The impetus behind this work lies in the mounting pressures on the global food system, where climate change, unpredictable weather events, and rapid urbanization increasingly diminish arable land and threatening overall agricultural productivity. Vertical farming has emerged as a revolutionary agricultural approach, with its promise of dense crop production in controlled indoor environments. However, the application of vertical farming has been limited largely to leafy greens due to spatial and growth habit constraints inherent in many fruit-bearing crops like tomatoes, which typically exhibit indeterminate growth patterns unsuitable for confined cultivation spaces. Addressing this gap required a fundamental rethinking of tomato plant architecture and physiology.

Jung and Kwon’s team focused their genetic engineering efforts on the SlGA20ox gene family, known regulators of plant height through their role in gibberellin biosynthesis pathways. Through meticulous screening of twelve SlGA20ox homologs, they identified SlGA20ox2 and SlGA20ox4 as prime candidates for manipulation. Employing the revolutionary multiplex CRISPR-Cas9 system, the researchers generated both single and double knockout mutants within a triple-determinate tomato cultivar background, thereby sculpting plant stature without altering flowering time or reproductive development. This targeted gene editing effectively reduced internode length and overall plant height, rendering the tomato plants compact and more compatible with vertical farming setups.

Crucially, the altered tomato genotypes retained photosynthetic efficiency and fruit quality attributes, two parameters often compromised in growth-restricted crops. Metrics such as Fv/Fm ratios—a measure of the maximum quantum efficiency of photosystem II—chlorophyll and carotenoid content, fruit set frequency, yield per plant, fruit size, ripening kinetics, and sugar content remained statistically indistinguishable from wild-type controls. This stability was confirmed across two markedly different growing environments: traditional greenhouses and state-of-the-art vertical farming chambers. The implication is profound: compact architecture was achieved without sacrificing productivity or crop quality, a major hurdle in modern plant breeding.

Beyond the genetic modifications, the study’s innovation extends into deep learning-based phenotyping methodologies. Conventional plant phenotyping methods often lack sensitivity to subtle physiological changes and are time-consuming or destructive. The team developed an advanced 3D convolutional neural network (3D-CNN) trained on time-resolved chlorophyll fluorescence imaging data. This volumetric deep learning approach extracted intricate spatiotemporal features of chlorophyll fluorescence dynamics, capturing minute variations in photosynthetic behavior. Notably, the model excelled in discriminating between wild-type and mutant genotypes, achieving classification accuracy exceeding 84%. The 3D-CNN model outperformed conventional machine learning algorithms such as Support Vector Machines (SVM), Long Short-Term Memory Networks (LSTM), and one-dimensional CNNs, showcasing its superior generalization and feature extraction capacity.

A particularly insightful aspect was the 3D-CNN’s ability to decode genotype-specific fluorescence signatures, especially within the domain of non-photochemical quenching (NPQ). NPQ mechanisms are critical for plants to dissipate excess light energy and protect photosystems under fluctuating environmental conditions. Differences in NPQ dynamics observed through the deep learning phenotyping pipeline suggest distinct physiological adaptations conferred by SlGA20ox knockouts, offering deeper insight into the complex interplay between genetic modification and photosynthetic regulation.

These findings are poised to catalyze a paradigm shift in intelligent crop breeding strategies. By integrating next-generation CRISPR technology with sophisticated, non-invasive AI-based phenotyping, breeders can rapidly identify and select elite plants exhibiting optimal growth form and physiological function. The presented framework circumvents the need for multi-sensor, cost-prohibitive phenotyping setups, instead relying on accessible chlorophyll fluorescence imaging and scalable computational models. This is a critical step toward automating and accelerating genotype prioritization in complex breeding programs.

From an application standpoint, the development of compact, high-performance tomato cultivars with stable yields and preserved fruit quality offers an immediate boon for urban agriculture initiatives. Vertical farms, constrained by limited vertical space, can now feasibly incorporate fruit crop production alongside leafy greens, diversifying crop portfolios and enhancing food security in metropolitan centers. This aligns with a global push towards sustainable, resource-efficient food systems tailored to the realities of diminishing arable land and climate instability.

