Biology subjects

Darwin, E. C.

Publications and source records attributed to Darwin, E. C..

6 recordsLinked to original sources

bioRxiv2026

Distinct mechanical signatures of dairy and plant-based cheeses

Plant-based cheeses account for about 1% of U.S. retail cheese sales and often fail to match the texture and flavor of dairy cheese. Here we compare three commercial dairy and plant-based pairs, cheddar, feta, and mozzarella, with texture profile analysis (n = 60), tension, compression, and shear tests (n = 219), constitutive artificial neural networks, and a consumer panel (n = 306). Plant mozzarella is at least five times stiffer than dairy mozzarella at small strain, yet softer and less cohesive under 50% compression. Plant feta matches the initial stiffness of dairy feta but shows a peak in its shear response. Plant cheddar differs in both stiffness and shear response. Model discovery selects first-invariant models for all six cheeses, but no model term separates the two groups. Consumers rate 68--78% of attributes "just about right" for dairy cheeses and 29--38% for plant-based cheeses. These single-product comparisons define product-specific targets for plant-based cheese design.

bioengineering↗

bioRxiv2026

Mechanical, rheological, and sensory characterization of lion's mane mushroom steak

Mushrooms are increasingly recognized as delicious, nutritious, and sustainable foods, with an intrinsic umami flavor and fibrous microstructure that can approximate meat-like texture. Among them, lions mane mushroom has emerged as a promising candidate for whole-cut meat alternatives. Yet, its mechanical, rheological, and sensory properties remain largely unquantified. Here we show that a minimally processed lions mane mushroom steak exhibits distinctive mechanical, rheological, and sensory characteristics that position it favorably among existing meat alternatives. Despite its pronounced fibrous morphology, lions mane steak behaves predominantly as an isotropic material under both mechanical loading and rheological testing, with elastic stiffnesses of E = 33.2 kPa and E = 34.8 kPa in-plane and cross-plane. A fundamental challenge in alternative protein development is to understand how these measurable physical properties relate to human texture perception. In a complementary sensory survey, n = 21 participants ranked lions mane steak as more fatty, fibrous, moist, and meaty than eight animal- and plant-based comparison meats. Strikingly, our perceived sensory softness correlates inversely with our experimentally measured mechanical stiffness ({tau}=-0.60, p = 0.02) and rheological loss modulus ({tau}=-0.56, p = 0.03). Taken together, our results demonstrate that lions mane steak combines favorable mechanical performance with desirable sensory attributes and provide a mechanistic link between physics and taste. Our findings highlight lions mane mushroom as a compelling whole-cut alternative protein and underscore the value of integrated mechanical-sensory characterization for rational food design.

bioengineering↗

bioRxiv2025

Biaxial testing and sensory texture evaluation of plant-based and animal deli meat

Animal agriculture is one of the largest contributors to global carbon emissions. Plant-based meats offer a sustainable alternative to animal meat; yet, people are reluctant to switch their diets and spending habits, in large due to the taste and texture of plant-based meats. Deli meat is a convenient form of protein commonly used in sandwiches, yet little is known about its material or sensory properties. Here we performed biaxial testing with multiple different stretch ratios of four plant-based and four animal deli meats and fit accurate material models to the resulting stress-stretch data. Strikingly, the plant-based products, turkey, ham, deli, and prosciutto, with stiffnesses of 378 {+/-} 15 kPa, 343 {+/-} 62 kPa, 213 {+/-} 25 kPa, and 113 {+/-} 56 kPa, were more than twice as stiff as their animal counterparts, turkey, chicken, ham, and prosciutto, with 134 {+/-} 46 kPa, 117 {+/-} 17 kPa, 117 {+/-} 21 kPa, and 49 {+/-} 21 kPa. In a complementary sensory texture survey, n = 18 participants were able to correlate the physical stiffness with the sensory brittleness, with Spearmans correlation coefficient of{rho} = 0.857 and p = 0.011, but not with the sensory softness or hardness. Notably, the participants perceived all four plant-based products as less fibrous, less moist, and less meaty than the four animal products. Our study confirms the common belief that plant-based products struggle to meet the physical and sensory signature of animal deli meats. We anticipate that integrating rigorous mechanical testing, physics-based modeling, and sensory texture surveys could shape the path towards designing delicious, nutritious, and environmentally friendly meats that mimic the texture and mouthfeel of animal products and are healthy for people and for the planet. Data and code are freely available at https://github.com/LivingMatterLab/CANN.

