Modelling phenological and agronomic adaptation options for narrow-leafed lupins in the southern grainbelt of Western Australia

Australian modern narrow-leafed lupin (Lupinus angustifolius L.) cultivars tend to flower early and are vernalisation-unresponsive (VU). Cultivars have generally been selected for the warmer climates zones and sandy soils of the northern grain belt of Western Australia (NWA), where lupins are predominantly grown. In areas where climates are cooler and growing seasons are longer and wetter, such as the southern grain belt of Western Australia (SWA), it is probable that lupin would have a higher yield potential. Given that VU cultivars would have a longer vegetative phase (i.e. late flowering) we hypothesise that they may be more productive than those that are early flowering. Here we used a modelling approach to: 1) test the hypothesis that cool-climate SWA would have higher lupin yield than warm-climate NWA; 2) explore lupin phenological adaptation and yield potential in SWA over a range of proposed VU cultivars; and 3) further evaluate the combined effects of cultivar phenology, sowing time and seasonal type on lupin yields.Simulations from the Agricultural Production Systems Simulator (APSIM) showed that, on average, lupin yield in SWA was higher than that in NWA, with 23% greater yield for the early-flowering cultivar Mandelup. Proposed cultivars flowering 22 days (late-flowering) and 15 days (medium flowering) later than Mandelup would have their phenology better adapted in the high and medium rainfall zones of SWA, producing 16 and 7% more grain in the two rainfall zones, respectively. The proposed late-flowering cultivar sown before the end of April achieved higher yields for all seasons in the high rainfall zone and for above average and average rainfall seasons in the medium rainfall zone. In more water-limited situations early sowing was preferable with no obvious difference in yield among cultivars. Despite this, the early-flowering cultivar yielded more when sown in late April. The results indicate that lupin production would benefit from breeding VU varieties with a long vegetative phase for the SWA that should be sown in mid to late April.     

A global sensitivity analysis of cultivar trait parameters in a sugarcane growth model for contrasting production environments in Queensland,Australia

New sugarcane cultivars are continuously developed to improve sugar industry productivity. Despite this sugarcane crop models such as the ‘Sugar’ module in the Agricultural Productions System sIMulator (APSIM-Sugar) have not been updated to reflect the most recent cultivars. The implications of misrepresenting cultivar parameters in APSIM-Sugar is difficult to judge as little research has been published on the likely values of these parameters and how uncertainty in parameter values may affect model outputs. A global sensitivity analysis can be used to better understand how cultivar parameters influence simulated yields. A Gaussian emulator was used to perform a global sensitivity analysis on simulated biomass and sucrose yield at harvest for two contrasting sugarcane-growing regions in Queensland, Australia. Biomass and sucrose yields were simulated for 42 years to identify inter-annual variability in output sensitivities to 10 parameters that represent physiological traits and can be used to simulated differences between sugarcane cultivars. Parameter main effect (S_i) and total effect (ST_i) sensitivity indices and emulator accuracy were calculated for all year-region-output combinations. When both regions were considered together parameters representing radiation use efficiency (rue), number of green leaves (green_leaf_no) and a conductance surrogate parameter (k_L) were the most influential parameters for simulated biomass in APSIM-Sugar. Simulated sucrose yield was most sensitive to rue, sucrose_fraction (representing the fraction of biomass partitioned as sucrose in the stem) and green_leaf_no. However, climate and soil differences between regions changed the level of influence cultivar parameters had on simulation outputs. Specifically, model outputs were more sensitive to changes in the transp_eff_cf and k_L parameters in the Burdekin region due to lower rainfall and poor simulated soil conditions. Collecting data on influential traits that are relatively simple to measure (e.g. number of green leaves) during cultivar development would greatly contribute to the simulation of new cultivars in crop models. Influential parameters that are difficult to measure directly such as transp_eff_cf and sucrose_fraction are ideal candidates for statistical calibration. Calibrating crop models either through direct observation or statistical calibration would allow crop modellers to better test how new cultivars will perform in a range of production environments.     

基于APSIM模型的旱地小麦和豌豆水肥协同效应分析

为探索水肥协同作用对作物产量影响的机制和规律,在田间试验的基础上调试APSIM模型参数,并对模型进行检验,然后用该模型模拟近30多年来研究区的小麦/豌豆产量,并采用多元回归方法分析了施N量(X1)、生育期降水量(X2)和休闲期降水量(X3)对小麦/豌豆模拟产量的协同效应.结果表明,APSIM模型可以准确用来模拟小麦和豌...     