Moreover, the volumetric deep learning–based phenotyping platform holds broad potential beyond tomatoes. It can be adapted to a range of agronomically important crops, enabling breeders to non-destructively monitor physiological responses to genetic, environmental, or agronomic variables at unprecedented resolution. By capturing complex phenotypic traits underlying stress tolerance, growth habit, or yield components, this tool can drive data-driven decision-making in precision agriculture.

Funded by the National Research Foundation of Korea and supported by affiliated academic programs, this study exemplifies multidisciplinary collaboration across plant genetics, computational modeling, and agricultural engineering. The Kyung Hee University team highlights how integrating gene editing technology with artificial intelligence not only accelerates breeding cycles but also generates fundamental biological insights, expanding the frontier of plant phenomics.

In conclusion, the fusion of CRISPR-mediated genetic modification with volumetric deep learning phenotyping constitutes a pioneering approach to modern plant breeding. The compact SlGA20ox-edited tomato plants developed by Jung and Kwon’s research group represent a vital innovation for making vertical farming of fruit crops feasible on a commercial scale. Simultaneously, the robust AI-driven phenotyping pipeline offers scalable solutions for accurate, high-throughput screening of complex plant traits, heralding a new era of sustainable, smart agriculture poised to meet future global food production challenges.

As the global population continues to urbanize and climate stresses mount, technologies that enable space-efficient crop production without compromising yield or quality will become indispensable. This study not only delivers engineered solutions for the pressing spatial challenges of urban farming but also establishes a flexible analytical framework adaptable to a variety of other crop species. By marrying cutting-edge genetic tools with deep learning phenomics, researchers are charting a promising path toward resilient, efficient, and sustainable food systems worldwide.

Subject of Research: Not applicable

Article Title: Volumetric Deep Learning-Based Precision Phenotyping of Gene-Edited Tomato for Vertical Farming

News Publication Date: 14-Aug-2025

Web References: http://dx.doi.org/10.1016/j.plaphe.2025.100095

References: 10.1016/j.plaphe.2025.100095

Keywords: Plant sciences, Biochemistry, Engineering

Traditional agriculture has long restrained itself within natural and geographic limits. Climatic unpredictability, extreme weather episodes, and growing urban densities challenge the ability of conventional farming models to satisfy ever-escalating nutritional demands. Vertical farming thus offers a compelling alternative—enabling cultivation in stacked layers within controlled environments adjacent to urban centers. Dr. Vanesa Calvo-Baltanás, lead researcher at TUMCREATE, highlights how vertical farming operates independently of climatic constraints, utilizing space vertically to dramatically increase productivity without necessitating vast land usage. The integration of controlled environmental variables—such as light spectrum, temperature, humidity, and nutrient delivery—enables the optimization of plant and protein production with unparalleled precision.

The Proteins4Singapore project forms the foundation of this inquiry, aiming to realize Singapore’s ambitious “30-by-30” vision, where 30% of all nutritional requirements are produced locally by 2030. By examining a 10-layer vertical farming system, the research reveals the extraordinary potential of CEA to escalate protein yields. Comparatively, protein production can increase nearly three hundred times for conventional crops and astonishingly more than six thousand-fold for organisms like mushrooms and insects. This research reinforces vertical farming not only as a technological marvel but as a necessity for dense urban environments where land scarcity is a pressing concern.

Vertical farming’s environmental benefits extend distinctly beyond yield. The technology eliminates the dependency on pesticides and antibiotics prevalent in open-field agriculture. This aspect not only results in cleaner, safer food but also reduces the ecological impact associated with agrochemical runoff—one of the primary contributors to environmental degradation and biodiversity loss. Farmers and researchers alike find value in these systems’ ability to drastically reduce land footprint and water consumption, alongside mitigating pathogen risks through sterile, closed-loop environments.

A particularly innovative dimension of the study explores symbiotic relationships among food groups within vertical farms. Unlike traditional monocultures, vertical farming’s closed-loop approach facilitates resource cycling. Mushrooms and insects prove pivotal as biological converters of agricultural byproducts, digesting crop residue and transforming waste into high-value protein sources. This circular economy model within the farm environment elevates sustainability by minimizing external inputs and maximizing nutrient recycling, thereby creating an efficient, zero-waste food production ecosystem inside the controlled agriculture chambers.

