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시장보고서
상품코드
2095577
소 결핵 진단 시장 예측(2026-2032년)Bovine Tuberculosis Diagnosis Market - Global Forecast 2026-2032 |
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360iResearch
소 결핵 진단 시장은 2032년까지 연평균 복합 성장률(CAGR) 8.92%로, 17억 4,816만 달러 성장이 전망되고 있습니다.
| 주요 시장 통계 | |
|---|---|
| 기준 연도 : 2025년 | 9억 6,080만 달러 |
| 추정 연도 : 2026년 | 10억 4,170만 달러 |
| 예측 연도 : 2032년 | 17억 4,816만 달러 |
| CAGR(%) | 8.92% |
소 결핵 진단은 동물 위생 모니터링, 가축의 생물 보안, 공중 보건 보호, 국제 무역 규정 준수 측면에서 매우 중요한 요소입니다. 주로 마이코박테리움 보비스(Mycobacterium bovis)에 의해 유발되는 소 결핵은 소에게 영향을 미칠 뿐만 아니라, 야생동물의 보균자나 인간에게도 감염될 가능성이 있으므로, ‘원헬스(One Health)’ 프레임워크 하에서 정확한 검출이 필수적입니다. 진단 전략에서는 일반적으로 현장 선별 검사, 실험실에서의 확정 진단, 군 단위 모니터링, 도축장 검사, 역학적 추적을 결합하여 감염을 특정하고, 감염 확산을 억제하며, 질병 대책 프로그램을 지원합니다.
진단 기법에는 기존 투베르쿨린 피부 반응 검사, 인터페론-γ 방출 검사, 배양, 조직병리학, PCR 등의 분자 검사, 집단 발생 조사 및 균주 특성 평가를 위한 전체 유전체 염기서열 분석이 포함됩니다. 각 기법에는 각각 명확한 역할이 있습니다. 피부 반응 검사는 군 단위 선별 검사에 널리 활용되고 있으며, 실험실 배양은 소요 시간이 길지만 확실한 증거를 제공하며, 분자진단은 인프라와 검증된 프로토콜이 갖춰진 경우 보다 신속한 동정을 지원합니다. 신뢰성 높은 소 결핵 검사에 대한 수요는 동물 이동에 관한 규제 강화, 식품 안전 요건, 인수공통감염병에 대한 인식 제고, 유제품 및 쇠고기 공급망을 질병으로 인한 막대한 경제적 손실로부터 보호해야 할 필요성에 의해 형성되고 있습니다.
진단 방식의 혁신적인 변화
소 결핵 진단 현황은 단일 검사에 대한 의존에서 통합된 위험 기반 진단 시스템으로 실질적인 전환을 이루고 있습니다. 수의 당국과 목장 관리자들은 위양성 및 위음성을 관리하면서 사례 검출률을 높이기 위해, 피부 반응 검사, 보조 혈액 검사, 도체 검사, 분자진단을 통한 확인을 조합하는 사례가 늘고 있습니다. 이러한 전환은 야생동물의 보균자, 혼합 농업 시스템, 국경을 넘는 가축 이동, 목장의 생물보안 상황의 편차가 박멸 노력을 복잡하게 만드는 지역에서 특히 중요합니다.
인공지능(AI)의 누적 영향
인공지능(AI)은 진단 데이터, 역학 데이터, 모니터링 데이터의 해석 방법을 개선함으로써 소 결핵 진단에 영향을 미치기 시작했습니다. AI를 활용한 분석을 통해 소 무리의 위험도 평가, 고위험 지역에서의 검사 우선순위 지정, 공간적 클러스터 식별이 가능해지며, 나아가 가축 이동, 농장 이력, 야생동물과의 접촉, 도축장 소견, 검사 결과 등의 데이터를 통합할 수 있습니다. 이러한 응용은 수의 당국이 제한된 검사 자원을 대규모 소 무리나 지리적으로 분산된 농장에 배분해야 하는 경우에 특히 효과적입니다.
지역별 주요 인사이트
아시아태평양에서는 집약적인 낙농 시스템부터 소규모 농업 종사자 및 다품종 혼방목 환경까지, 소 결핵 진단 수요가 다양해지고 있습니다. 낙농 생산이 확대되고 가축 이동 네트워크가 밀집된 국가에서는 감시, 검사 능력, 인수공통감염병 모니터링이 중시되고 있지만, 야생동물과 가축의 접촉 및 수의 서비스 접근 상황의 편차가 진단 포괄률에 영향을 미치고 있습니다. 북미에서는 가축 식별, 소군 검사, 이동 규제, 도축장 모니터링, 검사실 확인에 기반한 체계적인 소 결핵 대책 프로그램이 유지되고 있으며, 특히 야생동물의 보균원이나 국경과 관련된 가축 무역 요건에 중점을 두고 있습니다.
