Plant Factory Research Articles

Acclimation and hardness enhancement through ultraviolet-B irradiation of fruit vegetable seedlings grown in a plant factory with artificial light

Acclimation and hardness enhancement through ultraviolet-B irradiation of fruit vegetable seedlings grown in a plant factory with artificial light

Transcriptome-Based Identification of Candidate Flowering-Associated Genes of Blueberry in a Plant Factory with Artificial Lighting (PFAL) under Short-Day-Length Conditions.

In blueberry (Vaccinium corymbosum L.), a perennial shrub, flower bud initiation is mediated by a short-day (SD) photoperiod and buds bloom once the chilling requirement is satisfied. A plant factory with artificial lighting (PFAL) is a planting system that can provide a stable and highly efficient growing environment for blueberry production. However, the characteristics of bud differentiation of blueberry plants inside PFAL systems are poorly understood. To better understand flower bud initiation and the flowering mechanism of blueberry in PFAL systems, the anatomical structure of apical buds under SD conditions in a PFAL system was observed using the southern highbush cultivar 'Misty' and a transcriptomic analysis was performed to identify the candidate flowering genes. The results indicated that the apical bud of 'Misty' differentiated gradually along with SD time course and swelled obviously when chilling was introduced. A total of 39.28 Gb clean data were generated, and about 20.31-24.11 Mb high-quality clean reads were assembled, yielding a total of 17370 differentially expressed genes (DEGs), of which 9637 were up-regulated and 7733 were down-regulated. Based on the functional annotation, 26 DEGs were identified including 20 flowering-related and 6 low-temperature DEGs, out of which the expressive level of four flowering-related DEGs (VcFT2, VcFPA, VcFMADS1, and VcCOP1) and two low-temperature-induced DEGs (VcTIL-1 and VcLTI 65-like) were confirmed by qRT-PCR with a good consistency with the pattern of transcriptome. Functional analysis indicated that VcFT2 was highly conserved with nuclear and cytoplasmic subcellular localization and was expressed mainly in blueberry leaf tissue. In Arabidopsis, ectopic overexpression of VcFT2 results in an early flowering phenotype, indicating that VcFT2 is a vital regulator of the SD-mediated flowering pathway in blueberry. These results contribute to the investigation of photoperiod-mediated flowering mechanisms of blueberry in PFAL systems.

The roles of light in a plant factory: photosynthesis efficiency and gas exchange parameters of lettuce as a function of light spectra

The roles of light in a plant factory: photosynthesis efficiency and gas exchange parameters of lettuce as a function of light spectra

The Growth and Tuber Yield of Potatoes (Solanum tuberosum L.) under Varying LED Light Spectrums in Controlled Greenhouse Conditions

Plant growing using light-emitting diodes (LEDs) in a controlled environment is a revolutionary and innovative idea, regardless of the external environmental disturbances. Studying the growth and tuber yield of potatoes (Solanum tuberosum L.) in an LED-based plant factory system is a relatively innovative concept. The current study was conducted in a plant factory to evaluate the effects of different LED spectral compositions on potato tuberization. Potato tuberization was analyzed under six different LED light spectral combinations with irradiances of 300 mol m−2 s−1, with natural light considered the control treatment. The findings stated that the L2 treatment (red70 + blue20 + white10) increased the plant height, branch number, and biomass accumulation, while photosynthetic pigments and photosynthetic activity increased significantly in L5 (red60 + blue20 + green10 + white10). Higher gibberellic acid (GA3) content was recorded in L1 (red70 + blue30), whereas the tuber number and tuber fresh weight were recorded in L3 (red70 + blue20 + green10) and L7 (natural light), respectively. On the other hand, a higher number of smaller-sized tubers were observed in L5, while L2 and L4 (red70 + blue20 + far-red10) resulted in a higher number of medium-sized tubers. In conclusion, a high proportion of red and blue light, along with white and far-red light, increased the plant height, branch number, plant biomass, and production of small- and medium-sized tubers. On the other hand, the inclusion of green light with red and blue enhanced the chlorophyll content, photosynthesis, and leaf expansion, and promoted the production of smaller-sized tubers. Finally, with regard to tuberization, the treatment using L4 followed by L2 outperformed the other treatments.

