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농업 분석 시장 : 구성요소별, 농장 규모별, 전개별, 지역별(2026-2032년)

Agriculture Analytics Market By Component (Solutions, Services), Farm Size (Medium-Sized Farms, Small Farms), Deployment (Cloud-Based, On-Premise) & Region for 2026-2032

발행일: | 리서치사: Verified Market Research | 페이지 정보: 영문 202 Pages | 배송안내 : 2-3일 (영업일 기준)

    
    
    



※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

농업 분석 시장 평가(2026-2032년)

농업 생산성 및 효율성 향상을 위한 데이터 기반 솔루션에 대한 수요가 증가함에 따라 농업 분석 시장의 수요가 빠르게 증가하고 있습니다. 세계 인구 증가와 이에 따른 식량 공급 부족으로 농부들은 인공지능(AI), 머신러닝(ML), 사물인터넷(IoT)과 같은 첨단 기술을 활용하여 작물 수확량을 최적화하고, 자원을 효율적으로 관리하며, 운영 비용을 절감하고 있습니다. 시장 규모는 2024년 12억 3,000만 달러, 2032년에는 34억 6,000만 달러에 달할 것으로 예상됩니다.

이러한 분석 플랫폼은 날씨 패턴, 토양 건강, 해충 발생, 작물 성능에 대한 인사이트를 통해 더 나은 의사결정을 내릴 수 있게 하여 보다 스마트한 농업 기술과 지속가능한 농업 관행을 가능하게 합니다. 비용 효율적이고 효율적인 농업 분석에 대한 수요가 증가함에 따라 시장은 2026년부터 2032년까지 CAGR 15.17%로 성장할 것으로 예상됩니다.

농업 분석 시장 정의/개요

농업 분석은 농법, 생산성, 효율성을 개선하기 위해 데이터 분석 도구와 기술을 적용하는 것을 말합니다. 날씨 패턴, 토양 조건, 작물 수확량, 시장 동향 등 다양한 정보원으로부터 데이터를 수집하고 분석하는 것을 포함합니다. 인공지능(AI), 머신러닝(ML), 위성 이미지, 센서 등의 기술을 활용하여 농업 분석은 농부들이 작물 재배, 관개, 시비, 병충해 방제 등에 대한 정보에 입각한 의사결정을 내릴 수 있도록 돕습니다. 이러한 데이터 기반 접근 방식은 정밀농업을 가능하게 하고, 자원 활용을 최적화하고 낭비를 줄일 수 있도록 돕습니다.

농업 분석은 농업 산업이 디지털 전환을 계속 받아들이는 가운데, IoT(사물인터넷) 기기 및 드론의 도입이 증가함에 따라 실시간 모니터링 및 예측 분석이 전 세계 농부들에게 더욱 친숙해질 것으로 예상됩니다. 더욱 가까워질 것으로 보입니다. 이는 보다 지속가능한 농법, 더 높은 수확량, 더 나은 자원 관리로 이어질 것입니다. 세계 인구가 증가함에 따라 농업 분석은 식량 안보 문제를 해결하는 데 중요한 역할을 하게 될 것이며, 농부들이 환경에 미치는 영향을 최소화하면서 식량 생산량을 늘리는 데 도움을 줄 수 있습니다. 공급망의 투명성을 높이는 블록체인 기술과 첨단 데이터 분석 도구의 통합은 농업 부문의 효율성을 더욱 향상시킬 것으로 보입니다.

정밀농업 도입 증가로 농업 분석 시장이 활성화될까?

GPS 기반 토양 매핑의 사용은 2010년부터 2020년까지 미국 옥수수 농장의 20%에서 40%로 증가하여 데이터 기반 의사결정 도구에 대한 수요 증가를 강조하는 등 정밀농업의 채택 증가가 농업 분석 시장에 박차를 가하고 있습니다. 정밀농업 기술은 물, 비료, 농약 등의 투입을 최적화하고 생산성과 지속가능성을 높이기 위해 상세한 실시간 데이터에 의존하고 있습니다. 농부들이 효율성 향상과 비용 절감을 추구하면서 이 데이터를 처리하고 해석하는 고급 분석에 대한 요구가 농업 분석 시장의 성장을 촉진하고 있습니다.