주요 그룹의 견해
아세안(ASEAN)에서는 집약적인 낙농 경영, 소규모 농업 종사자에 의한 소 사육 시스템, 국경을 넘는 가축 이동 등이 존재하기 때문에 소 결핵 진단 환경은 매우 다양하며, 조정된 모니터링과 실용적인 현장 진단이 필요합니다. 이 지역의 우선 과제로는 수의학 검사 기관의 강화, 추적성 향상, 동물 위생 모니터링과 식품 안전 및 인수공통감염병 예방 간의 연계 등이 포함됩니다. GCC의 진단상 중점 사항은 가축 수입에 대한 의존도, 식량 안보 프로그램, 관리된 낙농 생산 시스템에 의해 형성되어 있으며, 여기에서는 검역 검사, 건강 증명서 발급, 검사실을 통한 검증된 모니터링이 중요한 역할을 수행하고 있습니다.
주요 국가별 인사이트
미국과 캐나다에서는 군 검사, 처리 과정 모니터링, 역학 조사, 이동 규제를 활용한 공식적인 소 결핵 모니터링 체계를 유지하고 있으며, 진단상의 중점은 질병 관리 상황 유지와 야생동물과 관련된 위험 관리에 두어지고 있습니다. 멕시코의 진단 상황은 소 거래, 지역별 대책 프로그램, 인증 요건과 밀접하게 연관되어 있으며, 신뢰성이 높은 투베르쿨린 검사, 검사, 실험실 확인이 필수적입니다. 브라질의 대규모 축산 부문에서는 특히 소 무리의 건강과 수출에 대한 신뢰가 최우선 과제인 젖소와 육우 생산 지역에서 확장 가능한 질병 감시 체계의 필요성이 높아지고 있습니다.
산업 리더를 위한 실용적인 권고 사항
산업 리더는 현장 선별 검사와 확인을 위한 실험실 기법을 결합한, 검증되고 목적에 적합한 진단 전략을 우선시해야 합니다. 검사법 선정 시에는 소 무리의 위험도, 규제 요건, 가축의 이동 패턴, 야생동물과의 접촉, 잘못된 진단 결과가 초래하는 영향을 고려해야 합니다. 검체 물류, 검사실의 품질 관리, 능력 검사, 표준화된 보고 체계에 대한 투자는 결과에 대한 신뢰성을 높이고, 질병 대책에 대한 의사결정을 적시에 지원할 수 있습니다.
조사 방법
본 요약본은 검증된 동물 위생, 수의학적 진단 및 공중보건 관련 정보원을 바탕으로 한 2차 조사 방법을 사용하여 작성되었습니다. 본 조사 방법론에서는 공적 수의 당국, 정부 간 동물 위생 지침, 동료 심사를 거친 과학 문헌, 각국의 감시 자료, 규제 체계, 공인된 ‘원헬스(One Health)’ 관련 자료에서 얻은 증거를 중시합니다. 시장 규모·추정치, 시장 점유율 또는 예측에 의존하지 않고, 진단 실무, 지역별 우선순위, 기술 동향, 운영상의 고려 사항을 기술하기 위해 관련 지식을 통합하고 있습니다.
결론
소 결핵 진단은 동물 건강 보호, 인수공통감염병 예방, 탄력적인 축산업을 위해 여전히 핵심적인 역할을 수행하고 있습니다. 이 부문은 현장 검사, 실험실 확인, 디지털 추적성, 분자역학, 위험 기반 감시를 결합한 통합적인 진단 생태계로 전환되고 있습니다. 투베르쿨린 검사와 같이 오랫동안 확립된 기법이 계속해서 중요한 역할을 수행하는 한편, 분자진단, 염기서열 분석, 데이터 분석, AI를 활용한 의사결정 지원의 활용 확대에 따라 대책 프로그램의 정확성과 대응 능력이 향상되고 있습니다.
