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Gene-Editing in Crops Market by Technology Platform (Base Editing & Prime Editing, CRISPR-based systems, Meganucleases), Crop Type (Cereal Crops, Fruits & Vegetables, Legumes & Pulses), Delivery Method, Application, End-User - Global Forecast 2025-2030

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    Report

  • 189 Pages
  • August 2025
  • Region: Global
  • 360iResearch™
  • ID: 6159110
UP TO OFF until Jan 01st 2026
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Gene-editing technologies have emerged as the cornerstone of modern agricultural innovation, promising to redefine how crops are developed, cultivated, and commercialized. Over the past decade, breakthroughs in precision editing tools have enabled the design of plant varieties that exhibit enhanced traits ranging from improved yield potential to fortified nutritional profiles. This convergence of molecular biology, computational analysis, and advanced breeding methods has created unprecedented opportunities to address global challenges such as climate change, resource scarcity, and an expanding population demanding nutritious food.

Moreover, the democratization of gene-editing platforms has shifted research from exclusive institutional domains into broader collaboration networks that include public research institutes, private companies, and international consortia. As a result, the pace of innovation has accelerated, paving the way for pilot demonstrations and regulatory filings around the world. Regulatory agencies, in turn, are evolving their frameworks to adapt to the fine-tuned precision of these approaches, distinguishing gene-edited products from traditional transgenic modifications. Consequently, stakeholders across the agricultural value chain-from seed developers to farmer cooperatives-are reevaluating their R&D pipelines, resource allocations, and go-to-market strategies in light of this transformative trend.

In this executive summary, we synthesize the critical developments and emerging patterns that define the gene-editing crop landscape today. By examining technological shifts, policy dynamics, market segmentation, regional variances, and strategic imperatives, decision-makers will gain a clear line of sight into both the near-term realities and the longer-term horizon of gene-editing’s role in sustainable agriculture.

Exploring the Paradigm Shift in Crop Development Through Gene-Editing Technologies and Their Profound Influence on Breeding and Cultivation Practices Worldwide

In recent years, gene-editing has sparked what many regard as a new green revolution, characterized by the rapid translation of genomic insights into viable agricultural solutions. Traditional breeding approaches, which relied on phenotypic selection and random mutagenesis, are now complemented by technologies that allow scientists to target specific genetic loci with surgical precision. This transition from serendipitous mutation to directed editing has dramatically shortened development cycles and increased the predictability of trait expression.

Furthermore, the advent of multiple editing platforms has diversified the toolkit available to researchers. While CRISPR-based systems continue to dominate headlines due to their versatility and ease of use, emerging modalities such as base editing and prime editing offer even greater control over single nucleotide changes. Alternative systems-including meganucleases, site-directed nucleases, transcription activator-like effector nucleases, and zinc finger nucleases-contribute additional layers of specificity and broaden the range of genomes that can be manipulated.

These technological advances are reinforced by shifting regulatory landscapes. A growing number of jurisdictions now differentiate between alterations that mimic naturally occurring mutations and those that introduce foreign DNA, leading to streamlined approval pathways for certain gene-edited crops. Coupled with increased public-private collaboration and open-access licensing models, these developments have set the stage for a fundamental rethinking of breeding programs. As a result, more stakeholders are investing in precision breeding, from small biotechnology startups to multinational seed producers, all seeking to harness gene-editing’s transformative potential.

Assessing the Far-Reaching Consequences of United States Tariffs Implemented in 2025 on Gene-Edited Crop Supply Chains, Investment Dynamics, and International Trade Patterns

The introduction of new tariff measures by the United States in 2025 has reverberated throughout global gene-editing research and commercialization efforts. As duties were imposed on critical inputs, including specialized reagents, laboratory equipment, and certain delivery materials, research institutions and commercial entities faced escalating operational costs. This shift prompted many organizations to reassess their supply chain strategies, seeking alternative sourcing options or passing cost increases along to downstream partners.

Consequently, collaborative R&D projects that depended on cross-border material transfers experienced delays, and the pace of pilot field trials in certain regions was temporarily hindered. Simultaneously, some biotechnology companies accelerated their investments in domestic manufacturing capabilities and localized partnerships to mitigate exposure to international trade barriers. This trend fostered a renewed focus on vertical integration, with several players choosing to internalize steps ranging from reagent production to delivery system development.