세계 식량 수요의 증가는 농업 분석 시장의 활성화로 이어지고 있습니다. FAO에 따르면 2050년까지 식량 생산량은 60% 증가해야 하며, 이는 농부들과 농업 관련 기업들에게 엄청난 압력을 가할 것으로 예상됩니다. 이러한 수요에 대응하기 위해 농부들과 농업 관련 기업들은 작물 수확량 향상, 자원 관리 최적화, 데이터 기반 의사결정 등 지속가능한 식량 생산을 대규모로 수행하는 데 필수적인 농업 분석의 채택을 늘리고 있습니다.

데이터 품질과 가용성이 농업 분석 시장의 성장을 저해하는 요인은 무엇인가?

데이터 품질과 가용성은 농업 분석 시장의 성장을 저해하는 요인으로 작용할 수 있습니다. 일관성이 없거나 불완전한 데이터는 부정확한 인사이트으로 이어져 예측 분석, 의사결정 및 수확량 최적화의 효과를 제한하며, IoT, 위성 이미지 및 정밀농업 기술의 발전은 데이터 수집 능력을 강화하고 분석을 위한 보다 신뢰할 수 있고 종합적인 데이터를 확보함으로써 시장 성장을 촉진하고 있습니다. 시장 성장을 촉진하고 있습니다.

농업 분석 솔루션의 도입은 비용과 복잡성으로 인해 시장 성장에 걸림돌이 될 수 있습니다. 기술, 인프라, 숙련된 인력에 대한 높은 초기 투자 비용과 다양한 데이터 소스를 통합하는 복잡성이 소규모 농장과 이해관계자들의 발목을 잡을 수 있습니다. 그러나 클라우드 기반 솔루션과 정부 이니셔티브의 발전과 함께 농업의 디지털 혁신이 가속화되면서 비용 절감과 도입 간소화를 통해 시장 성장을 촉진하고 있습니다.

목차

제1장 농업 분석 세계 시장 소개

  • 시장 개요
  • 조사 범위
  • 가정

제2장 주요 요약

제3장 VERIFIED MARKET RESEARCH 조사 방법

  • 데이터 마이닝
  • 검증
  • 1차 자료
  • 데이터 소스 리스트

제4장 농업 분석 세계 시장 전망

  • 개요
  • 시장 역학
    • 성장 촉진요인
    • 성장 억제요인
    • 기회
  • Porter's Five Forces 모델
  • 밸류체인 분석

제5장 농업 분석 세계 시장, 전개별

  • 개요
  • 클라우드
  • 온프레미스

제6장 농업 분석 세계 시장 : 구성요소별

  • 개요
  • 솔루션
  • 서비스

제7장 농업 분석 세계 시장 : 농장 규모별

  • 개요
  • 중규모 농장
  • 소규모 농장

제8장 농업 분석 세계 시장 : 지역별

  • 개요
  • 북미
    • 미국
    • 캐나다
    • 멕시코
  • 유럽
    • 독일
    • 영국
    • 프랑스
    • 기타 유럽
  • 아시아태평양
    • 중국
    • 일본
    • 인도
    • 기타 아시아태평양
  • 세계 기타 지역
    • 라틴아메리카
    • 중동 및 아프리카

제9장 농업 분석 세계 시장 경쟁 구도

  • 개요
  • 각사의 시장 순위
  • 주요 발전 전략

제10장 기업 개요

  • IBM
  • SAP SE
  • Deere & Company
  • Oracle
  • Trimble
  • Accenture

제11장 부록

  • 관련 조사
ksm 25.06.10

Agriculture Analytics Market Valuation - 2026-2032

The demand for the agriculture analytics market is rising rapidly due to the growing need for data-driven solutions to enhance farm productivity and efficiency. With increasing global population and the subsequent pressure on food supply, farmers are turning to advanced technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to optimize crop yields, manage resources efficiently, and reduce operational costs. The market size surpass USD 1.23 Billion valued in 2024 to reach a valuation of around USD 3.46 Billion by 2032.