Design, Integration, and Experiment of Transplanting Robot for Early Plug Tray Seedling in a Plant Factory

In the context of plant factories relying on artificial light sources, energy consumption stands out as a significant cost factor. Implementing early seedling removal and replacement operations has the potential to enhance the yield per unit area and the per-energy consumption. Nevertheless, conventional transplanting machines are limited to handling older seedlings with well-established roots. This study addresses these constraints by introducing a transplanting workstation based on the UR5 industrial robot tailored to early plug tray seedlings in plant factories. A diagonal oblique insertion end effector was employed, ensuring stable grasping even in loose substrate conditions. Robotic vision technology was utilized for the recognition of nongerminating holes and inferior seedlings. The integrated robotic system seamlessly managed the entire process of removing and replanting the plug tray seedlings. The experimental findings revealed that the diagonal oblique-insertion end effector achieved a cleaning rate exceeding 65% for substrates with a moisture content exceeding 70%. Moreover, the threshold-segmentation-based method for identifying empty holes and inferior seedlings demonstrated a recognition accuracy surpassing 97.68%. The success rate for removal and replanting in transplanting process reached an impressive 95%. This transplanting robot system serves as a reference for the transplantation of early seedlings with loose substrate in plant factories, holding significant implications for improving yield in plant factory settings.

Effect of Light Quality on Seed Potato (Solanum tuberose L.) Tuberization When Aeroponically Grown in a Controlled Greenhouse.

A plant factory equipped with artificial lights is a comparatively new concept when growing seed potatoes (Solanum tuberosum L.) for minituber production. The shortage of disease-free potato seed tubers is a key challenge to producing quality potatoes. Quality seed tuber production all year round in a controlled environment under an artificial light condition was the main purpose of this study. The present study was conducted in a plant factory to investigate the effects of distinct spectrum compositions of LEDs on potato tuberization when grown in an aeroponic system. The study was equipped with eight LED light combinations: L1 = red: blue: green (70 + 25 + 5), L2 = red: blue: green (70 + 20 + 10), L3 = red: blue: green (70 + 15 + 15), L4 = red: blue: green (70 + 10 + 20), L5 = red: blue: far-red (70 + 25 + 5), L6 = red: blue: far-red (70 + 20 + 10), L7 = red: blue: far-red (70 + 15 + 15), L8 = red: blue: far-red (70 + 10 + 20), and L9 = natural light with 300 µmol m-2 s-1 of irradiance, 16/8 h day/night, 65% relative humidity, while natural light was used as the control treatment. According to the findings, treatment L4 recorded a higher tuber number (31/plant), tuber size (>3 g); (9.26 ± 3.01), and GA3 content, along with better plant growth characteristics. Moreover, treatment L4 recorded a significantly increased trend in the stem diameter (11.08 ± 0.25), leaf number (25.32 ± 1.2), leaf width (19 ± 0.81), root length (49 ± 2.1), and stolon length (49.62 ± 2.05) compared to the control (L9). However, the L9 treatment showed the best performance in plant fresh weight (67.16 ± 4.06 g) and plant dry weight (4.46 ± 0.08 g). In addition, photosynthetic pigments (Chl a) (0.096 ± 0.00 mg g-1, 0.093 ± 0.00 mg g-1) were found to be the highest in the L1 and L2 treatments, respectively. However, Chl b and TCL recorded the best results in treatment L4. Finally, with consideration of the plant growth and tuber yield performance, treatment L4 was found to have the best spectral composition to grow quality seed potato tubers.

Yield and Photosynthesis Related to Growth Forms of Two Strawberry Cultivars in a Plant Factory with Artificial Lighting