In parallel, tariff-induced pressures influenced investment dynamics within venture capital and corporate development channels. Financing rounds became more scrutinized, with investors demanding clearer pathways to cost recovery and robust risk mitigation strategies. At the same time, stakeholders began exploring new markets where regulatory frameworks and trade agreements offered more predictable cost structures. As an outcome, the gene-editing ecosystem has started to pivot toward diversified geographies and more resilient operational models, reflecting lessons learned from the 2025 tariff cycle.

Analyzing Critical Market Segmentation Drivers Shaping Gene-Editing Adoption Across Technology Platforms Crop Categories Delivery Techniques Applications and User Segments

An in-depth understanding of the gene-editing market requires a granular examination of varied segmentation criteria that collectively shape demand and adoption. When evaluating technology platforms, approaches such as base editing and prime editing are redefining possibilities for single base changes, while CRISPR-based systems remain the workhorses for versatile genome modifications. Complementing these, meganucleases and site-directed nucleases offer high specificity for targeted cuts, and transcription activator-like effector nucleases and zinc finger nucleases serve distinct niches where bespoke editing requirements arise.

Turning to crop types, the focus encompasses a range of agricultural staples and specialty produce. Cereal crops continue to attract substantial R&D attention given their global caloric contributions, whereas fruits and vegetables are often targeted for quality enhancements and shelf-life improvements. In parallel, legumes and pulses are emerging as key candidates for trait improvements related to protein content and nitrogen fixation. Oilseed crops, meanwhile, remain essential for both edible oil production and industrial applications, driving demand for edits that enhance oil composition and yield.

Delivery methods represent another critical axis of segmentation, with established techniques such as agrobacterium-mediated transformation and electroporation coexisting alongside emerging systems. Gene gun applications remain relevant for species recalcitrant to other approaches, while nanoparticle-based delivery and ribonucleoprotein complexes are gaining traction for their reduced integration footprints. Viral vector delivery, too, continues to evolve, offering high-efficiency transfer in both dicotyledonous and monocotyledonous plants.

Applications span multiple agronomic goals, including disease resistance, drought tolerance, herbicide tolerance, and nutritional enhancement. Notably, within disease resistance, targeted strategies address bacterial, fungal, and viral pathogens, leveraging tailored edits to fortify plant immune responses. Each application area dictates unique R&D workflows and regulatory considerations, influencing time to market and commercialization strategies.

Finally, end users cover a spectrum of stakeholders from agricultural biotechnology companies driving innovation pipelines, to farmers and grower associations evaluating cost-benefit trade-offs in field conditions. Government and regulatory bodies set policy frameworks that determine market access, research institutes and universities push the boundaries of foundational science, and seed companies focus on scale-up, distribution, and branding. Understanding the interplay among these segments is essential for designing robust business models and capturing value in a competitive landscape.

Illuminating Regional Dynamics and Growth Trajectories for Gene-Edited Crops Across the Americas Europe Middle East & Africa and Asia-Pacific Markets

Regional dynamics in the gene-editing crop arena reflect a mosaic of regulatory stances, investment climates, and public sentiment. Within the Americas, supportive frameworks and early clarifications on the regulation of gene-edited products have fueled an environment where field trials proceed with relative ease. This environment has drawn significant private investment, catalyzing partnerships between multinational agribusiness firms and local research entities. These collaborations have accelerated the translation of lab-scale successes into pre-commercial demonstrations across varied agroecological zones.

Across Europe, the Middle East and Africa, divergent regulatory approaches have created a patchwork of opportunities and constraints. Some European nations have taken a precautionary approach, subjecting gene-edited crops to standard GMO approval processes, while others are advocating for differentiated protocols that reflect advances in precision editing. In parallel, Middle Eastern countries are investing heavily in agrotechnology hubs, and select African nations are exploring gene-editing for staple crops vulnerable to climate stress. This heterogeneity underscores the importance of tailored engagement strategies and adaptive regulatory roadmaps.

In Asia-Pacific, the confluence of large-scale food security imperatives and rapid technological adoption has positioned the region as a potential growth hotspot. Several governments have launched incentives to bolster domestic R&D, and public-private consortia are emerging to address region-specific challenges such as monsoon variability and soil salinity. Moreover, regulatory dialogues are underway to harmonize safety assessments, paving the way for cross-border collaboration and enabling producers to scale innovations across diverse national markets.