APSIM模型的研究进展及其在中国的应用

作物模型可以在已有研究资料基础上对在多种模拟条件下的作物生长情况进行模拟,预测未知风险,优化农业资源管理措施,为农业生产的管理经营提供科学指导。APSIM模型就是作物模型的典型代表。为了研究APSIM模型的结构特征和它在中国的应用现状,本文首先阐述了APSIM模型的发展历史、运行框架、模块结构组成,其次归纳总结了APSIM模型在中国气候变化评估和农田管理方面的应用以及在中国各个气候区域的应用,最后指出了APSIM模型在中国应用时所出现的问题,并为APSIM模型的应用提出了与RS技术和GIS技术相结合等一些意见。     

室内模拟实验研究中国北方不同管理方式对土壤固碳潜力的影响

Soil has been identified as a possible carbon(C) sink for sequestering atmospheric carbon dioxide(CO_2).However,soil organic carbon(SOC) dynamics in agro-ecosystems is affected by complex interactions of various factors including climate,soil and agricultural management practices,which hinders our understanding of the underlying mechanisms.The objectives of this study were to use the Agricultural Production Systems sIMulator(APSIM) model to simulate the long-term SOC dynamics under different management practices at four long-term experimental sites,Zhengzhou and Xuzhou with double cropping systems and Gongzhuling and Uriimqi with single cropping systems,located in northern China.Firstly,the model was calibrated using information from the sites and literature,and its performance to predict crop growth and SOC dynamics was examined.The calibrated model was then used to assess the impacts of different management practices,including fertilizer application,irrigation,and residue retention,on C dynamics in the top 30 cm of the soil by scenario modelling.Results indicate a significant SOC sequestration potential through improved management practices of nitrogen(N) fertilizer application,stubble retention,and irrigation.Optimal N fertilization(N_(opt)) and 100%stubble retention(R100) increased SOC by about 11.2%,208.29%,and 283.67%under irrigation at Gongzhuling,Zhengzhou,and Xuzhou,respectively.Soil organic carbon decreased rapidly at(U|¨)rumqi under irrigation,which was due to the enhanced decomposition by increased soil moisture.Under rainfed condition,SOC remained at a higher level.The combination of N_(opt) and R100 increased SOC by about 0.46%under rainfed condition at Uriimqi.Generally,agricultural soils with double cropping systems(Zhengzhou and Xuzhou) showed a greater potential to sequester C than those with single cropping systems(Gongzhuling and(U|¨)r(u|¨)mqi).     

基于APSIM模型分析不同降水年型下施氮深度对旱地小麦的产量效应

氮肥深施有助于提高旱地作物产量,但施氮深度对黄土高原丘陵沟壑区旱地小麦产量在不同降水年型的影响尚不清楚。利用1990—2020年气象观测数据,基于APSIM模型和数学统计方法探讨施氮深度对不同降水年型小麦产量的影响。结果表明:模型模拟的小麦产量和生物量模拟值与观测值相关性决定系数(R²)>0.9、模型有效性指数(M_E)>0.8及归一化均方根误差(NRMSE)<0.2,表明该模型在该地区具有较好的适用性;模拟的麦田生育期土壤水分动态变化和收获期土壤剖面含水量的NRMSE分别为0.05~0.07和0.13~0.29,表明该模型基本能够较准确模拟麦田土壤水分变化。氮肥深施增产效应在丰水年最高,平水年次之。与干旱年相比,相同施氮量下丰水年和平水年增加施氮深度可提高农田生产力稳定性和可持续性。在施氮水平为150 kg/hm²时,丰水年和平水年增加施氮深度对农田生产力稳定性没有明显影响,但有助于提高农田生产力可持续性。不同降水年型下,施氮深度和施氮量与产量交互关系表明,丰水年和平水年拟合关系较好,R²分别为0.76(P<0.05)和0.61(P<0.05),丰水年和平水年增加施氮深度至约20~23 cm可获得潜在最高产量。干旱年R²为0.29(P>0.05),增加施氮深度对干旱年小麦产量没有显著影响。研究结果以期为黄土高原丘陵沟壑区小麦在区域尺度优化施肥措施提供理论指导。     

基于APSIM模型的不同施肥处理下春玉米产量模拟及气候敏感性分析

以平凉市泾川县大田试验为基础,利用农业生产系统模拟模型,探究不同类型施肥处理对春玉米产量的影响以及气候变化对春玉米产量影响的敏感性差异,分析 APSIM模型对模拟该地区春玉米产量的适应性。结果表明, APSIM模型对该区域春玉米产量的模拟效果较好,决定系数(R²)介于 0.934～0.975,归一化均方根误差(NRMSE)介于 6.073%～9.758%,模型一致性指标(D)介于 0.952～0.987。模型敏感分析显示,年平均温度是模拟不同施肥处理下春玉米产量的敏感参数,其变化程度对模拟结果影响较大,不同施肥处理(CK、 N、 NP)下的敏感指数分别为 0.533 2、 0.558 7和 0.568 2。     

