Search Results (140)

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

The integration of digital twin technology with robotic automation holds significant promise for advancing sustainable horticulture in controlled environment agriculture. This article presents DigiHortiRobot, a novel AI-driven digital twin architecture tailored for hydroponic greenhouse systems. The proposed framework integrates real-time sensing, predictive modeling, task planning, and dual-arm robotic execution within a modular, IoT-enabled infrastructure. DigiHortiRobot is structured into three progressive implementation phases: (i) monitoring and data acquisition through a multimodal perception system; (ii) decision support and virtual simulation for scenario analysis and intervention planning; and (iii) autonomous execution with feedback-based model refinement. The Physical Layer encompasses crops, infrastructure, and a mobile dual-arm robot; the virtual layer incorporates semantic modeling and simulation environments; and the synchronization layer enables continuous bi-directional communication via a nine-tier IoT architecture inspired by FIWARE standards. A robot task assignment algorithm is introduced to support operational autonomy while maintaining human oversight. The system is designed to optimize horticultural workflows such as seeding and harvesting while allowing farmers to interact remotely through cloud-based interfaces. Compared to previous digital agriculture approaches, DigiHortiRobot enables closed-loop coordination among perception, simulation, and action, supporting real-time task adaptation in dynamic environments. Experimental validation in a hydroponic greenhouse confirmed robust performance in both seeding and harvesting operations, achieving over 90% accuracy in localizing target elements and successfully executing planned tasks. The platform thus provides a strong foundation for future research in predictive control, semantic environment modeling, and scalable deployment of autonomous systems for high-value crop production. Full article

The two-spotted spider mite Tetranychus urticae Koch (Acari: Tetranychidae) is a major pest of horticultural, ornamental, fruit, and strawberry crops worldwide. Currently, various management tools have been explored for this pest, with nanoparticles being one of them, which stand out for their characteristics and multiple effects. This study evaluated the effects of green-synthesized gold nanoparticles (AuNPs) on the mortality and repellency of T. urticae and its natural predator Phytoseiulus persimilis under laboratory conditions, as well as their efficacy in greenhouse tomatoes against T. urticae. In the laboratory, a biological window for AuNPs (50–100 mg L⁻¹) on the pest and predator was established using a residual film method and a free-choice assay. In the greenhouse, four concentrations (300, 500, 750, and 1000 mg L⁻¹) were evaluated via foliar application at 10-day intervals. The results showed susceptibility to AuNPs in all stages of T. urticae and the adult P. persimilis. The death times from AuNPs were similar in both species. Furthermore, the AuNPs were selective for the pest rather than the natural enemy. In greenhouses, AuNPs affected T. urticae populations in tomato plants, and significant differences were observed on some continuous and final agronomic variables (associated with fruits). This study showed that T. urticae and P. persimilis were susceptible to green-synthesized AuNPs. AuNPs can be a management tool, although studies on other non-target species and estimating agronomic effects on other crops are recommended. Full article

Greenhouse horticulture plays an important role globally by producing nutritious fruits and vegetables with high resource use efficiency. Modern greenhouses are large-scale high-tech production factories that are increasingly data-driven, and where climate and irrigation control are gradually becoming more autonomous. This is enabled by technological developments and driven by shortages in skilled labor and the demand for improved resource use efficiency. In the Autonomous Greenhouse Challenge, it has been shown that controlling greenhouse cultivation can be done efficiently with intelligent algorithms. For an optimal strategy, however, it is essential that control algorithms properly account for crop responses, which requires appropriate sensors, reliable data, and accurate models. This paper presents the results of the 4th Autonomous Greenhouse Challenge, in which international teams developed six intelligent algorithms that fully controlled a dwarf tomato cultivation, a crop that is well-suited for robotic harvesting, but for which little prior cultivation data exists. Nevertheless, the analysis of the experiment showed that all teams managed to obtain a profitable strategy, and the best algorithm resulted a production equivalent to 45 kg/m²/year, higher than in the commercial practice of high-wire cherry tomato growing. The predominant factor was found to be the much higher plant density that can be achieved in the applied growing system. More difficult challenges were found to be related to measuring crop status to determine the harvest moment. Finally, this experiment shows the potential for novel greenhouse cultivation systems that are inherently well-suited for autonomous control, and results in a unique and rich dataset to support future research. Full article

