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市场调查报告书
商品编码
1535865

农业分析市场 - 按产品（软体、服务）、按农场规模（中小型农场、大型农场）、按应用（畜牧业、水产养殖、精准农业、传统农业）、按技术和预测，2024 - 2032

Agriculture Analytics Market - By Offering (Software, Services), By Farm Size (Small & Medium Farms, Large Farms), By Application (Livestock Farming, Aquaculture Farming, Precision Farming, Conventional Farming), By Technology & Forecast, 2024 - 2032
出版日期: | 出版商: Global Market Insights Inc. | 英文 240 Pages | 商品交期: 2-3个工作天内

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简介目录

由于人工智慧 (AI)、机器学习和巨量资料分析等先进技术在农业领域的采用，农业分析市场预计在 2024 年至 2032 年期间将呈现 10% 的复合年增长率。这些技术为农民提供了有关作物健康、土壤条件和天气的见解，从而实现数据驱动的决策。在这些技术的推动下，精准农业可以优化资源利用、提高产量并减少对环境的影响。无人机和物联网感测器等智慧农业工具进一步增强资料收集和分析，改善农业实践和生产力。

全球对粮食安全和永续农业的需求正在推动市场成长。根据联合国的估计，到 2050 年，世界人口预计将达到 97 亿。 农业分析有助于管理资源和优化作物，提高生产力，同时最大限度地减少浪费和环境危害。政府对农业技术的措施和投资也促进了分析技术的采用。例如，2024 年4 月，美国农业部宣布在2024 财年历史性地投资15 亿美元，透过区域保护伙伴计画(RCPP) 支持合作伙伴驱动的保育和气候解决方案，与拜登总统的投资美国倡议保持一致。这些努力旨在加强粮食安全并应对气候变迁和资源短缺的挑战。

整个农业分析产业根据产品、农场规模、应用、技术和地区进行分类。

由于精准农业应用能够彻底改变传统农业实践，因此到 2032 年，精准农业应用将实现强劲成长。透过利用卫星影像、GPS 和物联网感测器等各种来源的资料，精准农业使农民能够根据具体的田间条件实施有针对性的干预措施。这种方法提高了资源利用效率，优化了作物管理，并最大限度地提高了产量，同时最大限度地减少了对环境的影响。精准农业解决方案有助于即时监测土壤健康、天气模式和作物发育，从而可以精确调整灌溉、施肥和病虫害防治。将先进分析技术融入精准农业不仅可以提高生产力，还可以透过减少浪费和改善整体农场管理来支持永续农业实践。

到 2032 年，供应链分析领域将占据显着的市场份额，因为它可以更有效地解决管理农业供应链的复杂性。透过利用先进的资料分析和预测模型，利害关係人能够深入了解供应链的每个阶段，从生产和加工到分销和零售。这种增强的可视性有助于优化物流、降低成本并提高需求预测的准确性。透过整合天气状况、市场趋势和运输物流等各种来源的资料，供应链分析技术可以增强决策、降低风险并确保生鲜农产品的及时交付。

在该地区重要的农业基础和不断增加的技术投资的推动下，亚太地区农业分析产业将在 2032 年实现快速扩张。人工智慧、机器学习和物联网等先进技术在农业中的采用正在帮助农民优化作物产量、更有效地管理资源并改善供应链管理。此外，政府对数位农业创新的措施和支持正在促进市场成长。随着亚太国家寻求农业实践现代化，以满足人口增长和气候条件变化的需求，市场参与者将发现利润丰厚的成长机会。

目录

第 1 章：方法与范围

第 2 章：执行摘要

第 3 章：产业洞察

  • 产业生态系统分析
  • 供应商格局
    • 软体供应商
    • 服务商
    • 技术提供者
    • 终端用户
  • 利润率分析
  • 技术与创新格局
  • 专利分析
  • 重要新闻和倡议
  • 监管环境
  • 衝击力
    • 成长动力
      • 网路安全事件增多
      • 严格的监管合规性，严格的资料保护
      • 越来越多采用数位平台
      • 品牌声誉问题日益严重
      • 人工智慧和机器学习的日益普及
    • 产业陷阱与挑战
      • 监理合规的复杂性
  • 成长潜力分析
  • 波特的分析
  • PESTEL分析

