both energy efficiency and crop productivity. While tailored to lettuce, the modular system design allows for adaptation to a variety of leafy greens and other crops with species-specific calibration. This research demonstrates the potential of IoT-driven adaptive lighting systems to advance precision agriculture in indoor environments, offering scalable, energy-efficient solutions for sustainable food production. Full article

Aeroponic plant cultivation is a novel technology explored for its potential in indoor farming. In this study, we evaluated the effects of seed treatments with cold plasma on growth, physiological processes, and biochemical parameters in two lettuce cultivars—green variety ‘Perl Gem’ and red variety ‘Cervanek’ cultivated in an aeroponic system for 45 days. Seeds were treated with low-pressure air plasma for 3 min (further denoted as LCP3) or atmospheric dielectric barrier discharge (DBD plasma) for 3 and 5 min (referred to as DBD3 and DBD5 groups). We estimated the effects of seed treatments on parameters of seedling growth, photosynthetic efficiency, amounts of photosynthetic pigments, anthocyanins, total phenolic compounds (TPC), and antioxidant activity in leaves. Despite the observed effects on germination and early growth, seed treatments did not affect biomass gain or head/root ratio in both lettuce cultivars. Seed treatments increased the photosynthetic performance index and amounts of photosynthetic pigments in ‘Pearl Gem’ but not ‘Cervanek’ leaves. Seed treatments enhanced the content of protective phenolic compounds and antioxidant activity in ‘Pearl Gem’, and anthocyanin content in ‘Cervanek’ leaves, indicating potential to improve the nutritional value of the edible part of lettuce cultivated in an aeroponic system. Full article

Modern commercial poultry farming typically occurs indoors, where partial or complete environmental control is employed to enhance production efficiency. Maintaining optimal conditions, such as temperature, relative humidity, carbon dioxide, and ammonia levels, is essential for ensuring bird comfort and maximizing productivity. Monitoring the conditions of poultry houses requires reliable and intelligent management systems. This study introduces a Wireless Monitoring and Control System developed to regulate environmental conditions within poultry facilities. The system continuously monitors key parameters via a network of distributed sensor nodes, which transmit data wirelessly to a centralized control unit using Wi-Fi. The control unit processes the incoming data, stores it in a database, and adjusts actuators accordingly to maintain ideal conditions. A web-based dashboard allows users to monitor and control the environment in real time. Field testing confirmed the system’s effectiveness in keeping conditions optimal, supporting poultry welfare and operational efficiency. Full article