The main objective of this work was to evaluate new variants of passive heating systems used for horticultural crop cycles planted in the cold period in low-cost greenhouses on the Mediterranean Spanish coast (a mild-winter area). The double low cover (DLC) is variant of the conventional fixed plastic screen that reduces the air volume and increases the airtightness around crops. Three identical DLCs were installed inside a typical greenhouse, and the microclimate measured in the three DLCs was similar. The DLCs reduced the solar radiation transmissivity coefficient by around 0.05 but increased the mean daily substrate and air temperatures (up to 1.6 and 3.6 °C, respectively). They also modified the air humidity, although this can be modulated by opening the vertical sheets located on the greenhouse aisles (DLC vents). The black plastic mulch forming an air chamber around the substrate bags (BMC), a new mulch variant used in substrate-grown crops, increased the substrate temperature with respect to the conventional black mulch covering the entire ground surface. The combination of BMC plus DLC increased the mean daily substrate temperature by up to 2.9 °C, especially at night. Low tunnels covered with transparent film and with a spun-bonded fabric sheet were also compared, and both materials were efficient heating systems regarding substrate and air temperatures. Low tunnels combined with the DLC substantially increased air humidity, but this can be partially offset by opening the DLC vents. The combination of low tunnels and DLC does not seem recommendable for greenhouse crops planted in winter, since both systems reduce solar radiation transmissivity. Full article

In our previous study, we developed a monitoring system for automatically counting tomatoes produced in protected horticulture using deep learning–based object detection. In this study, we adapted the system for sweet peppers and developed a monitoring system tailored to this crop. We evaluated its fruit detection and counting performance in a large-scale commercial greenhouse. Furthermore, we investigated the relationship between fruit counts at different ripeness stages and the total yield in the cultivation area, and we assessed the accuracy when predicting the yield for the following week. The results confirmed that the system maintained a stable fruit detection performance throughout the trial, and that its outputs were reliable enough to indicate its potential to replace manual counting. In addition, the average number of fruits at the 1–40% and 41–80% ripeness stages across six planting rows showed a correlation with the total weekly yield in the entire 0.6 ha cultivation area the following week. A yield prediction model using average fruit counts at these two ripeness stages as explanatory variables achieved a WAPE of 21.35%, indicating that the monitoring system is effective for yield prediction. Full article

Rapid urbanization, climate variability, and land degradation are increasingly challenging traditional open-field farming systems. Soilless farming (SLF) has emerged as a complementary approach to enhance horticultural resilience in space-constrained and climate-stressed environments. This review critically evaluates the role of SLF within the broader framework of climate-smart agriculture (C-SA), with a particular focus on its applications in urban and peri-urban settings. Drawing on a systematic review of the existing literature, the study explores how SLF technologies contribute to efficient resource use, localized food production, and environmental sustainability. By decoupling crop cultivation from soil, SLF enables precise control over nutrient delivery and water use in enclosed environments, such as vertical farms, greenhouses, and container-based units. These systems offer notable advantages regarding water conservation, increased yield per unit area, and adaptability to non-arable or degraded land, making them particularly relevant for high-density cities, arid zones, and climate-sensitive regions. SLF systems are categorized into substrate-based (e.g., coco peat and rock wool) and water-based systems (e.g., hydroponics, aquaponics, and aeroponics), each with distinct design requirements, nutrient management strategies, and crop compatibility. Emerging technologies—including artificial intelligence, the Internet of Things, and automation—further enhance SLF system efficiency through real-time data monitoring and precision control. Despite these advancements, challenges remain. High setup costs, energy demands, and the need for technical expertise continue to limit large-scale adoption. While SLF is not a replacement for traditional agriculture, it offers a strategic supplement to bolster localized food systems and address climate-related risks in horticultural production. Urban horticulture is no longer a peripheral activity; it is becoming an integral element of sustainable urban development. SLF should be embedded within broader resilience strategies, tailored to specific socioeconomic and environmental contexts. Full article

