{"title":"基于形态特征的判别分析(DA)技术鉴别家兔的性别和品种","authors":"F. Abdallah","doi":"10.5455/ajvs.120266","DOIUrl":null,"url":null,"abstract":"ABSTRACT Rabbits are a basic source of protein in many areas around the world. Rabbits are characterized by meat of good quality and high protein source. It is of importance to study and predict different rabbit characters. A total of 720 data values of three different breeds of rabbits (NewZeland White, Californian, and Rex) and both sexes were used. Discriminant analysis (DA) was used to classify the three rabbit breeds and genders based on the morphological characters (body length (BL), chest circumference (CHC), abdominal circumference (ABDC), thigh circumference (THC), ear length (EL) and ear width (EW)). Data were analyzed using the procedures of DA on SPSS 23 statistical package. The results were that ear width showed a strong participation (0.646) in discriminating the three breeds and explained most of the variance while body length (-0.608) was next in importance as a predictor followed by abdominal circumference (0.531) and the other variables were less contribution. Abdominal circumference is the most significant morphological trait as a discriminating variable (0.695) in discrimination between male and female and explained most of the variance followed by ear width (0.560) then the body length (-0.531). It is found that 59.2 % correct classification of the rabbit breeds using the discriminant functions was achieved and 70.8 % correct classification of the rabbit sexes using the discriminant functions was achieved.","PeriodicalId":7928,"journal":{"name":"alexandria journal of veterinary sciences","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discriminant Analysis (DA) Technique for Identification Sex and Breed of Rabbits Depending on Morphological Traits\",\"authors\":\"F. Abdallah\",\"doi\":\"10.5455/ajvs.120266\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Rabbits are a basic source of protein in many areas around the world. Rabbits are characterized by meat of good quality and high protein source. It is of importance to study and predict different rabbit characters. A total of 720 data values of three different breeds of rabbits (NewZeland White, Californian, and Rex) and both sexes were used. Discriminant analysis (DA) was used to classify the three rabbit breeds and genders based on the morphological characters (body length (BL), chest circumference (CHC), abdominal circumference (ABDC), thigh circumference (THC), ear length (EL) and ear width (EW)). Data were analyzed using the procedures of DA on SPSS 23 statistical package. The results were that ear width showed a strong participation (0.646) in discriminating the three breeds and explained most of the variance while body length (-0.608) was next in importance as a predictor followed by abdominal circumference (0.531) and the other variables were less contribution. Abdominal circumference is the most significant morphological trait as a discriminating variable (0.695) in discrimination between male and female and explained most of the variance followed by ear width (0.560) then the body length (-0.531). It is found that 59.2 % correct classification of the rabbit breeds using the discriminant functions was achieved and 70.8 % correct classification of the rabbit sexes using the discriminant functions was achieved.\",\"PeriodicalId\":7928,\"journal\":{\"name\":\"alexandria journal of veterinary sciences\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"alexandria journal of veterinary sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5455/ajvs.120266\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria journal of veterinary sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5455/ajvs.120266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discriminant Analysis (DA) Technique for Identification Sex and Breed of Rabbits Depending on Morphological Traits
ABSTRACT Rabbits are a basic source of protein in many areas around the world. Rabbits are characterized by meat of good quality and high protein source. It is of importance to study and predict different rabbit characters. A total of 720 data values of three different breeds of rabbits (NewZeland White, Californian, and Rex) and both sexes were used. Discriminant analysis (DA) was used to classify the three rabbit breeds and genders based on the morphological characters (body length (BL), chest circumference (CHC), abdominal circumference (ABDC), thigh circumference (THC), ear length (EL) and ear width (EW)). Data were analyzed using the procedures of DA on SPSS 23 statistical package. The results were that ear width showed a strong participation (0.646) in discriminating the three breeds and explained most of the variance while body length (-0.608) was next in importance as a predictor followed by abdominal circumference (0.531) and the other variables were less contribution. Abdominal circumference is the most significant morphological trait as a discriminating variable (0.695) in discrimination between male and female and explained most of the variance followed by ear width (0.560) then the body length (-0.531). It is found that 59.2 % correct classification of the rabbit breeds using the discriminant functions was achieved and 70.8 % correct classification of the rabbit sexes using the discriminant functions was achieved.