Background and aims <p>Soybean is vital for global food security, necessitating understanding its response to environmental changes. We examined how growing season weather and rising atmospheric CO<sub>2</sub> affect seed traits of historical short-season soybean cultivars in Eastern Canada, with particular focus on water-use efficiency and nitrogen fixation dynamics.</p> Methods <p>Field trials data from 1993 to 2016 were analyzed for 14 cultivars spanning seven decades (1932–1992). Impacts of precipitation, mean maximum temperature (MTemp), mean maximum vapor pressure deficit (MVPD), and historical atmospheric CO<sub>2</sub> (which increased by 47&#xa0;ppm during the study period) on seed yield, protein and oil percentages, carbon isotope discrimination (Δ<sup>13</sup>C), and nitrogen isotopic composition (δ<sup>15</sup>N) were assessed using linear mixed-effect models and hierarchical partitioning analysis.</p> Results <p>Seed yield and Δ<sup>13</sup>C showed positive correlations with precipitation but negative correlations with MTemp and MVPD. Seed carbon percentage and Δ<sup>13</sup>C increased with atmospheric CO<sub>2</sub>, while seed protein and oil percentages, and δ<sup>15</sup>N decreased. Hierarchical partitioning highlighted yield vulnerability during early reproductive stages (R1-R3, July) and protein yield sensitivity during pod-formation and seed-filling (R4-R6, August). Historical cultivar selection favored seed and oil yields, but not protein yield, Δ<sup>13</sup>C, and δ<sup>15</sup>N. MVPD emerged as a better predictor of seed traits than temperature.</p> Conclusions <p>Correlations between Δ<sup>13</sup>C, δ<sup>15</sup>N, and seed yield suggest selecting for higher yield may indirectly reduce water-use efficiency (indicated by higher Δ<sup>13</sup>C) and enhance biological nitrogen fixation (reflected by lower δ<sup>15</sup>N). These findings highlight the need to consider both seasonal weather variability and rising CO<sub>2</sub> in soybean breeding programs.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Long-term field trials assess temporal trends and growing season weather on soybean seed yield, nutrient composition and nitrogen dynamics

  • Yi Hu,
  • Raju Y. Soolanayakanahally,
  • Robert D. Guy,
  • Xuyang Lu,
  • Salim N. Silim,
  • Elroy R. Cober,
  • Malcolm J. Morrison

摘要

Background and aims

Soybean is vital for global food security, necessitating understanding its response to environmental changes. We examined how growing season weather and rising atmospheric CO2 affect seed traits of historical short-season soybean cultivars in Eastern Canada, with particular focus on water-use efficiency and nitrogen fixation dynamics.

Methods

Field trials data from 1993 to 2016 were analyzed for 14 cultivars spanning seven decades (1932–1992). Impacts of precipitation, mean maximum temperature (MTemp), mean maximum vapor pressure deficit (MVPD), and historical atmospheric CO2 (which increased by 47 ppm during the study period) on seed yield, protein and oil percentages, carbon isotope discrimination (Δ13C), and nitrogen isotopic composition (δ15N) were assessed using linear mixed-effect models and hierarchical partitioning analysis.

Results

Seed yield and Δ13C showed positive correlations with precipitation but negative correlations with MTemp and MVPD. Seed carbon percentage and Δ13C increased with atmospheric CO2, while seed protein and oil percentages, and δ15N decreased. Hierarchical partitioning highlighted yield vulnerability during early reproductive stages (R1-R3, July) and protein yield sensitivity during pod-formation and seed-filling (R4-R6, August). Historical cultivar selection favored seed and oil yields, but not protein yield, Δ13C, and δ15N. MVPD emerged as a better predictor of seed traits than temperature.

Conclusions

Correlations between Δ13C, δ15N, and seed yield suggest selecting for higher yield may indirectly reduce water-use efficiency (indicated by higher Δ13C) and enhance biological nitrogen fixation (reflected by lower δ15N). These findings highlight the need to consider both seasonal weather variability and rising CO2 in soybean breeding programs.