宠物犬猫毛发质量的评定方法及营养调控技术研究进展
Research Progress on Evaluation Methods of Pet Hair Quality and Nutrition Regulation Technology
蔡文韬 1李天尊 1王盛琪 1季新雨 2王柔淇 1齐智利3
作者信息
- 1. 华中农业大学动物科技学院,湖北武汉 430070
- 2. 赣南医学院公共卫生与健康管理学院,江西赣州 341000
- 3. 华中农业大学动物科技学院,湖北武汉 430070;华中农业大学深圳营养与健康研究院,湖北武汉 430070;中国农业科学院深圳农业基因组研究所和岭南现代农业科学与技术广东省实验室深圳分中心,广东深圳 518000
- 折叠
摘要
宠物犬猫的毛发质量是宠物主人尤为关注的问题,而在影响犬猫毛发质量的各种因素中,营养因素备受重视.目前主要的营养调控手段是通过调节宠物犬猫食品中的营养成分(矿物质、维生素、脂肪酸、氨基酸)比例或额外饲喂营养保健品来改善犬猫的毛发质量.科学合理的毛发质量评定方法可以更清晰地展现犬猫毛发质量的变化,有助于进一步判断营养调控是否有效改善了犬猫毛发质量.而由于现阶段对犬猫毛发质量评定方法的研究不够系统和深入,难以建立统一的标准,一定程度上限制了营养调控犬猫毛发质量的研究.本文综述近年来研究中所使用的宠物犬猫毛发质量评定的方法及营养调控技术的研究进展,以期为犬猫的美毛护毛饲粮配制和调控犬猫毛发质量的研究提供参考.
Abstract
The quality of pet dog and cat hair is a particularly concerned issue for pet owners.Among the various factors affecting the quality of dog and cat hair,nutritional factors have attracted much attention.At present,the main nutritional regulation method is to improve the hair quality of dogs and cats by adjusting the proportion of nutrients(minerals,vitamins,fatty acids,amino acids)in pet dog and cat food.The scientific and reasonable hair quality evaluation method is helpful for us to observe the changes of hair quality in dogs and cats in the study,and then further judge whether the nutrients can effectively improve the hair quality of dogs and cats.However,due to the lack of systematic and in-depth research on the evaluation methods of canine and cat hair quality,it is difficult to establish a unified standard,which limits the research on nutritional regulation of canine and cat hair quality to a certain extent.This paper reviews the research progress of various methods used in recent years to evaluate the hair quality of pet dogs and cats and the effects of various nutrients on the hair quality of dogs and cats,in order to provide reference for the preparation of hairy diets for dogs and cats and the regulation of hair quality of dogs and cats.
关键词
宠物犬猫/毛发质量/营养调控/评定方法Key words
Pet dogs and cats/Nutrition regulation/Evaluation method/Hair quality引用本文复制引用
基金项目
湖北省自然科学基金(2022CFB327)
华中农业大学-中国农业科学院深圳农业基因组研究所联合项目(SZYJY2022008)
出版年
2024
国家科技期刊平台
NSTL
万方数据