Collectively, these regional trends signal the need for strategic agility. Companies and research organizations must navigate varied approval pathways, engage diverse stakeholder groups, and anticipate evolving consumer perceptions. As harmonization efforts advance and trade agreements mature, the interplay among these markets will further define the global trajectory of gene-editing adoption.

Profiling Leading Innovators and Key Players in the Gene-Editing Crop Landscape Who Are Driving Research Commercialization and Strategic Alliances

The competitive landscape of gene-editing in crops is defined by a blend of established agrifood corporations, specialized biotechnology firms, and agile startups. Leading innovators have secured broad intellectual property portfolios covering core editing technologies and associated delivery systems. These companies are channeling resources into proof-of-concept trials that demonstrate trait efficacy across multiple crop species and environmental conditions. They also maintain active collaborations with academic institutions to sustain a pipeline of emerging applications.

Alongside these incumbents, seed companies and agricultural biotechnology enterprises are integrating proprietary editing capabilities into their product lines, often through licensing agreements or joint ventures. These partnerships enable rapid commercialization of traits ranging from drought resilience to improved nutrient profiles. Simultaneously, a cohort of nimble startups is focusing on niche markets, pursuing differentiated strategies such as non-transgenic edits or specialty crop improvements where regulatory clarity is relatively advanced.

Investment patterns reveal a convergence of capital from venture investors, strategic corporate backers, and government grant programs. This multi-pronged financing environment supports a spectrum of initiatives, from foundational research in novel editing modalities to late-stage commercial demonstrations. Mergers and acquisitions continue to shape the field, as larger players assimilate technology assets and talent from innovative smaller enterprises.

In addition, alliances with seed distributors, equipment manufacturers, and contract research organizations are increasingly common. These cross-industry collaborations streamline field trial execution, accelerate data collection, and facilitate market entry across different geographies. Ultimately, the interplay of proprietary innovation, strategic alliances, and targeted investments defines how companies vie for leadership in the evolving gene-edited crop ecosystem.

Actionable Strategic Recommendations for Industry Leaders to Navigate Regulatory Complexities Foster Collaboration and Accelerate Market Entry and Adoption of Gene-Edited Crops

Industry leaders seeking to capitalize on gene-editing advancements should begin by engaging proactively with regulatory authorities to shape evidence-based approval pathways and reduce uncertainty around product launches. Concurrently, investment in integrated platforms that combine multiple editing modalities will enhance the ability to address complex trait architectures and unlock novel opportunities in underexplored crop categories.

Forming strategic partnerships with regional research institutions and local distributors can accelerate pilot programs while ensuring adaptations to specific agroecological conditions. Such collaborations also facilitate knowledge transfer and strengthen stakeholder buy-in, which is critical for managing public perception and regulatory scrutiny. Moreover, organizations should implement flexible supply chain strategies to buffer against future trade disruptions and tariff fluctuations.

A robust intellectual property strategy is equally vital, encompassing both core editing patents and freedom-to-operate analyses. This approach helps mitigate litigation risks and creates leverage in licensing negotiations. Additionally, companies should prioritize transparent communication of safety data and trait benefits to foster consumer trust and differentiate their offerings in competitive markets.

Finally, establishing quantitative field validation studies with clear performance metrics will substantiate value propositions to farmers and end users. By focusing on demonstrable agronomic gains-such as yield improvements under stress conditions or nutrient enhancements-stakeholders can drive adoption and justify premium positioning. Collectively, these actions form a cohesive roadmap for navigating regulatory, operational, and market complexities.

Comprehensive Research Methodology Outlining Data Sources Analytical Frameworks and Validation Processes Underpinning the Gene-Editing Crops Market Study

The findings presented in this executive summary derive from a rigorous research methodology that combines both primary and secondary data sources. Primary research involved in-depth interviews with leading scientists, regulatory officials, industry executives, and agronomic specialists. These conversations were structured to capture real-world perspectives on technical feasibility, commercial viability, and regulatory considerations.

Secondary research encompassed a systematic review of peer-reviewed journals, technical white papers, patent filings, regulatory databases, and publicly available corporate disclosures. Trade publications and industry reports supplemented these sources to provide context on market trends, investment flows, and adoption case studies. Additionally, real-time tracking of legislative developments in major markets informed the analysis of regulatory impacts.

Analytical frameworks such as SWOT analysis, PESTEL evaluation, and Porter’s Five Forces were applied to assess the competitive environment, macroeconomic influences, and industry dynamics. Segmentation analyses were conducted by mapping technology platforms, crop categories, delivery methods, application areas, and end-user groups to evaluate demand drivers and adoption barriers.

