Abstract The repetitive use of ALS inhibitors for smallflower umbrella sedge (Cyperus difformis L.) control has selected for herbicide-resistant (R) populations that threaten the sustainability of rice (Oryza sativa L.) production and demand alternative control measures be developed. A better understanding of seedling recruitment patterns at the field level is required to optimize the timing and efficacy of control measures. Therefore, a population-based threshold model was developed for optimizing germination prediction in multiple acetolactate synthase (ALS)-R and ALS-susceptible (ALS-S) C. difformis biotypes and applied to field-level emergence predictions. Estimated base temperatures (Tb) ranged from 16.5 to 17.6 C with no clear pattern between biotypes; such values are higher than Tb values of other important rice weeds, as well as for rice. Germination rates increased linearly from 16 to 33.7 C. ALS-R seeds germinate faster due to smaller median thermal times to germination (θT(50)) while also displaying lower germination synchronicity across water potentials. Interestingly, ALS-R biotypes were capable of germinating under lower moisture availability, as indicated by their lower (more negative) base water potential values (Ψb(50)) for seed germination; Ψb(50) values ranged from –0.24 to –1.13 MPa. In-field soil germination measurements found thermal times to emergence varied across three water regimes (daily water, flooded, or saturated). Seedling emergence under the daily water treatment was fastest; however, total seedling density was lower than for the other water regimes. In order to optimize springtime C. difformis seedling emergence, soil moisture should be kept around field capacity, as germination is hindered at lower moisture contents. By predicting when most of the seed population germinates, the thermal-time model can address issues regarding the optimal timing for herbicide applications, thereby allowing for improved C. difformis management in rice fields.

中文翻译：

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ALS 抑制剂抗性香附种子萌发需要更少的生长天数和更低的土壤水分

摘要 重复使用 ALS 抑制剂控制小花伞形莎草 (Cyperus difformis L.) 已选择用于威胁水稻 (Oryza sativa L.) 生产可持续性并需要开发替代控制措施的抗除草剂 (R) 种群。需要更好地了解田间幼苗补充模式，以优化控制措施的时间和效果。因此，开发了一种基于种群的阈值模型，用于优化多种乙酰乳酸合酶 (ALS)-R 和 ALS 易感 (ALS-S) C. diffformis 生物型的发芽预测，并应用于田间出现预测。估计的基础温度 (Tb) 范围为 16.5 至 17.6 C，生物型之间没有明确的模式；这些值高于其他重要水稻杂草以及水稻的 Tb 值。发芽率从 16 C 线性增加到 33.7 C。ALS-R 种子发芽速度更快，因为发芽的中值热时间较短 (θT(50))，同时还显示出较低的水势发芽同步性。有趣的是，ALS-R 生物型能够在较低的水分可用性下发芽，正如其种子发芽的较低（更负）基础水势值（Ψb（50））所表明的；Ψb(50) 值的范围为 –0.24 至 –1.13 MPa。田间土壤发芽测量发现，三种水体（日常水、淹水或饱和水）的热时间不同。日常水处理下出苗最快；然而，总的幼苗密度低于其他水分条件。为了优化春季 C. difformis 幼苗的出苗，土壤水分应保持在田间持水量附近，因为在较低的水分含量下会阻碍发芽。通过预测大多数种子种群何时发芽，热时间模型可以解决有关除草剂施用最佳时机的问题，从而改进稻田中的 C. difformis 管理。