瓦赫宁根大学和研究中心

The growing demand for plant-based food systems has led to increased interest in legume proteins as natural emulsifiers. However, their poor solubility, slow interfacial adsorption, and limited emulsion stability restrict broader applications. Therefore, in this study, the effects of protein-glutaminase (PG)-induced deamidation on the physicochemical and interfacial properties of common vetch protein isolate (CVPI) and pea protein isolate (PPI) were systematically investigated to enhance their emulsifying performance. Enzymatically modified samples (ECVPI and EPPI) were prepared and compared with untreated samples. Deamidation markedly improved protein dispersibility and solubility, reflected by smaller particle sizes, increased surface hydrophobicity, and more negative ζ-potentials. Interfacial tensiometry and dilatational rheology demonstrated that ECVPI and EPPI rapidly adsorbed at the oil-water interface, forming dense and viscoelastic interfacial films. Deamidation (ECVPI & EPPI) generated an interfacial network with enhanced stiffness and resistance to deformation, indicating that deamidation enhanced intermolecular interactions. At the emulsion level, PG treatment significantly enhanced the interfacial activity of deamidated proteins, leading to decreased droplet sizes and improved stabilization of droplets upon storage. ECVPI-stabilized emulsions exhibited the smallest and most homogeneous droplets with strong electrostatic stabilization and minimal flocculation. These findings demonstrate that PG-induced deamidation effectively alters the interfacial behavior of legume proteins, providing a controlled design of stable plant-based emulsions.

The protein aggregates present in plant protein powders, such as soy and pea protein isolates, often lead to high friction in liquid foods containing these ingredients. This can contribute to undesirable mouthfeel. In the work presented in this paper, we evaluated two types of food ingredients with potential to compensate for this high friction in models that can be considered representative of plant protein beverages: oil droplets (incorporated as O/W emulsions) and polysaccharides, including xanthan gum, guar gum and carboxymethyl cellulose (CMC). We measured the tribological properties of the dispersions and linked the results to mouthfeel. Stable oil droplets effectively improved the lubrication of dispersions with large plant protein aggregates, based on a synergistic effect between the oil droplets and the protein aggregates. In contrast, when polysaccharides were added to protein dispersions, the lubrication behavior remained the same, indicating that lubrication was dominated by protein aggregates. The effect of oil droplets on sensory perception was concentration-dependent; 3% oil content reduced friction and increased creaminess and mouthcoating, whereas 0.5% oil content had limited sensory impact. Polysaccharides increased thickness, creaminess, and mouthcoating. Since polysaccharides did not affect lubrication, these sensory changes were primarily driven by bulk rheology. Correlation network analysis further revealed that relationships between friction and sensory attributes depended on the size of the protein aggregates. Reducing particle size slightly influenced lubrication properties, but strongly reduced grittiness. In the case of large protein aggregates, high grittiness perception masked the effect of oil and polysaccharides on creaminess and mouthcoating, thereby weakening the relationships between these attributes and friction. For samples with small protein aggregates and thus low grittiness, negative correlations between friction coefficient and the sensory attributes creaminess and mouthcoating were obtained. Overall, these findings show that lubrication mechanisms observed in single-component systems cannot be directly translated to complex beverage systems containing plant protein aggregates. Tribology can explain some sensory differences in these systems, but does not fully capture particle size-related effects. Using tribology results as a direct predictor for a sensory profile is therefore not always suitable.