자주 묻는 질문
목차
제1장 서문
제2장 조사 방법
제3장 주요 요약
제4장 시장 개요
제5장 시장 인사이트
제6장 AI의 누적 영향, 2026년
제7장 소 결핵 진단 시장 : 테스트 유형별
제8장 소 결핵 진단 시장 : 제품별
제9장 소 결핵 진단 시장 : 검체 유형별
제10장 소 결핵 진단 시장 : 기술별
제11장 소 결핵 진단 시장 : 최종 사용자별
제12장 소 결핵 진단 시장 : 지역별
제13장 소 결핵 진단 시장 : 그룹별
제14장 소 결핵 진단 시장 : 국가별
제15장 경쟁 구도
제16장 기업 개요
JHS 26.08.03The Bovine Tuberculosis Diagnosis Market is projected to grow by USD 1,748.16 million at a CAGR of 8.92% by 2032.
| KEY MARKET STATISTICS | |
|---|---|
| Base Year [2025] | USD 960.80 million |
| Estimated Year [2026] | USD 1,041.70 million |
| Forecast Year [2032] | USD 1,748.16 million |
| CAGR (%) | 8.92% |
Bovine tuberculosis diagnosis is a critical component of animal health surveillance, livestock biosecurity, public health protection, and international trade compliance. Caused primarily by Mycobacterium bovis, bovine tuberculosis affects cattle and can infect wildlife reservoirs and humans, making accurate detection essential within One Health frameworks. Diagnostic strategies typically combine field-based screening, laboratory confirmation, herd-level surveillance, abattoir inspection, and epidemiological tracing to identify infection, reduce transmission, and support disease control programs.
The diagnostic landscape includes traditional tuberculin skin testing, interferon-gamma release assays, culture, histopathology, molecular assays such as PCR, and whole-genome sequencing for outbreak investigation and strain characterization. Each method serves a distinct role: skin testing remains widely used for herd screening, laboratory culture provides confirmatory evidence despite long turnaround times, and molecular diagnostics support faster identification where infrastructure and validated protocols are available. Demand for reliable bovine TB testing is being shaped by stricter animal movement rules, food safety requirements, zoonotic disease awareness, and the need to protect dairy and beef supply chains from costly disease disruption.
Transformative Shifts in the Diagnostic Landscape
The bovine tuberculosis diagnosis landscape is undergoing a practical shift from single-test reliance toward integrated, risk-based diagnostic systems. Veterinary authorities and herd managers increasingly combine skin testing, ancillary blood-based assays, post-mortem inspection, and molecular confirmation to improve case detection while managing false positives and false negatives. This shift is especially important in regions where wildlife reservoirs, mixed farming systems, cross-border livestock movement, and variable herd biosecurity complicate eradication efforts.
Another major transformation is the movement toward faster, more traceable, and digitally connected surveillance. Laboratory information systems, electronic animal identification, geospatial mapping, and structured outbreak reporting are improving the ability to link diagnostic findings with animal movement histories and herd-level risk factors. Molecular epidemiology, including sequencing-based strain comparison, is also strengthening source tracing and helping authorities distinguish reintroduction from local persistence. At the same time, diagnostic adoption remains influenced by test validation standards, veterinary workforce capacity, sample transport quality, national compensation policies, and farmer participation in surveillance programs.
Cumulative Impact of Artificial Intelligence
Artificial intelligence is beginning to influence bovine tuberculosis diagnosis by improving how diagnostic, epidemiological, and surveillance data are interpreted. AI-enabled analytics can support risk scoring for herds, prioritize testing in high-risk zones, identify spatial clusters, and integrate data from animal movements, farm history, wildlife exposure, abattoir findings, and laboratory results. These applications are particularly relevant where veterinary services must allocate limited testing resources across large cattle populations and geographically dispersed farms.
AI also has potential to enhance laboratory and field workflows. Image analysis may support pathology review, automated pattern recognition can assist interpretation of large surveillance datasets, and predictive models can help evaluate the probability of infection under defined epidemiological conditions. However, the cumulative impact of AI depends on data quality, transparent model validation, interoperability with veterinary databases, and clear governance for decision support. In bovine TB control, AI should complement rather than replace validated diagnostic tests, official case definitions, and veterinary judgment.
Key Regional Insights
Asia-Pacific faces diverse bovine tuberculosis diagnosis needs, ranging from intensive dairy systems to smallholder and mixed-species farming environments. Countries with expanding dairy production and dense animal movement networks are emphasizing surveillance, laboratory capacity, and zoonotic disease monitoring, while wildlife-livestock interfaces and variable access to veterinary services influence diagnostic coverage. North America maintains structured bovine TB control programs supported by animal identification, herd testing, movement controls, abattoir surveillance, and laboratory confirmation, with particular attention to wildlife reservoirs and border-related livestock trade requirements.