These analytics platforms enable better decision-making through insights into weather patterns, soil health, pest infestations, and crop performance, resulting in smarter farming techniques and sustainable agricultural practices. The rising demand for cost-effective and efficient agriculture analytics is enabling the market grow at a CAGR of 15.17% from 2026 to 2032.

Agriculture Analytics Market: Definition/ Overview

Agriculture analytics refers to the application of data analysis tools and techniques to improve farming practices, productivity, and efficiency. It involves gathering and analyzing data from various sources such as weather patterns, soil conditions, crop yields, and market trends. By using technologies like artificial intelligence (AI), machine learning (ML), satellite imagery, and sensors, agriculture analytics helps farmers make informed decisions about planting, irrigation, fertilization, and pest control. This data-driven approach allows for precision farming, optimizing the use of resources and reducing waste.

Agriculture analytics is vast as the agricultural industry continues to embrace digital transformation. With the increasing adoption of IoT (Internet of Things) devices and drones, real-time monitoring and predictive analytics will become more accessible to farmers globally. This will lead to more sustainable farming practices, higher yields, and better resource management. As the global population grows, agriculture analytics will play a critical role in addressing food security challenges, helping farmers meet the demand for increased food production while minimizing environmental impacts. The integration of blockchain technology for supply chain transparency and advanced data analytics tools will further enhance the efficiency of the agricultural sector.

Will the Increasing Adoption of Precision Agriculture Fuel the Agriculture Analytics Market?

The increasing adoption of precision agriculture is fueling the agriculture analytics market. The use of GPS-based soil mapping, which grew from 20% to 40% of U.S. corn farms between 2010 and 2020, highlights the rising demand for data-driven decision-making tools. Precision agriculture techniques rely on detailed, real-time data to optimize inputs like water, fertilizer, and pesticides, enhancing productivity and sustainability. As farmers seek to improve efficiency and reduce costs, the need for advanced analytics to process and interpret this data is driving the growth of the agriculture analytics market.

Rising global food demand is fueling the agriculture analytics market. As the global population grows, the need to boost agricultural productivity becomes critical. According to the FAO, food production must increase by 60% by 2050, placing immense pressure on farmers and agribusinesses. To meet this demand, they are increasingly adopting agriculture analytics to enhance crop yields, optimize resource management, and make data-driven decisions, all of which are essential for sustainable food production at scale.

Will the Data Quality and Availability Hamper the Growth of the Agriculture Analytics Market?

Data quality and availability can hamper the growth of the agriculture analytics market. Inconsistent or incomplete data can lead to inaccurate insights, limiting the effectiveness of predictive analytics, decision-making, and yield optimization. Improvements in IoT, satellite imagery, and precision farming technologies are driving market growth by enhancing data collection capabilities and ensuring more reliable and comprehensive data for analysis.

The cost and complexity of implementing agriculture analytics solutions can hamper market growth. High initial investments in technology, infrastructure, and skilled personnel, along with the complexity of integrating diverse data sources, may deter smaller farms and stakeholders. However, the push for digital transformation in agriculture, along with advancements in cloud-based solutions and government initiatives, is driving market growth by reducing costs and simplifying adoption.

Category-Wise Acumens

Will the Increased Efficiency and Productivity Propel the Solutions Segment for the Agriculture Analytics Market?

