薯片和零食

Their dominance comes from a combination of affordability, accessibility, long shelf life and strong emotional appeal linked to taste and comfort. Even with health concerns, their convenience and sensory satisfaction often outweigh nutritional drawbacks in consumer decision-making, making them a resilient category across cultures and income groups.

Healthy snacks are growing rapidly, but they currently exist alongside traditional indulgent snacks rather than replacing them. Many consumers adopt a dual behavior—choosing healthy options during routine consumption and indulgent snacks for pleasure. This suggests that the market is expanding rather than transforming completely.

Beyond food production, the industry contributes to environmental challenges through intensive agriculture (potatoes, corn, palm oil), energy-heavy frying processes, and plastic-based packaging waste. This has led to growing pressure for sustainable sourcing, reduced oil consumption and recyclable or biodegradable packaging solutions.

Generally, no. Technologies like vacuum frying and low-oil systems preserve natural potato flavor better than old methods. Sustainable production mainly reduces fat, acrylamide and energy usage without altering the classic taste people love.

Not likely. Although machines are costly at first, automation reduces waste, oil usage, energy consumption and labor costs. Over time, production becomes cheaper, keeping chip prices stable sometimes even lower.

Very possible. As APAC demand rises, regional flavors like masala, seaweed, chili-lime or schezwan may become global favorites. AI-driven flavor analysis also helps companies export trending Asian tastes to international markets.

Yes. Modern optical sorters use multispectral imaging and AI, catching defects like sugar-end browning, bruises, black spots, foreign materials before slicing. This level of detection was impossible with human eyes. As automation increases, food safety becomes more consistent and less dependent on human judgment.

Yes. Modern optical sorters use multispectral imaging and AI, catching defects like sugar-end browning, bruises, black spots, foreign materials before slicing. This level of detection was impossible with human eyes. As automation increases, food safety becomes more consistent and less dependent on human judgment.