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A plant factory with artificial light (PFAL) is defined as an advanced agricultural production system with a precisely controlled environment, playing an important role in vertical farming and urban food supply. Artificial light is one of the core technologies in PFALs and accounts for a large part of energy consumption; elevating the light utilization efficiency of plants is vital for the sustainable development of PFALs. Meanwhile, the enclosed structure of the plant factory resulted in the independence of its light environment, indicating that the light environment in PFALs can be custom-made. Lighting strategy is an attempt to reprogram the light environmental parameters in unconventional ways, resulting in innovative lighting modes for energy-saving, high-yield, and high-quality production in PFALs. This article reviewed the recent endeavors aiming to increase light conversion efficiency and nutritive properties of crops by different lighting strategies, providing economic irradiation patterns or modes for various PFALs production goals.

The objective of this study was to determine the efficiency of balloon flower sprout’s saponin production in a plant factory with artificial lighting (PFAL). Balloon flower has been traditionally used as herbal medicine and now, it is used as a medicinal plant as well as a functional food. It is important to establish the cultivation conditions for the stable production of high-quality balloon flower. Therefore, this study aimed to investigate the effects of culture systems and temperature conditions on the growth and saponin accumulation of balloon flower sprouts in controlled environment systems. One-year balloon flower roots were cultivated in soil and soilless culture systems at different temperature conditions (20, 25, and 30 °C) for 17 days. The results showed that the shoot fresh weight and shoot dry weight of the balloon flower sprouts grown in the soilless culture system at 25 °C were significantly increased by about 1.29 and 1.58 times, respectively, as compared with those of the sprouts grown in a soil culture system. Sprouts grown in the soilless culture system at 25 °C also recorded the highest root fresh weight, whereas there was no significant difference in root dry weight among the treatments. The plant height results showed an increased trend similar to that of the shoot fresh weight and shoot dry weight of the balloon flower sprouts. The concentrations of platycodin D3 (Pd-D3), polygalcin D (Pc-D), and total saponin in the shoot parts were highest in the soilless culture system at 20 and 25 °C. The root parts of sprouts grown in the soilless culture system at 30 °C also had higher deapioplatycodin D (Dpd-D) and total saponin concentrations. Overall, these results suggest that a soilless culture system with temperature conditions at 20 and 25 °C is suitable for improving the growth and saponin concentration of balloon flower cultivated in PFALs. Ultimately, our research should be a valuable resource for future research on the production of medicinal plants such as sprouts and should provide basic information to establish methods for enhancing the growth and bioactive compounds in balloon flower.

(1) Background: We studied how the generation position of air anions in a closed-type plant factory affects the growth characteristics of lettuce and identified the optimal position. (2) Methods: We used LEDs (red/green/blue = 8:1:1) as a light source and set the temperature and RH of the plant factory to 20 ± 2 ℃ and 50% ± 5%, respectively. We grew lettuce under three air anion conditions—sideward, upward, and downward—and compared the growth characteristics to those of a control grown without air anions. We measured the growth characteristics of the lettuce at 3 and 4 weeks after sowing, and the measurement items were shoot fresh weight (FW) and dry weight (DW); leaf area (LA), length (LL), and width (LW); SPAD; antioxidant capacity; and total phenol content. (3) Results: At 4 weeks, FW in the downward treatment condition was 25.3% higher than in the control, and DW showed a similar difference. LA was about 1943.94 cm²/plant in the downward treatment condition, which was about 15.5% higher than in the control. (4) Conclusions: We conclude that air anion generation has a positive effect on lettuce growth, and the optimal generation position for air anions is downward.

This article identifies the potential environmental effects large-scale indoor farming may have on air, water, and soil. We begin with an overview of what indoor farming is with a focus on greenhouses and indoor vertical farms (eg, plant factories). Next, the differences between these 2 primary methods of indoor farming are presented based on their structural requirements, methods of growing, media, nutrient sources, lighting requirements, facility capacity, and methods of climate control. We also highlight the benefits and challenges facing indoor farming. In the next section, an overview of research and the knowledge domain of indoor and vertical farming is provided. Various authors and topics for research are highlighted. In the next section, the transformative environmental effects that indoor farming may have on air, soil, and water are discussed. This article closes with suggestions for additional research on indoor farming and its influence on the environment. [ABSTRACT FROM AUTHOR]

Background: The sunfleck is an important light environmental factor for plants that live under the shade of trees. Currently, the smartfarm has a system that can artificially create these sunfleks. Therefore, it was intended to find optimal light conditions by measuring and analyzing photosynthetic responses of Eutrema japonica (Miq.) Koidz., a plant living in shade with high economic value under artificial sunflecks. Results: For this purpose, we used LED pulsed light as the simulated sunflecks and set the light frequency levels of six chambers to 20 Hz, 60 Hz, 180 Hz, 540 Hz, 1620 Hz, and 4860 Hz of a pulsed LED grow system in a plant factory and the duty ratio of the all chambers was set to 30%, 50%, and 70% every 2 weeks. We measured the photosynthetic rate, transpiration rate, stomatal conductance, and substomatal CO2 partial pressure of E. japonica under each light condition. We also calculated the results of measurement, A/Ci, and water use efficiency. According to our results, the photosynthetic rate was not different among different duty ratios, the transpiration rate was higher at the duty ratio of 70% than 30% and 50%, and stomatal conductance was higher at 50% and 70% than at 30%. In addition, the substomatal CO2 partial pressure was higher at the duty ratio of 50% than 30% and 70%, and A/Ci was higher at 30% than 50% and 70%. Water use efficiency was higher at 30% and 50% than at 70%. While the transpiration rate and stomatal conductance generally tended to become higher as the frequency level decreased, other physiological items did not change with different frequency levels. Conclusions: Our results showed that 30% and 50% duty ratios could be better in the cultivation of E. japonica due to suffering from water stress as well as light stress in environments with the 70% duty ratio by decreasing water use efficiency. These results suggest that E. japonica is adapted under the light environment with nature sunflecks around 30–50% duty ratio and low light frequency around 20 Hz. [ABSTRACT FROM AUTHOR]

The effect of the ratio of red and blue light on fruit biomass radiation-use efficiency (FBRUE) in dwarf tomatoes has not been well studied. Additionally, whether white light offers a greater advantage in improving radiation-use efficiency (RUE) and FBRUE over red and blue light under LED light remains unknown. In this study, two dwarf tomato cultivars ('Micro-Tom' and 'Rejina') were cultivated in three red-blue light treatments (monochromatic red light, red/blue light ratio = 9, and red/blue light ratio = 3) and a white light treatment at the same photosynthetic photon flux density of 300 μmol m -2 s -1 . The results evidently demonstrated that the red and blue light had an effect on FBRUE by affecting RUE rather than the fraction of dry mass partitioned into fruits (F fruits ). The monochromatic red light increased specific leaf area, reflectance, and transmittance of leaves but decreased the absorptance and photosynthetic rate, ultimately resulting in the lowest RUE, which induced the lowest FBRUE among all treatments. A higher proportion of blue light (up to 25%) led to a higher photosynthetic rate, resulting in a higher RUE and FBRUE in the three red-blue light treatments. Compared with red and blue light, white light increased RUE by 0.09-0.38 g mol -1 and FBRUE by 0.14-0.25 g mol -1 . Moreover, white light improved the F fruits in 'Rejina' and Brix of fruits in 'Micro-Tom' and both effects were cultivar-specific. In conclusion, white light may have greater potential than mixed red and blue light for enhancing the dwarf tomato FBRUE during their reproductive growth stage., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Ke, Yoshida, Hikosaka and Goto.)