第 4 章：竞争格局

  • 介绍
  • 公司市占率分析
  • 竞争定位矩阵
  • 战略展望矩阵

第 5 章：市场估计与预测：依产品分类，2021 - 2032 年

  • 主要趋势
  • 软体
  • 服务
    • 专业的
    • 託管

第 6 章：市场估计与预测：依农场规模，2021 - 2032

  • 主要趋势
  • 大型农场
  • 中小型农场

第 7 章：市场估计与预测：依应用分类，2021 - 2032

  • 主要趋势
  • 畜牧业
  • 水产养殖
  • 精准农业
  • 传统农业
  • 其他的

第 8 章：市场估计与预测：依技术分类，2021 - 2032

  • 主要趋势
  • 牲畜分析
    • 产量图
    • 现场监控
    • 天气追踪
    • 其他的
  • 供应链分析
  • 农场分析
  • 其他的

第 9 章：市场估计与预测：按地区，2021 - 2032

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 欧洲其他地区
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳新银行
    • 东南亚
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
    • 拉丁美洲其他地区
  • MEA
    • 阿联酋
    • 南非
    • 沙乌地阿拉伯
    • MEA 的其余部分

第 10 章：公司简介

  • Accenture
  • AGCO Corporation
  • Bayer
  • Corteva Agriscience
  • Deere and Co.
  • DeLaval
  • Geosis, Inc.
  • IBM
  • Oracle
  • PrecisionHawk
  • SAP SE
  • Taranis
  • Trimble
  • Wipro
  • Xylem, Inc.
简介目录
Product Code: 9930

The agriculture analytics market is projected to exhibit 10% CAGR over 2024-2032, due to the adoption of advanced technologies like artificial intelligence (AI), machine learning, and big data analytics in agriculture sector. These technologies provide farmers with insights into crop health, soil conditions, and weather, enabling data-driven decisions. Precision agriculture, driven by these technologies, optimizes resource use, increasing yields and reducing environmental impact. Smart farming tools, such as drones and IoT sensors, further enhance data collection and analysis, improving farming practices and productivity.

The global demand for food security and sustainable agriculture are augmenting the market growth. As per the UN estimates, the world population is projected to reach 9.7 billion by 2050. Agriculture analytics help manage resources and optimize crops, boosting productivity while minimizing waste and environmental harm. Government initiatives and investments in agricultural technology are also promoting analytics adoption. For instance, in April 2024, The USDA announced a historic $1.5 billion investment in fiscal year 2024 to support partner-driven conservation and climate solutions through the Regional Conservation Partnership Program (RCPP), aligning with President Biden's Investing in America initiative. These efforts aim to enhance food security and address climate change and resource scarcity challenges.

The overall agriculture analytics industry is classified based on offering, farm size, application, technology, and region.

The precision farming application is set to experience robust growth through 2032, due to its ability to revolutionize traditional farming practices. By leveraging data from various sources such as satellite imagery, GPS, and IoT sensors, precision farming enables farmers to implement targeted interventions tailored to specific field conditions. This approach enhances the efficiency of resource use, optimizes crop management, and maximizes yields while minimizing environmental impact. Precision farming solutions facilitate real-time monitoring of soil health, weather patterns, and crop development, allowing for precise adjustments in irrigation, fertilization, and pest control. The integration of advanced analytics into precision farming not only boosts productivity but also supports sustainable agricultural practices by reducing waste and improving overall farm management.

The supply chain analytics segment will hold a notable market share by 2032, as it addresses the complexities of managing agricultural supply chains more effectively. By utilizing advanced data analytics and predictive modeling, it enables stakeholders to gain deep insights into every stage of the supply chain, from production and processing to distribution and retail. This enhanced visibility helps optimize logistics, reduce costs, and improve the accuracy of demand forecasting. By integrating data from various sources, such as weather conditions, market trends, and transportation logistics, supply chain analytics technology enhances decision-making, mitigates risks, and ensures the timely delivery of fresh produce.

