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中国农学通报 ›› 2025, Vol. 41 ›› Issue (31): 149-158.doi: 10.11924/j.issn.1000-6850.casb2025-0312

• 畜牧·动物医学·蚕·蜂 • 上一篇    下一篇

风沙草滩区紫花苜蓿品种选择与综合性能评价

卜会荣1,2(), 尹诗瑜1, 徐伟洲1(), 常瑜池1, 史雷1, 贾建英2   

  1. 1 榆林学院现代农学院,陕西榆林 719000
    2 榆林市榆阳区牛家梁林场,陕西榆林 719000
  • 收稿日期:2025-04-21 修回日期:2025-06-25 出版日期:2025-11-05 发布日期:2025-11-07
  • 通讯作者:
    徐伟洲,男,1985年出生,陕西蓝田人,教授,博士,主要从事人工草地高效栽培与管理研究。通信地址:719000 陕西省榆林市榆阳区崇文西路4号,E-mail:
  • 作者简介:

    卜会荣,男,1978年出生,陕西榆林人,高级工程师,本科,主要从事林草新品种引种栽培研究。通信地址:719000 陕西省榆林市榆阳区牛家梁林场,E-mail:

  • 基金资助:
    陕西省秦创原“科学家+工程师”队伍建设项目榆林特色高蛋白饲草产业提质增效“科学家+工程师”队伍(2024QCY-KXJ-101); 陕西省科技资源开放共享平台项目“陕北饲草全产业链综合性检验检测平台”(2024CX-GXPT-31)

Selection and Comprehensive Performance Evaluation of Alfalfa Varieties in Wind-sand Grassland Area

BU Huirong1,2(), YIN Shiyu1, XU Weizhou1(), CHANG Yuchi1, SHI Lei1, JIA Jianying2   

  1. 1 College of Advanced Agricultural Sciences, Yulin University, Yulin, Shaanxi 719000
    2 Niujialiang Forest Farm, Yuyang District, Yulin City, Yulin, Shaanxi 719000
  • Received:2025-04-21 Revised:2025-06-25 Published:2025-11-05 Online:2025-11-07

摘要:

本研究评估榆林北部风沙草滩区不同紫花苜蓿品种的生产适应性与生产潜力,以期为该地区苜蓿产业发展与生态建设提供科学依据。选取20个紫花苜蓿品种,开展3茬田间试验,采用随机区组设计,结合近红外光谱技术与化学分析测定营养指标,最终通过灰色关联度法进行综合评价。采用近红外光谱技术快速测定苜蓿营养品质,结合化学分析验证数据准确性。该技术操作简便捷高效,可在短时间内提供多项关键营养指标。此外,运用灰色关联度分析法对不同品种的生产性能与营养品质进行综合排序。研究发现,不同品种的生产性能与营养品质存在显著差异。‘大银河’‘擎天柱’和‘三得利’在年干草产量方面表现最佳,分别为545.62、544.12、544.72 t/hm²。‘皇后’在第1茬的表现最佳,尤其是在中性洗涤纤维、酸性洗涤纤维、干物质和相对饲喂价值等指标上。灰色关联度分析显示,‘擎天柱’、‘普沃4.2’和‘皇后’在综合性状居前3位,具有较强的推广潜力。本研究表明,‘擎天柱’、‘普沃4.2’和‘皇后’在榆林风沙草滩区具有优良的生产性能与营养品质,适合在该地区种植。研究结果可为该地区的牧草选育及可持续农业发展提供科学依据,并为类似地区的牧草种植提供参考。

关键词: 紫花苜蓿, 引种试验, 营养指标, 生产适应性, 综合评价

Abstract:

This study aimed to evaluate the adaptability and production potential of different Medicago sativa varieties in the northern sandy grassland area of Yulin, providing a scientific basis for the development of the alfalfa industry and ecological construction in this region. Twenty Medicago sativa varieties were selected for a three-cut field experiment. The experiment adopted a randomized block design. Near-infrared spectroscopy and chemical analysis were combined to determine nutritional indicators, and finally, the grey relational analysis method was used for comprehensive evaluation. Near-infrared spectroscopy was employed to rapidly determine the nutritional quality of alfalfa, and chemical analysis was integrated to ensure the accuracy of the data. This technique is simple, convenient, fast, and efficient, capable of providing multiple key nutritional indicators in a short period. Additionally, the grey relational analysis method was utilized to comprehensively rank the production performance and nutritional quality of different varieties, thereby presenting a comprehensive evaluation result. There were significant differences in the production performance and nutritional quality among different varieties. ‘Big galaxy’, ‘Optimus prime’, and ‘Santali’ exhibited the best annual dry hay yields, reaching 545.62, 544.12, and 544.72 t/hm2 respectively. The ‘Queen’ variety performed best in the first cut, especially in terms of neutral detergent fiber (NDF), acid detergent fiber (ADF), dry matter (DM), and relative feed value. Grey relational analysis indicated that ‘Optimus Prime’, ‘Prower 4.2’, and ‘Queen’ ranked top three in comprehensive traits and had strong promotion potential. This study demonstrates that ‘Optimus Prime’, ‘Prower 4.2’, and ‘Queen’ possess excellent production performance and nutritional quality in the sandy grassland area of Yulin and are suitable for cultivation in this region. The results provide a scientific basis for forage selection and sustainable agricultural development in this area, and offer a reference for forage cultivation in similar regions.

Key words: Medicago sativa, introduction experiment, nutritional indicators, production adaptability, comprehensive evaluation