Outputs (18)

Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation (2025)
Journal Article
Long, G., Nica-Avram, G., Harvey, J., Lukinova, E., Mansilla, R., Welham, S., Engelmann, G., Dolan, E., Makokoro, K., Thomas, M., Powell, E., & Goulding, J. (2025). Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation. Food Policy, 131, Article 102826. https://doi.org/10.1016/j.foodpol.2025.102826

Deprivation pushes people to choose cheap, calorie-dense foods instead of nutritious but expensive alternatives. Diseases, such as obesity, cardiovascular disease, and diabetes, resulting from these poor dietary choices place a significant burden on... Read More about Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation.

Wet spinning of sodium carboxymethyl cellulose-sodium caseinate hydrogel fibres: relationship between rheology and spinnability (2025)
Journal Article
Vaniyan, L., Borah, P. K., Pavlovskaya, G. E., Terrill, N., Reid, J. E., Boehm, M., Prochasson, P., Nicholson, R. A., Baier, S., & Yakubov, G. E. (2025). Wet spinning of sodium carboxymethyl cellulose-sodium caseinate hydrogel fibres: relationship between rheology and spinnability. Soft Matter, 21(20), 3946-3956. https://doi.org/10.1039/d4sm00705k

Mimicking the fibrous structures of meat is a significant challenge as natural plant protein assemblies lack the fibrous organisation ubiquitous in mammalian muscle tissues. In this work, wet-spun hydrogel fibres resembling the anisotropic fibrous mi... Read More about Wet spinning of sodium carboxymethyl cellulose-sodium caseinate hydrogel fibres: relationship between rheology and spinnability.

Gaussian mixture model clustering allows accurate semantic image segmentation of wheat kernels from near-infrared hyperspectral images (2025)
Journal Article
Kartakoullis, A., Caporaso, N., Whitworth, M. B., & Fisk, I. D. (2025). Gaussian mixture model clustering allows accurate semantic image segmentation of wheat kernels from near-infrared hyperspectral images. Chemometrics and Intelligent Laboratory Systems, 259, Article 105341. https://doi.org/10.1016/j.chemolab.2025.105341

In this study, an ad-hoc image processing pipeline has been developed and proposed for the purpose of semantically segmenting wheat kernel data acquired through near-infrared hyperspectral imaging (HSI). The Gaussian Mixture Model (GMM), characterize... Read More about Gaussian mixture model clustering allows accurate semantic image segmentation of wheat kernels from near-infrared hyperspectral images.

It tastes sweeter when melted: Exploring the impact of food temperature on tongue temperature and perceived sweetness/vanilla (2025)
Journal Article
McNeill, H., Ford, R., Fisk, I., Thibodeau, M., Liu, G., Doyennette, M., & Yang, Q. (2025). It tastes sweeter when melted: Exploring the impact of food temperature on tongue temperature and perceived sweetness/vanilla. Science Talks, 13, Article 100424. https://doi.org/10.1016/j.sctalk.2025.100424

The relationship between perceived sweetness intensity and temperature of food is complex. Previous research on the effect of temperature on sweetness perception primarily focused on single solutions. This study aimed to address the gap by using an i... Read More about It tastes sweeter when melted: Exploring the impact of food temperature on tongue temperature and perceived sweetness/vanilla.

Effects of feed nutrients on growth, development and the deposition of protein and fat in Tenebrio molitor larvae (2025)
Journal Article
Tamim, B., Salter, A., Parr, T., & Brameld, J. (2025). Effects of feed nutrients on growth, development and the deposition of protein and fat in Tenebrio molitor larvae. Journal of Insects as Food and Feed, 1-14. https://doi.org/10.1163/23524588-00001331

An understanding of the impact of dietary nutritional composition on growth, development and composition of Tenebrio molitor larvae (mealworms) could help optimise production systems. Replicate containers of mealworms fed for 24 days on synthetic cel... Read More about Effects of feed nutrients on growth, development and the deposition of protein and fat in Tenebrio molitor larvae.

Freeze-thaw stability of oilseed rape oleosome emulsions (2025)
Journal Article
Bramante, F., di Bari, V., Adams, G., Beaudoin, F., Waschatko, G., Jakobi, R., Billecke, N., & Gray, D. (2025). Freeze-thaw stability of oilseed rape oleosome emulsions. Journal of Food Engineering, 392, Article 112471. https://doi.org/10.1016/j.jfoodeng.2025.112471

This work investigated the stability of natural oleosome emulsions on freeze-thawing. Oleosomes were recovered from oilseed rape seeds following an aqueous extraction process using sodium bicarbonate (0.1 M). The final emulsions pH was adjusted to 9,... Read More about Freeze-thaw stability of oilseed rape oleosome emulsions.

Assessing Water Content of the Human Colonic Chyme Using the MRI Parameter T1: A Key Biomarker of Colonic Function (2025)
Journal Article
Dellschaft, N., Murray, K., Ren, Y., Marciani, L., Gowland, P., Spiller, R., & Hoad, C. (2025). Assessing Water Content of the Human Colonic Chyme Using the MRI Parameter T1: A Key Biomarker of Colonic Function. Neurogastroenterology and Motility, 37(4), Article e14999. https://doi.org/10.1111/nmo.14999

Background
The human colon receives 2 L of fluid daily. Small changes in the efficacy of absorption can lead to altered stool consistency with diarrhea or constipation. Drugs and formulations can also alter colonic water, which can be assessed using... Read More about Assessing Water Content of the Human Colonic Chyme Using the MRI Parameter T1: A Key Biomarker of Colonic Function.

Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots (2025)
Journal Article
Kaya Kaçar, H., Kaçar, Ö. F., & Avery, A. (2025). Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots. Nutrients, 17(2), Article 206. https://doi.org/10.3390/nu17020206

Background/Objectives: With the rise of artificial intelligence (AI) in nutrition and healthcare, AI-driven chatbots are increasingly recognised as potential tools for generating personalised diet plans. This study aimed to evaluate the capabilities... Read More about Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots.