As the global population continues to rise, so does the demand for more protein-rich foods – putting pressure on producers and the planet. The ball is already rolling with AI supporting protein innovation, and we’re just beginning to unlock its full potential in farming and food production.
AI-powered digital agriculture is transforming protein crop cultivation, enabling precision agriculture techniques that monitor soil health, predict weather patterns, and detect pests in real time. This continuous monitoring ensures that crops receive optimal care, leading to higher yields and better-quality produce.
Optimising crops also leads to more sustainable farming practices. It’s about getting more value from less resources. For example, AI facilitates water and fertiliser efficiency by anticipating each crop’s precise needs. This targeted approach boosts productivity, while minimising waste.
Beyond cultivation, AI has the potential to revolutionise plant protein processing for developing into ingredients and consumer-ready products. For instance, AI models can improve the efficiency of traditional protein extraction methods, while maximising the chickpea protein’s integrity and nutritional value.
AI can also analyse consumer preferences and market trends to create plant-based protein products that best match taste, texture, and nutritional expectations. By simulating how different protein combinations behave under various cooking and processing conditions, AI can predict structural and functional changes in the proteins.
This enables product formulations that closely replicate the texture, taste, and nutritional profile of animal proteins, increasing choice for consumers.
AI could soon be used to help us choose which crops to plant. AI-driven tools can identify high-yielding, protein-rich varieties that require fewer resources. Machine learning algorithms analyse vast datasets to predict how different crop varieties will perform in different conditions.
This technology could optimise crop rotations and improve soil health, leading to more resilient and sustainable crop selection. In turn, this can help farmers adapt to climate change while reducing the environmental footprint of crops.
Our AI-driven food innovation is at the forefront of integrating AI into food innovation. For example, our MAGDA++ platform leverages AI to predict the yield, taste and functional properties of different plant proteins. This predictive capability accelerates new ingredient and product development, reducing time-to-market while fostering innovation.
These new digital agriculture and food processing technologies will position Australia as a leader in sustainable food production. And we’re working with industry to ensure that AI-driven solutions are practical, scalable, and aligned with market needs.
The future of AI in plant-based protein innovation is promising. AI-driven analytics are expected to enhance supply chain efficiency, reducing waste and ensuring the timely delivery of fresh products to market. Future research may also seek to improve the functionalities of plant-based proteins, such as better emulsification properties or heat stability, broadening their application into different products.
For some, the thought of AI can be daunting, but in the plant world it is set to make an important impact.