Medicinal plants (MPs) are valued for their contributions to human health. However, the growing demand for MPs and the concerns regarding their quality and sustainability have prompted the reassessment of conventional production practices. Controlled environment cropping systems, such as vertical farms, offer a transformative approach to MP production. By enabling precise control over environment factors, such as light, carbon dioxide, temperature, humidity, nutrients, and airflow, controlled environments can improve the consistency, concentration, and yield of bioactive phytochemicals in MPs. This review explores the potential of controlled environment systems for enhancing MP production. First, we describe how controlled environments can overcome the limitations of conventional production in improving the quality of MP. Next, we propose strategies based on plant physiology to manipulate environment conditions for enhancing the levels of bioactive compounds in plants. These strategies include improving photosynthetic carbon assimilation, light spectrum signalling, purposeful stress elicitation, and chronoculture. We describe the underlying mechanisms and practical applications of these strategies. Finally, we highlight the major knowledge gaps and challenges that limit the application of controlled environments, and discuss future research directions., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

While it is commonly understood that air temperature can greatly affect the process of photosynthesis and the growth of higher plants, the impact of root zone temperature (RZT) on plant growth, metabolism, essential elements, as well as key metabolites like chlorophyll and carotenoids, remains an area that necessitates extensive research. Therefore, this study aimed to investigate the impact of raising the RZT on the growth, metabolites, elements, and proteins of red leaf lettuce. Lettuce was hydroponically grown in a plant factory with artificial light at four different air temperatures (17, 22, 27, and 30°C) and two treatments with different RZTs. The RZT was raised 3°C above the air temperature in one group, while it was not in the other group. Increasing the RZT 3°C above the air temperature improved plant growth and metabolites, including carotenoids, ascorbic acids, and chlorophyll, in all four air temperature treatments. Moreover, raising the RZT increased Mg, K, Fe, Cu, Se, Rb, amino acids, and total soluble proteins in the leaf tissue at all four air temperatures. These results showed that raising the RZT by 3°C improved plant productivity and the metabolites of the hydroponic lettuce by enhancing nutrient uptake and activating the metabolism in the roots at all four air temperatures. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology. Overall, this research demonstrates that plant growth and metabolites can be improved simultaneously with an increased RZT relative to air temperature. This study serves as a foundation for future research on optimizing RZT in relation to air temperature. Further recommended studies include investigating the differential effects of multiple RZT variations relative to air temperature for increased optimization, examining the effects of RZT during nighttime versus daytime, and exploring the impact of stem heating. This research has the potential to make a valuable contribution to the ongoing growth and progress of the plant factory industry and fundamental advancements in root zone physiology., Competing Interests: Authors MU and AY were employed by the company Plants Laboratory Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hayashi, Levine, Yu, Usui, Yukawa, Ohmori, Kusano, Kobayashi, Nishizawa, Kurimoto, Kawabata and Yamori.)

This study investigates and quantifies the integrative effects of CO2 concentration (500, 1000 and 1500 µmol mol−1), illumination intensity (100, 200 and 300 μmol m−2 s−1) and air speed (0.25, 0.50 and 0.75 m s−1) on the growth, gas exchange and light use efficiency of lettuce plants (Lactuca sativa L.) grown under artificial lighting. The results show that lettuce growth and gas exchange are closely related to CO2 concentration and illumination intensity, while air speed enhances CO2 transport during photosynthesis. The most influential two-way interactions were observed between CO2 concentration and illumination intensity on the fresh and dry weights of lettuce shoots with effect sizes of 34% and 32%, respectively, and on the photosynthesis, transpiration and light use efficiency, with effect sizes of 52%, 47% and 41%, respectively. The most significant three-way interaction was observed for the photosynthetic rate, with an effect size of 51%. In general, the fresh and dry weights of lettuce plants increased by 36.2% and 20.1%, respectively, with an increase in CO2 concentration from 500 to 1500 µmol mol−1 and by 48.9% and 58.6%, respectively, with an increase in illumination intensity from 100 to 300 μmol m−2 s−1. The photosynthetic rate was found to be positively correlated with CO2 concentration, illumination intensity and air speed. The transpiration rate and stomatal conductance increased by 34.9% and 42.1%, respectively, when the illumination intensity increased from 100 to 300 μmol m−2 s−1. However, as CO2 concentration increased from 500 to 1500 μmol mol−1 and air speed increased from 0.25 to 0.75 m s−1, the transpiration rate decreased by 17.5% and 12.8%, respectively. With the quantified data obtained, we were able to adequately determine how CO2 concentration, illumination intensity and air speed interact with their combined effects on the growth of lettuce plants grown in indoor cultivation systems with artificial lighting.

The optimization of plant-specific LED lighting protocols for indoor plant growing systems needs both basic and applied research. Experiments with lettuce, Lactuca sativa L., plants using artificial lighting based on narrow-band LEDs were carried out in a controlled environment. We investigated plant responses to the exclusion of certain spectral ranges of light in the region of photosynthetically active radiation (PAR); in comparison, the responses to quasimonochromatic radiation in the red and blue regions were studied separately. The data on plant phenotyping, photosynthetic activity determination, and PAM fluorometry, indicating plant functional activity and stress responses to anomalous light environments, are presented. The study on carbon isotopic composition of photoassimilates in the diel cycle made it possible to characterize the balance of carboxylation and photorespiration processes in the leaves, using a previously developed oscillatory model of photosynthesis. Thus, the share of plant photorespiration (related to plant biomass enrichment with 13C) increased in response to red-light action, while blue light accelerated carboxylation (related to 12C enrichment). Blue light also reduced water use efficiency. These data are supported by the observations from the light environments missing distinct PAR spectrum regions. The fact that light of different wavelengths affects the isotopic composition of total carbon allowed us to elucidate the nature of its action on the organization of plant metabolism.

