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市場調查報告書
商品編碼
2024167

人工智慧害蟲檢測市場預測至2034年—按作物類型、組件、部署模式、技術、應用、最終用戶和地區分類的全球分析

AI Pest Detection Market Forecasts to 2034 - Global Analysis By Crop Type (Cereals, Fruits, Vegetables, and Cash Crops), Component, Deployment, Technology, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球 AI 害蟲偵測市場規模將達到 24 億美元，並在預測期內以 13.9% 的複合年成長率成長，到 2034 年將達到 68 億美元。

人工智慧病蟲害檢測技術結合了無人機搭載的頻譜相機、安裝在田間的物聯網感測器網路、衛星遙感探測和基於智慧型手機的影像識別應用程式，並運用深度學習電腦視覺模型，對農田病蟲害的爆發模式進行識別、分類、量化和繪製。這使得農民能夠採取更有針對性的作物保護措施，在確保有效作物保護效果的同時，減少農藥用量、降低投入成本並最大限度地減少對環境的影響。

減少農藥使用的相關法規

歐盟的「從農場到餐桌戰略」要求到2030年將農藥使用量減少50%，加之世界各地不同的農藥法規，使得農業生產者越來越迫切地需要遵守相關規定。這促使人們投資於人工智慧驅動的病蟲害檢測系統，以實現精準的病蟲害防治，從而取代傳統的按日曆進行統一噴灑的農藥施用方式（這種方式不考慮特定田塊在噴灑時的實際病蟲害水平）。

連接基礎設施方面的差異

開發中國家主要農業區農村寬頻和行動電話通訊基礎設施的差距，嚴重阻礙了雲端人工智慧病蟲害偵測系統的普及應用。這類系統依賴從田間感測器、無人機系統和智慧型手機成像設備到人工智慧分析平台的可靠數據傳輸。這限制了在地域遼闊、通訊覆蓋不足以支援即時人工智慧病蟲害監測系統運作的農業區域的市場滲透。

無人機偵察技術的整合

將人工智慧病蟲害檢測演算法與能夠一次飛行覆蓋數百公頃的自主農業無人機測繪平台結合，正在創造一個突破性的市場機會。這使得對整個田地病蟲害壓力進行全面測繪成為可能，其頻率和空間解析度遠超人工測繪，從而為農民提供基於無人機圖像人工智慧分析自動生成的、針對特定田塊的、可操作的作物保護方案，而無需農藝師的專業知識。

人工智慧模型準確性的局限性

人工智慧害蟲檢測模型在識別早期害蟲危害、區分需要不同防治策略的相似害蟲種類以及在不同的作物生長階段、光照條件和地理環境下保持可靠性方面存在局限性，導致假陽性和假陰性率較高。當人工智慧系統的建議與經驗豐富的農藝師的田間觀察結果相矛盾時，會削弱農民的信心，從而限制其在試點評估計畫之外的推廣應用。

新冠疫情的影響：

新冠疫情期間，作物保護顧問和農業推廣人員因疫情封鎖而減少了實地走訪農場的機會，這導致人們對無需現場檢查即可評估作物健康狀況的自主遠程病蟲害監測技術的興趣激增。疫情期間供應鏈中斷影響了農藥的供應，進一步推動了精準施藥效率的提升。後疫情時代，對數位農業的加速投資以及精密農業技術在商業化農業生產的廣泛應用，正推動人工智慧病蟲害檢測市場強勁成長。

在預測期內，經濟作物領域預計將佔據最大的市場佔有率。

在預測期內，經濟作物預計將佔據最大的市場佔有率。這主要是因為棉花、甘蔗、咖啡和特種作物每公頃的經濟價值很高。在這些作物中，病蟲害防治時機的精準度直接決定收成的品質和數量，而這些因素又直接影響農場的盈利。因此，投資人工智慧病蟲害檢測技術具有顯著的經濟意義，因為早期識別病蟲害並進行精準干預可以避免每公頃數千美元的產量損失。

