DSSAT模型在中国农业与气候变化领域应用进展

为了掌握农业转移支持决策系统(Decision Support System for Agrotechnology Transfer, DSSAT)模型在国内农业与气候变化领域的研究进展,更好地让模型在今后气候变化对农业生产影响评估和适应研究中应用,本文以近年来国内的研究和实践为基础,通过梳理模型应用的相关研究案例、方法和成果,从DSSAT 模型本地化适用性验证、数据库构建、参数订正和优化方案、气候变化影响评估及适应的应用等方面全面总结了模型的应用进展。结果表明：DSSAT模型在我国应用比较广泛,包括不同地区和不同作物之间;利用DSSAT模型研究气候变化对农业生产的影响的研究较多,研究结果比较丰富。但模型在应用中存在研究方法和结果比较分散、应用的作物种类有限、数据需求量大而实验数据有限等问题,这些都需要在今后的研究中不断完善解决。     

4M-software package for modelling cropping systems

4M is an easy-to-handle software that has been designed for both educational and scientific purposes. Our main goal in developing 4M was to preserve the features of CERES in a user-friendly software that can be easily extended with additional modules. The package has several characteristics that make it more than a simple crop model. 4M offers optional routines for several processes of the described soil-plant-atmosphere system. The users can build different system models, according to specific purposes. 4M includes input data generators for estimating soil and weather input data that are difficult to measure. 4M is able to simulate crop rotations by using the final conditions of the system after crop harvest as initial conditions for the following crop.     

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.     

Evaluating maize growth models “CERES-Maize” and “IXIM-Maize” under elevated temperature conditions

It would be preferable to use a reliable crop growth model for studies on climate change impact assessment. The objectives of this study was to evaluate simulation performance for two maize models, including CERES-Maize and IXIM models, included in the DSSAT model (version 4.6) in terms of phenology and yield. Two early maturing cultivars, Chalok#1 and Junda# 6, were grown under controlled environment in plastic houses at Suwon, Korea. Each cultivar, which was sown at four different date in 2013 and 2014, was subjected to four sets of temperature conditions including ambient (AT), AT+1.5°C, AT+3°C, and AT+5°C. In simulations of phenology under given conditions, the anthesis date and grain filling ratio were underestimated, especially when temperature was unusually high, e.g., in 2013. The maize models also had poor accuracy in grain yield, which resulted from the fact that these models had relatively large errors in simulation of kernel number and kernel weight under elevated temperature conditions. In addition, both models were not able to simulate the drastic decrease of kernel number due to heat stress around flowering periods. These results indicated that two maize models would need improvements in simulation of crop response to supra-optimal temperature before they would be used to assess the impact of the climate change on maize yield. This studies merits further study to improve algorithms in phenology simulation at supraoptimal temperature.     

Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment

In recent years, maize has become one of the main alternative crops for the Autumn–Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.     

A sequential approach for improving AZODYN crop model under conventional and low-input conditions

Advances in scientific understanding of the plant and soil behaviour in a cultivated field led to the design of numerous soil–crop models simulating crop growth. The frequent low predictive quality of these models is linked to uncertainties in inputs, parameters and equations. The AZODYN crop model predicting wheat grain yield and grain protein content was previously developed to support decision for N management of conventional and organic wheat crops. This paper outlines a sequential approach to improve the predictions of the AZODYN model by testing various formalisms. This study is based on the comparison of 38 versions of the model assessed in multi-environment trials carried out under conventional or low-input conditions. This paper describes and discusses the methodology. The results show that the predictive value of grain yield and grain protein content could be largely improved without increasing model complexity.     