bioengineering↗

bioRxiv2024

Texture profile analysis and rheology of plant-based and animal meat

Plant-based meat can help combat climate change and health risks associated with high meat consumption. To create adequate mimics of animal meats, plant-based meats must match in mouthfeel, taste, and texture. The gold standard to characterize the texture of meat is the double compression test, but this test suffers from a lack of standardization and reporting inconsistencies. Here we characterize the texture of five plant-based and three animal meats using texture profile analysis and rheology, and report ten mechanical features associated with each products elasticity, viscosity, and loss of integrity. Our findings suggest that, of all ten features, the stiffness, storage, and loss moduli are the most meaningful and consistent parameter to report, while other parameters suffer from a lack of interpretability and inconsistent definitions. We find that the sample stiffness varies by an order of magnitude, from 418.9{+/-}41.7kPa for plant-based turkey to 56.7{+/-}14.1kPa for tofu. Similarly, the storage and loss moduli vary from 50.4{+/-}4.1kPa and 25.3{+/-}3.0kPa for plant-based turkey to 5.7{+/-}0.5kPa and 1.3{+/-}0.1kPa for tofu. All three animal products, animal turkey, sausage, and hotdog, consistently rank in between these two extremes. Our results suggest that-with the right ingredients, additives, and formulation-modern food fabrication techniques can create plant-based meats that successfully replicate the full viscoelastic texture spectrum of processed animal meat.

bioengineering↗

bioRxiv2024

Got meat? The mechanical signature of plant-based and animal meat

Eating less meat is associated with a healthier body and planet. Yet, we remain reluctant to switch to a plant-based diet, largely due to the sensory experience of plant-based meat. Food scientists characterize meat using a double compression test, which only probes one-dimensional behavior. Here we use tension, compression, and shear tests-combined with constitutive neural networks-to automatically discover the behavior of eight plant-based and animal meats across the entire three-dimensional spectrum. We find that plant-based sausage and hotdog, with stiffnesses of 95.9{+/-}14.1kPa and 38.7{+/-}3.0kPa, successfully mimic their animal counterparts, with 63.5{+/-}45.7kPa and 44.3{+/-}13.2 kPa, while tofurky is twice as stiff, and tofu is twice as soft. Strikingly, a complementary food tasting survey produces in nearly identical stiffness rankings for all eight products ({rho} =0.833, p=0.015). Probing the fully three-dimensional signature of meats is critical to understand subtle differences in texture that may result in a different perception of taste. Our data and code are freely available at https://github.com/LivingMatterLab/CANN

bioengineering↗

bioRxiv2023

Discovering the mechanics of artificial and real meat

Artificial meat is an eco-friendly alternative to real meat that is marketed to have a similar taste and feel. The mechanical properties of artificial meat significantly influence our perception of taste, but how precisely the mechanics of artificial meat compare to real meat remains insufficiently understood. Here we perform mechanical tension, compression, and shear tests on isotropic artificial meat (Tofurky(R) Plant-Based Deli Slices), anisotropic artificial meat (Daring Chickn Pieces) and anisotropic real meat (chicken) and analyze the data using constitutive neural networks and automated model discovery. Our study shows that, when deformed by 10%, artificial and real chicken display similar maximum stresses of 21.0 kPa and 21.8 kPa in tension, -7.2 kPa and -16.4 kPa in compression, and 2.4 kPa and 0.9 kPa in shear, while the maximum stresses for tofurky were 28.5 kPa, -38.3 kP, and 5.5 kPa. To discover the mechanics that best explain these data, we consulted two constitutive neural networks of Ogden and Valanis-Landel type. Both networks robustly discover models and parameters to explain the complex nonlinear behavior of artificial and real meat for individual tension, compression, and shear tests, and for all three tests combined. When constrained to the classical neo Hooke, Blatz Ko, and Mooney Rivlin models, both networks discover shear moduli of 94.4 kPa for tofurky, 35.7 kPa for artificial chickn, and 21.4 kPa for real chicken. Our results suggests that artificial chicken succeeds in re-producing the mechanical properties of real chicken across all loading modes, while tofurky does not, and is about three times stiffer. Strikingly, all three meat products display shear softening and their resistance to shear is about an order of magnitude lower than their resistance to tension and compression. We anticipate our study to inspire more quantitative, mechanistic comparisons of artificial and real meat. Our automated-model-discovery based approach has the potential to inform the design of more authentic meat substitutes with an improved perception of taste, with the ultimate goal to reduce environmental impact, improve animal welfare, and mitigate climate change, while still offering the familiar taste and texture of traditional meat. Our source code, data, and examples will be available at https://github.com/LivingMatterLab/CANNs.

bioengineering↗