Consumer eating habits are rapidly evolving due to heightened awareness of health, environmental sustainability, and ethical considerations. More consumers are adopting flexitarian diets, seeking to reduce animal-based food intake by incorporating plant-based alternatives, such as meat, fish, egg, and dairy substitutes—without sacrificing the quality and sensory characteristics of traditional animal-derived products. To cater to this shift, it is crucial to understand how the texturization of alternative proteins affects consumer acceptance, nutritional value, and cost- effectiveness, especially in the Asian context. This presentation will provide insights into SIFBI’s approach to sustainable future food production, focusing on its flagship initiative, the Alternative Protein Development Platform (APDP). The program seeks to develop innovative food ingredients from alternative protein sources—such as grains, fungi, and yeast—with specific functionalities tailored for a range of food applications. The talk will also explore the impact of various processing techniques on the nutritional, sensory, and functional properties of these proteins and introduce the Food Tech Innovation Center— a cutting-edge pilot-scale facility aimed at supporting companies and research institutions in accelerating the commercialization and scale-up of alternative protein-based foods.

Present meat production system has been dependent on grain cultivation and livestock breeding, which have caused enormous greenhouse gas emission. Therefore, research and development of "cellular agriculture", which produces food from isolated cells, has become popular. We have applied our original technology for regenerative therapy, “cell sheet-based tissue engineering” to cultured meat production. Cell sheets can be harvested from temperature-responsive culture surfaces only by lowering temperature. The advantage of the technology is that they do not contain any scaffolds. Chick and bovine myoblast sheets have been harvested from the temperature-responsive culture dishes and layered into three-dimensional meat-like tissues. On the other hand, animal-free and low-cost culture media is critical for producing sustainable cultivated meat. The major nutrients such as glucose, amino acids and vitamins contained in the animal cell culture medium are conventionally originated from grains, which need various chemical fertilizers and pesticides for their cultivation. Huge amount of fossil fuel is consumed for their production, leading additional greenhouse gas emission. Furthermore, the culture waste media will also cause siginificant environmental load. To clear these problems, we have proposed “Circular Cell Culture (CCC) system” using microalgae and animal cells. The nutrients are extracted from microalgae in place of grains, then target animal cells are successfully cultured with these microalgae extracts. As alternative of FBS or recombinant proteins for animal cell growth, we have used supernatant obtained from growth factor producing cells. Additionally, animal cell culture waste medium has been up-cycled by culturing microalgae. Microalgae used ammonia which is a typical waste of animal cells and proliferated. The proliferated microalgae were also used for nutrient extraction as the next cycle. Thus, we have developed CCC system by repeating these processes. CCC system will realize more sustainable cultivated meat production in future.

In the rapidly advancing field of food research, particularly within alternative proteins, the need for measurement-based insights is more urgent than ever. Traditional trial-and-error methods are no longer sufficient to address the pressing challenges in this area. Instead, precise, early-stage measurements are key to screening recombinant proteins for functionality and better predicting their performance in final applications, ultimately saving time and resources. I will highlight how building an innovation engine through academic partnerships and leveraging grants has fueled this work, allowing us to explore new structuring technologies beyond traditional extrusion and conventional protein targets. This presentation will showcase how integrating foundational research focused on method development can drive innovations in plant-based and precision fermentation-derived proteins, helping to overcome constraints such as cost and market timelines. I will demonstrate how a measurement-focused approach served as a powerful discovery engine for the rational design of plant-based meat analogues. By linking formulation strategies with detailed analyses of texture, mouthfeel, and other sensory attributes, we were able to accelerate the development of products. This approach also enabled us to explore new structuring technologies beyond traditional extrusion and conventional protein targets. Additionally, it provides a strong basis for intellectual property protection, helping to safeguard breakthroughs and ensuring their successful market entry.

Abstract: Colloidal interactions are ubiquitous in food systems but nevertheless, often difficult to characterize. Herein, I will present our recent efforts in developing novel tools for the study of colloidal building blocks [1-3], their interaction [4] and self-assembly [5]. In particular, I will present a novel protein-mimetic model system that enables the deployment of small-angle X-ray scattering (SAXS) [6]. Extracting detailed information on colloidal interaction from scattering curves typically requires fitting with a selected model and closure relation. However, the applicability of this approach is constrained by the limited number of existing models that can be fitted analytically, as well as the narrow operating range for which the models are valid. Recently, we have demonstrated a proof of concept for using an artificial neural network (ANN) trained on SAXS curves obtained from Monte Carlo (MC) simulations to predict values of the effective macroion valency (Zeff) and the Debye length (κ–1) for a given SAXS profile. This ANN, which was trained on 200,000 simulated SAXS curves, was able to predict values of Zeff and κ–1 for a test set containing 25,000 simulated SAXS curves, where most predicted values had errors smaller than 20%. Subsequently, an ANN was used as a surrogate model in a Markov chain Monte Carlo sampling algorithm to obtain maximum a posteriori estimates of Zeff and κ–1, as well as the associated confidence intervals and correlations between Zeff and κ–1 for an experimentally obtained SAXS profile. This platform now serves us to elucidate complex colloidal phenomena, such as the role of hydrotropes for protein solubility. [1] Nanoscale, vol. 12, pp. 12007 – 12013, 2020. [2] Chemistry of Materials, vol. 31, pp. 6750 – 6758, 2019 [3] Chemistry of Materials vol. 32, pp. 3701 – 3706, 2020 [4] Langmuir, vol. 35, pp. 16605 – 16611, 2019 [5] Nanoscale, vol. 11, pp. 11107 – 11113, 2019 [6] JACS Au, vol. 4, pp. 2492-3500, 2024