Appropriate growth forms for strawberry production in a plant factory with artificial lighting (PFAL), which is a recently developed production system, remain undetermined. Improving strawberry productivity in a PFAL requires insights into the interplay between production characteristics (growth and photosynthesis) and growth forms, such as plant height and leaf area (LA), which are major determinants of crop yield. Growth status, yield, and photosynthetic characteristics of the two cultivars of strawberries (Fragaria ×ananassa Duch. Tochiotome and Koiminori) with different growth forms were examined. ‘Koiminori’ exhibited a 1.9-fold higher yield and a 2.0-fold greater total dry weight of respective organs compared with ‘Tochiotome’. The single-plant photosynthetic rate (AP), serving as an index for both cultivars, was 2.2-times higher for Koiminori than for Tochiotome. The photosynthetic rates of a single leaf (AL) and LA were also analyzed as important factors that influence the AP. The AL for ‘Koiminori’ surpassed that of ‘Tochiotome’ by 1.4 times. This was attributed to the elevated photosynthetic photon flux density received by the upper leaves of Koiminori, which is a consequence of its higher plant height in proximity to the light source. Evaluation of four photosynthetic capacities, maximum rate of carboxylation, maximum rate of electron transport, photosynthetic rate under saturating light, and light utilization efficiency, which are potential factors that affect AL, revealed no differences in these capacities between cultivars. ‘Koiminori’ exhibited a significantly larger LA (2.3- to 3.1-times) than ‘Tochiotome’, indicating that the former’s higher AP resulted mainly from its higher AL and larger LA. Thus, strawberry production in a PFAL can be improved by growing cultivars with growth forms such as higher plant height and larger LA.

Control of a Semi-closed Plant Factory with Artificial Lighting-based on Two Different LED with NB-IoT

Plant factory artificial light (PFAL) is an effective technique for producing large amounts of crops per area and high-quality plant growth. This work aims to construct a semi-closed PFAL growth system based on NB-IoT using two types of LED arrays: phosphor-converted LED (pc-LED) and RB-LED. Next, while examining the features of the artificial light spectrum, compare the Curry leaf kale and Chinese kale in seedlings under various LED light sources. An NB-IoT module with the MAGELLAN platform monitored and controlled the temperature, humidity, and illumination of the semi-closed PFAL growing system. The results indicate that cos lettuce cultivated with PCLEDs is likely more photosynthesis-capable than cos lettuce grown with RBLEDs. Compared to RB-LED, the average fresh weight of the cos lettuce from PC-LED was significantly higher. The data gathered from the cloud system under the MAGELLAN platform during the 7-day trial, the control of lighting and watering in the semi-closed PFAL system, and the measurement results of environmental factors were all accurately completed. Organic veggies could be grown in a home or school using the semi-PFAL growing technique.

GY-SLAM: A Dense Semantic SLAM System for Plant Factory Transport Robots.

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network, GY, based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and the SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While mAP@0.5 increased by 0.514% to 95.364, the model simultaneously reduced the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system localization accuracy and robustness. It shows a remarkable 92.59% improvement in RMSE for Absolute Trajectory Error (ATE), along with a 93.11% improvement in RMSE for the translational drift of Relative Pose Error (RPE) and a 92.89% improvement in RMSE for the rotational drift of RPE. Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.

A Concept of Hydroponic System in Horticultural Crops

In now a day’s soil based cultivation is major difficulties due to different man made reason such as urbanization and industrialization. Hydroponic system such as the deep flow technique, nutrient film technique and aeroponic systems are essential tools in plant factories more over sudden natural disaster, climate change and unlimited use of chemical for agriculture purpose lead to reduction in soil fertility and quality. That’s why scientist have evolved a new alternative approach to the agriculture system is called as hydroponic system. Hydroponic is a technique of growing plants in a water based and nutrient rich solution by hydroponic large number of crops for plants can be grown easily. The quality of yield and nutritive value of end products produced by hydroponically is generally greater than the natural soil based cultivation. This type of cultivation is diseases free, eco-friendly and growing popularity across the whole world including the both developed and developing countries.

Increased Accumulation of Ginsenosides in Panax ginseng Sprouts Cultivated with Kelp Fermentates

Currently, new agri-tech has been developed and adapted for the cultivation of crops using smart farming technologies, e.g., plant factories and hydroponics. Kelp (Laminaria japonica), which has a high industrial value, was considered as an alternative to chemicals for its eco-friendly and sustainably wide use in crop cultivation. In this study, a fermented kelp (FK) was developed for use in hydroponics. The FK contained various free and protein-bound amino acid compositions produced by fermenting the kelp with Saccharomyces cerevisiae. Supplementing FK as an aeroponic medium when cultivating ginseng sprouts (GSs) elevated the total phenolic and flavonoid contents. Additionally, seven ginsenosides (Rg1, Re, Rb1, Rc, Rg2, Rb2, and Rd) in GSs cultivated with FK in a smart-farm system were identified and quantified by a high-performance liquid chromatography-evaporative light scattering detector/mass spectrometry analysis. Administering FK significantly increased the ginsenosides in the GSs compared to the control group, which was cultivated with tap water. These results indicate the FK administration contributed to the increased accumulation of ginsenosides in the GSs. Overall, this study suggests that FK, which contains abundant nutrients for plant growth, can be used as a novel nutrient solution to enhance the ginsenoside content in GSs during hydroponic cultivation.

Flow and heat transfer performance of microchannel heat sinks with circular concave cavities and ribs for water cooling LEDs

ABSTRACT The poor heat dissipation of LED light sources limits their applications in plant factories. This paper combines a microchannel heat sink (MHS) with circular concave cavities and ribs with the water irrigation system of an LED plant factory to develop water-cooled LEDs. By using this approach, four types of MHSs were designed: circular concave cavities (circular), circular concave cavities and single-sided ribs (circular-single), circular concave cavities and odd-symmetric ribs (circular-odd), and circular concave cavities and double symmetric ribs (circular-double). The influence of the arrangement of circular concave cavities and ribs on the flow and heat transfer performance was numerically investigated by ANSYS Fluent 21.0 R1. Corresponding MHSs with circular concave cavities and ribs were manufactured, and an experimental platform was built to experimentally verify the numerical results. The results showed that a circular concave cavity in the microchannel caused the fluid to form a secondary flow, which led to the continuous destruction and reconstruction of the flow and thermal boundary layer in the microchannel. This contributed to heat and mass transfer, while the presence of ribs altered the flow direction of the fluid and enhanced mass and heat transfer within the cavities. The pressure drop at the inlet and outlet of the MHS increased in the case of circular concave cavities and ribs as the inlet flow rate increased. Compared with MHSs with circular concave cavities, the ribs increased the pressure drop at the inlet and outlet. The inlet and outlet pressure drop of MHS with circular concave cavities and double-symmetric ribs was the highest, followed by MHS with circular concave cavities and odd-symmetric ribs, and the smallest was the MHS with circular concave cavities and single-sided ribs. As the inlet flow rate increased from 10 ml/min to 60 ml/min, the pressure drop between the inlet and outlet of the MHS with circular concave cavities increased from 22.54 Pa to 165.98 Pa (an increase of 143.44 Pa); the pressure drop of the MHS with circular concave cavities and single-sided ribs increased from 24.72 Pa to 187.31 Pa (an increase of 162.59 Pa); the pressure drop of the MHS with circular concave cavities and odd-symmetric ribs increased from 27.92 Pa to 212.12 Pa (an increase of 184.20 Pa) and that of the MHS with circular concave cavities and double symmetric ribs increased from 29.32 Pa to 221.21 Pa (an increase of 191.89 Pa). Under the same inlet flow rate and LED chip input power, the cooling water outlet temperature of MHS with circular concave cavities and double symmetric ribs was the highest, followed by MHS with circular concave cavities and odd-symmetric ribs, MHS with circular concave cavities and single-sided ribs, and MHS with circular concave cavities was the lowest. These results indicated that the heat transfer performance of MHS with circular concave cavities and double-symmetric ribs was the best, followed by MHS with circular concave cavities and odd-symmetric ribs, and MHS with circular concave cavities and single-sided ribs. The MHS with circular concave cavities had the worst heat transfer performance. The outlet temperature of the MHS with concave cavities and ribs reaches the highest value at the inlet flow rate of 30 ml/min. At this flow rate, the outlet temperature is 343.89 K for the MHS with circular concave cavities, 344.73 K for the MHS with circular concave cavities and single-sided ribs, 346.53 K for the MHS with circular concave cavities and odd-symmetric ribs; and 347.58 K for the MHS with circular concave cavities and double symmetric ribs.

