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市场调查报告书
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1880441

人工智慧驱动的产量预测市场预测至2032年：全球薄膜类型、材料、厚度、包装形式、技术、最终用户和区域分析

AI-Powered Yield Forecasting Market Forecasts to 2032 - Global Analysis By FilmType, Material, Thickness, Packaging Format, Technology, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，全球基于人工智慧的产量预测市场预计到 2025 年将达到 16 亿美元，到 2032 年将达到 49 亿美元，在预测期内的复合年增长率为 17%。

人工智慧驱动的产量预测是指利用机器学习、深度学习和预测分析等先进的人工智慧技术，准确估算未来作物产量。它分析包括天气模式、土壤状况、卫星图像、历史产量记录和即时农场数据在内的大型数据集，以识别规律并预测产量。人工智慧系统不断从新数据中学习，提供动态的、在地化的、及时的预测，使农民能够优化资源配置、制定收割计画、管理风险并提高盈利。总而言之，人工智慧驱动的产量预测将复杂的农业数据转化为可操作的洞察，从而增强永续农业的决策能力。

准确作物预测的需求日益增长

农民和农业相关企业越来越依赖预测分析来预测产量、优化资源配置并降低风险。人工智慧模型整合了卫星影像、气象资料和土壤状况，提供精准的预测，进而改善决策。准确的预测有助于缓解气候变迁的影响，并确保粮食供应稳定。各国政府和农业合作社也正在采用人工智慧预测来加强粮食安全规划。全球人口的成长和农业系统面临的日益增长的压力，进一步增加了对可靠产量预测的需求。

安装和维修成本高昂

部署人工智慧驱动的预测系统需要投资于感测器、资料基础设施和先进的软体平台。中小农场往往难以负担这些技术的实施成本，从而限制了其普及。维护成本，包括定期更新和技术支持，也会加重农场的经济负担。与现有农场管理系统的整合也可能十分复杂且耗费资源。这些挑战减缓了成本敏感地区和土地所有权分散地区的推广应用。因此，高成本仍然是人工智慧驱动的产量预测解决方案广泛应用的一大障碍。

对优化农业生产力的需求日益增长

人工智慧驱动的预测技术使农民能够更精准地规划播种、灌溉和收割。这种优化能够减少废弃物、提高资源利用效率并最大限度地提高产量。随着全球粮食需求持续成长，提高生产力对于满足供应需求至关重要。人工智慧解决方案还能透过数据驱动的决策来最大限度地减少对环境的影响，从而支持永续农业实践。各国政府和农业技术公司正日益推动人工智慧的应用，以实现粮食安全和永续性目标。因此，对生产力优化的需求预计将为市场创造巨大的成长机会。

对数据品质和可用性的依赖

不准确或不完整的资料集会导致预测不可靠，并削弱农民的信心。许多地区缺乏健全的资料基础设施，限制了人工智慧的应用范围。季节性变化和不稳定的天气记录进一步挑战了模型的准确性。资料隐私问题也限制了农场层级资讯的获取，减缓了人工智慧的普及。如果没有高品质的输入数据，人工智慧系统就无法提供有效预测所需的准确性。因此，对数据可用性的依赖仍然是市场信誉和成长的一大威胁。

新冠疫情的影响：

新冠疫情对人工智慧驱动的产量预测市场产生了复杂的影响。供应链中断延缓了感测器和资料基础设施的部署，导致多个地区的应用速度放缓。疫情期间，农民面临财务不确定性，减少了对先进技术的投资。然而，疫情也凸显了农业韧性和效率的重要性，重新激发了人们对预测解决方案的兴趣。由于实地考察农场受到限制，远端监控和数位平台得到了广泛应用。各国政府日益重视粮食安全，也加速了人工智慧预测工具的采用。

预计在预测期内，聚乙烯（PE）细分市场将占据最大的市场份额。

由于聚乙烯 (PE) 在农业领域的广泛应用，预计在预测期内，PE 细分市场将占据最大的市场份额。 PE 薄膜和涂层在资料撷取系统中至关重要，能够为精确的产量预测提供可控环境。其耐用性、成本效益和多功能性使其成为防护和监测解决方案的首选材料。农民依靠基于 PE 的基础设施来支援人工智慧驱动的感测器和成像设备。已开发市场和新兴市场对该细分市场的强劲需求均推动了这一领域的发展。人工智慧预测工具的日益普及进一步提升了 PE 材料在农业领域的重要性。