Geospatial delineation of South Korea for adjusted barley cultivation under changing climate

Determining effective measures to alleviate the impact of climate change on crops under various regional environments is one of the most urgent issues facing agriculture. In this study, geographic regions of South Korea for future-adjusted barley cultivation were outlined and the impact of climate change on barley production in the next 100 years was evaluated under two greenhouse gas concentration trajectory scenarios: the representative concentration pathway (RCP) 4.5 and RCP 8.5. To achieve our intended study goals, a geospatial crop simulation modeling (GCSM) scheme was formulated using CERES-barley model of Decision Support System for Agricultural Technology (DSSAT) crop model package version 4.6 to simulate grid-based geospatial crop yields. Two experiments were carried out at an open field to obtain model coefficients for the nation and at temperature gradient field chambers to evaluate the performance of the CERES-barley model under elevated temperature conditions. Suitable cultivation regions for three different types of barley (naked, hooded, and malting) under changing climate were projected to expand to the northern regions under both RCP 8.5 and RCP 4.5. However, they were projected to expand more rapidly under RCP 8.5 than those under RCP 4.5. Projected yields of four barley varieties were increased with a slow phase as year progressed under RCP 4.5 scenario. However, they were rapidly increased under RCP 8.5 scenario. It appears that geospatial variation in barley yield under changing climate can be effectively outlined. Therefore, GCSM system might be useful for determining impacts of climate change on geospatial variations of crops, potentially providing means to impede food insecurity.     

RNAi技术在作物中的应用及安全评价研究

RNA干扰（RNAi）技术在基因功能研究方面应用广泛。近年来,RNAi被认为是具有应用潜力的育种新方法。具有良好抗虫性状的RNAi转基因作物已研究成功,预示其商业化应用成为可能。RNAi转基因作物如何监管成为人们关注的新问题。本文介绍了RNAi转基因作物的发展现状,分析了RNAi技术与传统育种技术及传统转基因技术之间的不同点,总结了RNAi转基因作物的潜在风险,并以美国和欧盟为代表总结了RNAi转基因作物的监管态度,最后分析了RNAi转基因作物存在的监管问题并提出了相关建议,为我国对RNAi转基因作物的监管提供参考。     

Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment

In recent years, maize has become one of the main alternative crops for the Autumn–Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.     

Towards an optimal management regime to facilitate the coexistence of GM herbicide tolerant and non-GM oilseed rape

Although a national strategy for the coexistence of GM and conventional/organic crops in Ireland has been published (McGill et al., 2005), measures pertaining to the coexistence of GM and non-GM oilseed rape (OSR) crops was omitted pending the completion of regional specific research. As the evaluation of gene flow between coexisting OSR varieties cannot be solely studied through field experiments and to assist policy makers in the generation of coexistence guidelines for GM herbicide tolerant (HT) OSR, the present work utilized the gene flow model GeneSys to simulate the influence of management strategies on gene escape from GM OSR across the Irish agri-environment. The model predicted that the incorporation of GMHT OSR into an existing winter wheat-based rotation without a complimentary modification to the cropping regime would rapidly compromise coexistence, recorded as the % harvest impurities in non-GM OSR crops at the silo and the % of non-GM OSR fields whose harvest exceeded the European Union labelling threshold of 0.9% GM content. Enhanced herbicide efficacy, the application of spring weed control, the inclusion of a single spring crop (potato, barley, maize) post-OSR, reduced regional harvest impurities in non-GM OSR crops below the 0.9% threshold. The simulations showed that the establishment of GM zones by clustering of GMHT OSR fields presents for early adopters a viable mechanism to achieve coexistence with neighboring non-GM OSR sites. By incorporating a 50 m non-OSR (GM/non-GM) buffer zone to circumvent each GM cluster, the simulations concluded that regional harvest purity can be assured with up to 6 separate clusters accommodating up to 10% regional GM adoption across the landscape. Significantly, these simulations were completed using GMHT OSR as a break crop in the standard winter wheat rotation, which in previous simulations was deemed to be impractical for coexistence purposes. Organizing cultivation through GM clusters, presents a workable option to those early adopters who will seek to investigate the potential of the technology by (i) concentrating the necessity for intensive volunteer control in a specific, localised area (ii) increasing the potential for allocating machinery via GM/non-GM purposes and (iii) facilitating regulatory requirements in regards to farmer-to-farmer communication.     