Soil pore water electrical conductivity (EC), as a comprehensive indicator of soil nutrient status, is closely linked to crop growth and development. Accurate prediction of pore water EC is therefore essential for informed and scientific crop management. This study focuses on a greenhouse rose cultivation site in Jiangchuan District, Yuxi City, Yunnan Province, China. Leveraging multi-parameter sensors deployed within the facility, we collected continuous soil data (temperature, moisture, EC, and pore water EC) and meteorological data (air temperature, humidity, and vapor pressure deficit) from January to December of 2024. We propose a hybrid prediction model—PSO–CNN–LSTM–BOA–XGBoost (PCLBX)—that integrates a particle swarm optimization (PSO)-enhanced convolutional LSTM (CNN–LSTM) with a Bayesian optimization algorithm-tuned XGBoost (BOA–XGBoost). The model utilizes highly correlated environmental variables to forecast soil pore water EC. The experimental results demonstrate that the PCLBX model achieves a mean square error (MSE) of 0.0016, a mean absolute error (MAE) of 0.0288, and a coefficient of determination (R²) of 0.9778. Compared to the CNN–LSTM model, MSE and MAE are reduced by 0.0001 and 0.0014, respectively, with an R² increase of 0.0015. Against the BOA–XGBoost model, PCLBX yields a reduction of 0.0006 in MSE and 0.0061 in MAE, alongside a 0.0077 improvement in R². Furthermore, relative to an equal-weight ensemble of CNN–LSTM and BOA–XGBoost, the PCLBX model shows improved performance, with MSE and MAE decreased by 0.0001 and 0.0005, respectively, and R² increased by 0.0007. These results underscore the superior predictive capability of the PCLBX model over individual and ensemble baselines. By enhancing the accuracy and robustness of soil pore water EC prediction, this model contributes to a deeper understanding of soil physicochemical dynamics and offers a scalable tool for intelligent perception and forecasting. Importantly, it provides agricultural researchers and greenhouse managers with a deployable and generalizable framework for digital, precise, and intelligent management of soil water and nutrients in protected horticulture systems. Full article

The use of seaweed-derived biostimulants has gained attention as a sustainable strategy to enhance crop production. Brown seaweeds, in particular, are rich in bioactive compounds that can improve plant growth, yield, and quality parameters. This study investigated the biostimulant potential of extracts derived from Cystoseira barbata for promoting tomato growth and improving fruit quality. Three different extracts (water, alkali, and acid), applied as soil drenches, were tested on a determinate tomato cultivar under greenhouse conditions. In young plants, alkali and acid extracts increased stem length by 40% and 60%, respectively, while water and acid extracts accelerated early flowering. Alkali and acid extracts also improved fruit yield by approximately 65%. Additionally, all extracts enhanced fruit quality by increasing fruit EC and Brix values, soluble carbohydrate levels, total phenolic content, total antioxidant capacity, lycopene and β-carotene concentrations, and vitamin C content, albeit to varying degrees. Along with increases in fruit K concentration in response to water and alkali extracts, all seaweed extract-treated groups showed elevated fruit S concentrations, accompanied by increases in reduced glutathione levels. These results indicate that C. barbata extracts can enhance plant performance while improving the nutritional and nutraceutical properties of tomato fruits. The observed effects were strongly influenced by the extraction method, which alters the extract composition. Extracts from sustainably sourced C. barbata may contribute to improved productivity and quality in horticulture; however, further research is needed to enable the standardized production of C. barbata, optimize biostimulant formulations, and validate their effectiveness under field conditions. Full article

