Simulating winter wheat yields under temperate conditions: exploring different management scenarios

This paper describes a methodology for analysing management strategies to find best agronomic practices using a crop simulation model (CERES-Wheat). The study area is the estate of Imperial College at Wye, in the Stour Catchment, Kent, UK, an area highly suited to winter wheat production. The model is validated using historic crop performance data. Yield responses to differing sowing rates (range 200–450 seeds m⁻²), sowing dates and rates of nitrogen application (between 100 and 220 kg ha⁻¹) with soil types of medium to heavy texture were simulated under water-limited conditions using historical daily weather data. In model validation, observed yields ranged between 6.9 and 7.4 t ha⁻¹, while simulated ranges were between 6.9 and 7.8 ha⁻¹. The RSMD of the difference was small (0.24 t ha⁻¹) and non-significant. Optimum management practices (in terms of planting date, seed density and nitrogen application) were thereby defined. Also, simulations of potential yield (i.e. yield with no water and nutrient stress) were run for comparison. Results of this study reveal that the calibrated and validated CERES-Wheat model can be successfully used for the prediction of wheat growth and yield under conditions appropriate to Western Europe.     

Phenological response of spring wheat to timing of photoperiod perception: The effect of sowing depth on final leaf number in spring wheat

Wheat phenological modelling literature suggests final leaf number (FLN) targets of wheat (Triticum aestivum) will be set only once daylight is perceived and will be based upon environmental and cultivar-specific genetics at that time. Development is thought to proceed relative to thermal time regardless of light perception prior to emergence. Modelled predictions of final leaf number (FLN) and thence anthesis are based on this mechanism. Results did not support this hypothesis, and we suggest and alternative hypothesis based on molecular interactions between vernalization genes Vrn1, Vrn2 and Vrn3.     

Performance and sensitivity of the DSSAT crop growth model in simulating maize yield under conservation agriculture

With the practice of conservation agriculture (CA) soil water and nutrient dynamics are modified by the presence of a mulch of crop residues and by reduced or no-tillage. These alterations may have impacts on crop yields. The crop growth model DSSAT (Decision Support Systems for Agrotechnology Transfer) has recently been modified and used to simulate these impacts on crop growth and yield. In this study, we applied DSSAT to a long-term experiment with maize (Zea mays L.) grown under contrasting tillage and residue management practices in Monze, Southern Province of Zambia. The aim was (1) to assess the capability of DSSAT in simulating crop responses to mulching and no-tillage, and (2) to understand the sensitivity of DSSAT model output to input parameters, with special attention to the determinants of the model response to the practice of CA. The model was first parameterized and calibrated for the tillage treatment (CP) of the experiment, and then run for the CA treatment by removing tillage and applying a mulch of crop residues in the model. In order to reproduce observed maize yields under the CP versus CA treatment, optimal root development in the model was restricted to the upper 22 cm soil layer in the CP treatment, while roots could optimally develop to 100 cm depth under CA. The normalized RMSE values between observed and simulated maize phenology and total above ground biomass and grain yield indicated that the CA treatment was equally well simulated as the CP treatment, for which the model was calibrated. A global sensitivity analysis using co-inertia analysis was performed to describe the DSSAT model response to 32 model input parameters and crop management factors. Phenological cultivar parameters were the most influential model parameters. This analysis also demonstrated that in DSSAT mulching primarily affects the surface soil organic carbon content and secondly the total soil moisture content, since it is negatively correlated with simulated soil water evaporation and run-off. The correlations between the input parameters or crop management factors and the output variables were stable over a wide range of seasonal rainfall conditions. A local sensitivity analysis of simulated maize yield to three key parameters for the simulation of the CA practice revealed that DSSAT responds to mulching particularly when rooting depth is restricted, i.e., when water is a critical limiting crop growth factor. The results of this study demonstrate that DSSAT can be used to simulate crop responses to CA, in particular through simulated mulching effects on the soil water balance, but other, often site-specific, factors that are not modeled by DSSAT, such as plough pan formation under CP or improved soil structure under CA, may need to be considered in the model parameterization to reproduce the observed crop yield effects of CA versus CP.     

