歐洲智慧收穫市場：依產品、應用、國家：分析與預測（2023-2028）

2023年歐洲智慧收穫市場規模（不包括英國）為11.217億美元。

該市場預計到 2028 年將達到 18.644 億美元，2023-2028 年預測期間年複合成長率為 10.7%。這種擴張主要是由於農業產業越來越注重提高作物產量，同時降低投入成本。智慧收割系統提供精確、集中的生產管理方法、改良的收割應用和高效率的收割。這些技術將使農民能夠做出資料驅動的決策、提高營運效率、減少資源浪費並減少環境影響，從而在未來幾年幫助世界實現智慧收穫，預計將推動市場成長。

智慧收穫是一種尖端農業技術解決方案，有潛力改變農業企業。在糧食生產需求不斷成長的背景下，這項新策略為農業領域的所有公司帶來了顯著的效益。智慧收穫系統使用先進的感測器、資料分析和自動化來改善作物管理和收穫結果。這使農民能夠做出明智的決策，準確監測作物健康狀況，並更有效地管理水和肥料等資源。其結果是提高了生產力和盈利，並減少了廢棄物和對環境的影響。

Smart Harvest 讓您能夠透過提供即時資料洞察來應對不斷變化的天氣條件、市場需求和資源可用性。該技術可實現永續和穩健的作物生產，最終確保客戶的收益，無論他們是小規模經營還是大型農業組織。將智慧收割納入您的農業公司不僅可以提高營運效率，還可以使您成為創新且對環境負責的行業領導者。

市場擴張受到各種重要因素的影響。其中包括全球糧食需求增加、水資源和耕地減少、農業勞動力短缺以及收穫勞動成本等農業投入成本上升。這些原因預計將推動整個農業部門更多地使用智慧收割技術。這些最尖端科技使農民能夠改善資源配置，提高作物產量，最終提高農業生產力。

本報告考察了歐洲智慧收穫市場，並提供了市場概述、按產品、應用、國家/地區分類的趨勢以及參與市場的公司概況。

目錄

調查範圍

執行摘要

第1章 市場

• 產業展望
• 業務動態
• 案例研究
• Start-Ups狀況
• 市場主要產品架構/技術對比

第2章 區域

• 歐洲
  • 德國
  • 法國
  • 荷蘭
  • 義大利
  • 烏克蘭
  • 比利時
  • 瑞士
  • 希臘
  • 西班牙
  • 其他
• 英國

第3章市場：基準化分析與公司概況

• 競爭基準化分析
  • 機器人收割機公司
  • 自走式智慧收割機企業
  • 機器人收割機廠商市場佔有率分析
  • 自走式智慧收割機廠商市場佔有率分析
• 公司簡介
  • Agrobot
  • Antobot Ltd.
  • AMB Rousset
  • CNH Industrial NV

第4章調查方法

Introduction to Europe Smart Harvest Market

The Europe smart harvest market (excluding U.K.) was valued at $1,121.7 million in 2023 and is anticipated to reach $1,864.4 million by 2028, witnessing a CAGR of 10.7% during the forecast period 2023-2028. This expansion is mostly driven by the agriculture industry's growing emphasis on increasing crop yields while lowering input costs. Smart harvesting systems provide accurate and focused approaches to production management, improved harvesting application, and efficient harvesting. These technologies are anticipated to fuel the growth of the worldwide smart harvest market in the next years by enabling farmers to make data-driven decisions, improve operational efficiency, decrease resource waste, and limit environmental impact.

Market Introduction

Smart harvest is a cutting-edge agricultural technology solution that has the potential to transform the farming business. This new strategy offers significant benefits to enterprises throughout the agricultural spectrum in a world where food production demands are increasing. A smart harvest system uses advanced sensors, data analytics, and automation to improve crop management and yield outcomes. It enables farmers to make informed decisions, precisely monitor crop health, and manage resources like water and fertilizer more efficiently. As a result, productivity and profitability grow while waste and environmental impact decrease.

Smart harvest enables organizations to react to changing weather conditions, market demands, and resource availability by providing real-time data insights. This technology enables sustainable and robust crop production, eventually securing the customer's bottom line, whether the customer is a small-scale operator or a major agricultural organization. Incorporating smart harvest into the customer's agricultural company not only improves operational efficiency, but it also positions the customer as an innovative and environmentally conscious industry leader.

A variety of key elements influence the market's expansion. These include the growing global food demand, the decreasing availability of water resources and arable land, the shortage of agricultural labor, and the rising trend in agricultural input costs such as harvesting labor expenses. These reasons are expected to stimulate increased use of smart harvest technology in the agriculture sector as a whole. These cutting-edge technologies enable farmers to improve resource allocation, increase crop production, and ultimately increase agricultural productivity.