预计在预测期内，透明阻隔薄膜细分市场将呈现最高的复合年增长率。

由于透明阻隔薄膜在提高数据准确性方面发挥重要作用，预计在预测期内，该细分市场将实现最高成长率。这些薄膜可确保感测器和成像设备获得最佳可视性，从而提高人工智慧预测的准确性。其轻盈柔韧的特性使其适用于各种农业应用。对先进监测解决方案日益增长的需求正在加速透明阻隔薄膜的普及。製造商正致力于创新，采用永续的高性能材料来满足不断变化的需求。与智慧农业基础设施的整合将进一步巩固该细分市场的成长动能。

占比最大的地区：

由于北美拥有先进的农业基础设施，预计在预测期内，北美将占据最大的市场份额。美国和加拿大的农民正在利用预测分析来优化产量和资源利用。政府的大力支持和对农业技术创新的投资正在巩固该地区的主导地位。领先的人工智慧公司和农业合作社的存在正在加速预测解决方案的商业化。人们对永续性和效率的高度重视进一步推动了市场需求。零售和合作网路也在促进人工智慧工具的广泛应用。

预计年复合成长率最高的地区：

由于食品需求不断增长，亚太地区预计将在预测期内实现最高的复合年增长率。中国、印度和澳洲等国家正越来越多地采用人工智慧驱动的预测技术来提高生产力。不断壮大的中产阶级和政府推动智慧农业的措施正在促进这一趋势。该地区的农民日益认识到预测分析在风险管理方面的益处。电子商务和数位平台正使人工智慧解决方案在各个市场更容易获得。对农业技术Start-Ups的投资不断增加，进一步推动了该地区的成长。

免费客製化服务：

购买此报告的客户可以选择以下免费自订选项之一：

  • 公司概况
    • 对其他市场公司（最多 3 家公司）进行全面分析
    • 主要企业SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户要求，提供主要国家的市场估算和预测以及复合年增长率（註：可行性需确认）。
  • 竞争基准化分析
    • 根据主要企业的产品系列、地理覆盖范围和策略联盟基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 原始研究资料
    • 次级研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章 全球基于人工智慧的产量产量预测市场

  • 介绍
  • 金属化阻隔膜
  • 透明阻隔膜
  • 共挤出多层薄膜
  • 层压膜
  • 其他胶片类型

第六章 全球基于人工智慧的产量预测市场（按材料划分）

  • 介绍
  • 聚乙烯（PE）
  • 聚丙烯（PP）
  • 聚对苯二甲酸乙二醇酯（PET）
  • 乙烯 - 乙烯醇（EVOH）
  • 聚偏二氯乙烯（PVDC）
  • 其他成分

第七章 全球基于人工智慧的产量预测市场（按厚度划分）

  • 介绍
  • 50微米或更小
  • 50至100微米
  • 100至150微米
  • 150微米或以上

第八章 全球基于人工智慧的产量预测市场（按包装类型划分）

  • 介绍
  • 小袋
  • 包包
  • 盖膜
  • 包装纸
  • 泡壳
  • 其他包装形式

9. 全球基于人工智慧的产量预测市场（按技术划分）

  • 介绍
  • 挤出涂层
  • 溶剂型涂料
  • 无溶剂涂料
  • 水性涂料
  • 其他技术

第十章 全球基于人工智慧的产量预测市场（按最终用户划分）

  • 介绍
  • 个人护理及化妆品
  • 家居用品
  • 工业产品
  • 其他最终用户

第十一章 全球基于人工智慧的产量预测市场（按地区划分）

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与併购
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十三章：企业概况

  • IBM
  • Microsoft
  • Google
  • Amazon Web Services
  • SAP SE
  • Oracle Corporation
  • Siemens AG
  • Deere & Company（John Deere）
  • AG Leader Technology
  • Trimble Inc.
  • Climate LLC
  • Granular（Corteva Agriscience）
  • Prospera Technologies
  • Taranis
  • CropX Technologies
Product Code: SMRC32513

According to Stratistics MRC, the Global AI-Powered Yield Forecasting Market is accounted for $1.6 billion in 2025 and is expected to reach $4.9 billion by 2032 growing at a CAGR of 17% during the forecast period. AI-powered yield forecasting refers to the use of advanced artificial intelligence techniques-such as machine learning, deep learning, and predictive analytics-to estimate future crop yields with high accuracy. It analyzes vast datasets including weather patterns, soil conditions, satellite imagery, historical yield records, and real-time farm inputs to identify patterns and predict productivity. By continuously learning from new data, AI systems deliver dynamic, location-specific, and timely forecasts. This helps farmers optimize resource allocation, plan harvesting, manage risks, and improve profitability. Overall, AI-powered yield forecasting enhances decision-making by transforming complex agricultural data into actionable insights for sustainable farming.