Latin America's diagnostic priorities are closely connected to cattle production, dairy safety, export certification, and regional differences in veterinary infrastructure. Programs often rely on tuberculin testing and slaughterhouse inspection, with laboratory confirmation used to support control actions and epidemiological investigation. Europe has long-standing bovine TB surveillance and control frameworks, but diagnostic intensity varies by country depending on herd prevalence, wildlife reservoirs, and national eradication status. The region places strong emphasis on harmonized testing standards, movement regulation, and food chain safety under established animal health legislation.
The Middle East is strengthening animal health surveillance as livestock trade, dairy development, and food security strategies increase the importance of reliable bovine TB detection. Diagnostic implementation is shaped by import controls, veterinary laboratory readiness, and the need to monitor transboundary animal disease risks. Africa carries high One Health relevance for bovine tuberculosis diagnosis due to close contact between cattle, wildlife, and people in many settings, combined with variable access to laboratory diagnostics. Surveillance enhancement, field-applicable testing, veterinary workforce development, and integration with human TB awareness are central to improving detection across the region.
Key Group Insights
ASEAN countries present a highly varied bovine tuberculosis diagnosis environment, with intensive dairy operations, smallholder cattle systems, and cross-border animal movement creating a need for coordinated surveillance and practical field diagnostics. Regional priorities include strengthening veterinary laboratories, improving traceability, and aligning animal health monitoring with food safety and zoonotic disease prevention. The GCC's diagnostic focus is shaped by livestock import dependence, food security programs, and controlled dairy production systems, where quarantine testing, health certification, and laboratory-backed surveillance play important roles.
The European Union operates within a highly regulated animal health framework that supports harmonized testing, movement controls, eradication programs, and official disease status recognition. Diagnostic strategies are closely tied to veterinary legislation, trade rules, and risk-based surveillance. BRICS countries show wide differences in cattle population structure, veterinary infrastructure, and disease control maturity, but collectively emphasize the importance of scalable diagnostics, molecular confirmation, and surveillance systems that can support large and complex livestock sectors.
G7 countries generally maintain advanced veterinary surveillance capacity, laboratory networks, digital reporting systems, and structured bovine TB control policies, while continuing to address persistent challenges such as wildlife reservoirs, farm-level biosecurity gaps, and test performance limitations. NATO member countries overlap significantly with high-capacity veterinary systems in North America and Europe, where disease preparedness, biosecurity, and resilient food supply chains reinforce the importance of accurate bovine tuberculosis diagnosis within broader animal health security planning.
Key Country Insights
The United States and Canada maintain formal bovine tuberculosis surveillance systems using herd testing, slaughter surveillance, epidemiological investigation, and movement controls, with diagnostic attention focused on maintaining disease control status and managing wildlife-associated risks. Mexico's diagnostic landscape is strongly linked to cattle trade, regional control programs, and certification requirements, making reliable tuberculin testing, inspection, and laboratory confirmation essential. Brazil's large cattle sector creates a need for scalable disease surveillance, particularly in dairy and beef production areas where herd health and export confidence are priorities.
The United Kingdom has a high-profile bovine TB challenge, especially where cattle infection intersects with wildlife reservoirs, leading to intensive testing regimes, movement restrictions, and ongoing evaluation of diagnostic strategies. Germany and France operate under structured European animal health frameworks, with surveillance intensity shaped by official disease status, movement compliance, and veterinary monitoring. Russia's large geography and varied livestock systems require regionally adaptable bovine TB diagnostic approaches, while Italy and Spain maintain surveillance systems aligned with European regulatory requirements and national animal health programs.
China and India have significant relevance for bovine tuberculosis diagnosis due to large cattle and buffalo populations, expanding dairy demand, and One Health concerns related to zoonotic transmission. Diagnostic priorities include surveillance expansion, laboratory strengthening, and field-compatible testing pathways. Japan and South Korea emphasize regulated animal health systems, import safeguards, and high biosecurity standards, supporting structured testing and rapid response capability. Australia benefits from a strong animal health surveillance culture and biosecurity controls, with bovine TB diagnosis positioned as part of continued vigilance to protect livestock health, trade access, and public confidence.
Actionable Recommendations for Industry Leaders
Industry leaders should prioritize validated, fit-for-purpose diagnostic strategies that combine field screening with confirmatory laboratory methods. Test selection should account for herd risk, regulatory requirements, animal movement patterns, wildlife exposure, and the consequences of false diagnostic outcomes. Investment in sample logistics, laboratory quality management, proficiency testing, and standardized reporting can improve confidence in results and support timely disease control decisions.