Market Segmentation:

Segmentation 1: by Site of Operation

• On-Field
• Controlled Environment

Segmentation 2: by Product

• Robotic Harvester
• Self-Propelled Smart Harvester
• Others

Segmentation 3: by Country

• Germany
• France
• Italy
• Spain
• The Netherlands
• Belgium
• Switzerland
• Ukraine
• Greece
• Rest-of Europe

How can this report add value to an organization?

Product/Innovation Strategy: The product segment helps the reader to understand the different technologies used for smart harvest and their potential globally. Moreover, the study gives the reader a detailed understanding of the different solutions provided by smart harvest providers for imaging, processing, and analyzing. Compared to conventional agricultural methods, smart harvest enables more exact targeting of harvest, crop mapping, and crop growth detection, allowing farmers to save money by maximizing the use of their inputs.

Growth/Marketing Strategy: The Europe smart harvest market has seen major development by key players operating in the market, such as business expansion, partnership, collaboration, and joint venture. The favored strategy for the companies has been partnership, collaboration, and joint venture activities to strengthen their position in the global smart harvest market.

Competitive Strategy: Key players in the Europe smart harvest market analyzed and profiled in the study involve smart harvest-based product manufacturers, including market segments covered by distinct product kinds, applications served, and regional presence, as well as the influence of important market tactics employed. Moreover, a detailed competitive benchmarking of the players operating in the global smart harvest market has been done to help the reader understand how players stack against each other, presenting a clear market landscape. Additionally, comprehensive competitive strategies such as partnerships, agreements, and collaborations will aid the reader in understanding the untapped revenue pockets in the market.

Key Market Players and Competition Synopsis

The companies that are profiled have been selected based on inputs gathered from primary experts and analyzing company coverage, type portfolio, and market penetration.

Some prominent names in the market include:

• Agrobot
• AMB Rousset

Table of Contents

Scope of the Study

Executive Summary

1 Market

• 1.1 Industry Outlook
  • 1.1.1 Market Definition
  • 1.1.2 Market Trends
    • 1.1.2.1 Role of Artificial Intelligence and Machine Learning in Smart Harvesting
    • 1.1.2.2 Increased Focus on Sustainable Agriculture Practices
  • 1.1.3 Ecosystem/Ongoing Programs
    • 1.1.3.1 Consortiums and Associations
    • 1.1.3.2 Regulatory Bodies
    • 1.1.3.3 Government Initiatives/Programs
• 1.2 Business Dynamics
  • 1.2.1 Business Drivers
    • 1.2.1.1 Rising Crop Losses Caused by Improper Harvesting Practices
      • 1.2.1.1.1 Minimizing Crop Yield Depletion throughout Harvesting Process
    • 1.2.1.2 Need for Reducing the Cost of Crop Production
      • 1.2.1.2.1 Optimizing Farm Profitability through Climate-Resilient Smart Harvest Solutions
  • 1.2.2 Business Challenges
    • 1.2.2.1 Less Adoption of Smart Harvesters among Small-Scale Farmers
    • 1.2.2.2 High Initial Cost of Smart Harvesting Equipment
    • 1.2.2.3 Technical Complexities Affecting Smart Harvest Adoption
  • 1.2.3 Business Strategies
    • 1.2.3.1 Product Development and Innovation
    • 1.2.3.2 Market Development
  • 1.2.4 Corporate Strategies
    • 1.2.4.1 Partnerships, Joint Ventures, Collaborations, and Alliances
  • 1.2.5 Business Opportunities
    • 1.2.5.1 Integration of Smart Technologies in Agriculture Machineries or Equipment
    • 1.2.5.2 Development of Innovative and Affordable Small Harvesting Robot
    • 1.2.5.3 Government Initiatives to Promote Digital Agriculture
    • 1.2.5.4 Opportunities in ATaaS Market
• 1.3 Case Studies
  • 1.3.1 Smart Harvesting Case Study
  • 1.3.2 Automation of Crop Yield Assessment Case Study
  • 1.3.3 Lettuce Harvesting Robot Case Study
• 1.4 Startup Landscape
  • 1.4.1 Startup Traction Analysis (by Product)
  • 1.4.2 Funding Analysis
    • 1.4.2.1 Total Investments and Number of Funding Deals
    • 1.4.2.2 Top Funding Deals, 2022
    • 1.4.2.3 Funding (by Technology)
    • 1.4.2.4 Funding (by Year)
• 1.5 Architectural/Technical Comparison of Key Products in the Market

2 Region

• 2.1 Europe
  • 2.1.1 Germany
  • 2.1.2 France
  • 2.1.3 Netherlands
  • 2.1.4 Italy
  • 2.1.5 Ukraine
  • 2.1.6 Belgium
  • 2.1.7 Switzerland
  • 2.1.8 Greece
  • 2.1.9 Spain
  • 2.1.10 Rest-of-Europe
• 2.2 U.K.

