Topic Editors

College of Animal Science, South China Agricultural University, Guangzhou 510642, China
College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
College of Animal Science and Technology, China Agricultural University, Beijing 100193, China

Research on Companion Animal Nutrition

Abstract submission deadline
31 October 2024
Manuscript submission deadline
31 December 2024
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Topic Information

Dear Colleagues,

Companion animals play an important role in our lives. Nutrition is one of the main factors related to the maintenance of the health of companion animals. Malnutrition or overnutrition may lead to health problems in companion animals, such as gastrointestinal diseases, renal diseases, dermatological diseases, obesity and diabetes. Researchers are searching for healthier pet foods to prolong animals’ lifespan and improve their quality of life. Therefore, a deep understanding of companion animal nutrition is important for the development of novel pet foods to maintain pet health. The goal of this Topic is to share information related to companion animal nutrition. Subtopics may include but are not limited to:

(1) The nutritional requirements of companion animals

(2) Nutrient metabolism in companion animals

(3) The relationship between nutrients and diseases in companion animals

(4) Ingredients and additives used in pet foods

Dr. Baichuan Deng
Dr. Lian Li
Dr. Yun Ji
Topic Editors

Keywords

  • companion animal
  • pet nutrition
  • pet food
  • cat
  • dog
  • exotic pet
  • working animals

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Animals
animals
3.0 4.9 2011 18.1 Days CHF 2400 Submit
Antioxidants
antioxidants
7.0 10.6 2012 13.9 Days CHF 2900 Submit
Metabolites
metabolites
4.1 5.7 2011 13.2 Days CHF 2700 Submit
Pets
pets
- - 2024 15.0 days * CHF 1000 Submit
Veterinary Sciences
vetsci
2.4 2.9 2014 19.6 Days CHF 2600 Submit

* Median value for all MDPI journals in the second half of 2023.


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Published Papers (2 papers)

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17 pages, 11511 KiB  
Article
The Effects of Dietary Saccharomyces cerevisiae Supplementation on Gut Microbiota Composition and Gut Health in Aged Labrador Retrievers
by Yingyue Cui, Deping Li, Mingrui Zhang, Pan Liu, Haotian Wang, Yingying Li and Yi Wu
Animals 2024, 14(12), 1713; https://doi.org/10.3390/ani14121713 - 7 Jun 2024
Viewed by 422
Abstract
The intestinal microbiome changes with age, influencing the host’s health and immune status. Saccharomyces cerevisiae (S. cerevisiae) positively affects intestinal function in humans and animals, but its effects on gut health and the microbiota profile in aged dogs have not been [...] Read more.
The intestinal microbiome changes with age, influencing the host’s health and immune status. Saccharomyces cerevisiae (S. cerevisiae) positively affects intestinal function in humans and animals, but its effects on gut health and the microbiota profile in aged dogs have not been thoroughly investigated. Twenty aged Labrador Retrievers were divided into two groups: a control group (CON) and a S. cerevisiae group (SC). The experiment lasted for 42 days, with assessments of their intestinal barrier function, inflammatory factors, antioxidant markers, and fecal microbiome composition. The results showed that dietary S. cerevisiae reduced the levels of TNF-α, IL-6, and IL-1β in the serum (p < 0.05). In the SC group, plasma superoxide dismutase and glutathione peroxidase activities increased, while the level of malondialdehyde significantly decreased (p < 0.05). Additionally, dietary S. cerevisiae lowered the serum zonulin and lipopolysaccharide (LPS) levels (p < 0.05) and inhibited fecal ammonia production (p < 0.05). Furthermore, the microbiota profile showed that dietary S. cerevisiae decreased the abundance of Firmicutes but increased the Chao index, the abundance of Bacteroidetes, and the proportion of Bacteroidetes to Firmicutes (p < 0.05). To conclude, dietary S. cerevisiae can regulate the gut’s microbial structure and gut health, which may contribute to the overall health of companion animals as they age. Full article
(This article belongs to the Topic Research on Companion Animal Nutrition)
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17 pages, 648 KiB  
Article
Evaluation of Effective Energy Values of Six Protein Ingredients Fed to Beagles and Predictive Energy Equations for Protein Feedstuff
by Qiaoru Zhang, Haoran Sun, Zuer Gao, Hui Zhao, Zhangrong Peng and Tietao Zhang
Animals 2024, 14(11), 1599; https://doi.org/10.3390/ani14111599 - 29 May 2024
Viewed by 406
Abstract
This study evaluated the nutrition composition, the nutrient digestibility, and the energy value of six protein ingredients used in pet food by the difference method in six beagles within a 7 × 6 incomplete Latin square design. The results showed that the apparent [...] Read more.
This study evaluated the nutrition composition, the nutrient digestibility, and the energy value of six protein ingredients used in pet food by the difference method in six beagles within a 7 × 6 incomplete Latin square design. The results showed that the apparent total tract digestibility of gross energy (GE) and organic matter (OM) in beagles fed the fish meal (FM) and corn gluten meal (CGM) diets was higher than for those fed the meat and bone meal (MBM), soybean meal (SBM), mealworm meal (MM), and yeast extract (YE) diets (p < 0.05). The digestible energy (DE), metabolizable energy (ME), and net energy (NE) of the MM diet were greater than the other diets, and MBM was the lowest (p < 0.05). The ME of protein ingredients was positively correlated with organic matter and negatively correlated with the ash content. The NE of protein ingredients was positively correlated with the crude protein content and negatively correlated with the ash content. The study resulted in predictive energy equations for protein ingredients that were more accurate than the NRC’s predictive equation of ME when the ash content of the ingredient was more than 30% DM. In conclusion, the nutrient digestibility and energy value of corn gluten meal were similar to those of fish meal and those of soybean meal were similar to yeast extract. All predictive energy equations for six protein feedstuffs had slight differences with measured energy values. Full article
(This article belongs to the Topic Research on Companion Animal Nutrition)
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