Lighting, a critical factor in vertical farming’s energy equation, is presented with nuanced understanding. Whereas crops and algae depend heavily on continuous artificial lighting—representing a significant operational cost and environmental challenge—mushrooms and insects require minimal to no light. Their cultivation thereby not only diversifies protein sources but also offers pathways to reduce the system’s overall energy consumption. Incorporating such low-light organisms could address one of vertical farming’s most significant limitations: energy intensity. Research is ongoing to optimize LED lighting spectra and duration, seeking an ideal balance between energy input and biological yield.

Despite the technology’s promising outlook, several barriers remain. Energy consumption for climate control and lighting continues to be the most substantial operational expense. Moreover, cultural acceptance of certain protein sources—particularly insects and algae—poses challenges. These food groups, though nutritionally advantageous and efficient to produce in CEA systems, often encounter consumer resistance rooted in taste preferences, societal norms, or unfamiliarity. Overcoming these social hurdles requires not only advances in cultivation technology but also concerted efforts in public education, culinary innovation, and policy frameworks.

The TUMCREATE team envisions a multi-pronged strategy to unlock vertical farming’s full potential. Central to this vision is the collaboration of engineers, biologists, nutritionists, and social scientists to jointly address technical, economic, and cultural factors. Innovations in energy-efficient climate control, automation, and crop genetics are imperative. Furthermore, interdisciplinary research must inform regulation and incentivize sustainable practices, ensuring that policies align with ecological and social objectives. Investment in outreach programs and marketing efforts will be equally crucial to shift public perceptions and embed these novel protein sources into mainstream diets.

Proteins4Singapore exemplifies a forward-thinking approach to urban food production specifically tailored to meet metropolitan challenges. By situating vertical farms near consumption centers like Singapore, impaired by limited arable land and climatic vulnerabilities, the project pioneers a scalable solution capable of reducing dependency on imports while enhancing food resilience. This regional model offers transferable lessons for global cities facing similar sustainability dilemmas—melding cutting-edge technology with localized production to build adaptive food systems.

The study’s methodological rigor, integrating empirical results from experimental vertical farm setups with quantitative environmental assessments, paves the way for evidence-based decision-making. This scientific framework equips policymakers, investors, and industry stakeholders with a reliable tool to evaluate the trade-offs and benefits of diverse controlled environment agriculture strategies. Ultimately, it promotes transparency and fosters the adoption of scientifically validated interventions critical for meeting future food security goals sustainably.

Looking ahead, vertical farming’s trajectory is fueled by rapid advancements in automation, artificial intelligence, and sensor technologies, enabling more refined control and optimization than ever before. Real-time monitoring of crop health, nutrient delivery systems, and climate parameters will soon allow for adaptive management and predictive maintenance, reducing waste and maximizing yields. The synergy of these innovations—with continued interdisciplinary collaboration—positions vertical farming not only as a means to feed urban populations but as an integral component of a regenerative, resilient food ecosystem.

In conclusion, vertical farming embodies more than a futuristic agricultural method; it manifests as a crucial nexus of technology, sustainability, and nutrition. By transcending traditional crop categories to embrace a wide spectrum of protein sources, this technology redefines the possible. It promises to alleviate the pressures of climate change, urbanization, and resource scarcity while delivering nutritious food with markedly reduced environmental costs. The research from TUMCREATE and its Proteins4Singapore initiative charts a roadmap for how controlled environment agriculture can be a keystone in achieving a sustainable, secure, and equitable global food future.

Subject of Research: Not applicable
Article Title: The future potential of controlled environment agriculture
News Publication Date: 6-Mar-2025
Web References:

• TUMCREATE
• Proteins4Singapore
• DOI: 10.1093/pnasnexus.pgaf078
  Image Credits: Israel Tan Si Lie/TUM
  Keywords: Vertical farming, controlled environment agriculture, protein yield, urban food production, sustainability, mushrooms, insects, algae, cultivated meat, Proteins4Singapore, food security, energy efficiency