Stakeholders should also strengthen data integration across farms, veterinary authorities, laboratories, abattoirs, and movement databases. Digital traceability and geospatial risk analysis can help identify infection pathways and optimize surveillance coverage. Partnerships between veterinary services, livestock producers, public health agencies, and wildlife authorities are essential where bovine TB persists across species boundaries. For organizations adopting AI or advanced analytics, leaders should ensure model transparency, independent validation, data governance, and alignment with official diagnostic protocols.
Research Methodology
This executive summary is developed using a secondary research approach grounded in verified animal health, veterinary diagnostics, and public health sources. The methodology emphasizes evidence from official veterinary authorities, intergovernmental animal health guidance, peer-reviewed scientific literature, national surveillance documentation, regulatory frameworks, and recognized One Health resources. Insights are synthesized to describe diagnostic practices, regional priorities, technology trends, and operational considerations without relying on market sizing, market estimation, market share, or forecasting.
The analysis focuses on the role of established and emerging diagnostic tools, including tuberculin skin testing, interferon-gamma assays, microbiological culture, molecular detection, pathology, sequencing, and digital surveillance. Regional and country-level interpretations are derived from documented disease control structures, livestock system characteristics, trade and biosecurity requirements, and known epidemiological factors such as wildlife reservoirs and cross-border animal movement. All conclusions are framed to support strategic understanding of bovine tuberculosis diagnosis rather than commercial volume prediction.
Conclusion
Bovine tuberculosis diagnosis remains central to animal health protection, zoonotic disease prevention, and resilient livestock production. The sector is moving toward integrated diagnostic ecosystems that combine field testing, laboratory confirmation, digital traceability, molecular epidemiology, and risk-based surveillance. While long-established tools such as tuberculin testing continue to play a major role, the growing use of molecular diagnostics, sequencing, data analytics, and AI-enabled decision support is improving the precision and responsiveness of control programs.
Future progress will depend on test validation, laboratory capacity, farmer engagement, wildlife-livestock management, and harmonized reporting across jurisdictions. Regions and countries with strong surveillance infrastructure are focusing on persistence, traceability, and rapid response, while emerging systems are prioritizing access, scalability, and One Health integration. For industry leaders, the most effective path forward is to strengthen diagnostic reliability, connect surveillance data, and align technology adoption with official veterinary standards and practical field realities.
Table of Contents
1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Definition
- 1.3. Market Segmentation & Coverage
- 1.4. Years Considered for the Study
- 1.5. Currency Considered for the Study
- 1.6. Language Considered for the Study
- 1.7. Key Stakeholders
2. Research Methodology
- 2.1. Introduction
- 2.2. Research Design
- 2.2.1. Primary Research
- 2.2.2. Secondary Research
- 2.3. Research Framework
- 2.3.1. Qualitative Analysis
- 2.3.2. Quantitative Analysis
- 2.4. Market Size Estimation
- 2.4.1. Top-Down Approach
- 2.4.2. Bottom-Up Approach
- 2.5. Data Triangulation
- 2.6. Research Outcomes
- 2.7. Research Assumptions
- 2.8. Research Limitations
3. Executive Summary
- 3.1. Introduction
- 3.2. CXO Perspective
- 3.3. Market Size & Growth Trends
- 3.4. New Revenue Opportunities
