In warm-temperate regions, the adoption of warm-season forage grasses has been hindered by low and unpredictable seedling emergence because of seed dormancy. Developing models driven by temperature (T) and soil water potential (Ψ) may provide tools for choosing adequate sowing conditions. Models are usually developed with controlled chamber germination data, but they can be built using field emergence and weather station data. Seedling emergence data of four Paspalum populations (two dallisgrass subspecies, bahiagrass and vaseygrass) were gathered from five experiments in three Campos locations (Buenos Aires, Montevideo and Salto) during two years, with fall and spring sowing dates and irrigated and non-irrigated plots. Thermal and hydrothermal time models were used for emergence timing. The predictions were better for irrigated plots and fall sowings. For maximum emergence proportion (MEP), a mixed linear model was adjusted. Within a non-irrigated treatment, the higher MEP was for early-spring sowings, but the lowest for late-spring ones. Additionally, a thermal time index (TTI) was modified to model MEP. A coefficient which weighs degree-days accumulation according to the hydrothermal range (HTR) of each day was set. The HTRs were defined by T and Ψ thresholds. Thresholds and coefficient values were optimized by genotype until linear regressions between MEP and modified TTI achieved higher fit. Days with high temperature (>18°C or 20°C according to genotype) accumulated half or none of degree-days when high- or mid-soil water content was available, respectively. Differences among Paspalum genotypes, sowing date recommendations and modified TTI usefulness were discussed.

中文翻译：

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使用来自田间试验的环境数据模拟雀稗物种的幼苗出现

在暖温带地区，由于种子休眠，出苗率低且不可预测，阻碍了暖季牧草的采用。开发由温度 ( T ) 和土壤水势 ( Ψ )驱动的模型可以为选择合适的播种条件提供工具。模型通常是使用受控室发芽数据开发的，但它们可以使用现场出现和气象站数据来构建。4种雀稗的出苗数据两年期间，从三个坎波斯地区（布宜诺斯艾利斯、蒙得维的亚和萨尔托）的五个实验中收集了种群（两个 dallisgrass 亚种，巴伊亚草和 vaseygrass），秋季和春季播种日期以及灌溉和非灌溉地块。热液和热液时间模型用于出现时间。灌溉地块和秋播的预测更好。对于最大出现比例（MEP），调整了混合线性模型。在非灌溉处理中，早春播种的 MEP 较高，但晚春播种的 MEP 最低。此外，还修改了热时间指数 (TTI) 以模拟 MEP。设置根据每天的热液范围（HTR）衡量度-日累积的系数。HTR 由T和Ψ定义阈值。阈值和系数值通过基因型进行优化，直到 MEP 和修改后的 TTI 之间的线性回归达到更高的拟合。高温天（根据基因型 >18°C 或 20°C）在高或中土含水量可用时分别累积一半或没有度日。讨论了雀稗基因型、播种日期建议和改良 TTI 有用性之间的差异。