Plant-based food manufacturers often struggle with batch-to-batch ingredient inconsistency and variability between suppliers. Better analytical tools for predicting plant-based ingredient performance could improve manufacturing efficiency and create more transparent ingredient markets. Tools are needed to predict how ingredients will perform after various processing methods and in end-product applications like plant-based meat and dairy.
Processing crops into flours, isolates, and concentrates often relies on chemical and mechanical methods. Biological processing techniques may impart the desired composition and molecular structure for optimal functionality with increased precision, lower cost, and greater suitability for small-scale processing. Biological processing techniques include using enzymes to fine-tune functional properties like solubility, gelling capacity, and fat- and water-binding capacity or using microbial fermentation to convert plant protein feedstocks into more functional forms.
Many alternative protein companies use similar inputs, but individually lack the purchasing power to negotiate favorable contract terms. A pooled procurement/group purchasing mechanism for ingredients, inputs (growth factors, media, etc.), and feedstocks would help reduce costs and increase industry leverage.
Techno-economic models are critical for process design and cost of goods projections. Open-access models based on generalized or exemplar processes with standardized unit operations and designs can form the foundation for individual companies’ work, reducing duplicative effort. Furthermore, techno-economic models can identify key cost drivers and opportunities for process improvements to guide future research efforts. The independent research consultancy CE Delft recently published a cultivated meat techno-economic analysis. However, similar efforts are needed for fermentation-derived and plant-based meat production.
After identifying specific target molecules or desired functionalities in animal-derived foods, scientists can work backward, mining microbial sequences for candidate molecules in the microbial realm that might provide similar functionality. This process can also elucidate the pathways that produce these molecules and inform strategies for designing microbial strains that produce these molecules at scale.
There is a need for deeper fundamental research on the relationships between protein sequence, structure, functionality, and ultimately performance in plant-based food products. While several plant-based companies have claimed a competitive advantage from building databases of functional properties and applying machine learning to inform protein selection and formulation, these capabilities remain proprietary and the efforts duplicative. An open-access database could provide functional and characterization data using standardized methods to facilitate direct performance comparisons among proteins and train predictive algorithms.
This peer-reviewed article discusses how advances from the biomedical cell culture industry can contribute to the development of cultivated meat.