Creation of fibrous plant protein foods

A transition from animal to plant-based protein is required to produce sufficient protein for the growing world population, while at the same time mitigates climate change. Especially the production of meat imposes a burden on the environment. Meat analogues, which are products that are similar to meat in its functionality, can help consumers to lower their meat consumption. The anisotropic, fibrous nature of meat is perhaps the most important characteristic of meat, which can be mimicked by structuring biopolymers, such as proteins and polysaccharides with the shear cell technology. The aim of this thesis is to obtain insight in the key mechanisms that play a role in the transformation of plant-based biopolymer blends into anisotropic/fibrous structures with shear cell technology. These two key mechanisms are the deformation of the two phases present in biopolymer blends, and the subsequent entrapment of this deformation during solidification. It was concluded that successful structure formation requires matching of the properties of the two phases. During structuring at elevated temperature, the two phases are deformed, while subsequent cooling ensures entrapment of the deformed dispersed phase(s) in the (continuous) phase. Ideally, the continuous and dispersed phase have different strength in the final product,. Chapter 2 presents a method to determine the water distribution in soy protein isolate (SPI) – wheat gluten (WG) blends. The concentration of water in each separate phase was directly determined with time-domain nuclear magnetic resonance relaxometry (TD-NMR), and oscillatory rheology was used to indirectly asses the water distribution by determining the viscoelastic properties of the separate phases and the blend. It was shown that water distributes unevenly in SPI-WG blends: more water was absorbed by the SPI as compared to the WG phase. This methodology was developed for SPI-WG blends at room temperature and subsequently also applied to heated and sheared samples in Chapter 3. First, water distribution in the blend after a heat and/or shear treatment was assessed with TD-NMR and the outcomes were then used to predict the viscoelastic properties of the SPI and WG phase in the blend. This yielded insight in the deformability of the two phases in the blend. The viscoelastic properties were measured under conditions that are relevant for structure formation, i.e. during and after heating and shearing. It was shown that the water distribution was hardly affected by a heat or shear treatment, whereas the viscoelastic properties of the two phases changed significantly. The viscoelastic properties of SPI and WG became more similar due to water redistribution in the blend, which allows deformation and alignment of the dispersed phase during structuring. Chapter 4 describes a study using a model blend that mimics soy protein concentrate (SPC). It consists of a relatively pure protein phase, soy protein isolate (SPI), and a soluble, more or less pure polysaccharide phase, pectin. This SPI-pectin blend formed fibrous materials at a similar heating temperature as SPC, being 140°C. Pectin formed the dispersed phase and was deformed when heated and sheared at optimal conditions. Chapter 5 extends the study on structure formation with SPI-pectin blends. Here, the deformation of the dispersed pectin phase and the influence of incorporated air were considered. The fibrous nature of these products appears upon tearing, and originates from detachment through or along the long side of the weak dispersed phase(s), being pectin and/or air. A model based on the rule of mixing was used to predict the mechanical anisotropy based on the volume fraction and the deformation of the weak, dispersed phase. The size and orientation of the dispersed phases, tailored by using different shear rates, were related to differences in fracture behavior when deforming the structures. Besides deformation, the strength and volume fraction of the weak phase(s) were important when composing a blend for fibrous structure formation. In Chapter 6, the behavior of the SPI and pectin phases in a blend was investigated by determining the viscoelastic properties while shearing and heating over time. A closed cavity rheometer (CCR) was used to determine these properties under similar conditions as used during fibrous structure formation. The addition of a small amount of pectin (2.2 wt.%) to a SPI dispersion (41.8 wt.%) resulted in viscoelastic behavior that changed in time during a shear treatment at elevated temperatures. Although one can clearly discern two distinct phases with SEM, the viscoelastic behavior of the SPI-pectin blend is more complex than that of a simple composite material. Chapter 7 demonstrates the importance of the fractionation process on the structuring potential of soy proteins. An enriched soy protein fraction was obtained through an aqueous fractionation process. Those fractions could be used to make fibrous structures when: i) the soy protein fractions were toasted, which is a dry heating step, and ii) when a concentrate (75% protein) was combined with full fat flour, in such a ratio that the protein content was similar to commercial SPC. Toasting results in decreased protein solubility, increased water holding capacity and increased viscosity of the fractions, and these changes turned out to be important for fibrous structure formation. Lastly, literature was reviewed to put all findings in perspective (Chapter 8). An overview is presented of all techniques that are commercially used and currently investigated to create meat-like structures. Structuring techniques are compared in their approach, being either bottom-up, which refers to assembly of structural elements that are then combined, or top-down, which refers to structuring of biopolymer blends using an overall force field. A bottom-up strategy has the potential to resemble the structure of meat most closely, by structuring the molecules including proteins into structural components (e.g. muscle cells) followed by assembly of individual structural components. A top-down strategy is more efficient in its use of resources and is better scalable, but can only create the desired structure on larger length scales. The techniques with a top-down strategy were further investigated by reviewing literature on similar processes outside this particular field of application, i.e. not meant to create fibrous structures. These insights were subsequently translated to the conditions as used in structure formation for meat analogues. Chapter 9 concludes with a general discussion of all results presented in this thesis. The different chapters are integrated in design rules for fibrous structure formation. Furthermore, the complexity encountered when studying material and conditions during fibrous structure formation are discussed. Then, the potential and the challenges for understanding and applying fibrous structure formation with simple shear flow are summarized. The overall societal goal of developing meat analogue food products is to help consumers in the transition from animal-based to a more plant-based diet. The scientific goal to obtain insight in fibrous structure formation with the shear technology as developed in this thesis is of importance, and can be the basis for developing the technology for the next generation meat analogues.</p