Vertical farming (VF) systems require massive amounts of electricity, primarily for artificial lighting, resulting in high carbon emissions and challenging profitability. Although integrating on-site renewable energy (RE) offers a promising pathway, its effectiveness depends on the joint design of cultivation intensity and energy infrastructure, which remains underexplored. This study develops a multi-objective VF-RE co-design framework that jointly optimises cultivation intensity through lighting capacity, together with photovoltaic panels, wind turbines, and battery storage using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Annual net profit (ANP) and grid-related CO2 emissions are defined as the optimisation objectives and evaluated using an integrated VF-RE model linking crop growth, indoor climate, electricity demand, RE generation, battery storage, and grid electricity exchange. Case studies in the Netherlands and Spain demonstrate that jointly optimising cultivation intensity and RE infrastructure expands the attainable Pareto design space compared with conventional fixed-light configurations. Fixed low lighting limits profitability, whereas excessive lighting increases electricity demand faster than the associated revenue gains. For the TOPSIS-selected designs (Technique for Order Preference by Similarity to Ideal Solution), RE integration reduces emission intensities by approximately 44–53% relative to grid-only baselines and lowers electricity cost intensities by 46–73% compared with a literature benchmark. Scenario analyses further show that lettuce price, battery cost, and electricity price influence the preferred VF-RE configuration by altering the economic trade-offs between cultivation intensity and RE-storage investment. Overall, the results highlight that jointly optimising cultivation intensity and RE infrastructure is essential for improving both the economic and environmental performance of VF systems.

Robotic handling can reduce postharvest losses, but its mechanical impacts on fresh produce require evaluation for hidden damage. This study assessed the effects of robotic gripper design (soft silicone vs. rigid rubber; two vs. three fingers) and vacuum pressure (1.8–3.0 bar) on the quality of tomato (Solanum lycopersicum) and strawberry (Fragaria × ananassa) fruit. Across three experiments, fruit were subjected to controlled gripping treatments, followed by macro-scale measurements (respiration, weight loss, colour, firmness) and contact-area-specific analyses (hardness, electrolyte leakage, polyphenol oxidase [PPO] activity, and early gene expression). Red-ripe tomatoes were separated into two stages based on colour a* values, with higher a* values representing the more advanced red-ripe stage. Tomatoes at the more advanced red-ripe stage handled with the rigid two-finger gripper exhibited increased respiration and softening, with no detectable cell wall degradation. In strawberries, damage incidence and severity were higher with the rigid gripper and the soft three-finger gripper. Compared with the soft two-finger gripper, the soft three-finger gripper caused greater localized softening at both pressures and greater weight loss at 3.0 bar. Even in the absence of visible injury, microscopy, biochemical and molecular analyses revealed cuticle disruption, increased electrolyte leakage, and early activation of stress-related pathways. Localized increases in PPO activity accompanied greater colour changes during storage. Findings highlight that cultivar traits, gripper configuration, and operating pressure determine the extent of injury. Multi-scale evaluation is essential for detecting latent damage and optimising robotic handling to minimise quality loss in fresh produce.

During the late 20th century, evolutionary biology contributed to the notion that much of the genome is nonfunctional. This particularly applied to endogenous retroviruses (ERVs), which were seen as parasitic elements. However, growing evidence shows that ERVs play diverse and important roles, especially in gene regulation, development, and immunity. This article examines whether such findings pose a challenge to evolutionary biology, using Imre Lakatos’ model of scientific growth, which judges research programs by their ability to direct fruitful research and anticipate new data. I argue that the current number of known functional ERVs does not significantly contradict the evolutionary program’s low expectations, but that the degree of functionality will rise to anomalous levels if the recent trend of new discoveries continues. Moreover, the evolutionary program has contributed little to the discovery of the functions that have been found so far, except for a few cases where functionality was implied by sequence conservation. Nevertheless, evolutionary biology does possess the theoretical tools to retroactively produce mechanistic explanations for the origin of functional ERVs. The most common type of function—tissue-specific regulation of nearby genes—can be neatly explained in a neo-Darwinian fashion if the newly inserted ERVs immediately exerted a beneficial effect on host gene expression. This model predicts, often successfully, that the relevant transcription factor binding sites are present in the family’s consensus sequence, but has been criticized because ERV insertions with strong regulatory effects are nearly always deleterious. Another notable ERV function is facilitating cell–cell fusion in the placenta. Here, the program is forced to invoke the independent origin of ERV-derived fusion proteins in different mammalian lineages. Taken together, this evaluation yields an ambivalent verdict on the success of the evolutionary research program.