The solutions segment is dominating the agriculture analytics market. Increased efficiency and productivity are expected to propel the solutions segment in the agriculture analytics market. As farms adopt advanced analytics tools, they can optimize resource use, improve crop yields, and reduce operational costs. This demand for data-driven solutions is driven by the need to manage large-scale farming operations more efficiently, address climate variability, and meet the growing food demand. Solutions that provide actionable insights allow farmers to make informed decisions, enhancing overall productivity and sustainability.

Cost-effectiveness is likely to propel the solutions segment in the agriculture analytics market. This is because advanced analytics solutions help farmers optimize resources, reduce waste, and enhance productivity, all while lowering operational costs. As agricultural operations become more data-driven, affordable and efficient solutions are increasingly attractive, especially for small and mid-sized farms that need to balance performance with budget constraints.

Will the Balance of Scale and Adaptability Promote the Medium-Sized Farms Segment for the Agriculture Analytics Market?

The medium-Sized farms segment is dominating in the agriculture analytics market. The balance of scale and adaptability will likely promote the medium-sized farms segment in the agriculture analytics market. Medium-sized farms offer a unique advantage by having enough scale to benefit from advanced analytics while maintaining the flexibility to quickly implement and adapt new technologies. This balance enables them to optimize production, reduce costs, and respond to changing market conditions more effectively than larger, less nimble operations or smaller farms with fewer resources. As a result, medium-sized farms are well-positioned to benefit from agriculture analytics, driving growth in this segment.

Receptiveness to innovation will likely promote the medium-sized farms segment in the agriculture analytics market. Medium-sized farms are more agile than large-scale operations and have greater capacity than small farms to invest in new technologies. Their willingness to adopt innovative analytics tools allows them to optimize yields, manage resources efficiently, and stay competitive, driving growth in this segment.

Country/Region-wise Acumens

Will the Rapid Adoption of Precision Agriculture Technologies Accelerate the North American Region for Agriculture Analytics Market?

North America's dominance in the agriculture analytics market. The rapid adoption of precision agriculture technologies is accelerating the agriculture analytics market in North America. According to the USDA, adoption of these technologies in the U.S. has surged from 30% in 2010 to over 70% in 2023, with further growth expected. This widespread adoption is driving market expansion by enabling farmers to gather more accurate data, improve resource management, and optimize crop yields, making analytics tools more essential for modern farming practices.

Increasing concerns about food security and sustainable farming practices are accelerating the agriculture analytics market in North America. The FAO projects that global food production needs to rise by 70% by 2050, putting pressure on North American farmers to optimize their operations. This demand for greater efficiency and sustainability is driving the adoption of data-driven agricultural solutions, helping farmers maximize yields while minimizing resource use, thus fueling the growth of agriculture analytics in the region.

Will the Government Initiatives Escalate the Asia Pacific Region for the Agriculture Analytics Market?

Asia Pacific is rapidly growing in the agriculture analytics market due to several factors. Government initiatives are significantly driving the growth of the agriculture analytics market in the Asia Pacific region. For instance, India's Digital Agriculture Mission aims to integrate digital technologies into farming, targeting 100 million farmers by 2025. By 2023, over 50 million farmers have already benefited from such initiatives, demonstrating the potential for widespread adoption and the expansion of agriculture analytics across the region.

Climate change is accelerating the growth of the agriculture analytics market in the Asia Pacific region. A study published in Nature Climate Change predicts a potential 20% decrease in crop yields in Southeast Asia by 2050, driving the need for predictive analytics to manage risks. This urgency for data-driven strategies is pushing farmers and governments to adopt advanced analytics for climate adaptation and crop management.

Competitive Landscape

The agriculture analytics market is a dynamic and competitive space, characterized by a diverse range of players vying for market share. These players are on the run for solidifying their presence through the adoption of strategic plans such as collaborations, mergers, acquisitions, and political support.

