Table_3_Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.xlsx

Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and −10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha−1, and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in South-West of France and therefore may represent an important agronomic lever to escape summer drought that markedly limit soybean yield in this region.

大豆出苗与产量易受诸多因素影响。深入解析品种×播期×环境的互作效应，有助于明晰大豆与其他作物的竞争能力，尤为关键的是，可助力调控制约大豆生产的主要生物与非生物因子。本研究开展了为期2年的田间试验，针对3个不同熟期组的大豆品种，设置早播与常规播期两个处理，并在3个试验地点开展试验，以测定其出苗动态与最终出苗率。同时，通过控制条件下的室内试验测定了这3个不同熟期组大豆品种的萌发参数，用于参数化SIMPLE作物出苗模型（SIMPLE crop emergence model）。借此，本研究得以评估该模型对出苗率的预测性能，并开展相关模拟研究。田间条件下的最终出苗率范围为：早播处理62%~92%，常规播期处理51%~94%。该模型可精准预测出苗过程与最终出苗率，其预测均方根误差（root mean square error of prediction, RMSEP）、模型效率（efficiency, EF）与平均偏差（mean deviation, MD）分别介于2%~18%、0.46%~0.99%与−10%~15%，适用于测试范围内的多种播期条件。研究发现，不仅不同品种间的最终出苗率存在差异，同一品种在不同试验地点的出苗率也有所不同，但未观察到明确的变化趋势或一致的排名规律。建模分析表明，幼苗死亡率与土壤类型密切相关：粉壤土中因土壤结壳与土壤团粒分别导致的幼苗死亡率可达35%与14%。在所有土壤类型中，种子不萌发是导致出苗损失的最次要因素（最多造成3%的出苗损失），且未观测到由干旱导致的幼苗死亡。供试材料的平均籽粒产量介于3.1~4.0 t·ha⁻¹，其显著受灌溉制度（p < 0.001）与试验年份（p < 0.001）的影响，但不受试验地点、播期或品种的影响。综上，在法国西南部地区，早播大概率不会对大豆出苗产生不利影响，因此早播可作为一项重要的农艺调控手段，帮助规避显著制约该区域大豆产量的夏季干旱胁迫。