In this study, we investigated the effects of different-colored light-emitting diodes (LEDs) on the growth and quality of daughter cladodes of the edible cactus Nopalea cochenillifera. Cladodes were cultured hydroponically using the deep-flow technique under red, blue, or a combination of red and blue, or red, blue, and green light in an enclosed-type plant factory. We found that daughter cladodes developed from the mother cladodes in all the treatments, despite pH of the nutrient solution drastically decreasing over time. However, the elongation growth rate of the first daughter cladodes and the number of daughter cladodes produced were highest under red light and lowest under blue light, indicating that blue light suppresses daughter cladode development. The total fresh weight (FW) of the daughter cladodes emerging from a single mother cladode was also lowest under blue light. However, the average FW of the daughter cladodes was the highest under blue light, or under simultaneous irradiation with red and blue light. The number of spines, which is an undesirable characteristic in edible cacti, was significantly lower under red light than under blue light, while the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity of the daughter cladodes was the highest under blue light or under simultaneous irradiation with red and blue light. Our results show that light wavelength has a strong effect on daughter cladode development in N. cochenillifera, so controlling the light environment represents an effective approach for improving the growth and quality of this edible cactus.

A plant factory is an environmentally controlled facility that can sustain stable crop cultivation while ensuring fast production and better crop quality by manipulating temperature, humidity, lighting, nutrient supply, and other cultivation factors. It requires better cultivation planning to fully utilise the facility since the set up and operating costs are high. This study aims to schedule crops in a commercial plant factory to maximise revenue by determining which crops are cultivated, the quantity, and at what time. The model considers not only crop market prices but also crop properties such as cultivation duration, volume change, multiple periods of harvests, and yield rates under different environmental settings. The problem is formulated as a mixed integer programming problem to find an optimal schedule. For a large size problem, Lagrangian relaxation with surrogate subgradient method is applied to obtain a good solution in a short time. The numerical results show that, compared to the integer program solver, the proposed method provides faster solutions with more than 80% efficacy when longer planning periods and multiple cultivation rooms are considered. • Multi-crop schedule in a plant factory can be optimised for maximum revenue. • Crop transplanting maximises space utilisation and therefore revenue. • Linear programming schedules planting based on prices. • The constraints in linear programming include yield, volume and harvests. • Lagrangian relaxation can be applied to obtain near-optimal solutions. [ABSTRACT FROM AUTHOR]

Summary: Vertical farming is a type of indoor agriculture where plants are cultivated in stacked systems. It forms a rapidly growing sector with new emerging technologies. Indoor farms often use soil‐free techniques such as hydroponics and aeroponics. Aeroponics involves the application to roots of a nutrient aerosol, which can lead to greater plant productivity than hydroponic cultivation. Aeroponics is thought to resolve a variety of plant physiological constraints that occur within hydroponic systems. We synthesize existing studies of the physiology and development of crops cultivated under aeroponic conditions and identify key knowledge gaps. We identify future research areas to accelerate the sustainable intensification of vertical farming using aeroponic systems. [ABSTRACT FROM AUTHOR]

Vertical farming (VF) is a novel plant production system that allows local production of high-quality fruits and vegetables for rapidly growing cities. VF offers a myriad of opportunities to move from genetic to environmental modification and to produce crops of guaranteed quality and quantity independent of weather, soil conditions, or climate change. [ABSTRACT FROM AUTHOR]

Controlled environment (CE) food crop production has existed in the United States for many years, but recent improvements in technology and increasing production warranted a closer examination of the industry. Therefore, our objectives were to characterize historical trends in CE production, understand the current state of the U.S. hydroponics industry, and use historical and current trends to inform future perspectives. In the 1800s, CE food production emerged and increased in popularity until 1929. After 1929, when adjusted for inflation (AFI), CE food production stagnated and decreased until 1988. From 1988 to 2014, the wholesale value of CE food production increased from $64.2 million to $796.7 million AFI. With the recent increase in demand for locally grown food spurring an increase in CE production, both growers and researchers have been interested in using hydroponic CE technologies to improve production and quality. Therefore, we surveyed U.S. hydroponic food crop producers to identify current hydroponic production technology adoption and potential areas for research needs. Producers cited a wide range of technology utilization; more than half employed solely hydroponic production techniques, 56% monitored light intensity, and more than 80% monitored air temperature and nutrient solution pH and electrical conductivity. Additionally, the growing environments varied from greenhouses (64%), indoors in multilayer (31%) or single-layer (7%) facilities, to hoop houses or high tunnels (29%). Overall, producers reported managing the growing environment to improve crop flavor and the development of production strategies as the most beneficial research areas, with 90% stating their customers would pay more for crops with increased flavor. Lastly, taking historical data and current practices into account, perspectives on future hydroponic CE production are discussed. These include the importance of research on multiple environmental parameters instead of single parameters in isolation and the emphasis on not only increasing productivity but improving crop quality including flavor, sensory attributes, and postharvest longevity. [ABSTRACT FROM AUTHOR]

Red plus blue light-emitting diodes (LEDs) are commonly applied in plant factories with artificial lighting due to photosynthetic pigments, which absorb strongly in red and blue light regions of the spectrum. However, plants grown under natural environment are used to utilizing broad-wide spectrum by long-term evolution. In order to examine the effects of addition light added in red plus blue LEDs or white LEDs, green and purple leaf lettuces (Lactuca sativa L. cv. Lvdie and Ziya) were hydroponically cultivated for 20 days under white LEDs, white plus red LEDs, red plus blue LEDs, and red plus blue LEDs supplemented with ultraviolet, green or far-red light, respectively. The results indicated that the addition of far-red light in red plus blue LEDs increased leaf fresh and dry weights of green leaf lettuce by 28% and 34%, respectively. Addition of ultraviolet light did not induce any differences in growth and energy use efficiency in both lettuce cultivars, while supplementing green light with red plus blue LEDs reduced the vitamin C content of green leaf lettuce by 44% and anthocyanin content of purple leaf lettuce by 30% compared with red plus blue LEDs, respectively. Spectral absorbencies of purple leaf lettuce grown under red plus blue LEDs supplemented with green light were lower in green light region compared with those grown under red plus blue LEDs, which was associated with anthocyanin contents. White plus red LEDs significantly increased leaf fresh and dry weights of purple leaf lettuce by 25%, and no significant differences were observed in vitamin C and nitrate contents compared with white LEDs. Fresh weight, light and electrical energy use efficiencies of hydroponic green and purple leaf lettuces grown under white plus red LEDs were higher or no significant differences compared with those grown under red plus blue LEDs. In conclusion, white plus red LEDs were suggested to substitute for red plus blue LEDs in hydroponic lettuce (cv. Lvdie and Ziya) production in plant factories with artificial lighting. [ABSTRACT FROM AUTHOR]