This study investigates the effectiveness of organic compost as a sustainable alternative to chemical fertilizers for improving soil health and enhancing crop productivity under greenhouse conditions. The experiment focused on sweet basil (Ocimum basilicum L.), an aromatic herb highly sensitive to soil fertility and structure, cultivated in sandy loam soil—a prevalent substrate in arid and semi-arid regions, often limited by poor water and nutrient retention. Using a randomized complete block design with six compost application rates, this study evaluated the physicochemical, biochemical, and agronomic responses of both soil and plants. The results demonstrated significant improvements across all parameters (p < 0.05), with the 30 t/ha compost treatment yielding the most notable enhancements in soil structure, nutrient content, and plant performance while maintaining acceptable levels of heavy metals. Soil organic matter (SOM) increased to 13.71%, while shoot length (SL), essential oil content (EOC), and the 100-seed weight improved to 42 cm, 0.83%, and 0.32 g, respectively, compared to the control. These finding underscore the benefits of high compost application rates in boosting greenhouse horticultural productivity while promoting sustainable agriculture. Moreover, this study supports the reduction in chemical fertilizer dependency and encourages the adoption of circular economy principles (CEPs) through organic waste recycling. Full article

In the last decade, interest in the use of seaweed and seaweed-derived products in horticulture has grown due to their great potential as biostimulants for increasing yields and improving food quality in multiple crops. A greenhouse experiment was conducted to investigate the effects of the application of the green seaweed Ulva ohnoi (either as a seaweed suspension [SWS] or seaweed extract [SWE]) on the yield, size, shape, and nutritional quality (i.e., proximate composition and dietary antioxidant content) of tomato fruits (Solanum lycopersicum L. cv. Rio Fuego). A total of 36 tomato plants were potted individually and organized into three experimental groups: SWS (plants drenched with 250 mL of seaweed suspension [2.0%]), SWE (plants drenched with 250 mL of seaweed extract [0.2%]), and control (plants irrigated with water). Each treatment included three replications. The fruits harvested (66%) from SWS-treated plants were produced during the earliest harvest stages. In contrast, the fruits harvested from SWE-treated plants (82%) and control plants (77%) were produced during the late and very late harvest stages. Notably, SWS application significantly enhanced the number of fruits harvested per plant, average fruit weight, yield (kg/plant), number of seeds per fruit, and fruit size. Furthermore, tomato fruits from plants treated with either SWS or SWE exhibited higher percentages of protein, fat, crude fiber, dry matter, and total soluble solids, as well as lower acidity and reduced total carbohydrate content, compared to the control. The antioxidant metabolites in tomatoes, including lycopene, β-carotene, flavonoids, and phenolic acids, increased following the application of SWS and SWE, while anthocyanin and ascorbic acid contents increased only in SWS-treated plants. These results demonstrate that both forms of U. ohnoi application have biostimulating effects on tomato. In particular, the use of SWS shows great potential as a strategy to enhance tomato fruit productivity and quality in sustainable horticultural systems. Full article

Greenhouse cultivation in Almería, Spain, has experienced continuous growth over the last five decades, and this area has established itself as one of Europe’s leading vegetable-producing regions. With 8201 hectares under cultivation, tomatoes are the most important crop, accounting for 63% of the total value of greenhouse tomato production in Spain. The aim of this study is to design and develop a tool that facilitates tomato trellising under greenhouse conditions and allows it to be carried out at the ground level. An operating principle is developed, and a static analysis of the tool is carried out. Time, costs, and risk of falling from height are compared with traditional methods (ladders, stilts, manual wheeled scaffolding, and motorized scaffolding). The tool incorporates a telescopic carbon fiber mast, a direct-current motor, and electromagnets. The results indicate that the tool is the second fastest method (4′38″) and has the second lowest cost (EUR 8026.93). It is concluded that it is a viable option for trellising, since it eliminates the risk of falling from height while maintaining competitive times and reasonable costs. Full article