預計在預測期內，硬體領域將呈現最高的複合年成長率。

在預測期內，硬體領域預計將呈現最高的成長率。這主要得益於人工智慧無人機田間調查系統、物聯網感測器網路和智慧相機陷阱等技術的快速普及。精密農業技術在商業化農業生產中的加速應用，以自動化感測器和無人機監測基礎設施取代人工病蟲害調查，擴大了作物健康監測的頻率和空間覆蓋範圍，從而顯著增加了硬體採購需求。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率。這主要歸功於美國大規模商業農業企業對精密農業技術的投資、農業科技（AgTech）人工智慧公司獲得的強勁創業投資投資、Taranis、Sentera 和 Prospera Technologies 等領先的人工智慧害蟲檢測平台開發商帶來的可觀國內收入，以及由於減少農藥使用的監管壓力而產生的推動精準害蟲管理技術應用的強大商業性動力。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率。這主要歸因於以下幾個因素：中國和印度擁有全球最大的農業用地面積，嚴重的病蟲害問題為人工智慧病蟲害檢測市場創造了巨大的機遇；亞太地區各國政府的精密農業投資計劃；在極飛（XAG）和大疆（DJI）等公司生態系統建設的推動下，中國無人機的快速推廣；

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  • 企業概況
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  • 區域細分
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧害蟲檢測市場：按作物類型分類

  • 穀類
  • 水果
  • 蔬菜
  • 經濟作物

第6章 全球人工智慧害蟲偵測市場：按組件分類

  • 硬體
  • 軟體
  • 服務

第7章：全球人工智慧害蟲偵測市場：依部署方式分類

  • 基於雲端的
  • 邊緣底座

第8章 全球人工智慧害蟲檢測市場：按技術分類

  • 電腦視覺
  • 機器學習模型
  • 影像識別系統
  • 無人機偵測
  • 基於感測器的檢測

第9章 全球人工智慧害蟲偵測市場：按應用分類

  • 作物監測
  • 害蟲識別
  • 疾病檢測
  • 產量最佳化

第10章 全球人工智慧害蟲偵測市場：按最終用戶分類

  • 農民
  • 農業技術公司
  • 政府機構

第11章 全球人工智慧害蟲偵測市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Bayer AG
  • Syngenta Group
  • Corteva Agriscience
  • BASF SE
  • Trimble Inc.
  • Deere & Company
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC
  • Taranis
  • CropX
  • Prospera Technologies
  • Plantix（PEAT）
  • AgEagle Aerial Systems
  • XAG Co., Ltd.
  • Sentera
  • Raven Industries
Product Code: SMRC35378

According to Stratistics MRC, the Global AI Pest Detection Market is accounted for $2.4 billion in 2026 and is expected to reach $6.8 billion by 2034 growing at a CAGR of 13.9 % during the forecast period. AI pest detection refers to artificial intelligence-powered precision agriculture systems that use drone-mounted multispectral cameras, field-deployed IoT sensor networks, satellite remote sensing, and smartphone-based image recognition applications combined with deep learning computer vision models to identify, classify, quantify, and map pest and disease infestation patterns across crop fields, enabling farmers to implement targeted site-specific crop protection interventions that reduce total pesticide applications, lower input costs, and minimize environmental impact while maintaining effective crop protection outcomes.

Market Dynamics:

Driver:

Pesticide Use Reduction Regulation

European Union Farm to Fork Strategy mandating 50 percent pesticide use reduction by 2030, combined with pesticide restriction regulations across multiple global jurisdictions creating compliance urgency for agricultural producers, is driving investment in AI pest detection systems that enable precision targeted pesticide application replacing conventional calendar-based blanket spraying programs that apply pesticides regardless of actual pest pressure levels present in specific field zones at treatment timing.

Restraint:

Connectivity Infrastructure Gaps

Rural broadband and cellular connectivity infrastructure gaps in major agricultural regions across developing economy markets create significant barriers to cloud-connected AI pest detection system deployment that depends on reliable data transmission from field sensors, drone systems, and smartphone capture devices to AI analysis platforms, limiting addressable market penetration in geographically large agricultural regions where connectivity coverage is insufficient for real-time AI pest monitoring system functionality.

Opportunity:

Drone-Based Scouting Integration

Integration of AI pest detection algorithms with autonomous agricultural drone scouting platforms capable of covering hundreds of hectares per flight is creating a transformative market opportunity enabling comprehensive field-wide pest pressure mapping at a frequency and spatial resolution impossible through manual scouting labor, providing farmers with actionable site-specific crop protection prescriptions generated automatically from drone imagery AI analysis without requiring agronomist interpretation expertise.