Groundwater source heat pumps have high efficiency and environmental protection in greenhouse temperature control. Most importantly, the operating energy consumption can be further reduced if the water storage technology were combined. Although the energy storage type ground source heat pump plant factory energy supply system avoids the problems of low primary energy utilization and serious pollution in traditional fossil energy supply, it currently lacks long-term operating experience. This study takes Shanghai Chongming Natural Light Plant Factory as an example to optimize the energy-saving operation of the energy storage groundwater source heat pump energy supply system. The total area of the plant factory is 21 000 square meters, which is divided into three areas A, B and C. The 7 greenhouses in area A use an energy storage groundwater source heat pump air-conditioning system with an area of 5 880 square meters. The greenhouse uses two cylindrical concrete storage tanks, of which the volume of the thermal storage tank is 400 cubic meters and the diameter is 7.65 meters; the volume of the cold storage tank is 600 cubic meters and the diameter is 9.29 meters. The plant factory has 2 hot water wells and 2 cold water wells. In winter, water was drawn from the 2 hot water wells and passed through a convection plate heat exchanger to exchange heat with the cold water flowing from the cold water tank. The low-temperature water after the heat exchange was pumped back by pressure fill 2 cold water wells. Under typical operating conditions in winter, the output temperature of hot water wells was basically maintained at 16-20℃.The inlet water temperature of cold water wells remained stable at about 7℃, and the pumping flow of hot water wells was maintained at about 40 m³/h. According to the statistics of the operating parameters of the heat pump in the first quarter, it could be concluded that the four output water temperatures and input water temperatures of the heat pump remain stable, and the heat pump operated normally during the heating season. The power consumption of the heat pump in the first quarter was 208 559.5 kWh. Among them, the power consumption in January was 83 525.9 kWh, February was 76 673.3 kWh, and March was 48 360.3 kWh; the total heat output to the greenhouse and hot water tank was 3 542.7 GJ, of which 1 445.9 GJ was output in January and 1 258.6 GJ was output in February. In March, the heat output was 838.2 GJ; in the first quarter, the total heat pump operation was 1 322.8 h, including 557.7 h in January, 454.4 h in February, and 310.7 h in March. After research, there are three unreasonable operating conditions of the system: A. The heat pump continued to supply heat when the plant factory heat load s negative; B. The heat pump output excessive heat to the hot water storage tank; C. The heat pump was still running during peak hours. After optimization and control, to avoid the A operation, the heat pump could finally reduce the output energy by 21.55 GJ in the first quarter, which could reduce the power consumption by 1 012.50 kWh, which could save 747 yuan when converted to electricity price; to avoid the B operation, set the upper limit of hot water charge rate at 85% in the first quarter, which can reduce the output of 97.2 GJ energy under the premise of ensuring that the heat pump is fully powered by the plant factory; to avoid the C operation, to avoid the C operation, assuming that the heat pump was used during the price trough, the total output energy of the heat pump was unchanged. Transferring the heat of the heat pump 140.25 GJ in the first quarter to the parity stage output could save 5 530 yuan, and the total power at this time was 8 654.07 kWh, at this time, the total amount of electricity was 8 654.07 kWh. By optimizing the operation process of the natural light plant factory's energy supply system, energy saving and consumption reduction can be achieved, and economic operation can be achieved. [ABSTRACT FROM AUTHOR]

The advancement of controlled-environment agriculture, particularly in plant factories, offers an innovative solution to address the rising demand for food due to global population growth and urbanization. These controlled environments provide consistent and predictable crop yields, irrespective of external weather conditions, and can be tailored to achieve optimal plant growth. However, the intensive energy requirements of these systems have raised sustainability concerns. In plant factories, which provide regulated environments for sustainable food production, it remains essential to minimize energy consumption while maintaining operational efficiency. This study introduces a novel cyber-physical-biological system (CPBS) for managing energy and crop production in plant factories. The CPBS accurately captures plant biological dynamics, such as temperature, humidity, lighting, and CO2 levels, optimizes control variables, and predicts crop growth within these controlled environments. To achieve these outcomes, we leverage physics-informed deep learning (PIDL) techniques to develop high-fidelity and computationally efficient digital twins for the plant factory's internal microclimate and crop states. PIDL enables us to capture complex relationships between environmental factors and crop growth, thereby improving accuracy and decision-making in control. Using the CPBS, we optimize energy usage and resource expenses to ensure sustainable crop production rates under different daylight scenarios in the plant factory. Simulation results from a full growth cycle demonstrate that our proposed CPBS, compared to a certainty equivalent model predictive control (MPC), reduces violation cases by 84.53%. Additionally, it achieves a reduction of 13.41% and 13.04% in energy and resource usage, respectively, compared to a traditional robust MPC that considers a box-shaped uncertainty set. • A CPBS for plant factory energy management and resource allocation. • An accurate PIDL for plant factory to predict the internal climate and crop states. • Optimal control to year-around production in plant factory. [ABSTRACT FROM AUTHOR]

• A new strategy of environment control is proposed based on Bouguer's law. • Energy loss is significantly reduced in the high-reflection environment. • Weight growth of lettuces increases 4.12 times in the high-reflection environment. Energy utilization for plant lighting is one of the primary constraints of the development of plant factories. Most researchers overlook the impact of energy attenuation during the propagation process on energy efficiency utilization, and the redistribution process of energy lacks corresponding theoretical guidance. Based on the expansion of Bouguer's law, a new strategy of environmental control is proposed to solve this problem by interfering the form of energy propagation and redistributing the energy. Through the method of environment control, we establish two different environments (by changing surface reflectance): high-reflection environment and high-absorption environment (resembling an unbounded space). Near the leaf canopy in the high-reflection environment, the photosynthetic photon flux density (PPFD) and illumination intensity are 116.15 μmol∙m−2∙s−1 and 7069 lx, respectively. In contrast, in the high-absorption environment, the values are significantly lower: 30.59 μmol∙m−2∙s−1 for the PPFD and 1815 lx for the illumination intensity. The results of further plant growth experiments show that the average weight and leaf number growth of lettuces increased by 4.12 and 3.22 times, respectively, in high-reflection environment. The growing status of plants is also better in the high-reflection environment compared with the high-absorption environment. The strategy of environmental control provides a new direction to reduce energy loss and increase crop yield in plant factories. [ABSTRACT FROM AUTHOR]

Three different LED spectra (W: White light; WFR: W + far-red light; WB: W + blue light) with similar photosynthetic photon flux density (PPFD) were designed to explore the effects of supplementary far-red and blue lights on leaf color, biomass and phytochemicals of two cultivars of red-leaf lettuce (“Yanzhi” and “Red Butter”) in an artificial lighting plant factory. Lettuce plants under WB had redder leaf color and significantly higher contents of pigments, such as chlorophyll a, chlorophyll b, chlorophyll (a + b) and anthocyanins. The accumulation of health-promoting compounds, such as vitamin C, vitamin A, total phenolic compounds, total flavonoids and anthocyanins in the two lettuce cultivars were obviously enhanced by WB. Lettuce under WFR showed remarkable increase in fresh weight and dry weight; meanwhile, significant decreases of pigments, total phenolic compounds, total flavonoids and vitamin C were found. Thus, in the plant factory system, the application of WB can improve the coloration and quality of red leaf lettuce while WFR was encouraged for the purpose of elevating the yield of lettuce.

