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人工智慧驅動的產量預測市場預測至2032年：全球薄膜類型、材料、厚度、包裝形式、技術、最終用戶和區域分析

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個工作天內

價格

根據 Stratistics MRC 的一項研究，全球基於人工智慧的產量預測市場預計到 2025 年將達到 16 億美元，到 2032 年將達到 49 億美元，在預測期內的複合年成長率為 17%。

人工智慧驅動的產量預測是指利用機器學習、深度學習和預測分析等先進的人工智慧技術，準確估算未來作物產量。它分析包括天氣模式、土壤狀況、衛星圖像、歷史產量記錄和即時農場數據在內的大型資料集，以識別規律並預測產量。人工智慧系統不斷從新數據中學習，提供動態的、在地化的、及時的預測，使農民能夠最佳化資源配置、制定收割計畫、管理風險並提高盈利。總而言之，人工智慧驅動的產量預測將複雜的農業數據轉化為可操作的洞察，從而增強永續農業的決策能力。

準確作物預測的需求日益成長

農民和農業相關企業越來越依賴預測分析來預測產量、最佳化資源配置並降低風險。人工智慧模型整合了衛星影像、氣象資料和土壤狀況，提供精準的預測，進而改善決策。準確的預測有助於緩解氣候變遷的影響，並確保糧食供應穩定。各國政府和農業合作社也正在採用人工智慧預測來加強糧食安全規劃。全球人口的成長和農業系統面臨的日益成長的壓力，進一步增加了對可靠產量預測的需求。

安裝和維修成本高昂

部署人工智慧驅動的預測系統需要投資於感測器、資料基礎設施和先進的軟體平台。中小農場往往難以負擔這些技術的實施成本，從而限制了其普及。維護成本，包括定期更新和技術支持，也會加重農場的經濟負擔。與現有農場管理系統的整合也可能十分複雜且耗費資源。這些挑戰減緩了成本敏感地區和土地所有權分散地區的推廣應用。因此，高成本仍然是人工智慧驅動的產量預測解決方案廣泛應用的一大障礙。

對最佳化農業生產力的需求日益成長

人工智慧驅動的預測技術使農民能夠更精準地規劃播種、灌溉和收割。這種最佳化能夠減少廢棄物、提高資源利用效率並最大限度地提高產量。隨著全球糧食需求持續成長，提高生產力對於滿足供應需求至關重要。人工智慧解決方案還能透過數據驅動的決策來最大限度地減少對環境的影響，從而支持永續農業實踐。各國政府和農業技術公司正日益推動人工智慧的應用，以實現糧食安全和永續性目標。因此，對生產力最佳化的需求預計將為市場創造巨大的成長機會。

對數據品質和可用性的依賴

不準確或不完整的資料集會導致預測不可靠，並削弱農民的信心。許多地區缺乏健全的資料基礎設施，限制了人工智慧的應用範圍。季節性變化和不穩定的天氣記錄進一步挑戰了模型的準確性。資料隱私問題也限制了農場層級資訊的獲取，減緩了人工智慧的普及。如果沒有高品質的輸入數據，人工智慧系統就無法提供有效預測所需的準確性。因此，對數據可用性的依賴仍然是市場信譽和成長的一大威脅。

新冠疫情的影響：

新冠疫情對人工智慧驅動的產量預測市場產生了複雜的影響。供應鏈中斷延緩了感測器和資料基礎設施的部署，導致多個地區的應用速度放緩。疫情期間，農民面臨財務不確定性，減少了對先進技術的投資。然而，疫情也凸顯了農業韌性和效率的重要性，重新激發了人們對預測解決方案的興趣。由於實地考察農場受到限制，遠端監控和數位平台得到了廣泛應用。各國政府日益重視糧食安全，也加速了人工智慧預測工具的採用。

預計在預測期內，聚乙烯（PE）細分市場將佔據最大的市場佔有率。

由於聚乙烯 (PE) 在農業領域的廣泛應用，預計在預測期內，PE 細分市場將佔據最大的市場佔有率。 PE 薄膜和塗層在資料擷取系統中至關重要，能夠為精確的產量預測提供可控環境。其耐用性、成本效益和多功能性使其成為防護和監測解決方案的首選材料。農民依靠基於 PE 的基礎設施來支援人工智慧驅動的感測器和成像設備。已開發市場和新興市場對該細分市場的強勁需求均推動了這一領域的發展。人工智慧預測工具的日益普及進一步提升了 PE 材料在農業領域的重要性。

預計在預測期內，透明阻隔薄膜細分市場將呈現最高的複合年成長率。

由於透明阻隔薄膜在提高數據準確性方面發揮重要作用，預計在預測期內，該細分市場將實現最高成長率。這些薄膜可確保感測器和成像設備獲得最佳可視性，從而提高人工智慧預測的準確性。其輕盈柔韌的特性使其適用於各種農業應用。對先進監測解決方案日益成長的需求正在加速透明阻隔薄膜的普及。製造商正致力於創新，採用永續的高性能材料來滿足不斷變化的需求。與智慧農業基礎設施的整合將進一步鞏固該細分市場的成長動能。

佔比最大的地區：

由於北美擁有先進的農業基礎設施，預計在預測期內，北美將佔據最大的市場佔有率。美國和加拿大的農民正在利用預測分析來最佳化產量和資源利用。政府的大力支持和對農業技術創新的投資正在鞏固該地區的主導地位。領先的人工智慧公司和農業合作社的存在正在加速預測解決方案的商業化。人們對永續性和效率的高度重視進一步推動了市場需求。零售和合作網路也在促進人工智慧工具的廣泛應用。

預計年複合成長率最高的地區：

由於食品需求不斷成長，亞太地區預計將在預測期內實現最高的複合年成長率。中國、印度和澳洲等國家正擴大採用人工智慧驅動的預測技術來提高生產力。不斷壯大的中產階級和政府推動智慧農業的措施正在促進這一趨勢。該地區的農民日益認知到預測分析在風險管理方面的益處。電子商務和數位平台正使人工智慧解決方案在各個市場更容易獲得。對農業技術Start-Ups的投資不斷增加，進一步推動了該地區的成長。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 原始研究資料
    • 次級研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 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
  • 競爭對手之間的競爭

第5章 全球基於人工智慧的產量產量預測市場

  • 介紹
  • 金屬化阻隔膜
  • 透明阻隔膜
  • 共擠出多層薄膜
  • 層壓膜
  • 其他膠片類型

第6章 全球基於人工智慧的產量預測市場（按材料分類）

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

第7章 全球基於人工智慧的產量預測市場（按厚度分類）

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

第8章 全球基於人工智慧的產量預測市場（按包裝類型分類）

  • 介紹
  • 小袋
  • 包包
  • 蓋膜
  • 包裝紙
  • 泡殼
  • 其他包裝形式

9. 全球基於人工智慧的產量預測市場（按技術分類）

  • 介紹
  • 擠出塗層
  • 溶劑型塗料
  • 無溶劑塗料
  • 水性塗料
  • 其他技術

第10章 全球基於人工智慧的產量預測市場（按最終用戶分類）

  • 介紹
  • 個人護理及化妝品
  • 家居用品
  • 工業產品
  • 其他最終用戶

第11章 全球基於人工智慧的產量預測市場（按地區分類）

  • 介紹
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第13章：企業概況

  • 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.