3 Markets - Competitive Benchmarking & Company Profiles

• 3.1 Competitive Benchmarking
  • 3.1.1 Robotic Harvester Companies
  • 3.1.2 Self-Propelled Smart Harvester Companies
  • 3.1.3 Market Share Analysis of Robotic Harvester Manufacturers
  • 3.1.4 Market Share Analysis of Self-Propelled Smart Harvester Manufacturers
• 3.2 Company Profiles
  • 3.2.1 Agrobot
    • 3.2.1.1 Company Overview
    • 3.2.1.2 Product Portfolio
    • 3.2.1.3 Customer Profiles
      • 3.2.1.3.1 Target Customers
    • 3.2.1.4 Analyst View
  • 3.2.2 Antobot Ltd.
    • 3.2.2.1 Company Overview
    • 3.2.2.2 Product Portfolio
    • 3.2.2.3 Customer Profiles
      • 3.2.2.3.1 Target Customers
    • 3.2.2.4 Analyst View
  • 3.2.3 AMB Rousset
    • 3.2.3.1 Company Overview
    • 3.2.3.2 Product Portfolio
    • 3.2.3.3 Customer Profiles
      • 3.2.3.3.1 Target Customers
    • 3.2.3.4 Analyst View
  • 3.2.4 CNH Industrial N.V.
    • 3.2.4.1 Company Overview
    • 3.2.4.2 Product Portfolio
    • 3.2.4.3 Customer Profile
      • 3.2.4.3.1 Target Customers
    • 3.2.4.4 Analyst View

4 Research Methodology

• 4.1 Data Sources
  • 4.1.1 Primary Data Sources
  • 4.1.2 Secondary Data Sources
  • 4.1.3 Data Triangulation
• 4.2 Market Estimation and Forecast

List of Figures

• Figure 1: Scope Definition
• Figure 2: Smart Harvest Market Coverage
• Figure 3: Factors Driving the Need for Smart Harvesting
• Figure 4: Europe Smart Harvest Market, $Billion, 2022-2028
• Figure 5: Europe Smart Harvest Market (by Site of Operation), $Billion, 2022 and 2028
• Figure 6: Europe Smart Harvest Market (by Product), $Billion, 2022 and 2028
• Figure 7: Smart Harvest Market (by Region), 2022
• Figure 8: Use of AI/ML in Traceability of Banana Value Chain in Ivory Coast, Africa
• Figure 9: Greenhouse Gas Emissions (Carbon Dioxide (CO2) Eq.) by Sector, Share (%), 2022
• Figure 10: Estimated Food Loss at Different Stages in Entire Supply Chain
• Figure 11: Average Labor Cost of Various Agricultural Operations, %, 2019-2022
• Figure 12: Product Development and Innovation (by Company), January 2018-June 2023
• Figure 13: Partnerships, Joint Ventures, Collaborations, and Alliances (by Company), January 2018-June 2023
• Figure 14: Agriculture Technology-as-a-Service (ATaaS) Market Revenue, $Million, 2022-2028
• Figure 15: Smart Harvesting Case Study - Extentia Information Technology
• Figure 16: Automation of Crop Yield Assessment Case Study
• Figure 17: Lettuce Harvesting Robot Case Study
• Figure 18: Total Investment and Number of Funding Deals, $Million, January 2020-December 2022
• Figure 19: Top Funding Deals in Smart Harvest Market, $Million, 2022
• Figure 20: Funding (by Technology), 2022
• Figure 21: Funding (by Year), $Million, 2021 and 2022
• Figure 22: Competitive Benchmarking for Robotic Harvester Companies
• Figure 23: Competitive Benchmarking for Self-Propelled Smart Harvester Companies
• Figure 24: Market Share Analysis of Robotic Harvester Manufacturers, 2022
• Figure 25: Market Share Analysis of Self-Propelled Smart Harvester Manufacturers, 2022
• Figure 26: Agrobot: Product Portfolio
• Figure 27: Antobot Ltd.: Product Portfolio
• Figure 28: AMB Rousset: Product Portfolio
• Figure 29: CNH Industrial N.V.: Product Portfolio
• Figure 30: Data Triangulation
• Figure 31: Top-Down and Bottom-Up Approach
• Figure 32: Assumptions and Limitations

List of Tables

• Table 1: Key Consortiums and Associations in the Smart Harvest Market
• Table 2: Key Regulatory Bodies
• Table 3: Key Government Initiatives/Programs
• Table 4: Key Startups in the Smart Harvest Market
• Table 5: Technical Parameters Comparison for Robotic Harvesters: MetoMotion vs. Harvest Automation
• Table 6: Smart Harvest Market (by Region), $Million, 2022-2028