[ Objective] To investigate the effects of different levels of metabolizable energy and crude protein on egg laying performance and hatch- ing efficiency in Magang geese. [Method] The healthy Magang geese at 2 years o...[ Objective] To investigate the effects of different levels of metabolizable energy and crude protein on egg laying performance and hatch- ing efficiency in Magang geese. [Method] The healthy Magang geese at 2 years old were randomly assigned into four groups, group Ⅰ, group Ⅱ, group Ⅲ and control group. They were fed with diets at different levels of metabolizable energy and crude protein, and then their eggs were collect- ed and hatched. During the test, their health was observed, and the egg weight, egg yield and hatching rate were recorded. [ Result] The average egg laying rates and average egg weight were significantly higher in the group Ⅰ, group Ⅱ and group Ⅲ than in the control group. The hatchable egg rates and egg fertilization rates of the group Ⅰ, group Ⅱ and group Ⅲ were also increased, and significance was found between the group Ⅲ and the other group （P 〈 0.05）. The feed costs of the three test groups were lower than that of the control group, and the feed cost was higher in the group Ⅲ than that in the group Ⅰ and Ⅱ. [ Conclusion] The levels of metabolizable energy and crude protein in diet have significant effects on laying performance and hatching efficiency in Magang geese.展开更多
Magang,situated in MaanshanPrefecture,near the lower reaches of theYangtze River and in eastern Anhui Province,is one of China’s super-large integrated ironand steel enterprises,and also Anhui’s largestindustrial en...Magang,situated in MaanshanPrefecture,near the lower reaches of theYangtze River and in eastern Anhui Province,is one of China’s super-large integrated ironand steel enterprises,and also Anhui’s largestindustrial enterprise.According to its netassets,it ranks the 16th of the country,and27th by its sales amount. Magang was formally established in1958.In 1992,it was approved as one ofChina’s first nine stock system normalizedexperiment enterprises,and now has becomeChina’s listing company with largest scaleand amount of capital issued inside andoutside China.Stock system makes it展开更多
Maanshan Magang Julong Co.Ltd.isa special enterprise assigned by the Ministryof Metallurgical Industry for making castiron tubes and accessories,assigned by theMinistry of Construction for makingrevolving bearing seri...Maanshan Magang Julong Co.Ltd.isa special enterprise assigned by the Ministryof Metallurgical Industry for making castiron tubes and accessories,assigned by theMinistry of Construction for makingrevolving bearing series products. The company is located betweenNanjing and Wuhu economic developmentzones,on the side of the State Highway 205,overlooking the Yangtze River,with展开更多
马岗鹅的行为与其生长状况和福利状况密切相关,马岗鹅关键行为监测对评估其生长性能具有重要的现实意义。为了实现对群养栏马岗鹅关键行为高效率精准监测,该研究探索一种基于YoloX的群养马岗鹅关键行为监测算法(Magang geese behavior m...马岗鹅的行为与其生长状况和福利状况密切相关,马岗鹅关键行为监测对评估其生长性能具有重要的现实意义。为了实现对群养栏马岗鹅关键行为高效率精准监测,该研究探索一种基于YoloX的群养马岗鹅关键行为监测算法(Magang geese behavior monitoring of based on Double Head-YoloX,MGBM-DH-YoloX),该算法通过减少YoloX的头部数量提升检测效率、使用损失函数减少前景背景干扰、使用迁移训练方式提高网络训练效率等技术对马岗鹅采食、饮水、休息和应激等关键行为及其规律进行分析。MGBM-DH-YoloX首先用Mosaic和Mixup对马岗鹅图像进行数据增强,然后使用增强后的数据集训练模型,并且利用模型检测马岗鹅的关键行为,最后累计得出马岗鹅关键行为的发生时长和行为节律;试验训练集为1400幅、验证集200幅和测试集为400幅,连续活动视频10 d。结果表明,MGBM-DH-YoloX算法的平均精度为98.98%、检测速度达到81帧/s、内存消耗为2520.04 MB。对马岗鹅的10 d养殖数据分析发现,MGBM-DH-YoloX能有效观察到马岗鹅随着日龄增长采食次数逐渐减少;试验鹅每日采食与饮水行为同时出现的比例为83.74%,呈现整体相伴趋势,但也从90.78%降低到74.57%,说明马岗鹅采食与饮水行为随着日龄增加呈现出逐渐分离趋势;试验鹅随着日龄增长休息时间逐渐加多,呈现出肉鸭对笼养的适应性逐步增强;应激行为随机性很强,突发性明显,发现人员随机走动等不规范饲喂带来的应激行为占据很大比例。该研究显示MGBM-DH-YoloX算法能利用监控视频对马岗鹅的关键行为进行智能提取,可为家禽智能养殖监管提供技术支撑。展开更多