Market Dynamics:

Driver:

Growing demand for accurate crop predictions

Farmers and agribusinesses increasingly rely on predictive analytics to anticipate yields, optimize resource allocation, and reduce risks. AI models integrate satellite imagery, weather data, and soil conditions to deliver precise forecasts, improving decision-making. Accurate predictions help mitigate the impact of climate variability and ensure food supply stability. Governments and cooperatives are also adopting AI forecasting to strengthen food security planning. Rising global population and pressure on agricultural systems further amplify the need for reliable yield estimates.

Restraint:

High implementation and maintenance costs

Deploying AI-powered forecasting systems requires investment in sensors, data infrastructure, and advanced software platforms. Small and medium-sized farmers often struggle to afford these technologies, limiting adoption. Maintenance costs, including regular updates and technical support, add to the financial burden. Integration with existing farm management systems can also be complex and resource-intensive. These challenges slow penetration in cost-sensitive regions and among fragmented landholdings. Consequently, high costs remain a significant restraint to widespread adoption of AI-powered yield forecasting solutions.

Opportunity:

Rising need for optimized farm productivity

AI-powered forecasting enables farmers to plan planting schedules, irrigation, and harvesting with greater precision. This optimization reduces waste, enhances resource efficiency, and maximizes yields. As global food demand continues to rise, productivity improvements are critical to meeting supply requirements. AI solutions also support sustainable farming practices by minimizing environmental impact through data-driven decisions. Governments and agritech firms are increasingly promoting AI adoption to achieve food security and sustainability goals. As a result, the need for optimized productivity is expected to unlock substantial growth opportunities for the market.

Threat:

Dependence on quality and availability of data

Inaccurate or incomplete datasets can lead to unreliable predictions, undermining farmer confidence. Many regions lack robust data infrastructure, limiting the scope of AI applications. Seasonal variability and inconsistent weather records further challenge model accuracy. Data privacy concerns also restrict access to farm-level information, slowing adoption. Without high-quality inputs, AI systems cannot deliver the precision required for effective forecasting. Consequently, dependence on data availability remains a critical threat to market credibility and growth.

Covid-19 Impact:

The COVID-19 pandemic had a mixed impact on the AI-powered yield forecasting market. Supply chain disruptions delayed deployment of sensors and data infrastructure, slowing adoption in several regions. Farmers faced financial uncertainty, reducing investment in advanced technologies during the crisis. However, the pandemic highlighted the importance of resilience and efficiency in agriculture, driving renewed interest in predictive solutions. Remote monitoring and digital platforms gained traction as physical access to farms was restricted. Governments also emphasized food security, accelerating adoption of AI forecasting tools.

The polyethylene (PE) segment is expected to be the largest during the forecast period

The polyethylene (PE) segment is expected to account for the largest market share during the forecast period, driven by its widespread use in agricultural applications. PE films and coverings are integral to data collection systems, enabling controlled environments for accurate yield forecasting. Their durability, cost-effectiveness, and versatility make them the preferred material for protective and monitoring solutions. Farmers rely on PE-based infrastructure to support AI-driven sensors and imaging devices. The segment benefits from strong demand across both developed and emerging markets. Rising adoption of AI forecasting tools further reinforces the importance of PE materials in agricultural setups.

The transparent barrier films segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the transparent barrier films segment is predicted to witness the highest growth rate due to its role in enhancing data accuracy. These films allow optimal visibility for sensors and imaging devices, improving the precision of AI-powered forecasts. Their lightweight and flexible properties make them suitable for diverse agricultural applications. Rising demand for advanced monitoring solutions is accelerating adoption of transparent barrier films. Manufacturers are innovating with sustainable and high-performance materials to meet evolving needs. Integration with smart farming infrastructure further strengthens the segment's growth trajectory.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share driven by advanced agricultural infrastructure. Farmers in the United States and Canada are leveraging predictive analytics to optimize yields and resource use. Strong government support and investment in agritech innovation reinforce regional leadership. The presence of leading AI firms and agricultural cooperatives accelerates commercialization of forecasting solutions. High awareness of sustainability and efficiency further strengthens demand. Retail and cooperative networks also facilitate widespread adoption of AI-powered tools.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR by rising food demand. Countries such as China, India, and Australia are increasingly adopting AI-powered forecasting to improve productivity. Expanding middle-class populations and government initiatives promoting smart farming support adoption. Farmers in the region are becoming more aware of the benefits of predictive analytics in managing risks. E-commerce and digital platforms are making AI solutions more accessible across diverse markets. Rising investment in agritech startups further accelerates regional growth.

