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Machine Learning for Crop Yield Prediction Market - By Component (Software, Services) By Deployment Model (Cloud-based, On-premises), By Farm Size, By End User & Forecast, 2024 - 2032

  • Report ID: GMI10736
  • Published Date: Aug 2024
  • Report Format: PDF

Report Content

Chapter 1   Methodology & Scope

1.1    Research design

1.1.1    Research approach

1.1.2    Data collection methods

1.2    Base estimates & calculations

1.2.1    Base year calculation

1.2.2    Key trends for market estimation

1.3    Forecast model

1.4    Primary research and validation

1.4.1    Primary sources

1.4.2    Data mining sources

1.5    Market scope & definition

Chapter 2   Executive Summary

2.1    Industry 3600 synopsis, 2021 - 2032

Chapter 3   Industry Insights

3.1    Industry ecosystem analysis

3.2    Supplier landscape

3.2.1    Software providers

3.2.2    Hardware providers

3.2.3    Service provider

3.2.4    System integrators

3.2.5    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    Growth in agritech startups

3.8.1.2    High accuracy provided by machine learning models

3.8.1.3    Integration of precision agriculture tools in the agriculture industry

3.8.1.4    Rapid technological investments by prominent players

3.8.2    Industry pitfalls & challenges

3.8.2.1    Data quality and availability challenges

3.8.2.2    High computational requirements of ML models

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 Component, 2021 - 2032 ($Bn)

5.1    Key trends

5.2    Software

5.2.1    Predictive modelling software

5.2.2    Data analytics platform

5.2.3    Others

5.3    Services

5.3.1    Professional

5.3.2    Managed

Chapter 6   Market Estimates & Forecast, By Deployment Model, 2021 - 2032 ($Bn)

6.1    Key trends

6.2    Cloud-based

6.3    On-premises

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

7.1    Key trends

7.2    Small

7.3    Medium

7.4    Large

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

8.1    Key trends

8.2    Farmers

8.3    Agricultural cooperatives

8.4    Research institutions

8.5    Government agencies

8.6    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    Nordics

9.3.8    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    South Africa

9.6.2    Saudi Arabia

9.6.3    UAE

9.6.4    Rest of MEA

Chapter 10   Company Profiles

10.1    Ag Leader Technology

10.2    Blue River Technology (John Deere)

10.3    Ceres Imaging

10.4    Corteva

10.5    Cropin Technology Solutions Pvt. Ltd.

10.6    Descartes Labs Inc.

10.7    Farmers Edge Inc.

10.8    FlyPard Analytics GmbH.

10.9    Lindsay Corporation

10.10    Microsoft Azure Farmbeats

10.11    OneSoil

10.12    Planet Labs PBC

10.13    SAP

10.14    Taranis

10.15    Trimble, Inc.
 

Authors: Preeti Wadhwani, Aishvarya Ambekar

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Premium Report Details

  • Base Year: 2023
  • Companies covered: 15
  • Tables & Figures: 310
  • Countries covered: 25
  • Pages: 240
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