基金funded by the Education Department Production and Research Program of Guangdong Province ( 2009B090300088)
文摘[ Objective] To investigate the effects of different levels of metabolizable energy and crude protein on egg laying performance and hatch- ing efficiency in Magang geese. [Method] The healthy Magang geese at 2 years old were randomly assigned into four groups, group Ⅰ, group Ⅱ, group Ⅲ and control group. They were fed with diets at different levels of metabolizable energy and crude protein, and then their eggs were collect- ed and hatched. During the test, their health was observed, and the egg weight, egg yield and hatching rate were recorded. [ Result] The average egg laying rates and average egg weight were significantly higher in the group Ⅰ, group Ⅱ and group Ⅲ than in the control group. The hatchable egg rates and egg fertilization rates of the group Ⅰ, group Ⅱ and group Ⅲ were also increased, and significance was found between the group Ⅲ and the other group （P 〈 0.05）. The feed costs of the three test groups were lower than that of the control group, and the feed cost was higher in the group Ⅲ than that in the group Ⅰ and Ⅱ. [ Conclusion] The levels of metabolizable energy and crude protein in diet have significant effects on laying performance and hatching efficiency in Magang geese.
文摘Magang,situated in MaanshanPrefecture,near the lower reaches of theYangtze River and in eastern Anhui Province,is one of China’s super-large integrated ironand steel enterprises,and also Anhui’s largestindustrial enterprise.According to its netassets,it ranks the 16th of the country,and27th by its sales amount. Magang was formally established in1958.In 1992,it was approved as one ofChina’s first nine stock system normalizedexperiment enterprises,and now has becomeChina’s listing company with largest scaleand amount of capital issued inside andoutside China.Stock system makes it
文摘Maanshan Magang Julong Co.Ltd.isa special enterprise assigned by the Ministryof Metallurgical Industry for making castiron tubes and accessories,assigned by theMinistry of Construction for makingrevolving bearing series products. The company is located betweenNanjing and Wuhu economic developmentzones,on the side of the State Highway 205,overlooking the Yangtze River,with
文摘马岗鹅的行为与其生长状况和福利状况密切相关,马岗鹅关键行为监测对评估其生长性能具有重要的现实意义。为了实现对群养栏马岗鹅关键行为高效率精准监测,该研究探索一种基于YoloX的群养马岗鹅关键行为监测算法(Magang geese behavior monitoring of based on Double Head-YoloX,MGBM-DH-YoloX),该算法通过减少YoloX的头部数量提升检测效率、使用损失函数减少前景背景干扰、使用迁移训练方式提高网络训练效率等技术对马岗鹅采食、饮水、休息和应激等关键行为及其规律进行分析。MGBM-DH-YoloX首先用Mosaic和Mixup对马岗鹅图像进行数据增强,然后使用增强后的数据集训练模型,并且利用模型检测马岗鹅的关键行为,最后累计得出马岗鹅关键行为的发生时长和行为节律;试验训练集为1400幅、验证集200幅和测试集为400幅,连续活动视频10 d。结果表明,MGBM-DH-YoloX算法的平均精度为98.98%、检测速度达到81帧/s、内存消耗为2520.04 MB。对马岗鹅的10 d养殖数据分析发现,MGBM-DH-YoloX能有效观察到马岗鹅随着日龄增长采食次数逐渐减少;试验鹅每日采食与饮水行为同时出现的比例为83.74%,呈现整体相伴趋势,但也从90.78%降低到74.57%,说明马岗鹅采食与饮水行为随着日龄增加呈现出逐渐分离趋势;试验鹅随着日龄增长休息时间逐渐加多,呈现出肉鸭对笼养的适应性逐步增强;应激行为随机性很强,突发性明显,发现人员随机走动等不规范饲喂带来的应激行为占据很大比例。该研究显示MGBM-DH-YoloX算法能利用监控视频对马岗鹅的关键行为进行智能提取,可为家禽智能养殖监管提供技术支撑。