不同降水状况下旱地玉米生长与产量对施氮量的响应

水分不足是旱地玉米生长主要限制因素,渭北旱塬雨养玉米种植区降水季节波动大,干旱频繁发生,已严重影响春玉米正常生长发育及产量稳定性。于2016—2018年在渭北旱塬合阳县进行旱地玉米施氮量定位试验,设置5个施氮量处理, 2016—2017年包括0、75、150、270、360 kg hm~(–2) (分别以N0、N75、N150、N270、N360表示), 2018年施氮量处理为0、90、180、270、360kgNhm~(–2) (分别以N0、N90、N180、N270、N360表示),供试品种为郑单958(ZD958)和陕单8806(SD8806)。分析了不同降水分布年份施氮量对春玉米生育期土壤水分变化动态、干物质积累动态、产量构成、经济效益及水分利用效率(WUE)的影响。结果表明,试验年份降水分布可分为穗期多雨、粒期干旱型(2016年和2018年)和穗期干旱、粒期多雨型(2017年)。生长季降水量及其分布显著影响土壤蓄水量和玉米地上部干物质积累,从而影响玉米产量及其构成因素,穗期干旱显著降低地上部干物质积累量和穗粒数,粒期干旱会明显降低粒重。不同降水分布年份施氮处理较N0增产6.72%～91.23%不等,施氮量对玉米产量、水分利用效率(WUE)影响呈现二次曲线关系,穗期多雨、粒期干旱型以N270处理籽粒产量和WUE最高,而穗期干旱、粒期多雨型以N150处理产量和WUE最好。籽粒产量与"休闲至抽雄期降水(FP2)"、"播前土壤蓄水量+播种至抽雄期降水(SP2)"相关性较强(FP2:R2=0.839**; SP2:R2=0.837**)。根据产量、水分利用和经济收益综合评价,渭北旱地玉米最适施氮方案为基施氮肥150kghm~(–2),再根据休闲至抽雄期降水量或播前土壤蓄水量与播种至抽雄期降水量之和预测产量,估算并及时追施适宜施氮量。     

Analysis of differences in growth of cucumber genotypes under low light conditions in relation to night temperature

Summary Growth of four breeding lines and two cultivars of slicing cucumber with different growth at low temperature and light intensity was analysed in relation to night temperature. Plants were grown from 17 days after sowing at 20°C day temperature and 20, 15 or 10°C night temperature (NT), a light intensity of 24 W/m² visible radiation and a daylength of 8 hours. Data from six successive harvests, ending 47 days after sowing, were analysed according to a MANOVA procedure.RGR, NAR, LAR, SLA and LWR generally decreased with time. Ln W and RGR were largely similar at 20 and 15°C NT, but reduced at 10°C NT. LAR and SLA decreased at each lower NT, whereas LWR increased. NAR was only marginally affected by NT. Significant genotypic differences occurred for 1n W, LAR, SLA, LWR, stem length and percentage of dry matter in leaves and stems at all NT's and for RGR and NAR only at 20°C. Genotypic differences for 1n W could not be explained by differences for RGR, but by differences for initial plant weight.Significant genotype × night temperature interactions were present for LWR. Breeding lines increased LWR in response to lower NT, while that of cultivars remained fairly constant. Implications for breeding are discussed.Abbreviations and definitions L plant length - LA leaf area - W dry weight of the shoot - RGR relative growth rate (the increase in W per unit of time and unit of W) - NAR net assimilation rate (the increase in W per unit of time and unit of LA) - LAR leaf area ratio (the leaf area at time t per unit of W) - SLA specific leaf area (the leaf area at time t per unit of leaf weight) - LWR leaf weight ratio (the leaf weight at time t per unit of W) - RGR NAR × LAR - LAR SLA × LWR - MANOVA multivariate analysis of variance