Vertical farming is on its way to becoming an addition to conventional agricultural practices, improving sustainable food production for the growing world population under increasing climate stress. While the early development of vertical farming systems mainly focused on technological advancement through design innovation, the automation of hydroponic cultivation, and advanced LED lighting systems, more recent studies focus on the resilience and circularity of vertical farming. These sustainability objectives are addressed by investigating water quality and microbial life in a hydroponic cultivation context. Plant growth-promoting rhizobacteria (PGPR) have been shown to improve plant performance and resilience to biotic and abiotic stresses. The application of PGPRs to plant-growing media increases microbial functional diversity, creating opportunities to improve the circularity and resilience of vertical farming systems by reducing our dependency on chemical fertilizers and crop protection products. Here, we give a brief historical overview of vertical farming, review its opportunities and challenges in an economic, environmental, social, and political context, and discuss advances in exploiting the rhizosphere microbiome in hydroponic cultivation systems.

Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, today’s plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.

Automatic transport can improve the operational efficiency in plant factory production and reduce the use of labor. However, a determination of a plant factory automation operation mode should comprehensively consider the economic strength of the enterprise, operation objects and operation mode, production scale, technical strength, labor costs, and other factors. In this study, a logistics transport system comprising a set of cultivation units was developed for plant factories, using a mode based on shelf-end delivery without power inside the shelf. Moreover, an analysis was conducted on four modes of common transportation methods for the cultivation units for vertical cultivation in plant factories. The results showed that, when comparing the progressive transport type and warehousing/reciprocating transport type for cultivation units, the transport productivity of the former is higher than that of the latter, and the difference in the two transport productivities is proportional to the capacity for cultivation units in each layer. When the capacities for cultivation units in each layer are 20 and 40, the transport productivity of the former is 115–200% and 130–250% higher than that of the latter, respectively. Moreover, the logistics transport system developed herein reaches an input (output) transport productivity of 330 (270) cultivation units h−1.

A "Plant factory" is one of the advanced facilities for vegetable cultivation in an artificially controlled environment, i.e., temperature, humidity, and CO2 concentration are controlled. Recently, it has become popular in Japan, USA, China and others. However, there are some problems to overcome before they become widespread. A project to develop a specific plant factory called the "Okinawa-type plant factory" has been funded by the Okinawa Prefecture. It addresses the severe environmental and social conditions of Okinawa. The main goal of the project was to reduce energy consumption by 30%. To achieve this, three methods were investigated using solar energy and LED lamps, since this plant factory used artificial illumination. Forty foot reefer containers were employed for the cultivation room, and insulation panels were partially used. Solar energy was used for lighting and air-conditioning. Solar energy was converted to thermal energy for air-conditioning using heat collecting panels. Hot water of 75-85 oC obtained by the collector was used for adsorption refrigeration. Sunlight was introduced in the cultivation room from the skylight windows. DC to DC system was also employed for photovoltaic utilization. The use of solar energy and LED lamps are effective to reduce energy consumption. A 30% reduction in energy use was achieved.

Productivity stabilization is a critical issue facing plant factories. As such, researchers have been investigating growth prediction with the overall goal of improving productivity. The projected area of a plant (PA) is usually used for growth prediction, by which the growth of a plant is estimated by observing the overall approximate movement of the plant. To overcome this problem, this study focused on the time-series movement of plant leaves, using optical flow (OF) analysis to acquire this information for a lettuce. OF analysis is an image processing method that extracts the difference between two consecutive frames caused by the movement of the subject. Experiments were carried out at a commercial large-scale plant factory. By using a microcomputer with a camera module placed above the lettuce seedlings, images of 338 seedlings were taken every 20 min over 9 days (from the 6th to the 15th day after sowing). Then, the features of the leaf movement were extracted from the image by calculating the normal-vector in the OF analysis, and these features were applied to machine learning to predict the fresh weight of the lettuce at harvest time (38 days after sowing). The growth prediction model using the features extracted from the OF analysis was found to perform well with a correlation ratio of 0.743. Furthermore, this study also considered a phenotyping system that was capable of automatically analyzing a plant image, which would allow this growth prediction model to be widely used in commercial plant factories.

Plant factories with artificial light are less affected than open-air areas to environmental factors in crop cultivation and are attracting attention as one of the solutions to the world's food problems. However, the cost of cultivation in plant factories is higher than open-air cultivation, and currently, profitable factory-grown crop varieties are limited to those that are small or have a short growing period. Tomatoes are one of the main crops consumed around the world, but due to their large plant height and width, they are not yet suitable for mass production in plant factories. In this study, the DWARF ( D ) and SELF-PRUNING ( SP ) genes of the GABA hyperaccumulating tomato variety #87-17 were genome-edited by the CRISPR-Cas9 method to produce dwarf tomato plants. The desired traits were obtained in the T 1 genome-edited generation, and the fruit traits were almost the same as those of the original variety. On the other hand, the F 2 cross between #87-17 and Micro-Tom containing the d and sp mutations was dwarfed, but the fruit phenotype was a mixture of the traits of the two varieties. This indicates that genome editing of these two genes using CRISPR-Cas9 can efficiently impart traits suitable for plant factory cultivation while retaining the useful traits of the original cultivar., (Copyright © 2024 by JAPANESE SOCIETY OF BREEDING.)

Recently, the interest in the plant factory-based crop production technologies is rising following the application of the smart farm technology to the agricultural arena. A lettuce production system platform is proposed in this study considering the effects of indoor environmental conditions and artificial light sources. The spectral characteristics of a visible ray according to growth performances were analyzed first to develop a control algorithm that can stimulate the plant’s growth for the proposal. Secondly, an imaging system was designed to analyze the plant’s growth characteristics based on the images and set up the system configuration. Lastly, a crop production system was proposed by using an experimental crop production group for environmental control and monitoring.

