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中国农学通报

中国农学通报 ›› 2026, Vol. 42 ›› Issue (13): 6-11.doi: 10.11924/j.issn.1000-6850.casb2025-0975

• 农学·农业基础科学 • 上一篇    下一篇

小麦籽粒产量、生物产量与收获指数的研究

田顺顺1(), 王冲2, 林坤1, 郭凤芝1, 李思同1(), 任自超1, 王应党1, 郭凌云1, 袁阳1, 李玉豪2   

  1. 1 菏泽市农业科学院， 山东菏泽 274000
    2 菏泽市农业科学院试验示范开发服务中心， 山东菏泽 274000
  • 收稿日期:2026-01-04 修回日期:2026-05-09 出版日期:2026-07-15 发布日期:2026-07-09
  • 通讯作者:
    李思同，男，1968年出生，山东菏泽人，研究员，本科，主要从事小麦育种与栽培研究。通信地址：274000 山东省菏泽市牡丹区黄堽镇菏泽市农业科学院，Tel：0530-652675，E-mail：。
  • 作者简介:

    田顺顺，女，1992年出生，山东菏泽人，农艺师，硕士，主要从事小麦育种和栽培研究。通信地址：274000 山东省菏泽市牡丹区黄堽镇 菏泽市农业科学院，Tel：0530-5646314，E-mail：。

  • 基金资助:
    山东省现代农业产业技术体系“小麦产业技术体系”(SDAIT-01-22); 山东省重点研发计划“核心亲本精准鉴定与新品种培育及示范推广”(2024LZGC0010301)

Studies on Grain Yield, Biological Yield and Harvest Index of Wheat

TIAN Shunshun1(), WANG Chong2, LIN Kun1, GUO Fengzhi1, LI Sitong1(), REN Zichao1, WANG Yingdang1, GUO Lingyun1, YUAN Yang1, LI Yuhao2   

  1. 1 Heze Academy of Agricultural Sciences, Heze, Shandong 274000
    2 Experimental Demonstration Development Service Center, Heze Academy of Agricultural Sciences, Heze, Shandong 274000
  • Received:2026-01-04 Revised:2026-05-09 Published:2026-07-15 Online:2026-07-09

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摘要：

为明确小麦籽粒产量、生物产量与收获指数的遗传关联及育种应用价值，以30个遗传性状稳定的小麦品系为材料，系统分析籽粒产量、生物产量与收获指数之间的关系及其遗传变异特征。结果表明，供试品系在生物产量、籽粒产量和收获指数方面均存在极显著差异，变异范围分别为8.79~13.4 g、4.35~5.90 g和0.407~0.539。变异系数分析表明，生物产量的遗传变异最为丰富(CV=11.7%)，为育种提供了广阔的改良空间，收获指数则较为稳定(CV=6.9%)。相关性分析显示，籽粒产量与生物产量呈极显著正相关(r=0.7904)，预示着提高生物产量是促进籽粒产量增长的关键。然而，生物产量与收获指数呈极显著负相关(r=-0.6949)，反映了两者间的固有权衡。综上，在当前收获指数提升难度加大的背景下，提高生物产量并协同优化收获指数，是未来实现小麦超高产育种的有效途径。本研究结果可为育种家精准筛选源库关系协调、光合产物分配高效的小麦品系提供直接的理论依据和实践参考，对缩短育种周期、提升超高产小麦选育效率具有重要价值。

关键词: 小麦, 籽粒产量, 生物产量, 收获指数

Abstract:

To clarify the genetic correlation and breeding application value among grain yield, biological yield and harvest index of wheat, this study systematically analyzed the relationships among grain yield, biological yield, and harvest index, as well as their genetic variation characteristics, using 30 stable inherited wheat lines. The results showed extremely significant differences among lines for biological yield, grain yield, and harvest index, with variation ranges of 8.79-13.4 g, 4.35-5.90 g, and 0.407-0.539, respectively. Coefficient of variation (CV) analysis revealed the highest genetic variability in biological yield (CV=11.7%), whereas that in harvest index was relatively stable (CV=6.9%). Correlation analysis indicated a highly significant positive correlation between grain yield and biological yield (r=0.7904), indicating that increasing biological yield was the key to promoting grain yield growth. However, there was a highly significant negative correlation between biological yield and harvest index (r=-0.6949), reflecting the inherent trade-off between them. In conclusion, enhancing biological yield with synergistically optimizing harvest index is proposed as an effective strategy for future ultra-high-yield wheat breeding, under the current challenge of limited gains in harvest index. These findings provide a direct theoretical basis and practical guidance for breeders to precisely select lines with coordinated source-sink relationships and efficient assimilate partitioning, thereby holding significant value for shortening the breeding cycle and improving selection efficiency.

Key words: wheat, grain yield, biological yield, harvest index

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