欧洲智慧收穫市场：依产品、应用、国家：分析与预测（2023-2028）

2023年欧洲智慧收穫市场规模（不包括英国）为11.217亿美元。

该市场预计到 2028 年将达到 18.644 亿美元，2023-2028 年预测期间复合年增长率为 10.7%。这种扩张主要是由于农业产业越来越注重提高作物产量，同时降低投入成本。智慧收割系统提供精确、集中的生产管理方法、改良的收割应用和高效率的收割。这些技术将使农民能够做出资料驱动的决策、提高营运效率、减少资源浪费并减少环境影响，从而在未来几年帮助世界实现智慧收穫，预计将推动市场成长。

智慧收穫是一种尖端农业技术解决方案，有潜力改变农业企业。在粮食生产需求不断增长的背景下，这项新策略为农业领域的所有公司带来了显着的效益。智慧收穫系统使用先进的感测器、资料分析和自动化来改善作物管理和收穫结果。这使农民能够做出明智的决策，准确监测作物健康状况，并更有效地管理水和肥料等资源。其结果是提高了生产力和盈利，并减少了废弃物和对环境的影响。

Smart Harvest 让您能够透过提供即时资料洞察来应对不断变化的天气条件、市场需求和资源可用性。该技术可实现永续和稳健的作物生产，最终确保客户的收益，无论他们是小规模经营还是大型农业组织。将智慧收割纳入您的农业公司不仅可以提高营运效率，还可以使您成为创新且对环境负责的行业领导者。

市场扩张受到各种重要因素的影响。其中包括全球粮食需求增加、水资源和耕地减少、农业劳动力短缺以及收穫劳动成本等农业投入成本上升。这些原因预计将推动整个农业部门更多地使用智慧收割技术。这些最尖端科技使农民能够改善资源配置，提高作物产量，最终提高农业生产力。

本报告考察了欧洲智慧收穫市场，并提供了市场概述、按产品、应用、国家/地区分類的趋势以及参与市场的公司概况。

目录

调查范围

执行摘要

第一章 市场

• 产业展望
• 业务动态
• 案例研究
• Start-Ups状况
• 市场主要产品架构/技术对比

第二章 区域

• 欧洲
  • 德国
  • 法国
  • 荷兰
  • 义大利
  • 乌克兰
  • 比利时
  • 瑞士
  • 希腊
  • 西班牙
  • 其他的
• 英国

第三章市场：基准化分析与公司概况

• 竞争基准化分析
  • 机器人收割机公司
  • 自走式智慧收割机企业
  • 机器人收割机厂商市场占有率分析
  • 自走式智慧收割机厂商市场占有率分析
• 公司简介
  • Agrobot
  • Antobot Ltd.
  • AMB Rousset
  • CNH Industrial NV

第四章调查方法

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