- 3.5. Next-Generation Business Models
- 3.6. Industry Roadmap
4. Market Overview
- 4.1. Introduction
- 4.2. Industry Ecosystem & Value Chain Analysis
- 4.2.1. Supply-Side Analysis
- 4.2.2. Demand-Side Analysis
- 4.2.3. Stakeholder Analysis
- 4.3. Market Dynamics
- 4.3.1. Key Drivers
- 4.3.2. Key Restraints
- 4.3.3. Key Opportunities
- 4.3.4. Key Challenges
- 4.4. Porter's Five Forces Analysis
- 4.5. PESTLE Analysis
- 4.6. Market Outlook
- 4.6.1. Near-Term Market Outlook (0-2 Years)
- 4.6.2. Medium-Term Market Outlook (3-5 Years)
- 4.6.3. Long-Term Market Outlook (5-10 Years)
- 4.7. Go-to-Market Strategy
5. Market Insights
- 5.1. Consumer Insights & End-User Perspective
- 5.2. Consumer Experience Benchmarking
- 5.3. Opportunity Mapping
- 5.4. Distribution Channel Analysis
- 5.5. Pricing Trend Analysis
- 5.6. Regulatory Compliance & Standards Framework
- 5.7. ESG & Sustainability Analysis
- 5.8. Disruption & Risk Scenarios
- 5.9. Return on Investment & Cost-Benefit Analysis
6. Cumulative Impact of Artificial Intelligence 2026
7. Bovine Tuberculosis Diagnosis Market, by Test Type
- 7.1. Introduction
- 7.2. Caudal Fold Test
- 7.2.1. Comparative Intradermal Cervical Test
- 7.2.2. Single Intradermal Cervical Test
- 7.3. Elisa
- 7.4. Gamma Interferon Assay
- 7.5. PCR
8. Bovine Tuberculosis Diagnosis Market, by Product
- 8.1. Introduction
- 8.2. Instruments
- 8.3. Kits
- 8.3.1. Caudal Fold Test Kits
- 8.3.2. Elisa Kits
- 8.3.3. Gamma Interferon Assay Kits
- 8.3.4. PCR Kits
- 8.4. Reagents
- 8.4.1. Antigens
- 8.4.2. Enzymes
- 8.4.3. Primers And Probes
9. Bovine Tuberculosis Diagnosis Market, by Sample Type
- 9.1. Introduction
- 9.2. Blood Samples
- 9.2.1. Whole Blood
- 9.2.2. Serum
- 9.2.3. Plasma
- 9.3. Milk Samples
- 9.4. Tissue And Lesion Samples
- 9.4.1. Lymph Node Tissue
- 9.4.2. Organ And Lesion Tissue
- 9.5. Respiratory And Swab Samples
- 9.5.1. Nasal Swabs
- 9.5.2. Bronchoalveolar Lavage Fluid
10. Bovine Tuberculosis Diagnosis Market, by Technology
- 10.1. Introduction
- 10.2. Immunodiagnostic Technology
- 10.3. Molecular Diagnostic Technology
- 10.4. Microbiological Technology
- 10.5. Automation Technology
11. Bovine Tuberculosis Diagnosis Market, by End User
- 11.1. Introduction
- 11.2. Diagnostic Laboratories
- 11.3. Government Agencies
- 11.4. Research Institutes
- 11.5. Veterinary Hospitals
12. Bovine Tuberculosis Diagnosis Market, by Region
- 12.1. Asia-Pacific
- 12.2. North America
- 12.3. Latin America
- 12.4. Europe
- 12.5. Middle East
- 12.6. Africa
13. Bovine Tuberculosis Diagnosis Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
14. Bovine Tuberculosis Diagnosis Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
15. Competitive Landscape
- 15.1. Market Share Analysis, 2025
- 15.2. FPNV Positioning Matrix, 2025
- 15.3. Market Concentration Analysis, 2025
- 15.3.1. Concentration Ratio (CR)
- 15.3.2. Herfindahl Hirschman Index (HHI)
- 15.4. Recent Developments & Impact Analysis, 2025
- 15.5. Product Portfolio Analysis, 2025
- 15.6. Benchmarking Analysis, 2025
16. Company Profiles
- 16.1. Abbott Laboratories
- 16.2. AdvaCare Pharma
- 16.3. Akonni Biosystems Inc
- 16.4. Bio-Rad Laboratories Inc
- 16.5. bioMerieux SA
- 16.6. Bionote Inc
- 16.7. Bruker Corporation
- 16.8. Creative Diagnostics
- 16.9. Enfer Group
- 16.10. Genedrive PLC
- 16.11. Hangzhou Frenovo Biotech Co Ltd
- 16.12. IDEXX Laboratories Inc
- 16.13. Innovative Diagnostics SAS
- 16.14. Lionex GmbH
- 16.15. Molbio Diagnostics Private Limited
- 16.16. Mylab Discovery Solutions Pvt Ltd
- 16.17. Neogen Corporation
- 16.18. PBD Biotech Ltd
- 16.19. QIAGEN NV
- 16.20. Randox Food Diagnostics
- 16.21. Ring Biotechnology Co Ltd
- 16.22. Sansure Biotech Inc
- 16.23. SD Biosensor Inc
- 16.24. Seegene Inc
- 16.25. Shenzhen Bioeasy Biotechnology Co Ltd
- 16.26. Thermo Fisher Scientific Inc
- 16.27. Vimian Group AB
- 16.28. Zoetis Inc