Key players in the market

Some of the key players in AI-Powered Yield Forecasting Market include IBM, Microsoft, Google, Amazon Web Services, SAP SE, Oracle Corporation, Siemens AG, Deere & Company (John Deere), AG Leader Technology, Trimble Inc., Climate LLC, Granular (Corteva Agriscience), Prospera Technologies, Taranis and CropX Technologies.

Key Developments:

In May 2024, Microsoft announced major new AI and cloud capabilities within its Azure AI Services, including updates to Azure OpenAI Service. These enhancements empower developers and agri-tech companies to build more sophisticated predictive analytics tools on the Azure platform, directly improving the power and accessibility of AI-driven yield forecasting solutions for farmers.

In February 2023, IBM partnered with NASA to deploy its foundational AI model for geospatial data, aiming to vastly improve climate and agricultural analytics. This collaboration enhances the ability to predict crop yields by analyzing environmental factors like soil moisture and land use from satellite imagery with unprecedented accuracy, providing a powerful tool for the agricultural sector.

Film Types Covered:

  • Metallized Barrier Films
  • Transparent Barrier Films
  • Co-Extruded Multilayer Films
  • Laminated Films
  • Other Film Types

Materials Covered:

  • Polyethylene (PE)
  • Polypropylene (PP)
  • Polyethylene Terephthalate (PET)
  • Ethylene Vinyl Alcohol (EVOH)
  • Polyvinylidene Chloride (PVDC)
  • Other Materials

Thicknesses Covered:

  • Below 50 microns
  • 50-100 microns
  • 100-150 microns
  • Above 150 microns

Packaging Formats Covered:

  • Pouches
  • Bags
  • Lidding Films
  • Wraps & Sheets
  • Blisters
  • Other Packaging Formats

Technologies Covered:

  • Extrusion Coating
  • Solvent-Based Coating
  • Solvent-Free Coating
  • Water-Based Coating
  • Other Technologies

End Users Covered:

  • Personal Care & Cosmetics
  • Household Products
  • Industrial Products
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & 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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-Powered Yield Forecasting Market, By Film Type

  • 5.1 Introduction
  • 5.2 Metallized Barrier Films
  • 5.3 Transparent Barrier Films
  • 5.4 Co-Extruded Multilayer Films
  • 5.5 Laminated Films
  • 5.6 Other Film Types

6 Global AI-Powered Yield Forecasting Market, By Material

  • 6.1 Introduction
  • 6.2 Polyethylene (PE)
  • 6.3 Polypropylene (PP)
  • 6.4 Polyethylene Terephthalate (PET)
  • 6.5 Ethylene Vinyl Alcohol (EVOH)
  • 6.6 Polyvinylidene Chloride (PVDC)
  • 6.7 Other Materials

7 Global AI-Powered Yield Forecasting Market, By Thickness

  • 7.1 Introduction
  • 7.2 Below 50 microns
  • 7.3 50-100 microns
  • 7.4 100-150 microns
  • 7.5 Above 150 microns

8 Global AI-Powered Yield Forecasting Market, By Packaging Format

  • 8.1 Introduction
  • 8.2 Pouches
  • 8.3 Bags
  • 8.4 Lidding Films
  • 8.5 Wraps & Sheets
  • 8.6 Blisters
  • 8.7 Other Packaging Formats

9 Global AI-Powered Yield Forecasting Market, By Technology

  • 9.1 Introduction
  • 9.2 Extrusion Coating
  • 9.3 Solvent-Based Coating
  • 9.4 Solvent-Free Coating
  • 9.5 Water-Based Coating
  • 9.6 Other Technologies

10 Global AI-Powered Yield Forecasting Market, By End User

  • 10.1 Introduction
  • 10.2 Personal Care & Cosmetics
  • 10.3 Household Products
  • 10.4 Industrial Products
  • 10.5 Other End Users

11 Global AI-Powered Yield Forecasting Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 IBM
  • 13.2 Microsoft
  • 13.3 Google
  • 13.4 Amazon Web Services
  • 13.5 SAP SE
  • 13.6 Oracle Corporation
  • 13.7 Siemens AG
  • 13.8 Deere & Company (John Deere)
  • 13.9 AG Leader Technology
  • 13.10 Trimble Inc.
  • 13.11 Climate LLC
  • 13.12 Granular (Corteva Agriscience)
  • 13.13 Prospera Technologies
  • 13.14 Taranis
  • 13.15 CropX Technologies