Asia Pacific agriculture analytics industry will record rapid expansion through 2032, driven by the region's significant agricultural base and increasing investments in technology. The adoption of advanced technologies such as AI, machine learning, and IoT in agriculture is helping farmers optimize crop yields, manage resources more efficiently, and improve supply chain management. Additionally, government initiatives and support for digital agriculture innovations are bolstering market growth. As Asia-Pacific countries seek to modernize their agricultural practices to meet the demands of a growing population and changing climate conditions, the market players will find lucrative opportunities for growth.

Table of Contents

Chapter 1 Methodology & Scope

  • 1.1 Market scope & definition
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Base estimates & calculations
    • 1.3.1 Base year calculation
    • 1.3.2 Key trends for market estimation
  • 1.4 Forecast model
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
    • 1.5.2 Data mining sources

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Supplier landscape
    • 3.2.1 Software providers
    • 3.2.2 Service provider
    • 3.2.3 Technology providers
    • 3.2.4 End-user
  • 3.3 Profit margin analysis
  • 3.4 Technology & innovation landscape
  • 3.5 Patent analysis
  • 3.6 Key news & initiatives
  • 3.7 Regulatory landscape
  • 3.8 Impact forces
    • 3.8.1 Growth drivers
      • 3.8.1.1 Increasing cyber security incidents
      • 3.8.1.2 Stringent regulatory compliance for strict data protection
      • 3.8.1.3 Growing adoption of digital platforms
      • 3.8.1.4 Increasing brand reputation concerns
      • 3.8.1.5 Growing adoption of artificial intelligence and machine learning
    • 3.8.2 Industry pitfalls & challenges
      • 3.8.2.1 Complexity of regulatory compliance
  • 3.9 Growth potential analysis
  • 3.10 Porter's analysis
  • 3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

  • 4.1 Introduction
  • 4.2 Company market share analysis
  • 4.3 Competitive positioning matrix
  • 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Offering, 2021 - 2032 ($Bn)

  • 5.1 Key trends
  • 5.2 Software
  • 5.3 Services
    • 5.3.1 Professional
    • 5.3.2 Managed

Chapter 6 Market Estimates & Forecast, By farm size, 2021 - 2032 ($Bn)

  • 6.1 Key trends
  • 6.2 Large farms
  • 6.3 Small and medium farms

Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)

  • 7.1 Key trends
  • 7.2 Livestock farming
  • 7.3 Aquaculture farming
  • 7.4 Precision farming
  • 7.5 Conventional farming
  • 7.6 Others

Chapter 8 Market Estimates & Forecast, By Technology, 2021 - 2032 ($Bn)

  • 8.1 Key trends
  • 8.2 Livestock analytics
    • 8.2.1 Yield mapping
    • 8.2.2 Field monitoring
    • 8.2.3 Weather tracking
    • 8.2.4 Others
  • 8.3 Supply chain analytics
  • 8.4 Farm analytics
  • 8.5 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 ($Bn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 UK
    • 9.3.2 Germany
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Russia
    • 9.3.7 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 South Korea
    • 9.4.5 ANZ
    • 9.4.6 Southeast Asia
    • 9.4.7 Rest of Asia Pacific
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
    • 9.5.4 Rest of Latin America
  • 9.6 MEA
    • 9.6.1 UAE
    • 9.6.2 South Africa
    • 9.6.3 Saudi Arabia
    • 9.6.4 Rest of MEA

Chapter 10 Company Profiles

  • 10.1 Accenture
  • 10.2 AGCO Corporation
  • 10.3 Bayer
  • 10.4 Corteva Agriscience
  • 10.5 Deere and Co.
  • 10.6 DeLaval
  • 10.7 Geosis, Inc.
  • 10.8 IBM
  • 10.9 Oracle
  • 10.10 PrecisionHawk
  • 10.11 SAP SE
  • 10.12 Taranis
  • 10.13 Trimble
  • 10.14 Wipro
  • 10.15 Xylem, Inc.