Data validation was achieved through triangulation, cross-referencing insights from multiple sources to ensure consistency and reliability. Quality assurance protocols, including peer reviews and expert validation rounds, further reinforced the credibility of the findings. Ethical guidelines governed all primary research engagements, ensuring confidentiality and unbiased reporting.

Concluding Insights on the Evolution of Gene-Edited Crops and Their Implications for Stakeholders Across the Agricultural Value Chain Moving Forward

Gene-editing technologies are poised to usher in a new era of agricultural productivity and sustainability. The convergence of advanced editing platforms, diversified delivery methods, and evolving regulatory frameworks creates a fertile landscape for innovation across crops and applications. However, stakeholders must remain vigilant in navigating trade challenges, aligning strategic partnerships, and adapting to region-specific market dynamics.

By leveraging robust segmentation insights and embracing agile operational models, organizations can position themselves to lead in trait development, field validation, and commercial deployment. At the same time, transparent engagement with regulators, investors, and end users will be critical to building trust and unlocking the full potential of gene-edited crops. As the industry continues its rapid evolution, collaboration and evidence-based decision-making will serve as the twin pillars driving success across the agricultural value chain.

Market Segmentation & Coverage

This research report categorizes to forecast the revenues and analyze trends in each of the following sub-segmentations:
  • Technology Platform
    • Base Editing & Prime Editing
    • CRISPR-based systems
    • Meganucleases
    • Site-Directed Nucleases
    • Transcription Activator-Like Effector Nucleases
    • Zinc Finger Nucleases
  • Crop Type
    • Cereal Crops
    • Fruits & Vegetables
    • Legumes & Pulses
    • Oilseed Crops
  • Delivery Method
    • Agrobacterium-Mediated Transformation
    • Electroporation
    • Gene Gun
    • Nanoparticle-Based Delivery
    • Ribonucleoprotein (RNP) Complexes
    • Viral Vector Delivery
  • Application
    • Disease Resistance
      • Bacterial Resistance
      • Fungal Resistance
      • Viral Resistance
    • Drought Tolerance
    • Herbicide Tolerance
    • Nutritional Enhancement
  • End-User
    • Agricultural Biotechnology Companies
    • Farmers & Grower Associations
    • Government & Regulatory Bodies
    • Research Institutes & Universities
    • Seed Companies
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-regions:
  • Americas
    • United States
      • California
      • Texas
      • New York
      • Florida
      • Illinois
      • Pennsylvania
      • Ohio
    • Canada
    • Mexico
    • Brazil
    • Argentina
  • Europe, Middle East & Africa
    • United Kingdom
    • Germany
    • France
    • Russia
    • Italy
    • Spain
    • United Arab Emirates
    • Saudi Arabia
    • South Africa
    • Denmark
    • Netherlands
    • Qatar
    • Finland
    • Sweden
    • Nigeria
    • Egypt
    • Turkey
    • Israel
    • Norway
    • Poland
    • Switzerland
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
    • Indonesia
    • Thailand
    • Philippines
    • Malaysia
    • Singapore
    • Vietnam
    • Taiwan
This research report delves into recent significant developments and analyzes trends in each of the following companies:
  • AgBiome, Inc.
  • BASF SE
  • Bayer AG
  • Benson Hill, Inc.
  • Calyxt, Inc.
  • Cibus, Inc.
  • Corteva Agriscience, Inc. by DuPont de Nemours, Inc
  • Creative Biogene
  • Elo Life Systems
  • Groupe Limagrain S.A.
  • Inari Agriculture, Inc.
  • KWS SAAT SE & Co. KGaA
  • Origin Agritech
  • Pairwise Foods, Inc.
  • Syngenta AG
  • Yield10 Bioscience, Inc.