Acoustic vibrations may induce different changes in plants that perceive them, and plants themselves can also emit acoustic signals. The aim of this review was to cover the past ten years of plant acoustic research and its shortcomings, with a focus on the reflecting, sensing, and emission of ultrasound by plants. Ultrasonication may alter plant growth and development, and an increasing number of studies are being carried out to investigate its effects on both in vitro plant culture and greenhouse or field plant production, as well as on the biochemical and molecular functions of plants. In this paper, we summarized the progress in the use of ultrasound in horticulture and agriculture for enhancing plant growth and development, either in vitro or in vivo, improving yield and crop quality and increasing stress tolerance, as well as for special methodological applications, like sonication-assisted Agrobacterium-mediated transformation. Some research gaps, such as the lack of a precise mechanism for plant ultrasound emission, the possible participation of some reactive radicals in ultrasound signaling, the effect of ultrasound on the epigenome, the role of ultrasound in plant-to-plant communication, and whether there is a specific, sound perceiving organ, etc., were also presented. In addition, a predictive vision is described of how ultrasonication of plants and ultrasound detection emitted by plants can be used in the future to develop green and sustainable agricultural and horticultural technologies. Furthermore, based on our current knowledge, a proposal is presented to combine them with machine learning and artificial intelligence for developing novel production technologies. Full article

This study aimed to evaluate the effect of two irrigation systems (deficit irrigation (DI)—70% of field capacity—and full irrigation (FI)—100% of field capacity) and a biostimulant formulation (silicon (Si) and calcium (Ca) at four different rates) on the chemical composition and fruit quality of greenhouse-grown tomatoes. Deficit irrigation and biostimulant application influenced the proximate composition of tomato fruits. Fructose and glucose were the main soluble sugars, while malic and citric acids were the predominant organic acids. Free sugar and organic acid content increased under DI and biostimulant applications. In contrast, deficit irrigation combined with biostimulant application decreased α-tocopherol levels. In terms of carotenoids, lycopene and β-carotene concentrations were higher under full irrigation. The main fatty acids were palmitic (C16:0) and linoleic (C18:2n6) acids, with saturated (SFA) and polyunsaturated (PUFA) fatty acids being the main classes. Moreover, biostimulant applications reduced the total phenolic content regardless of the irrigation regime, whereas the flavonoid content increased when biostimulants were applied under FI conditions. Regarding antioxidant activity (assessed by TBARS and OxHLIA assays), a variable response to irrigation and biostimulant application was observed. In conclusion, the application of Si and Ca under DI showed promising results in terms of yield and quality of tomato fruit and it could be considered a sustainable strategy to mitigate adverse effects of climate change on horticultural crops. Full article

Plasma-activated water (PAW) is a sustainable and innovative alternative for agriculture, especially in controlled environments like greenhouses. Tomato and pepper are key horticultural crops worldwide, with a considerable part of their production in greenhouses. This study examined the effects of PAW irrigation on seed germination, plant growth, and oxidative stress in tomato and bell pepper plants. PAW was activated for up to 15 min using a 1 L capacity plasma reactor based on a glow-type discharge in air with water-cathode. The concentration of nitrogen compounds and the energy efficiency of synthesis obtained with the reactor were moderately high (5.4 mM and 60 nmol/J, respectively). The most notable effects of PAW were observed in bell pepper. The germination percentage in bell pepper increased by up to 26%, while no significant effects were found in tomato seeds. PAW irrigation significantly promoted plant growth, with dry weight increasing by up to 61% in bell pepper and 42% in tomato. Lipid peroxidation results showed no oxidative damage in either crop. The biochemical analysis of antioxidant enzymes (catalase, superoxide dismutase, and guaiacol peroxidase) confirmed that plant defense systems responded adequately to PAW irrigation. These results highlight PAW’s potential as an innovative and eco-friendly alternative in agriculture. Full article