The recent increased market demand for locally grown produce is generating interest in the application of techniques developed for controlled environment agriculture (CEA) to urban agriculture (UA). Controlled environments have great potential to revolutionize urban food systems, as they offer unique opportunities for year-round production, optimizing resource-use efficiency, and for helping to overcome significant challenges associated with the high costs of production in urban settings. For urban growers to benefit from CEA, results from studies evaluating the application of controlled environments for commercial food production should be considered. This review includes a discussion of current and potential applications of CEA for UA, references discussing appropriate methods for selecting and controlling the physical plant production environment, resource management strategies, considerations to improve economic viability, opportunities to address food safety concerns, and the potential social benefits from applying CEA techniques to UA. Author's viewpoints about the future of CEA for urban food production are presented at the end of this review. [ABSTRACT FROM AUTHOR]

• This is the first study focused on the dynamic responses of ascorbate metabolism to long-term continuous light. • The increase of lettuce shoot biomass under continuous light dependent on specific leaf weight rather than leaf area. • Increased AsA and DHA level under continuous light was mainly attributed to greater GalLDH and APX activity respectively. • Ascorbate-glutathione cycle pays little contribution to ascorbate accumulation under continuous light. To understand the dynamic changes of lettuce growth, ascorbate pool and metabolism under long-term red and blue continuous light (CL, 24/0 h, 200 μmol·m−2·s−1), growth parameters, ascorbate pool size, as well as activities and gene expression levels of key enzymes involved in the ascorbate metabolism in lettuce leaves were investigated every 3 days during 15 days. In comparison with normal photoperiod (Control, 16/8 h, 200 μmol·m−2·s−1), lettuce plants gained greater shoot fresh weight and dry matter under CL, which depended more on specific leaf weight than leaf area. Both reduced ascorbate (AsA) and dehydroascorbate (DHA) contents were remarkably enhanced by CL and keep a relatively stable level during the experiment. The consistent greater contents of AsA and DHA were respectively attributed to the up-regulation of L-galactono-1,4-lactone dehydrogenase and ascorbate peroxidase activity rather than their gene expression. Although glutathione contents and glutathione reductase activities were elevated by CL, their contribution to AsA regeneration was limited on account of similar activity and expression level of dehydroascorbate reductase with control. In addition, H 2 O 2 content was also raised obviously under CL compared with control, but it was maintained at a relative safety and stable level from day 6. Fluorescence imaging results also showed that CL did not induce oxidative damage on lettuce leaves compared with control. It is concluded that lettuce plants grown under red and blue continuous light for 15 days obtained greater shoot biomass and ascorbate pool size without leaf injury, and 9 days was the most cost-effective duration for yield improvement from an energy standpoint. Ascorbate accumulation under continuous light was primarily and rapidly regulated by the enzymes involved in AsA biosynthesis and oxidation at enzymatic activity level rather than gene expression level. [ABSTRACT FROM AUTHOR]

Highlights • Lettuce cultivation in closed hydroponics experiences autotoxicity. • Due to autotoxicity yield and quality decrease in non-renewed nutrient solution. • Yield gradually decrease in accordance to increase culture solution reuse times. • Electro-degradation of culture solution recovers lettuce yield and quality. Abstract In this study we investigated autotoxicity in lettuce under successive cultivation and applied alternating current electro-degradation (ED) to non-renewed nutrient solution to degrade the accumulated allelochemicals and consequently to improve the retarded yield and quality of lettuce. In our first experiment, lettuce was grown in renewed, non-renewed and non-renewed + ED solution. Every two weeks interval nutrient solution was changed in the renewed treatment while non-renewed solution was unchanged throughout the growing period but major minerals were adjusted bi-weekly. ED was also applied bi-weekly for 24 h. Compared to renewed solution, shoot fresh weight was decreased to 24% (301.8 g plant−1) in non-renewed solution. But when ED was applied, non-renewed + ED solution produced shoot fresh weight statistically similar to renewed solution plants. In the second experiment, lettuce was grown in renewed nutrient solution, one culture non-renewed (non-renewed 1C), two culture non-renewed (non-renewed 2C) and non-renewed 2C + ED solutions. In non-renewed 1C, the starting solution was fresh nutrient solution while in non-renewed 2C it was once used. Lettuce grown in non-renewed 2C solution produced shoot fresh yield (258.8 g plant−1), about 35% lower compared to renewed solution. When ED was applied to non-renewed 2C solution produced shoot fresh weight 383.3 g plant-1 which was statistically similar to renewed solution. Calcium and iron concentration in lettuce followed the similar trend. Therefore, it was evident that yield and quality of lettuce could be improved through ED in non-renewed solution in two successive cultivations using same nutrient solution. In the following study, we tried to determine the proper ED interval in the third experiment. Results showed that ED to non-renewed solution both weekly and bi-weekly equally improved growth, yield and mineral concentration in lettuce. Hence, ED at two weeks interval was sufficient. [ABSTRACT FROM AUTHOR]

Highlights • Prospective leaf morphology of lettuce can be predicted based on chloroplast position. • Leaf area increased under weak light inducing chloroplast accumulation response. • Leaf thickness increased under strong light inducing chloroplast avoidance response. • Biomass production under weak light was comparable to that under strong light. • Compensatory growth occurred in lettuce under weak and strong light conditions. Abstract In the accumulation response, chloroplasts move toward weak blue light, staying at positions along the periclinal cell wall. By contrast, in the avoidance response, chloroplasts move away from strong blue light, escaping to positions along the anticlinal cell wall. The accumulation response maximizes light capture and the avoidance response reduces photodamage. The intracellular positioning of chloroplasts is important for optimizing photosynthesis and may have common signals with the regulators that determine leaf morphology, another factor that affects photosynthesis. Here, we propose that intracellular chloroplast position can be used to predict prospective leaf morphology in lettuce (Lactuca sativa). To test this, we induced the accumulation or avoidance response in lettuce cells through exposure to the appropriate strength of blue light and observed the growth of the plants. Our results indicated that leaf area increased in response to weak blue light inducing the accumulation response, and leaf thickness increased in response to strong blue light inducing the avoidance response. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effect of the red (R)-to-blue (B) ratio of light on the growth and phenolic compounds of Crepidiastrum denticulatum under a phytochrome photostationary state (PSS) for growth in a plant factory with artificial light (PFAL) using light-emitting diodes (LEDs). Three-week-old C. denticulatum seedlings were transplanted into a PFAL where the air temperature, relative humidity, CO2 concentration, and light period were set at 20 °C, 60%, 1000 μmol·mol−1, and 16 h, respectively. Three controls were used with different ratios of R to B light without supplemental FR light: 8:2, 7:3, and 6:4 (based on chip number; 130 µmol·m−2·s−1 photosynthetic photon flux density). For the treatments, the same R to B light ratios as in the controls were used but supplemented with FR light, plus a treatment with only R light supplemented with FR, set to a PSS of 0.71. Growth characteristics and total phenolic and individual phenolic contents were measured after a 6-week treatment. When the R light ratio increased, shoot dry weight, leaf length, leaf width, and leaf area increased regardless of supplemental FR light, and the R8B2 with FR light treatment was the most effective, with significantly higher values (1.6–2 times) than the control. FR irradiation did not have any negative effect on total phenolic content, chlorogenic acid, caffeic acid, and chicoric acid per unit dry weight (g); thus, the R8B2 with FR treatment had significantly higher total phenolic and individual phenolic contents per shoot (43% and 52–62%, respectively). Thus, supplemental lighting with FR LEDs was found to be effective to enhance the growth and bioactive compounds of C. denticulatum in a PFAL installed with a R and B lighting system, and the effectiveness could be changed by the RB ratio, with 8:2 considered the proper ratio. [ABSTRACT FROM AUTHOR]

