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比較華鵝與雜交鵝之生長性能及屠體性狀與加工方式之研究

Study on the growth performance, carcass characteristics and processing methods of Chinese geese and Chinese hybrid geese

摘要


本試驗為瞭解華鵝品種作為生產肉鵝之雜交組合對屠體性狀之影響,作為將來進一步之利用與研究。試驗分成五個處理組,A組:100%褐色華鵝;B組:100%白色華鵝;C組:50%白色華鵝×50%白羅曼鵝;D組:25%白色華鵝×25%白羅曼鵝×50%褐色華鵝;E組:75%白色華鵝×25%白羅曼鵝;每個組合於16週齡逢機屠宰8隻(4♂4♀),三重複,進行屠體性狀測定。試驗結果顯示,以C組之後裔在16週齡時體重最重,不同雜交組合之屠體分切各部位比例平均,屠宰率、胸及背、腿、頭頸、翅膀、腳、腹脂分別為A組68.21%、39.37%、19.81%、13.03%、21.91%、4.59%、1.29%,B組70.44%、40.26%、19.71%、14.49%、19.90%、4.27%、1.37%,C組68.93%、40.08%、21.20%、14.33%、18.93%、4.26%、1.20%,D組71.26%、41.46%、19.79%、14.18%、18.41%、4.27%、1.89%,E組68.52%、39.30%、20.64%、14.08%、19.19%、4.33%、2.46%,加工方式以醉鵝評價較佳,此研究結果可提供肉品加工業者之參考。

關鍵字

華鵝 生長性能 屠體性狀

並列摘要


This study was conducted to investigate the effects of hybridization of geese breeds on the growth performance and characteristics of carcass and processing methods. There were five experiments and three replicates for each treatment. The A was Brown Chinese geese. The B was White Chinese geese. The C breed composition was White Chinese geese 50% and White Roman geese 50%. The D breed composition was White Chinese geese 25% and White Roman geese 25% and Brown Chinese geese 50%. The E breed composition was White Chinese geese 75% and White Roman geese 25%. At 16 weeks of age, 8 goslings (4 males and 4 females) were sampled from each pen and sacrificed for measurements of carcass traits. The results were shown the body weight for C group was highest among the five groups at 16 weeks of age. The dressing percentage of carcass and yields of cut-up parts of breast and back, thigh, head and neck, wing, feet, abdominal fat for four hybrid combination geese were A group 68.21, 39.37, 19.81, 13.03, 21.91, 4.59 and 1.29%; B group 70.44, 40.26, 19.71, 14.49, 19.90, 4.27 and 1.37%; C group 68.93, 40.08, 21.20, 14.33, 18.93, 4.26 and 1.20%; D group 71.26, 41.46, 19.79, 14.18, 18.41, 4.27 and 1.89%; E group 68.52, 39.30, 20.64, 14.08, 19.19, 4.33 and 2.46%, respectively. Geese processing methods by Liquor- Soaked has better evaluation. The data can be applied by the meat processors.

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