Bayesian Methods for Genomic Prediction and Genome-Wide Association Studies combining Information on Genotyped and Non-Genotyped Individuals

Genomic prediction involves using high-density marker genotypes to characterize the impact on performance of every region of the genome, and using that information to predict performance of genotyped selection candidates. This is a relatively new technology and is now gaining traction in personalized medicine and in various livestock industries. Our new approach promises to overcome serious limitations with existing techniques for genomic prediction

New Diabetes Therapies and Diabetic Kidney Disease Progression:the Role of SGLT-2 Inhibitors

Purpose of Review Sodium-glucose co-transporter 2 (SGLT-2) inhibitors have emerged as a promising drug class for the treatment of diabetic kidney disease. Developed originally as glucose-lowering drugs by enhancing urinary glucose excretion, these drugs also lower many other renal and cardiovascular risk factors such as body weight, blood pressure, albuminuria, and uric acid. Results from the EMPA-REG OUTCOME and CANVAS trials show that these salutary effects translate into a reduction in cardiovascular outcomes and have the potential to delay the progression of kidney function decline. This review summarizes recent studies on the mechanisms and rationale of renoprotective effects. Recent Findings Effects of SGLT-2 inhibitors on the kidney are likely explained by multiple pathways. SGLT-2 inhibitors may improve renal oxygenation and intra-renal inflammation thereby slowing the progression of kidney function decline. Additionally, SGLT-2 inhibitors are associated with a reduction in glomerular hyperfiltration, an effect which is mediated through increased natriuresis and tubuloglomerular feedback and independent of glycemic control. Analogous to diabetic kidney disease, various etiologies of non-diabetic kidney disease are also characterized by single nephron hyperfiltration and elevated albuminuria. This offers the opportunity to reposition SGLT-2 inhibitors from diabetic to non-diabetic kidney disease. Clinical trials are currently ongoing to characterize the efficacy and safety of SGLT-2 inhibitors in patients with diabetic and non-diabetic kidney disease. Summary The glucose-independent hemodynamic mechanisms of SGLT-2 inhibitors provide the possibility to extend the use of SGLT-2 inhibitors to non-diabetic kidney disease. Ongoing dedicated trials have the potential to change clinical practice and outlook of high-risk patients with diabetic (and non-diabetic) kidney disease

A Nested Mixture Model for Genomic Prediction Using Whole-Genome SNP Genotypes

We propose a novel model (BayesN) for genomic prediction, where multiple markers in a small segment are simultaneously fitted to jointly capture the effect of major genes (QTL) in the segment. Compared with BayesB, in which the effects of neighboring markers are a prioriassumed to be independent, BayesN gave higher accuracies of prediction and required less computing effort. BayesN is an accurate and practical method for analyzing high-density markers, especially for traits influenced by rare QTL allele

IGF-1 Concentration at a Young Age is Associated with Feed Efficiency in Pigs

The concentration of IGF-I in blood of young pigs has previously been found to be genetically associated with feed efficiency and performance in pigs. To test these associations, data from the ISU selection line for residual feed intake (RFI) were used. Compared to controls, in the line selected for increased efficiency through reduced RFI, a correlated response in the expected downwards direction was observed for juvenile IGF-I. Genetic correlations of IGF-I were 0.63 with RFI and 0.78 with feed conversion ratio. These results confirm that juvenile IGF-I is a good physiological indicator of genetic merit for economically important efficiency traits, particularly since it is measured early in an animal’s life

Genomic selection of purebreds for crossbred performance

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A study on the minimum number of loci required for genetic evaluation using a finite locus model

For a finite locus model, Markov chain Monte Carlo (MCMC) methods can be used to estimate the conditional mean of genotypic values given phenotypes, which is also known as the best predictor (BP). When computationally feasible, this type of genetic prediction provides an elegant solution to the problem of genetic evaluation under non-additive inheritance, especially for crossbred data. Successful application of MCMC methods for genetic evaluation using finite locus models depends, among other factors, on the number of loci assumed in the model. The effect of the assumed number of loci on evaluations obtained by BP was investigated using data simulated with about 100 loci. For several small pedigrees, genetic evaluations obtained by best linear prediction (BLP) were compared to genetic evaluations obtained by BP. For BLP evaluation, used here as the standard of comparison, only the first and second moments of the joint distribution of the genotypic and phenotypic values must be known. These moments were calculated from the gene frequencies and genotypic effects used in the simulation model. BP evaluation requires the complete distribution to be known. For each model used for BP evaluation, the gene frequencies and genotypic effects, which completely specify the required distribution, were derived such that the genotypic mean, the additive variance, and the dominance variance were the same as in the simulation model. For lowly heritable traits, evaluations obtained by BP under models with up to three loci closely matched the evaluations obtained by BLP for both purebred and crossbred data. For highly heritable traits, models with up to six loci were needed to match the evaluations obtained by BLP