Productivity stabilization is a critical issue facing plant factories. As such, researchers have been investigating growth prediction with the overall goal of improving productivity. The projected area of a plant (PA) is usually used for growth prediction, by which the growth of a plant is estimated by observing the overall approximate movement of the plant. To overcome this problem, this study focused on the time-series movement of plant leaves, using optical flow (OF) analysis to acquire this information for a lettuce. OF analysis is an image processing method that extracts the difference between two consecutive frames caused by the movement of the subject. Experiments were carried out at a commercial large-scale plant factory. By using a microcomputer with a camera module placed above the lettuce seedlings, images of 338 seedlings were taken every 20 min over 9 days (from the 6th to the 15th day after sowing). Then, the features of the leaf movement were extracted from the image by calculating the normal-vector in the OF analysis, and these features were applied to machine learning to predict the fresh weight of the lettuce at harvest time (38 days after sowing). The growth prediction model using the features extracted from the OF analysis was found to perform well with a correlation ratio of 0.743. Furthermore, this study also considered a phenotyping system that was capable of automatically analyzing a plant image, which would allow this growth prediction model to be widely used in commercial plant factories. [ABSTRACT FROM AUTHOR]

Highlight • Exposure to 28-kHz underwater ultrasound works as a growth inhibitor of plants. • Oxygen supersaturation in hydroponic culture works as a growth promoter of plants. • Underwater ultrasound and oxygen supersaturation do not alter photosynthesis activity. Abstract The growth rate of vegetables in plant factories can be regulated by environmental factors including light, temperature, and chemicals, which might give rise to mutation in leaf health. Here, we aim to devise a new way that allows for controlling the growth rate of plants in hydroponics as well as maintaining the product quality; we apply underwater ultrasound and dissolved oxygen supersaturation as external stimuli to plants. As an example, we examine the growth of leaf lettuce in hydroponics with exposure to 28-kHz ultrasound and dissolved oxygen supersaturation up to 36 mg/L at 20 °C. Our results show that exposure to the ultrasound of peak-to-peak pressure at 20 kPa or larger works as the growth inhibitor of the leaves and the roots, while the oxygen supersaturation as the growth promoter, without any degradation of chlorophyll in the leaves. This suggests that these external stimuli can be used in the growth control system of plant factories. [ABSTRACT FROM AUTHOR]

The measurement of plant growth's light environment is the basis of urban agriculture, such as lightemitting diode plant factories. The photosynthetic photon flux density (PPFD) sensors, which measure the photon flux density of radiation in the spectral interval from 400 to 700 nm, cannot measure the spectral components, including the photon flux density of red light band and the photon flux density of blue light band, the light in these two bands are widely used in plant lighting. Facility agriculture, especially plant factories with artificial lighting, needs these data and their ratios by far, so a type of multichannel PPFD sensor is designed to solve these problems. First, we expound the design principle, circuit, and structure of the sensor, and calibrate the unregulated sensors by a standard PPFD sensor (PQS-1, Holland) under the calibration device constructed by controller based on DMX512 protocol. The test results show that the sensor's average variance is 0.9956, which approximates the ideal linear response value 1. Meanwhile, we make a black opaque soft plastic anticrosslight sleeve using three-dimensional printing to solve the problem of crosslight on the sidewall of the filter, which let the crosslight error coefficient of the red and blue channels reduced by an order of magnitude and approached 0. Finally, we designed a set of light environment control systems, which can autocontrol the PPFD and light quality ratios, and a set of supplemental lighting systems, which can control the daily light integral, based on the sensors. [ABSTRACT FROM AUTHOR]

BACKGROUND: In recent years, protected crop production using plant factories to produce high‐value crops with greater functional components has become more popular in many countries. The quantification of the components, however, is mainly conducted by laboratory analyses, which are both time‐ and labor‐consuming. The present study aimed to investigate the potential of a non‐destructive diffuse reflectance spectroscopy technique for estimating functional components (i.e. glucosinolates, amino acids, sugars and carotenoids) in the leaves of Chinese cabbage grown in a plant factory. RESULTS: From the overall analysis, better estimations were obtained using the partial least square regression procedure. The important wavelengths for each functional component were identified mainly in the ultraviolet‐visible regions. Identified wavelengths were 317, 390, 888 and 940 nm for sugars; 520 and 960 nm for amino acids; 385, 860 and 945 nm for glucosinolates; and 454, 472 and 530 nm for carotenoids. CONCLUSION: Optical reflectance spectroscopy shows potential as a tool for the estimation of functional components in the leaves of Chinese cabbage. The results of the present study provide useful information for the design and application of sensors with respect to on‐site quantification of the functional components. © 2018 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

It is important for crop growth to maintain suitable temperature in plant factory, however large heating energy consumption has been proved to be an obstacle that restricts its development. In Europe, the cost of heating accounts for about 30% of the total operation cost during the winter, but in the north of latitude 43° of China, the proportion reaches 60% to 70%. The traditional heating equipment such as coal-fired boilers has an energy utilization rate of only 40% to 50%. So it is very necessary to apply renewable energy to plant factory. Regulating heating modes by tracking and predicting the heating load changes in plant factory is the key to achieve energy saving. Because of the high energy consumption in winter, accurate heating load prediction can improve the energy saving effect of groundwater source heat pump with water energy storage. Changes of heating load in natural light plant factory are dynamic, time-varying, highly turbulent and uncertain. Artificial neural networks is ideal for predicting load changes, especially BP (back propagation) neural network has strong nonlinear mapping ability, which is generally used by many scholars for building heating load prediction, but rarely in plant factory. Given that heating load of both plant factory and building have nonlinear characteristics, we used BP neural network to predict the next day's heating load of plant factory to promote energy-saving control optimization. The BP neural network model has three levels: input layer, hidden layer and output layer. Input parameters include indoor and outdoor air temperature, solar radiation intensity, indoor relative humidity, indoor absolute humidity, indoor wind speed, etc. For plant factory, the next day's weather condition has a significant impact on the heating load. The output variable is determined as the next day's hourly glass greenhouse load value. The number of neurons in the input layer was 9, the number of neurons in the hidden layer was 13, the selected layer number of hidden layers was 1, the learning rate was 0.25 to 0.30, and the initial momentum factor was 0.9. Common evaluation indicators used to determine whether the neural network converges, included standard deviation, coefficient of variation, and expected error percentage. After algorithm steps being determined, the next day's heating load was predicted based on reasonable algorithmic procedures and steps. Experimental data in the paper was obtained from a natural light plant factory powered by groundwater source heat pump with water energy storage system in Chongming National Facility Agricultural Engineering Technology Research Center. Using the neural network toolbox of Matlab to train and simulate the model to process the experimental data from January 19th to 28th, the value of the error function was 0.002 999 94 which was less than the set value of 0.003, so the neural network was convergent. Prediction effect can be drawn by comparison between the actual surveyed value and the predicted value of the heating load. The main heating load was concentrated on 0:00-6:00 and 17:00-24:00 o’clock in the plant factory, and most of these periods were in the cheap electricity price period of Shanghai. Adjusting the operating strategy and operating mode of the energy supply system were based on the predicted heating load，the heat pump operated at full load or high load during the period of cheap electricity prices, and excess heat was stored in the hot storage tank. The hot storage tank provided heat to plant factory during the period of moderate and expensive electricity price. In this case, the energy cost would be reduced. Therefore, it was significantly economical to control start-stop time of the groundwater source heat pump with water energy storage for plant factory heating project. The error was controlled within ±6% basically between the actual value and the predicted value of the heating load, and the standard deviation was 27. 54, deviation factor was 9.4%, expected deviation percentage was 4.35%. Therefore, the results showed that the BP neural network was suitable for the next day's heating load prediction of plant factory. [ABSTRACT FROM AUTHOR]