Evaluating urban mini plant factories: engineering and software cost perspectives for agriculture sustainability

Precision agriculture serves as a crucial solution to address the challenges of food security and agriculture sustainability. It provides significant benefits and enables effective monitoring of agriculture throughout the entire supply chain using a technology-driven approach that prioritizes internet connectivity and leverages big data. A noteworthy application of precision agriculture is the Mini Plant Factory, where plants are cultivated in closed systems with artificial lighting. The development of the Mini Plant Factory requires an economic feasibility analysis as a determinant of technology viability before widespread implementation, aiming to promote agriculture sustainability. The Software Cost Estimation Model (SCEM) assesses software development’s cost and time requirements. Engineering economics evaluates economic feasibility using metrics like NPV, BCR, IRR, PBP, and BEP methods. Function Point Analysis for UMPF software development estimates a cost of Rp 33,052,414, equivalent to 1,311 man-hours. Investment feasibility analysis considers the utilization of UMPF as viable, with an NPV of IDR 46,938,615, BCR of 1.08, IRR of 28%, and projected profitability within four years. Precision agriculture strategically addresses complex agricultural challenges, fostering sustainability with innovations such as the UMPF. The SCEM and engineering economics confirm the feasibility and rationale for implementing UMPF technology, providing essential insights for sustainable agricultural practices.

The Optimum Photoperiod on Floral Differentiation of French Marigold Grown in a Closed-type Plant Factory

The Optimum Photoperiod on Floral Differentiation of French Marigold Grown in a Closed-type Plant Factory

Life Cycle Assessment of Carbon Capture by an Intelligent Vertical Plant Factory within an Industrial Park

Bio-based carbon capture and utilization emerges as a critical pathway to mitigate carbon dioxide (CO2) emissions from industrial activities. Within this context, plant factories become an innovative solution for biological carbon capture within industrial parks, fed with the substantial carbon emissions inherent in industrial exhaust gases to maximize their carbon sequestration capabilities. Among the various plant species suitable for such plant factories, Pennisetum giganteum becomes a candidate with the best potential, characterized by its high photosynthetic efficiency (rapid growth rate), perennial feature, and significant industrial value. This paper studies the feasibility of cultivating Pennisetum giganteum within an intelligent plant factory situated in an industrial park. An automated and intelligent plant factory was designed and established, in which multiple rounds of Pennisetum giganteum cultivations were performed, and life cycle assessment (LCA) was carried out to quantitatively evaluate its carbon capture capacity. The results show that the primary carbon emission in the plant factory arises from the lighting phase, constituting 67% of carbon emissions, followed by other processes (15%) and the infrastructure (10%). The absorption of CO2 during Pennisetum giganteum growth in the plant factory effectively mitigates carbon emissions from industrial exhaust gases. The production of 1 kg of dry Pennisetum giganteum leads to a net reduction in emissions by 0.35 kg CO2 equivalent. A plant factory with dimensions of 3 m × 6 m × 2.8 m can annually reduce carbon emissions by 174 kg, with the annual carbon sequestration per unit area increased by 56% compared to open-field cultivation. Furthermore, large-scale plant factories exhibit the potential to offset the carbon emissions of entire industrial parks. These findings confirm the viability of bio-based carbon capture using intelligent plant factories, highlighting its potential for carbon capture within industrial parks.

The Immune-Stimulating and Anti-Diabetic Effects of Allium hookeri Leaves Grown in a Plant Factory with Artificial Lights in Immunosuppressed Obese C57BL/6 Mice.

We investigated the immune-stimulating and anti-diabetic effects of Allium hookeri leaves grown in a plant factory with artificial lights. The immunomodulatory effects of A. hookeri leaves' ethanol extracts were evaluated with immune-related hematological factors in blood, the proliferation of splenocytes, NK cell activity, IgG and cytokine levels, and their mechanisms in immunosuppressed obese mice. Anti-diabetic effects were determined by the inhibitory activity against α-amylase and α-glucosidase in vitro and fasting blood glucose levels and biochemical factors in the serum of immunosuppressed obese mice. A. hookeri leaf extracts increased WBC and LYM counts, the proliferation of splenocytes, and serum IgG and IL-1β concentrations compared to those of the NC group, which was used as a negative control. A. hookeri leaf extracts also improved serum HDL levels while they decreased the activities of digestive enzymes, fasting blood glucose, and biochemical factors (ALT, AST, T-Chol, TG, LDL, and GLU). The expressions of IL-1β, JNK, c-Jun, p65, and iNOS in the thymus of immunosuppressed mice were activated by the treatment of A. hookeri leaf extracts. The results suggest that A. hookeri leaves grown in a plant factory with artificial lights also have immune-stimulatory and anti-diabetic effects and can be used as novel functional supplements to control related diseases and to improve public health.