两种冬小麦气候适宜度评价模型的比较

为比较DSSAT模型和模糊数学方法用于冬小麦气候适宜度评价的效果,利用河南省杞县和汤阴县1999-2013年的气象资料、冬小麦发育期及产量数据,采用DSSAT模型和模糊数学方法构建两种冬小麦气候适宜度评价模型,并计算不同生育期和全生育期的冬小麦气候适宜度。利用相关分析方法,检验两种方法估算的冬小麦气候适宜度的评价效果。结果表明：杞县和汤阴县的出苗至越冬期、返青至拔节期、拔节至开花期、开花至成熟期,模型法估算的冬小麦气候适宜度与模糊数学法估算的冬小麦气候适宜度变化趋势基本一致,且呈正相关,而两个地点的越冬至返青期,两种方法估算的冬小麦气候适宜度呈负相关。两个地点两种方法估算的全生育期冬小麦气候适宜度变化趋势与实测产量的变化趋势基本一致,且两种方法估算的冬小麦气候适宜度呈正相关。模型法估算的冬小麦气候适宜度的标准差和变异系数均高于模糊数学估算的冬小麦气候适宜度的标准差和变异系数。但与模糊数学法相比,DSSAT模型估算的冬小麦气候适宜度与实测产量变化更接近。DSSAT模型可用于冬小麦气候适宜度评价研究。     

A sequential approach for improving AZODYN crop model under conventional and low-input conditions

Advances in scientific understanding of the plant and soil behaviour in a cultivated field led to the design of numerous soil–crop models simulating crop growth. The frequent low predictive quality of these models is linked to uncertainties in inputs, parameters and equations. The AZODYN crop model predicting wheat grain yield and grain protein content was previously developed to support decision for N management of conventional and organic wheat crops. This paper outlines a sequential approach to improve the predictions of the AZODYN model by testing various formalisms. This study is based on the comparison of 38 versions of the model assessed in multi-environment trials carried out under conventional or low-input conditions. This paper describes and discusses the methodology. The results show that the predictive value of grain yield and grain protein content could be largely improved without increasing model complexity.     

作物非充分灌溉决策指标研究进展

为了有效地进行非充分灌溉,通过不同方面研究土壤和作物水分亏缺的诊断方法,从而制定科学有效的灌水指标。对目前非充分灌溉的土壤、灌溉、作物等指标的研究现状及存在的问题进行了的阐述,讨论了非充分灌溉决策指标今后研究发展的方向。从目前国内外研究情况来看,应用叶水势、茎直径变化、冠层温度等作物指标来精确诊断作物的水分状况,已逐渐成为非充分灌溉研究领域关注的热点,但其基础理论、监测方法及不同作物的应用效果仍需进一步研究完善。因此,单纯从一种灌溉决策指标出发确定灌溉量是不全面的,如何建立非充分灌溉条件下不同地区、作物的灌溉指标体系将是今后中国重要的研究内容。     

烯效唑(S3307)提高作物抗逆性研究进展

全球气候变暖,导致各类自然灾害时有发生,作物生长环境恶化。为了缓解逆境对作物生长带来的影响,本研究总结了S₃₃₀₇在提高作物抗倒伏性、抗盐碱胁迫、抗水分胁迫以及抗温度胁迫方面的生物学功能,分析了S₃₃₀₇在提高作物抵御逆境环境领域的研究现状和发展趋势,指出在施用植物生长调节剂来提高作物的抗逆性时,要根据实际情况对施用方式和施用浓度进行科学调整。合理施用植物生长调节剂对作物抗逆、耐逆生长发育以及节本增产具有重要意义,为今后农业生产抗逆研究提供理论依据和科学指导。     