The organizations are focusing on innovating their product line to serve the vast population in diverse regions. Some of the prominent players operating in the agriculture analytics market include:

  • IBM
  • SAP SE
  • Deere & Company
  • Oracle
  • Trimble
  • Accenture
  • Monsanto
  • Taranis
  • Agrivi

Latest Developments

  • In January 2023 Nutrien Ag Solutions announced their partnership with John Deere who are global farm equipment providers. This will help in optimizing logistics of both companies toward serving growers better as expected of them.
  • In October 2022, AGDATA was purchased by Levine Leichtman Capital, thus enabling it to offer workflow solutions together with data within the agribusiness and animal health sectors.

Agriculture Analytics Market, By Category

  • Component:
  • Solutions
  • Services
  • Farm Size:
  • Medium-Sized Farms
  • Small Farms
  • Deployment:
  • Cloud-Based
  • On-Premise
  • Region:
  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East & Africa

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL AGRICULTURE ANALYTICS MARKET

  • 1.1 Overview of the Market
  • 1.2 Scope of Report
  • 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

  • 3.1 Data Mining
  • 3.2 Validation
  • 3.3 Primary Interviews
  • 3.4 List of Data Sources

4 GLOBAL AGRICULTURE ANALYTICS MARKET OUTLOOK

  • 4.1 Overview
  • 4.2 Market Dynamics
    • 4.2.1 Drivers
    • 4.2.2 Restraints
    • 4.2.3 Opportunities
  • 4.3 Porters Five Force Model
  • 4.4 Value Chain Analysis

5 GLOBAL AGRICULTURE ANALYTICS MARKET, BY DEPLOYMENT TYPE

  • 5.1 Overview
  • 5.2 Cloud
  • 5.3 On-Premises

6 GLOBAL AGRICULTURE ANALYTICS MARKET, BY COMPONENT

  • 6.1 Overview
  • 6.2 Solution
  • 6.3 Services

7 GLOBAL AGRICULTURE ANALYTICS MARKET, BY FARM SIZE

  • 7.1 Overview
  • 7.2 Medium-Sized Farms
  • 7.3 Small Farms

8 GLOBAL AGRICULTURE ANALYTICS MARKET, BY GEOGRAPHY

  • 8.1 Overview
  • 8.2 North America
    • 8.2.1 U.S.
    • 8.2.2 Canada
    • 8.2.3 Mexico
  • 8.3 Europe
    • 8.3.1 Germany
    • 8.3.2 U.K.
    • 8.3.3 France
    • 8.3.4 Rest of Europe
  • 8.4 Asia Pacific
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 India
    • 8.4.4 Rest of Asia Pacific
  • 8.5 Rest of the World
    • 8.5.1 Latin America
    • 8.5.2 Middle East & Africa

9 GLOBAL AGRICULTURE ANALYTICS MARKET COMPETITIVE LANDSCAPE

  • 9.1 Overview
  • 9.2 Company Market Ranking
  • 9.3 Key Development Strategies

10 COMPANY PROFILES

  • 10.1 IBM
    • 10.1.1 Overview
    • 10.1.2 Financial Performance
    • 10.1.3 Product Outlook
    • 10.1.4 Key Developments
  • 10.2 SAP SE
    • 10.2.1 Overview
    • 10.2.2 Financial Performance
    • 10.2.3 Product Outlook
    • 10.2.4 Key Developments
  • 10.3 Deere & Company
    • 10.3.1 Overview
    • 10.3.2 Financial Performance
    • 10.3.3 Product Outlook
    • 10.3.4 Key Developments
  • 10.4 Oracle
    • 10.4.1 Overview
    • 10.4.2 Financial Performance
    • 10.4.3 Product Outlook
    • 10.4.4 Key Developments
  • 10.5 Trimble
    • 10.5.1 Overview
    • 10.5.2 Financial Performance
    • 10.5.3 Product Outlook
    • 10.5.4 Key Developments
  • 10.6 Accenture
    • 10.6.1 Overview
    • 10.6.2 Financial Performance
    • 10.6.3 Product Outlook
    • 10.6.4 Key Developments

11 Appendix

  • 11.1 Related Research
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