Threat:

AI Model Accuracy Limitations

AI pest detection model accuracy limitations in identifying early-stage pest infestations, distinguishing look-alike pest species requiring different management responses, and maintaining reliable performance across diverse crop developmental stages, lighting conditions, and geographic environments create false positive and false negative detection rates that generate farmer trust deficits limiting operational adoption beyond trial evaluation programs when AI system recommendations conflict with experienced agronomist field observations.

Covid-19 Impact:

COVID-19 reduced access of crop protection advisors and agricultural extension workers to farm fields during lockdown periods, creating urgent interest in autonomous remote pest monitoring technologies enabling crop health assessment without on-site scouting visits. Pandemic-era supply chain disruptions affecting pesticide availability amplified precision application efficiency motivation. Post-pandemic digital agriculture investment acceleration and precision farming technology adoption across commercial agricultural operations sustain strong AI pest detection market growth.

The cash crops segment is expected to be the largest during the forecast period

The cash crops segment is expected to account for the largest market share during the forecast period, due to high per-hectare economic value of cotton, sugarcane, coffee, and specialty crop production creating compelling economic justification for AI pest detection investment where early pest identification and precision intervention can prevent yield losses representing thousands of dollars per hectare in crops where pest management timing precision directly determines harvest quality and volume outcomes that determine farm profitability.

The hardware segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Hardware segment is predicted to witness the highest growth rate, driven by rapid deployment of AI-enabled drone scouting systems, field IoT sensor networks, and smart camera traps creating substantial hardware procurement demand as precision agriculture technology adoption accelerates across commercial farming operations that are replacing manual pest scouting labor with automated sensor and drone surveillance infrastructure providing higher frequency and broader spatial coverage for crop health monitoring.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to the United States hosting large-scale commercial farming operations investing in precision agriculture technologies, strong venture capital investment in agtech AI companies, leading AI pest detection platform developers including Taranis, Sentera, and Prospera Technologies generating substantial domestic revenue, and regulatory pesticide reduction pressure creating strong commercial motivation for precision pest management adoption.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to China and India representing the world's largest agricultural land areas with high pest pressure creating substantial AI detection market opportunity, government precision agriculture investment programs across Asia Pacific, rapidly growing drone agriculture adoption in China driven by XAG and DJI ecosystem development, and smallholder farmer digital extension platform adoption enabling AI pest detection at previously inaccessible smallholder farm scale.

Key players in the market

Some of the key players in AI Pest Detection Market include Bayer AG, Syngenta Group, Corteva Agriscience, BASF SE, Trimble Inc., Deere & Company, IBM Corporation, Microsoft Corporation, Google LLC, Taranis, CropX, Prospera Technologies, Plantix (PEAT), AgEagle Aerial Systems, XAG Co., Ltd., Sentera, and Raven Industries.

Key Developments:

In March 2026, Taranis launched an AI-powered autonomous crop scouting platform integrating high-resolution aerial imaging with real-time pest detection models identifying over 200 pest and disease conditions across major row crops.

In February 2026, XAG Co., Ltd. introduced a new agricultural AI drone system with integrated multispectral cameras and on-board pest detection AI providing real-time crop health mapping and variable rate pesticide application prescriptions.

In January 2026, Plantix (PEAT) expanded its smartphone-based AI crop disease detection platform to 15 new languages, enabling smallholder farmer pest identification access across Sub-Saharan African and Southeast Asian agricultural communities.

Crop Types Covered:

  • Cereals
  • Fruits
  • Vegetables
  • Cash Crops

Components Covered:

  • Hardware
  • Software
  • Services

Deployments Covered:

  • Cloud-Based
  • Edge-Based

Technologies Covered:

  • Computer Vision
  • Machine Learning Models
  • Image Recognition Systems
  • Drone-Based Detection
  • Sensor-Based Detection

Applications Covered:

  • Crop Monitoring
  • Pest Identification
  • Disease Detection
  • Yield Optimization

End Users Covered:

  • Farmers
  • Agritech Firms
  • Government Agencies

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Pest Detection Market, By Crop Type