APSIM模型对宁夏海原地区草田轮作系统的适应性

为验证APSIM模型对宁夏海原地区草田轮作系统的适用性,基于10年生苜蓿(Medicago sativa)与小麦(Triticum aestivum)、谷子(Oryza sativa)草田轮作试验数据和同期气象资料,运用APSIM模型对系统进行了模拟。通过试错法和文献记载完成了苜蓿、小麦和谷子几个品种的参数本地化。用统计和图形校验方法评价了APSIM模型模拟结果的可靠性和准确性。结果表明,谷子-小麦-小麦(MWW)、小麦-谷子-小麦(WMW)、谷子-谷子-小麦(MMW)、谷子-小麦-谷子(MWM)、小麦-谷子-谷子(WMM)、小麦-小麦-谷子(WWM)6种轮作方式下产量实测值和模拟值的决定系数R2值范围在0.83至0.98之间,D值范围在0.94至0.99之间,表现出了良好的相关性和一致性。土壤含水量实测值和模拟值的决定系数R2值范围在0.52至1之间,D值范围在0.92至0.97之间,相关性和一致性表现良好。表明APSIM模型对宁夏海原地区苜蓿与小麦、谷子轮作具有较好的模拟能力,可以用来模拟分析该地区草田轮作系统生产潜力和土壤水分动态,对该地区气候变化影响下草田轮作的优化管理具有一定指导意义。     

补灌量和覆盖量变化对旱地春小麦叶面积指数的影响

免耕覆盖中补灌量和秸秆覆盖量变化对叶片生长有较大影响,以甘肃省定西市安定区1979—2019年历史气象数据为基础,运用APSIM模型对补灌量与覆盖量耦合变化时旱地春小麦的叶面积指数进行模拟,并采用方差分析、二次多项式回归、单因素分析等方法,研究补灌量和覆盖量对旱地春小麦叶面积的影响机制。结果表明：在试验设计范围内,旱地春小麦叶面积指数随着补灌量变化在分蘖—拔节期呈开口向下的二次抛物线先增后减变化,补灌量在252.09 mm时春小麦叶面积指数出现最大值为1.83,其他各个时期均呈开口向上的二次抛物线递增变化。随着秸秆覆盖量变化,叶面积指数在出苗—分蘖期,呈开口向下的二次抛物线先增后减变化,试验设计范围内秸秆覆盖量为2397.09 kg/hm²时春小麦叶面积指数出现最大值为0.59,分蘖—拔节期呈开口向下的二次抛物线递增变化;其他各个时期均呈开口向上的二次抛物线递增变化。相同阶段下,补灌量每增加50 mm,春小麦叶面积指数最大增幅13.95%;秸秆覆盖量每增加1000 kg/hm²,春小麦叶面积指数最大增幅3.7%。补灌量对春小麦叶面积指数的影响程度远大于秸秆覆盖量的影响。免耕覆盖中,合理的进行秸秆覆盖和补灌能够保持土壤中的水分,有利于旱地春小麦叶片生长。     

A flexible approach to managing variability in grain yield and nitrate leaching at within-field to farm scales

We up-scaled the APSIM simulation model of crop growth, water and nitrogen dynamics to interpret and respond to spatial and temporal variations in soil, season and crop performance and improve yield and decrease nitrate leaching. Grain yields, drainage below the maximum root depth and nitrate leaching are strongly governed by interaction of plant available soil water storage capacity (PAWC), seasonal rainfall and nitrogen supply in the water-limited Mediterranean-type environment of Western Australia (WA). APSIM simulates the interaction of these key system parameters and the robustness of its simulations has been rigorously tested with the results of several field experiments covering a range of soil types and seasonal conditions in WA. We used yield maps, soil and weather data for farms at two locations in WA to determine spatial and temporal patterns of grain yield, drainage below the maximum root depth and nitrate leaching under a range of weather, soil and nitrogen management scenarios. On one farm, we up-scaled APSIM simulations across the whole farm using local weather and fertiliser use data and the average PAWC values of soil type polygons. On a 70 ha field on another farm, we used a linear regression of apparent soil electrical conductivity (EC_a) measured by EM38 against PAWC to transform an EC_a map of the field into a high resolution (5 m grid) PAWC map. We then used regressions of simulated yields, drainage below the maximum root depth and nitrate leaching on PAWC to upscale the APSIM simulations for a range of weather and fertiliser management scenarios. This continuous mapping approach overcame the weakness of the soil polygons approach, which assumed uniformity in soil properties and processes within soil type polygons. It identified areas at greatest financial and environmental risks across the field, which required focused management and simulated their response to management interventions. Splitting nitrogen applications increased simulated wheat yields at all sites across the field and decreased nitrate leaching particularly where the water storage capacity of the soil was small. Low water storage capacity resulted in both low wheat yields and large leaching loss. Another management option to decrease leaching may be to grow perennial vegetation that uses more water and loses less by drainage.Paper from the 5th European Conference on Precision Agriculture (5ECPA), Uppsala, Sweden, 2005