Savory Snacks Market by Type (Potato Chips, Extruded Snacks, Nuts & Seeds, Meat Snacks), Flavor (Barbeque, Spice, Salty, Plain), Distribution Channel (Supermarkets & Hypermarkets, Convenience Stores, Specialty Stores, Online Channels) — Global Forecasts to 2029

The Savory Snacks Market is expected to reach $347.2 billion by 2029, at a CAGR of 7.3% during the forecast period of 2022 to 2029. The growing consumer demand for healthy snacking, the rising popularity of convenience foods & on-the-go snacks, changing lifestyles and hectic schedules of the working population, and expansion of the retail industry across the globe are the key factors driving the growth of the savory snacks market. Furthermore, the growing E-commerce penetration in developing countries and emerging economies in Latin America, Asia, and the Middle East & Africa are expected to provide significant opportunities for the players operating in this market.

Autonomous Tractors Market by Type (Fully Autonomous, Semi-Autonomous Tractors), Component (LiDAR, Radar, Ultrasonic Sensors, GPS), Power Output (Up to 30 HP, 31–100 HP, 101 HP & Above), Application (Tillage, Seed Sowing, Harvesting) – Global Forecast to 2029

The Autonomous Tractors Market is expected to reach $5.38 billion by 2029, at a CAGR of 22.4% during the forecast period of 2022–2029. The growth of this market is driven by the rising adoption of modern agricultural techniques, the increasing government initiatives to support farmers, and improved credit availability. However, the high initial cost of advanced agriculture equipment and the rising fragmentation of land are factors restraining the growth of the autonomous tractors market.

Artificial Intelligence in Medical Diagnostics Market By Component (Software, Services), Specialty (Radiology, Cardiology, Neurology, Obstetrics/Gynecology, Oncology), Modality (MRI, CT, X-ray, Ultrasound), End User (Hospital, Diagnostic Center) – Global Forecast to 2029

The Artificial Intelligence in Medical Diagnostics Market is expected to reach $9.38 billion by 2029, at a CAGR of 36.2% from 2022 to 2029. The growth of this market is driven by the growing need for the adoption of AI in medical diagnosis to reduce errors, the shortage of healthcare professionals, and the rising incidence rate of chronic diseases. In addition, the growth potential in emerging economies and the growing number of cross-industry partnerships & collaborations are expected to provide significant growth opportunities for this market.

Sugar-free Products Market by Type (Beverages, Food Products, Tabletop, Others); Sweetening Type (Sugar Substitute-sweetened Sugar-free Products, Naturally Sweetened); Distribution Channel (Supermarkets & Hypermarkets, Others) – Global Forecasts to 2029

The Sugar-free Products Market is Expected to reach $65.31 Billion by 2029 at a CAGR of 6.2% from 2022 to 2029. The growth of this market is driven by factors such as the rising incidence rate of diabetes, the rising demand for low-calorie foods, and sugar taxes imposed on sugary drinks. However, the higher prices of sugar-free products restrain the growth of this market.

The rising consumption of sports and performance drinks drives the growth of the beverage packaging market. These beverages often contain ingredients like vitamins, electrolytes, and protein, making proper packaging essential for preserving their quality and freshness. Packaging materials that offer protection against light, oxygen, and temperature fluctuations are crucial to maintaining the efficacy and taste of these beverages.

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Increased offshore spending and new oilfield discoveries are expected to create significant growth opportunities for the players operating in the U.S. cold drawn seamless steel pipes market. Trade protectionism and the introduction of new substitutes pose serious challenges to the growth of this market.

Artificial Intelligence (AI) is used for image acquisition, processing, and analysis in microscopy. AI can help overcome the limitations of traditional microscopy tools. For instance, light-field microscopy and light-sheet microscopy have different challenges and advantages. To take advantage of the benefits of each technique, researchers at EMBL developed a machine-learning approach that uses light-sheet microscopy to train AI algorithms and light-field microscopy to image large 3D samples and then form an accurate 3D picture of the sample.