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Table of Contents

1. Preface
1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders
2. Research Methodology
2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update
3. Executive Summary
4. Market Overview
4.1. Introduction
4.2. Market Sizing & Forecasting
5. Market Dynamics
5.1. Integration of multiplexed gene-editing platforms to develop disease resistant tomato and potato varieties
5.2. Accelerating adoption of CRISPR base editors to improve drought and heat tolerance in staple crops
5.3. Commercialization strategies for gene-edited soybeans targeting increased protein content and nitrogen use efficiency
5.4. Advancements in tissue-specific promoter design enabling precise gene edits for pest resistance in maize
5.5. Regulatory harmonization efforts between the US, EU and Asia Pacific for gene-editing approvals in agriculture biotechnology
5.6. Collaborations between agri-biotech startups and academic institutions to accelerate wheat genome editing pipeline
5.7. Investment surge in predictive phenotyping and AI-driven target identification for optimized gene edits in rice
6. Market Insights
6.1. Porter’s Five Forces Analysis
6.2. PESTLE Analysis
7. Cumulative Impact of United States Tariffs 2025
8. Gene-Editing in Crops Market, by Technology Platform
8.1. Introduction
8.2. Base Editing & Prime Editing
8.3. CRISPR-based systems
8.4. Meganucleases
8.5. Site-Directed Nucleases
8.6. Transcription Activator-Like Effector Nucleases
8.7. Zinc Finger Nucleases
9. Gene-Editing in Crops Market, by Crop Type
9.1. Introduction
9.2. Cereal Crops
9.3. Fruits & Vegetables
9.4. Legumes & Pulses
9.5. Oilseed Crops
10. Gene-Editing in Crops Market, by Delivery Method
10.1. Introduction
10.2. Agrobacterium-Mediated Transformation
10.3. Electroporation
10.4. Gene Gun
10.5. Nanoparticle-Based Delivery
10.6. Ribonucleoprotein (RNP) Complexes
10.7. Viral Vector Delivery
11. Gene-Editing in Crops Market, by Application
11.1. Introduction
11.2. Disease Resistance
11.2.1. Bacterial Resistance
11.2.2. Fungal Resistance
11.2.3. Viral Resistance
11.3. Drought Tolerance
11.4. Herbicide Tolerance
11.5. Nutritional Enhancement
12. Gene-Editing in Crops Market, by End-User
12.1. Introduction
12.2. Agricultural Biotechnology Companies
12.3. Farmers & Grower Associations
12.4. Government & Regulatory Bodies
12.5. Research Institutes & Universities
12.6. Seed Companies
13. Americas Gene-Editing in Crops Market
13.1. Introduction
13.2. Canada
13.3. Mexico
13.4. United States
13.5. Argentina
13.6. Brazil
14. Europe, Middle East & Africa Gene-Editing in Crops Market
14.1. Introduction
14.2. Qatar
14.3. Turkey
14.4. Netherlands
14.5. Germany
14.6. United Arab Emirates
14.7. Nigeria
14.8. South Africa
14.9. France
14.10. Switzerland
14.11. Poland
14.12. Spain
14.13. Norway
14.14. United Kingdom
14.15. Israel
14.16. Denmark
14.17. Russia
14.18. Italy
14.19. Egypt
14.20. Saudi Arabia
14.21. Finland
14.22. Sweden
15. Asia-Pacific Gene-Editing in Crops Market
15.1. Introduction
15.2. Australia
15.3. China
15.4. Japan
15.5. India
15.6. Thailand
15.7. Indonesia
15.8. Philippines
15.9. Taiwan
15.10. Singapore
15.11. South Korea
15.12. Vietnam
15.13. Malaysia
16. Competitive Landscape
16.1. Market Share Analysis, 2024
16.2. FPNV Positioning Matrix, 2024
16.3. Competitive Analysis
16.3.1. AgBiome, Inc.
16.3.2. BASF SE
16.3.3. Bayer AG
16.3.4. Benson Hill, Inc.
16.3.5. Calyxt, Inc.
16.3.6. Cibus, Inc.
16.3.7. Corteva Agriscience, Inc. by DuPont de Nemours, Inc
16.3.8. Creative Biogene
16.3.9. Elo Life Systems
16.3.10. Groupe Limagrain S.A.
16.3.11. Inari Agriculture, Inc.
16.3.12. KWS SAAT SE & Co. KGaA
16.3.13. Origin Agritech
16.3.14. Pairwise Foods, Inc.
16.3.15. Syngenta AG
16.3.16. Yield10 Bioscience, Inc.
17. ResearchAI
18. ResearchStatistics
19. ResearchContacts
20. ResearchArticles
21. Appendix
List of Figures
FIGURE 1. GENE-EDITING IN CROPS MARKET MULTI-CURRENCY
FIGURE 2. GENE-EDITING IN CROPS MARKET MULTI-LANGUAGE
FIGURE 3. GENE-EDITING IN CROPS MARKET RESEARCH PROCESS
FIGURE 4. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 5. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 6. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 7. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2024 VS 2030 (%)
FIGURE 8. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 9. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2024 VS 2030 (%)
FIGURE 10. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 11. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2024 VS 2030 (%)
FIGURE 12. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 13. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2024 VS 2030 (%)
FIGURE 14. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 15. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2024 VS 2030 (%)
FIGURE 16. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 17. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
FIGURE 18. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 19. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY STATE, 2024 VS 2030 (%)
FIGURE 20. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 21. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
FIGURE 22. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 23. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
FIGURE 24. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
FIGURE 25. GENE-EDITING IN CROPS MARKET SHARE, BY KEY PLAYER, 2024
FIGURE 26. GENE-EDITING IN CROPS MARKET, FPNV POSITIONING MATRIX, 2024
List of Tables
TABLE 1. GENE-EDITING IN CROPS MARKET SEGMENTATION & COVERAGE
TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
TABLE 3. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 4. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
TABLE 5. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
TABLE 6. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 7. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY BASE EDITING & PRIME EDITING, BY REGION, 2018-2030 (USD MILLION)
TABLE 8. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY CRISPR-BASED SYSTEMS, BY REGION, 2018-2030 (USD MILLION)
TABLE 9. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY MEGANUCLEASES, BY REGION, 2018-2030 (USD MILLION)
TABLE 10. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY SITE-DIRECTED NUCLEASES, BY REGION, 2018-2030 (USD MILLION)
TABLE 11. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY TRANSCRIPTION ACTIVATOR-LIKE EFFECTOR NUCLEASES, BY REGION, 2018-2030 (USD MILLION)
TABLE 12. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY ZINC FINGER NUCLEASES, BY REGION, 2018-2030 (USD MILLION)
TABLE 13. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 14. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY CEREAL CROPS, BY REGION, 2018-2030 (USD MILLION)
TABLE 15. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY FRUITS & VEGETABLES, BY REGION, 2018-2030 (USD MILLION)
TABLE 16. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY LEGUMES & PULSES, BY REGION, 2018-2030 (USD MILLION)
TABLE 17. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY OILSEED CROPS, BY REGION, 2018-2030 (USD MILLION)
TABLE 18. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 19. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY AGROBACTERIUM-MEDIATED TRANSFORMATION, BY REGION, 2018-2030 (USD MILLION)
TABLE 20. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY ELECTROPORATION, BY REGION, 2018-2030 (USD MILLION)
TABLE 21. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY GENE GUN, BY REGION, 2018-2030 (USD MILLION)
TABLE 22. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY NANOPARTICLE-BASED DELIVERY, BY REGION, 2018-2030 (USD MILLION)
TABLE 23. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY RIBONUCLEOPROTEIN (RNP) COMPLEXES, BY REGION, 2018-2030 (USD MILLION)
TABLE 24. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY VIRAL VECTOR DELIVERY, BY REGION, 2018-2030 (USD MILLION)
TABLE 25. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 26. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 27. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY BACTERIAL RESISTANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 28. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY FUNGAL RESISTANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 29. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY VIRAL RESISTANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 30. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 31. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY DROUGHT TOLERANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 32. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY HERBICIDE TOLERANCE, BY REGION, 2018-2030 (USD MILLION)
