Global Computational Breeding Market Size By Type (Molecular Breeding, Hybrid Breeding), By Application (Oilseeds & Pulses, Cereals & Grains), By Region, And Segment Forecasts, 2023 to 2032

The Global Computational Breeding Market was valued at USD 1.4 billion in 2023 and is projected to reach USD 3.6 billion by 2031, registering a CAGR of 12.5% during the forecast period (2023–2031). Computational breeding integrates artificial intelligence (AI), machine learning (ML), and big data analytics to accelerate plant and animal breeding programs. The technology enhances genetic gain, crop resilience, and livestock productivity, addressing challenges in food security and climate change adaptation. The rising demand for higher-yielding, disease-resistant, and climate-adaptive crops and livestock is driving the adoption of computational breeding solutions across agricultural research institutions and agribusinesses.

Drivers

Rising Need for High-Yield Crops and Livestock

With a growing global population, the demand for high-yielding and disease-resistant crops and livestock is at an all-time high. Computational breeding enables the identification of optimal genetic combinations to enhance productivity and sustainability.

Integration of AI, Machine Learning, and Big Data

Advancements in AI and ML algorithms have revolutionized genomic selection and trait prediction, significantly reducing breeding cycles and increasing efficiency.

Climate Change and Food Security Challenges

Climate change poses a significant threat to agricultural productivity. Computational breeding assists in the development of drought-resistant, heat-tolerant, and climate-adaptive crops, ensuring global food security.

Restraints

High Cost of Implementation

The adoption of computational breeding requires substantial investment in infrastructure, software, and expertise, posing a challenge for small and medium-sized agricultural enterprises.

Data Privacy and Intellectual Property Concerns

With increasing digitization, concerns over data ownership, patent rights, and privacy in computational breeding are rising, limiting data-sharing collaborations.

Opportunity

Expansion in Emerging Markets

Emerging economies, particularly in Asia-Pacific and Latin America, are investing in smart agriculture and biotechnology, creating significant growth opportunities.

Advancements in Genomics and Precision Agriculture

The rise of gene-editing technologies (CRISPR), high-throughput sequencing, and precision farming is further enhancing the accuracy of computational breeding techniques, presenting lucrative opportunities for market players.

Market by System Type Insights

Based on system type, the Genomic Selection and Prediction segment dominated the market in 2023. The use of genomics and AI-driven predictive modeling allows for more accurate trait selection, reducing breeding cycle times and increasing efficiency. This segment is expected to witness continued growth due to increasing investment in agricultural biotechnology.

Market by End-use Insights

The Crop Breeding segment emerged as the largest revenue contributor in 2023, accounting for more than 55% of the market share. Computational breeding is widely applied in cereal, oilseed, and vegetable breeding programs, accelerating genetic improvement and seed development. The Livestock Breeding segment is also expanding, driven by demand for high-quality animal genetics and dairy production.

Market by Regional Insights

North America (Largest Market in 2023)

North America dominated the market, with the United States and Canada leading in genomic selection, AI-driven trait analysis, and smart agriculture adoption. The presence of major agritech firms and research institutions further strengthens market growth.

Asia-Pacific (Fastest-Growing Market)

Asia-Pacific is expected to witness the highest CAGR during 2023–2031, driven by increasing government initiatives in agricultural biotechnology, precision farming, and digital transformation in key countries such as China, India, and Australia.

Competitive Scenario

Key players in the Global Computational Breeding Market include:

Bayer CropScience

Syngenta AG

Corteva Agriscience

Benson Hill Biosystems

Neogen Corporation

Genus Plc

Evogene Ltd.

Indigo Agriculture

Bioceres Crop Solutions

NRGene Ltd.

These companies are investing in AI-driven breeding platforms, gene-editing technologies, and strategic partnerships to enhance computational breeding solutions.

Scope of Work – Global Computational Breeding Market

Key Market Developments

2023: Bayer CropScience launched an AI-powered computational breeding platform, accelerating trait discovery and genetic improvement.

2024: Corteva Agriscience partnered with leading genomics firms to integrate big data analytics in hybrid crop breeding.

2025: Neogen Corporation introduced cloud-based genomic prediction tools, enabling real-time genetic analysis for farmers.

FAQs

1. What is the current market size of the Global Computational Breeding Market?

The market was valued at USD 1.4 billion in 2023 and is projected to grow significantly by 2031.

2. What is the major growth driver of the Global Computational Breeding Market?

The market is primarily driven by AI & ML integration in breeding, increasing demand for high-yield crops and livestock, and climate change adaptation needs.

3. Which is the largest region during the forecast period in the Global Computational Breeding Market?

North America holds the largest market share, while Asia-Pacific is expected to experience the highest growth rate.

4. Which segment accounted for the largest market share in the Global Computational Breeding Market?

The Genomic Selection & Prediction segment led the market, while Crop Breeding held the largest revenue share.

5. Who are the key market players in the Global Computational Breeding Market?

Key players include Bayer CropScience, Syngenta AG, Corteva Agriscience, Benson Hill Biosystems, Neogen Corporation, and Indigo Agriculture, among others.

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