Highlights • Microalgal cultivation was incorporated into plant factory. • We isolated novel microalgal species suitable for growth in waste nutrients from a plant factory. • LED photobioreactor was constructed and operated to treat waste nutrient. • Treated waste nutrient solution was recycled back into the plant factory. Abstract Plant factories have been developed to replace traditional agriculture, aiming to solve future problems of food availability. However, the nutrient solution in a plant factory is discharged after a single batch of plant cultivation, giving rise to large amounts of waste nutrient solution. Microalgae can be used to treat a wide variety of wastewater and effectively remove excessive nutrients from wastewater. Therefore, the incorporation of microalgal cultivation into a plant factory to treat waste nutrients would be a reasonable approach facilitating removal of waste nutrients with concomitant production of algal biomass. In this study, we isolated novel microalgal species suitable for the growth in waste nutrients from a plant factory and subsequently an underwater LED photobioreactor was constructed being incorporated into the plant factory system. Finally, treated waste nutrient solution was recycled back into the plant factory and successfully used for the cultivation of plant of butterhead lettuce (Lactuca sativa L.). [ABSTRACT FROM AUTHOR]

under a deep-flow hydroponic culture system and irradiated with red or blue light alone or in combination (in the ratio 1:3 or 3:1) in an enclosed-type plant factory. Daughter cladodes developed from mother cladodes in all treatments. The rate of elongation of first cladodes was lower under blue light and the combination of red and blue light (in the ratio 1:3) compared with other treatments. The number of daughter cladodes was also low under blue light. Thus, compared with red light, blue light appears to suppress daughter cladode development. However, the width of daughter cladodes was higher under blue light and the combination of red and blue light (in the ratio 1:3) compared with other treatments. Total fresh weight (FW) of daughter cladodes emerging from one mother cladode was lowest under blue light and high under combined red and blue light (1:3 and 3:1). The number of spines, an undesirable characteristic of edible cacti, was significantly higher under both combinations of red and blue light (1:3 and 3:1) compared to other treatments. On the other hand, the 2,2-diphenyl-1 -picrylhydrazyl (DPPH) radical scavenging activity of extracts of the daughter cladodes was highest under blue light or under combined red and blue light (1:3). Our results show that light wavelength strongly affects daughter cladode growth and development. Thus, controlling the lighting environment is effective for improving growth and quality in edible cacti. [ABSTRACT FROM AUTHOR]

• A system was developed to monitor multi-node environments in a plant factory. • Applied monitoring system, collected data at 13 nodes in a plant factory. • Proved non-uniform indoor environments in the growing space and analyzed causes. • Correlations were found among indoor environmental factors. • Consider interplay between plant growth and indoor factors for environment setup. In plant factories, multi-layered shelves are used to maximize production per unit area by densely growing plants. The large number of plants placed in a spacious area leads to complex interactions between the plants and the growing environment, resulting in a potentially non-uniform growing environment. When the environment is non-uniform, achieving consistent production based on location becomes challenging. This study aims to analyze these interactions through multi-node, multi-factor monitoring in an actual plant factory that engages in hydroponics. To achieve this, we developed a monitoring system tailored for measuring the growth environment in plant factories. Specifically, we created a monitoring device capable of real-time measurement of six key indoor environmental factors, a network system that facilitates multi-node data collection by utilizing both Zigbee and WiFi, and a dashboard for simplified management. The developed monitoring system was implemented in an 'A' plant factory and collected 44,640 data points over a month. It empirically demonstrated that indoor environmental factors vary by location within the growing space, depending on the surrounding environment and the placement and operation of environmental facilities. The temperature of the nutrient solution showed a statistically strong correlation with other indoor environmental factors. This indicates that the operation of environmental facilities in a plant factory should be comprehensively managed in real-time, with a focus on the relationship of the nutrient solution temperature to other indoor environmental factors. Such management is especially crucial when considering the dynamic interrelationships among nutrient solution temperature, other indoor conditions, and the varying demands imposed by plant growth activity. These results offer valuable guidelines for optimizing the growing environment in plant factories and will serve as an important reference for plant factory operators. [ABSTRACT FROM AUTHOR]

• Realization of parameter acquisition and control of multi-environmental variable in the lower computer system. • Realize multi-environmental data display and remote control of plant factory in upper computer system. • Real-time mapping of multi-environmental variable data, and digital environment roaming from the first perspective. • Digital twin system helps managers to make intelligent decisions and realize remote adjustment. Internet of Things (IoT) technology develops rapidly and is increasingly used in the field of facility agriculture, the emergence of digital twin technology provides a possibility for the intelligent management of facility agriculture. In this study, IoT and digital twin technologies are combined to design a digital twin system for mapping multiple environmental variables in plant factories to realize the intelligent management and help plant factory managers make intelligent decision-making management schemes. The system includes a multi-environmental variable parameter acquisition system and an environment variable control system based on Arduino, a multi-environmental variable data monitoring and remote environment control system based on Android, and a multi-environmental variable mapping digital twin model. IoT and computer development technologies are used to monitor environmental parameters and control the state of various equipment in plant factories and realize the connection between things and networks. Digital twin technology maps the multi-environmental variables of plant factories to digital twin and intuitively feeds back the parameters of the multi-environmental variables to the plant factory managers, completing the connection between people and things. By combining the IoT technology with digital twin technology, a digital twin system based on multi-environmental variable mapping in plant factory is established, so that the parameters of environmental variables such as CO 2 , temperature and humidity in plant factory can be accurately adjusted according to the different needs of different stages of plant growth, and it can help plant factory managers to realize intelligent decision-making. [ABSTRACT FROM AUTHOR]