TABLE 33. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY NUTRITIONAL ENHANCEMENT, BY REGION, 2018-2030 (USD MILLION)
TABLE 34. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 35. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY AGRICULTURAL BIOTECHNOLOGY COMPANIES, BY REGION, 2018-2030 (USD MILLION)
TABLE 36. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY FARMERS & GROWER ASSOCIATIONS, BY REGION, 2018-2030 (USD MILLION)
TABLE 37. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY GOVERNMENT & REGULATORY BODIES, BY REGION, 2018-2030 (USD MILLION)
TABLE 38. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY RESEARCH INSTITUTES & UNIVERSITIES, BY REGION, 2018-2030 (USD MILLION)
TABLE 39. GLOBAL GENE-EDITING IN CROPS MARKET SIZE, BY SEED COMPANIES, BY REGION, 2018-2030 (USD MILLION)
TABLE 40. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 41. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 42. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 43. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 44. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 45. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 46. AMERICAS GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
TABLE 47. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 48. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 49. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 50. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 51. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 52. CANADA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 53. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 54. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 55. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 56. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 57. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 58. MEXICO GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 59. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 60. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 61. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 62. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 63. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 64. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 65. UNITED STATES GENE-EDITING IN CROPS MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
TABLE 66. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 67. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 68. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 69. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 70. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 71. ARGENTINA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 72. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 73. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 74. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 75. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 76. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 77. BRAZIL GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 78. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 79. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 80. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 81. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 82. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 83. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 84. EUROPE, MIDDLE EAST & AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
TABLE 85. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 86. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 87. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 88. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 89. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 90. QATAR GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 91. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 92. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 93. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 94. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 95. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 96. TURKEY GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 97. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 98. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 99. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 100. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 101. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 102. NETHERLANDS GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 103. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 104. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 105. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 106. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 107. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 108. GERMANY GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 109. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 110. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 111. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 112. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 113. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 114. UNITED ARAB EMIRATES GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 115. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 116. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 117. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 118. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 119. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 120. NIGERIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 121. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 122. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 123. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 124. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 125. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 126. SOUTH AFRICA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 127. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 128. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 129. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 130. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 131. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 132. FRANCE GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 133. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 134. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 135. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 136. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 137. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 138. SWITZERLAND GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 139. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 140. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 141. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 142. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 143. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 144. POLAND GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 145. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 146. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 147. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 148. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 149. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 150. SPAIN GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 151. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 152. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 153. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 154. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 155. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 156. NORWAY GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 157. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 158. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 159. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 160. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 161. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 162. UNITED KINGDOM GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 163. