The global demand for sustainable and functional food and nutritional supplements is on the rise, and plant-based options have emerged as a promising solution. With the ever-increasing emergence of Artificial Intelligence (AI) technology and the wealth of potential ingredients sourced from plants, AI has the potential to be a game-changer in the development and optimisation of plant-based foods and supplements. By harnessing the power of AI, companies have at their fingertips new innovative ways to create a future where plant-based ingredients can rival their animal-based counterparts in delivering taste, texture, and nutrition.

AI's impact on plant-based foods extends beyond taste and nutrition. As the world grapples with the urgent need for sustainable food production, AI can also play a pivotal role in optimising ingredient sourcing, reducing waste, and improving supply chain efficiency.

What is Artificial Intelligence in the context of plant-based foods?

AI in the context of plant foods refers to using advanced computational algorithms and techniques to enhance the development, optimisation, and production of plant-based food products. AI systems analyse vast amounts of data, including ingredient properties, sensory profiles, nutritional information, consumer preferences, and market trends to derive insights and make data-driven decisions in creating plant-based products.

How is AI being used in plant-based food product development?

• Recipe and formulation development: By identifying combinations of ingredients that mimic the taste, texture, and nutritional composition of animal-based products, AI algorithms can help determine appropriate substitutions that maintain the desired quality and characteristics of the final product at a lower cost, and lead to the creation of innovative plant-based alternatives.
• Predicting consumer preference: AI can analyse sensory data and consumer insight to understand flavour profiles and preferences. This information is then used to optimise plant-based foods and gain wider consumer acceptance.
• Nutritional analysis & optimisation: By analysing ingredient data and nutritional guidelines, AI can suggest adjustments to formulations to improve the nutritional profile of plant-based foods, ensuring they meet desired standards for protein, vitamins, minerals, and other essential nutrients.
• Production enhancement: Process data can be gleaned from production facilities and used to optimise process parameters, achieving a lower operating cost, reduced carbon footprint and higher quality plant-based product.

Who is using AI for plant-based product development?

A few startup companies are already making inroads into this space.

• Climax Foods (USA) is a data science company developing sophisticated machine intelligence tools to unlock smarter paths from plant to product, creating a new generation of plant-based foods that aim to out-compete animal-based predecessors.
• NotCo (Chile) is a company creating algorithms that can learn how to combine an infinite combination of plant-based ingredients to replicate the flavour and texture of animal products.
• Nuritas (Ireland) is developing an AI platform to identify, unlock, clinically test, and patent peptides to turn them into powerful, precise ingredients designed to supercharge natural efficacy.
• Protera Biosciences (France) is building the next generation of functional ingredients for the food industry using protein engineering and Artificial Intelligence.

Challenges of using AI in plant-based product development

• Ingredient diversity and complexity: Plant-based foods often require a wide range of ingredients to mimic animal-based products' taste, texture, and nutritional composition. However, plant ingredients' complexity and diversity present challenges in understanding their interactions and achieving desired outcomes.
• Limited data availability: AI models rely on high-quality data for training and optimisation. However, there may be limited data available for plant-based food ingredients, especially for novel or emerging ingredients and formulations. This scarcity of data can hinder the development and accuracy of AI models, making it challenging to achieve optimal results.
• Sensory perception and subjectivity: Taste, texture, and sensory attributes play a crucial role in consumer acceptance of plant-based food alternatives. However, sensory perception is subjective, varying from person to person. AI algorithms may struggle to accurately capture and replicate the complex nuances of sensory experiences.
• Regulatory and safety considerations: Foods need to comply with various regulations and safety standards which is currently an evolving landscape. Ensuring compliance with these requirements while utilising AI can pose interpretation, compliance, and transparency challenges.

By leveraging AI technologies in the development of plant-based foods, companies have the potential to accelerate product innovation, enhance taste and texture, improve nutritional profiles, and respond to changing consumer preferences. However, the application of these technologies is not without its challenges. These advancements will contribute to the growth and diversification of plant-based food options, providing consumers with more sustainable and healthy choices.