中国乳业 ›› 2024, Vol. 0 ›› Issue (12): 42-46.doi: 10.12377/1671-4393.24.12.07

• 饲草饲料 • 上一篇    下一篇

东北奶牛场使用近红外光谱分析仪检测玉米青贮的应用实例

刘彩娟, 张永久, 任亮, 王永信   

  1. 原生态牧业有限公司,黑龙江齐齐哈尔 161000
  • 出版日期:2024-12-25 发布日期:2025-01-03
  • 作者简介:刘彩娟(1986-),女,内蒙古通辽人,硕士,高级畜牧师,研究方向为动物营养与饲料科学;张永久(1973-),男,黑龙江哈尔滨人,本科,高级经济师,研究方向为数字化农牧业关键技术及装备;任 亮(1984-),男,山东临沂人,博士,中级兽医师,研究方向为动物遗传育种及信息管理;王永信(1977-),男,吉林白城人,本科,中级兽医师,研究方向为动物医学。
  • 基金资助:
    现代农业(奶牛)产业技术体系建设专项资金资助项目(CARS-36)

The Application of Near Infrared Spectrum Analyzer to the Detection of Corn Silage in Northeast Dairy Farms

LIU Caijuan, ZHANG Yongjiu, REN Liang, WANG Yongxin   

  1. YuanShengTai Dairy Farm Limited, Qiqihar Heilongjiang 161000
  • Online:2024-12-25 Published:2025-01-03

摘要: [目的] 玉米青贮是一种优质粗饲料,随着奶牛养殖的精准营养需要,快速环保的出具常规营养指标检测结果,为饲料配方制定及时有效提供数据支持,有利于提高东北奶牛场生产性能和牛只健康。[方法] 本文利用近红外光谱分析技术,建立不同样品状态的玉米青贮干物质(DM)、淀粉预测模型,同时对比两个不同厂家的近红外光谱分析仪,选择更适合东北奶牛场的近红外光谱分析仪。[结果] 本研究选取138 份玉米青贮样品作为定标集,23 份作为验证集。[结果] 表明:(1)建立新鲜玉米青贮干物质(DM)、淀粉预测模型后,对比A、 B厂家的近红外光谱分析仪用于实际检测的结果,B厂家的结果相对A厂家效果更优,A厂家的新鲜玉米淀粉预测模型需进一步优化。(2)使用A、B厂家的近红外光谱分析仪预测烘干粉碎后的玉米青贮样品淀粉,较新鲜玉米淀粉模型实际预测结果更好。(3)新鲜玉米青贮预测模型和烘干粉碎后玉米青贮预测模型有待进一步收集数据和优化。[结论] 本研究建立的玉米青贮干物质(DM)、淀粉预测模型可以用于玉米青贮实际预测生产实践,B厂家近红外光谱分析仪更适合东北奶牛场的使用。

关键词: 东北奶牛场, 玉米青贮, 近红外光谱分析仪, 湿化学, 应用实例

Abstract: [Objective] Corn silage is a high-quality roughage.With the precise nutrition needs of dairy farming,the regular nutrition index test results can be quickly and environmentally friendly,providing timely and effective data support for the formulation of feed formula,which is conducive to improving the production performance and cattle health of Northeast dairy farms. [Method] In this paper, Near Infrared Spectrum(NIRS)analysis technology was used to establish prediction models of corn silage dry matter(DM) and starch in different sample states. Meanwhile,NIRS analyzers from two different manufacturers were compared to select the one more suitable for Northeast dairy farms. [Result] In this study,138 corn silage samples were selected as the calibration set and 23 were selected as the validation set. The results showed that:(1)After establishing the prediction model of fresh corn silage dry matter(DM) and starch,compared with the results of the NIRS analyzers used by manufacturers A and B for practical detection,and the results of manufacturer B were better than those of manufacturer A,and fresh corn starch prediction model established by manufacturer A should be further optimized.(2)The NIRS analyzer of manufacturers A and B was used to predict the starch of corn silage samples after drying and crushing,which was better than that of fresh corn starch model.(3)Further data collection and optimization are needed for fresh corn silage prediction model and dried and crushed corn silage prediction model. [Conclusion] The prediction model of maize silage dry matter(DM)and starch established in this study can be used for the actual prediction and production practice of maize silage, and the near infrared spectrum analyzer of manufacturer B is more suitable for the use of dairy farms in northeast China.

Key words: Northeast dairy farm, corn silage, NIRS analyzer, wet chemistry, application example

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