List of Tables

  • Table 1 Global AI-Powered Yield Forecasting Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Powered Yield Forecasting Market Outlook, By Film Type (2024-2032) ($MN)
  • Table 3 Global AI-Powered Yield Forecasting Market Outlook, By Metallized Barrier Films (2024-2032) ($MN)
  • Table 4 Global AI-Powered Yield Forecasting Market Outlook, By Transparent Barrier Films (2024-2032) ($MN)
  • Table 5 Global AI-Powered Yield Forecasting Market Outlook, By Co-Extruded Multilayer Films (2024-2032) ($MN)
  • Table 6 Global AI-Powered Yield Forecasting Market Outlook, By Laminated Films (2024-2032) ($MN)
  • Table 7 Global AI-Powered Yield Forecasting Market Outlook, By Other Film Types (2024-2032) ($MN)
  • Table 8 Global AI-Powered Yield Forecasting Market Outlook, By Material (2024-2032) ($MN)
  • Table 9 Global AI-Powered Yield Forecasting Market Outlook, By Polyethylene (PE) (2024-2032) ($MN)
  • Table 10 Global AI-Powered Yield Forecasting Market Outlook, By Polypropylene (PP) (2024-2032) ($MN)
  • Table 11 Global AI-Powered Yield Forecasting Market Outlook, By Polyethylene Terephthalate (PET) (2024-2032) ($MN)
  • Table 12 Global AI-Powered Yield Forecasting Market Outlook, By Ethylene Vinyl Alcohol (EVOH) (2024-2032) ($MN)
  • Table 13 Global AI-Powered Yield Forecasting Market Outlook, By Polyvinylidene Chloride (PVDC) (2024-2032) ($MN)
  • Table 14 Global AI-Powered Yield Forecasting Market Outlook, By Other Materials (2024-2032) ($MN)
  • Table 15 Global AI-Powered Yield Forecasting Market Outlook, By Thickness (2024-2032) ($MN)
  • Table 16 Global AI-Powered Yield Forecasting Market Outlook, By Below 50 microns (2024-2032) ($MN)
  • Table 17 Global AI-Powered Yield Forecasting Market Outlook, By 50-100 microns (2024-2032) ($MN)
  • Table 18 Global AI-Powered Yield Forecasting Market Outlook, By 100-150 microns (2024-2032) ($MN)
  • Table 19 Global AI-Powered Yield Forecasting Market Outlook, By Above 150 microns (2024-2032) ($MN)
  • Table 20 Global AI-Powered Yield Forecasting Market Outlook, By Packaging Format (2024-2032) ($MN)
  • Table 21 Global AI-Powered Yield Forecasting Market Outlook, By Pouches (2024-2032) ($MN)
  • Table 22 Global AI-Powered Yield Forecasting Market Outlook, By Bags (2024-2032) ($MN)
  • Table 23 Global AI-Powered Yield Forecasting Market Outlook, By Lidding Films (2024-2032) ($MN)
  • Table 24 Global AI-Powered Yield Forecasting Market Outlook, By Wraps & Sheets (2024-2032) ($MN)
  • Table 25 Global AI-Powered Yield Forecasting Market Outlook, By Blisters (2024-2032) ($MN)
  • Table 26 Global AI-Powered Yield Forecasting Market Outlook, By Other Packaging Formats (2024-2032) ($MN)
  • Table 27 Global AI-Powered Yield Forecasting Market Outlook, By Technology (2024-2032) ($MN)
  • Table 28 Global AI-Powered Yield Forecasting Market Outlook, By Extrusion Coating (2024-2032) ($MN)
  • Table 29 Global AI-Powered Yield Forecasting Market Outlook, By Solvent-Based Coating (2024-2032) ($MN)
  • Table 30 Global AI-Powered Yield Forecasting Market Outlook, By Solvent-Free Coating (2024-2032) ($MN)
  • Table 31 Global AI-Powered Yield Forecasting Market Outlook, By Water-Based Coating (2024-2032) ($MN)
  • Table 32 Global AI-Powered Yield Forecasting Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 33 Global AI-Powered Yield Forecasting Market Outlook, By End User (2024-2032) ($MN)
  • Table 34 Global AI-Powered Yield Forecasting Market Outlook, By Personal Care & Cosmetics (2024-2032) ($MN)
  • Table 35 Global AI-Powered Yield Forecasting Market Outlook, By Household Products (2024-2032) ($MN)
  • Table 36 Global AI-Powered Yield Forecasting Market Outlook, By Industrial Products (2024-2032) ($MN)
  • Table 37 Global AI-Powered Yield Forecasting Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.