- Raw Materials, Ingredients, & Inputs
- Crop development
- Ingredient optimization
Animal proteins have unique sequences and structures that create the familiar attributes found in animal-based products, such as balanced amino acid composition, fibrous texture, juiciness, good mouthfeel, and changes in appearance, texture, and flavor upon cooking. Because of the inherent differences between animal and non-animal proteins, the functionalities associated with animal-based meat, dairy, and egg products are challenging to reproduce with non-animal proteins. However, innovations that leverage promising plant-based or fermentation-derived protein functionalities, like blending wheat gluten with other proteins to promote end product cohesiveness, have created products with qualities that more closely resemble animal-based foods.
Unfortunately, knowledge of non-animal protein functionality is limited, especially outside of soybean, pea, and wheat proteins. In particular, data that connects amino acid composition/sequence and overall protein structure to a protein’s performance is not openly accessible. Moreover, improved comprehension of the contributions of individual protein fractions to an enriched protein powder’s quality is needed. While animal and non-animal proteins have distinct sequences and structures, connecting the dots between these intrinsic properties and how they affect end-product properties would help plant-based products reach sensory parity with animal-based products.
Rigorous evaluations of the sequences, structures, and functionalities of proteins under standardized conditions would propel the application of non-animal proteins. A database with this information should be crafted so that researchers can quickly determine how the molecular and physical properties of proteins affect their functionalities and end-product performance. Some companies claim to have these databases and use them to boost product innovation. However, an open-access database that accumulates this research for many different crops and fermentation technologies will expand access to a much wider set of academic and commercial researchers and reduce duplication of efforts. Multiple researchers could contribute to the database with standardized evaluation parameters and make exact comparisons between protein types and sources. This information could be further expanded by including how specific crop and seed qualities, raw ingredient suppliers, and ingredient processing parameters affect protein qualities and performance. Moreover, collecting and comparing more data points could ultimately be paired with machine learning to predict novel protein performance without the need to conduct as many empirical functionality tests.
Creating an open-access database with advanced protein information would reduce duplicative efforts between companies and lead to more innovative and diverse products. Equipped with a sophisticated understanding of particular structural attributes and how they contribute to food production, researchers can develop mechanistic insights to improve their predictive capacity for developing novel ingredients or processing methods to improve protein performance in alternative protein foods. This database would allow food scientists to optimize protein combinations to achieve desirable attributes, understand and adapt to or mitigate the batch-to-batch variations between protein powders from different suppliers, and innovate ways to reduce resource-intensive downstream protein processing and manufacturing.
Upstream innovations would be more directed as well. Knowledge of the contributions of amino acid compositions, sequences, and interactions would allow researchers to identify specific protein properties of interest. Novel crop exploration and breeding could be geared directly toward creating optimal proteins for plant-based and fermentation-derived products. Additionally, recombinant protein technology could develop and scale proteins with compelling properties even if plants do not efficiently synthesize them.
- NotCo’s Giuseppe algorithm is a machine learning software that maps the amino acid structures of different animal and plant proteins to their functionality in plant-based foods.
- JUST (formerly Hampton Creek) has also claimed to have developed plant protein functionality databases that inform their product development.
- Open-access studies like this techno-functional comparison of blue lupin and white lupin (Vogelsang-O’Dwyer et al. 2020) demonstrate what could be accomplished through an open-access database.
Find information on nutrition, functionality, price, sourcing, and consumer perceptions of plant protein sources for plant-based meat.
GFI scientists explain how ingredients derived from plants and fermentation can be used to create animal-free meat, egg, and dairy alternatives.
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Open-access product formulation specifications could provide clear metrics and objectives for product developers on attributes like taste, price, nutrition, and ingredient ratios.
Fibers from non-traditional texturization techniques like electrospinning, jet spinning, or blow spinning could impart texture throughout a product even if they don’t comprise the bulk of the end product, which…
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…
Relevant research grants
Learn about Trophic LLC’s research developing plant-based meat ingredients from red seaweed protein through GFI’s grant program.
Dr. Caroline Mellinger at The Brazilian Agricultural Research Corporation (EMBRAPA) is exploring bean protein as ingredients for plant-based meat.
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