兰沙市东兰沙区肉牛人工授精成功的支持因素

Rini Mastuti, Reza Setiawan, Kiagus M Zain Basriwijaya
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引用次数: 2

摘要

养牛在确保粮食安全和满足人类蛋白质需求方面发挥着至关重要的作用。它不仅因其护理简单而吸引人,而且还因为它可以利用植物性饲料。人工授精(AI)可以用来增加牛的数量。本研究旨在分析影响兰沙市东兰沙区肉牛人工智能成功的因素。抽样方法为目的抽样,共42人。统计分析包括经典假设检验、多元线性回归和假设检验,以确定影响人工智能在肉牛中成功的因素。数据处理采用SPSS计算机软件。结果表明,人工授精工具变量(X2)(包括授精者来源、授精者服务、人工授精成功率和人工授精设备)对人工授精成功率(Y)有显著影响(显著值为0.010)。授精者变量(X4)(包括未受过特殊教育的授精者能力、人工授精者受过特殊教育的授精者探测牛热的能力)对人工授精成功率(Y)有显著影响(显著值为0.010)。而授精者即使在动物不发情的情况下也能将冷冻精液插入子宫的能力也证明了这一点。相反,检查家畜状况变量(X1),如去年没有生病的奶牛,人工智能前奶牛健康状况良好,每年产犊,没有显示出显著影响(显著性值0.816)。迫切需要进一步的研究,纳入更多的变量,以加强能够提高人工授精和提高牲畜产量的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Supporting the Success of Artificial Insemination in Beef Cattle in East Langsa District Langsa City
Cattle farming plays a crucial role in ensuring food security and meeting the protein requirements of humans. It is not only appealing due to its simplicity in care but also because it can make use of plant-based feed. Artificial insemination (AI) can be employed to boost the cattle population. This study aimed to analyze the factors influencing the success of AI in beef cattle within the East Langsa District of Langsa City. The sampling method utilized was purposive sampling, involving 42 respondents. Statistical analysis involved classical assumption tests, multiple linear regression, and hypothesis testing to identify the factors impacting the success of AI in beef cattle. Data processing was conducted using the SPSS computer software. The results revealed that the AI tool variables (X2), including inseminator origin, inseminator service, AI success rate, and AI equipment, had a significant effect (significance value 0.010) on the success of artificial insemination (Y). Similarly, the inseminator variable (X4), involving inseminator ability without special education, AI special education, inseminator ability to detect cattle in heat, and the inseminator's capability to insert frozen semen into the uterus even when the animal is not in heat, demonstrated a significant impact. Conversely, examining the livestock condition variable (X1), such as no sick cows in the last year, cows in good health before AI, and yearly calving, did not exhibit a significant effect (significance value 0.816). Further research is urgently required, incorporating additional variables to strengthen the factors that can enhance artificial insemination and increase livestock production.
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