A Method for Calculating the Leaf Area of Pak Choi Based on an Improved Mask R-CNN

The leaf area of pak choi is a critical indicator of growth rate, nutrient absorption, and photosynthetic efficiency, and it is required to be precisely measured for an optimal agricultural output. Traditional methods often fail to deliver the necessary accuracy and efficiency. We propose a method for calculating the leaf area of pak choi based on an improved Mask R-CNN. We have enhanced Mask R-CNN by integrating an advanced attention mechanism and a two-layer fully convolutional network (FCN) into its segmentation branch. This integration significantly improves the model’s ability to detect and segment leaf edges with increased precision. By extracting the contours of reference objects, the conversion coefficient between the pixel area and the actual area is calculated. Using the mask segmentation output from the model, the area of each leaf is calculated. Experimental results demonstrate that the improved model achieves mean average precision (mAP) scores of 0.9136 and 0.9132 in detection and segmentation tasks, respectively, representing improvements of 1.01% and 1.02% over the original Mask R-CNN. The model demonstrates excellent recognition and segmentation capabilities for pak choi leaves. The error between the calculation result of the segmented leaf area and the actual measured area is less than 4.47%. These results indicate that the proposed method provides a reliable segmentation and prediction performance. It eliminates the need for detached leaf measurements, making it suitable for real-life leaf area measurement scenarios and providing valuable support for automated production technologies in plant factories.

Modeling and Parameter Optimization of Plant Factory Production System Under Low-Carbon Constraints

Highlights A life cycle approach to modeling the carbon footprint of leafy vegetables. Determine the optimal design parameters through logical and mathematical relationship derivation. The simulation model of leaf vegetable production line was established. The optimal parameter scheme was determined by multifactorial simulation tests. Abstract. In recent years, a plant factory has gradually become a new model of facility agriculture, and the optimization problem of low-carbon design of production system in a plant factory has become more prominent. In the design of the production system, needs of high efficiency, high yield, and low carbon emission must be considered. In this study, the leafy vegetable factory is taken as the research object, and the carbon footprint calculation model of products is established based on the life cycle assessment method. Taking production capacity and carbon footprint as design indicators, the logical correlation and mathematical relationship between them and production line design parameters are analyzed layer by layer to determine the key design parameters. The leafy vegetable production line is modeled by plant simulation software, and multifactor simulation experiments are set up to explore the influence of key design parameters on design indexes to guide the optimal decision of parameter design scheme. The new design scheme increases the productivity of the plant factory by 35.40%, reduces the carbon footprint of leafy vegetables by 15.54%, and solves the problem that leafy vegetables at the bottom of the planting frame in the original plant factory grow poorly because of insufficient light. Keywords: Carbon footprint, Life cycle assessment, Plant factory, Product system, Production line modeling.

Genome editing of DWARF and SELF-PRUNING rapidly confers traits suitable for plant factories while retaining useful traits in tomato.

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 T1 genome-edited generation, and the fruit traits were almost the same as those of the original variety. On the other hand, the F2 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.

Technology of plant factory for vegetable crop speed breeding.

Sustaining crop production and food security are threatened by a burgeoning world population and adverse environmental conditions. Traditional breeding methods for vegetable crops are time-consuming, laborious, and untargeted, often taking several years to develop new and improved varieties. The challenges faced by a long breeding cycle need to be overcome. The speed breeding (SB) approach is broadly employed in crop breeding, which greatly shortens breeding cycles and facilities plant growth to obtain new, better-adapted crop varieties as quickly as possible. Potential opportunities are offered by SB in plant factories, where optimal photoperiod, light quality, light intensity, temperature, CO2 concentration, and nutrients are precisely manipulated to enhance the growth of horticultural vegetable crops, holding promise to surmount the long-standing problem of lengthy crop breeding cycles. Additionally, integrated with other breeding technologies, such as genome editing, genomic selection, and high-throughput genotyping, SB in plant factories has emerged as a smart and promising platform to hasten generation turnover and enhance the efficiency of breeding in vegetable crops. This review considers the pivotal opportunities and challenges of SB in plant factories, aiming to accelerate plant generation turnover and improve vegetable crops with precision and efficiency.