  • 5.1 Cereals
  • 5.2 Fruits
  • 5.3 Vegetables
  • 5.4 Cash Crops

6 Global AI Pest Detection Market, By Component

  • 6.1 Hardware
  • 6.2 Software
  • 6.3 Services

7 Global AI Pest Detection Market, By Deployment

  • 7.1 Cloud-Based
  • 7.2 Edge-Based

8 Global AI Pest Detection Market, By Technology

  • 8.1 Computer Vision
  • 8.2 Machine Learning Models
  • 8.3 Image Recognition Systems
  • 8.4 Drone-Based Detection
  • 8.5 Sensor-Based Detection

9 Global AI Pest Detection Market, By Application

  • 9.1 Crop Monitoring
  • 9.2 Pest Identification
  • 9.3 Disease Detection
  • 9.4 Yield Optimization

10 Global AI Pest Detection Market, By End User

  • 10.1 Farmers
  • 10.2 Agritech Firms
  • 10.3 Government Agencies

11 Global AI Pest Detection Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Bayer AG
  • 14.2 Syngenta Group
  • 14.3 Corteva Agriscience
  • 14.4 BASF SE
  • 14.5 Trimble Inc.
  • 14.6 Deere & Company
  • 14.7 IBM Corporation
  • 14.8 Microsoft Corporation
  • 14.9 Google LLC
  • 14.10 Taranis
  • 14.11 CropX
  • 14.12 Prospera Technologies
  • 14.13 Plantix (PEAT)
  • 14.14 AgEagle Aerial Systems
  • 14.15 XAG Co., Ltd.
  • 14.16 Sentera
  • 14.17 Raven Industries

List of Tables

  • Table 1 Global AI Pest Detection Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Pest Detection Market Outlook, By Crop Type (2023-2034) ($MN)
  • Table 3 Global AI Pest Detection Market Outlook, By Cereals (2023-2034) ($MN)
  • Table 4 Global AI Pest Detection Market Outlook, By Fruits (2023-2034) ($MN)
  • Table 5 Global AI Pest Detection Market Outlook, By Vegetables (2023-2034) ($MN)
  • Table 6 Global AI Pest Detection Market Outlook, By Cash Crops (2023-2034) ($MN)
  • Table 7 Global AI Pest Detection Market Outlook, By Component (2023-2034) ($MN)
  • Table 8 Global AI Pest Detection Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 9 Global AI Pest Detection Market Outlook, By Software (2023-2034) ($MN)
  • Table 10 Global AI Pest Detection Market Outlook, By Services (2023-2034) ($MN)
  • Table 11 Global AI Pest Detection Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 12 Global AI Pest Detection Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 13 Global AI Pest Detection Market Outlook, By Edge-Based (2023-2034) ($MN)
  • Table 14 Global AI Pest Detection Market Outlook, By Technology (2023-2034) ($MN)
  • Table 15 Global AI Pest Detection Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 16 Global AI Pest Detection Market Outlook, By Machine Learning Models (2023-2034) ($MN)
  • Table 17 Global AI Pest Detection Market Outlook, By Image Recognition Systems (2023-2034) ($MN)
  • Table 18 Global AI Pest Detection Market Outlook, By Drone-Based Detection (2023-2034) ($MN)
  • Table 19 Global AI Pest Detection Market Outlook, By Sensor-Based Detection (2023-2034) ($MN)
  • Table 20 Global AI Pest Detection Market Outlook, By Application (2023-2034) ($MN)
  • Table 21 Global AI Pest Detection Market Outlook, By Crop Monitoring (2023-2034) ($MN)
  • Table 22 Global AI Pest Detection Market Outlook, By Pest Identification (2023-2034) ($MN)
  • Table 23 Global AI Pest Detection Market Outlook, By Disease Detection (2023-2034) ($MN)
  • Table 24 Global AI Pest Detection Market Outlook, By Yield Optimization (2023-2034) ($MN)
  • Table 25 Global AI Pest Detection Market Outlook, By End User (2023-2034) ($MN)
  • Table 26 Global AI Pest Detection Market Outlook, By Farmers (2023-2034) ($MN)
  • Table 27 Global AI Pest Detection Market Outlook, By Agritech Firms (2023-2034) ($MN)
  • Table 28 Global AI Pest Detection Market Outlook, By Government Agencies (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.