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 164. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 165. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 166. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 167. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 168. ISRAEL GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 169. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 170. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 171. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 172. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 173. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 174. DENMARK GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 175. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 176. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 177. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 178. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 179. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 180. RUSSIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 181. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 182. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 183. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 184. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 185. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 186. ITALY GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 187. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 188. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 189. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 190. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 191. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 192. EGYPT GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 193. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 194. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 195. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 196. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 197. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 198. SAUDI ARABIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 199. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 200. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 201. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 202. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 203. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 204. FINLAND GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 205. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 206. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 207. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 208. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 209. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 210. SWEDEN GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 211. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 212. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 213. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 214. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 215. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 216. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 217. ASIA-PACIFIC GENE-EDITING IN CROPS MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
TABLE 218. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 219. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 220. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 221. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 222. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 223. AUSTRALIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 224. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 225. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 226. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 227. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 228. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 229. CHINA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 230. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 231. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 232. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 233. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 234. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 235. JAPAN GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 236. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 237. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 238. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 239. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 240. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 241. INDIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 242. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 243. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 244. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 245. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 246. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 247. THAILAND GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 248. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 249. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 250. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 251. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 252. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 253. INDONESIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 254. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 255. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 256. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 257. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 258. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 259. PHILIPPINES GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 260. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 261. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 262. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 263. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 264. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 265. TAIWAN GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 266. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 267. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 268. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 269. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 270. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 271. SINGAPORE GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 272. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 273. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 274. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 275. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 276. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 277. SOUTH KOREA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 278. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 279. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 280. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 281. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 282. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 283. VIETNAM GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 284. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY TECHNOLOGY PLATFORM, 2018-2030 (USD MILLION)
TABLE 285. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY CROP TYPE, 2018-2030 (USD MILLION)
TABLE 286. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY DELIVERY METHOD, 2018-2030 (USD MILLION)
TABLE 287. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 288. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY DISEASE RESISTANCE, 2018-2030 (USD MILLION)
TABLE 289. MALAYSIA GENE-EDITING IN CROPS MARKET SIZE, BY END-USER, 2018-2030 (USD MILLION)
TABLE 290. GENE-EDITING IN CROPS MARKET SHARE, BY KEY PLAYER, 2024
TABLE 291. GENE-EDITING IN CROPS MARKET, FPNV POSITIONING MATRIX, 2024

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Companies Mentioned

The companies profiled in this Gene-Editing in Crops market report include:
  • AgBiome, Inc.
  • BASF SE
  • Bayer AG
  • Benson Hill, Inc.
  • Calyxt, Inc.
  • Cibus, Inc.
  • Corteva Agriscience, Inc. by DuPont de Nemours, Inc
  • Creative Biogene
  • Elo Life Systems
  • Groupe Limagrain S.A.
  • Inari Agriculture, Inc.
  • KWS SAAT SE & Co. KGaA
  • Origin Agritech
  • Pairwise Foods, Inc.
  • Syngenta AG
  • Yield10 Bioscience, Inc.