氮肥利用率的研究进展

旨在为提高作物的氮肥利用率、减少资源浪费、降低环境污染和提高作物产量提供科学依据。文章回顾了国内外近年来氮肥利用率的研究成果,从氮肥利用率的研究方法及影响因素等方面分析了氮肥利用率的研究历史、现状和存在问题。归纳得出中国氮肥利用率较低,施肥缺乏科学性,具体表现为氮肥施用量过大、氮肥挥发及硝化反硝化损失严重、施肥时期及施用量与作物氮素吸收规律不协调、肥料品种较单一等。建议结合测土配方施肥、实时监控管理等技术,合理地确定氮肥种类、用量、施用方式及时期,加强新型肥料及肥料增效剂等新技术的研发和推广,并注重作物氮高效品种资源的挖掘和应用,进而从土壤、肥料、品种、管理方式等多方面提高氮肥利用率。     

基于阿里云的无土栽培营养液信息采集系统

为实现对无土栽培营养液中影响作物生长的各重要因子的精准测量与控制,笔者研制了一种基于阿里云的温室无土栽培营养液信息监测系统。该系统主要包括采集模块、控制模块、云平台和应用终端4个部分。首先利用传感器实时测量营养液的电导率、酸碱度、液温、液位和含氧量等影响因子信息,然后进行数据整合处理,并通过无线通信模块传送至控制模块及阿里云平台进行数据保存,最后通过Web端实时监控营养液各信息变化。研究结果表明,该系统能够实时准确监测营养液的信息,合理反馈供给作物所需营养液信息,达到功能设计要求,而且系统成本低,具有一定的实用价值。     

Estimation of Soil Evaporation During Fallow Seasons to Assess Water Balances for No‐Tillage Crop Rotations

Abstract Estimates of soil evaporation and available soil water of no‐tillage fields under farm conditions are important to assess soil water status at sowing of rainfed grain crops. The objective of this study was to predict stored soil water of no‐tillage fields during the fallow periods following soybean (Glycine max (L.) Merr.) and maize (Zea mays L.) crops by accounting for decreased soil evaporation as a result of the residues left on the soil surface. Three simple phenomenological models were used to simulate stored soil water under field conditions at seven locations in Argentina. Two models calculated decreased soil evaporation based on crop residue mass, and the third assumed a constant fractional decrease in bare soil evaporation. All models gave good estimates of soil water content during the fallow periods following a soybean crop. In cases with large quantities of maize residue, however, the models resulted in more water retention in the soil than observed as a consequence of underprediction of soil evaporation. These results indicate that full benefit of crop residue was not being achieved in these fields, probably due to a failure to finely chop and uniformly distribute the crop material on the soil surface.     

缓/控释肥的研究应用现状

就国内外缓/控释肥料应用效果、施用方法做了综述。重点总结了缓/控释肥在作物上的应用效果和对土壤、环境的影响。与普通肥料相比,施用缓/控释肥料可以提高肥料利用率、提高作物产量、改善品质、改善土壤物理性状、提高土壤养分有效性、促进作物生长、减少环境污染。     

不同降水条件下北方日光温室填闲季糯玉米对土壤残留氮风险阻控研究

我国北方设施蔬菜生产中存在着不合理灌溉施肥的现象,严重影响着设施农业的可持续发展。本试验在种植季节外填闲期间,以休闲田地为对照,采用填闲作物种植和溴深层示踪技术研究了夏季填闲作物对土壤提氮作用。试验结果表明:夏季种植填闲作物可显著降低根区土壤中无机氮素的含量,尤其是土壤表层的无机氮含量。休闲处理,土壤(0～180 cm)各层的无机氮含量均有增加。但在干旱条件处理下种植填闲作物后,土壤(0～120 cm)各层的无机氮含量均出现下降。夏季降雨量是造成土壤氮素淋洗的主要因素,且土壤中无机氮含量越高,氮素淋洗量越大。种植填闲作物可以有效地吸收土壤中氮养分,在模拟干旱年份和正常年份降雨量的处理中,种植糯玉米从土壤中吸收氮量分别为172.6,146.6 kg/hm2。溴标记试验进一步证明了填闲作物的提氮能力,下层土壤中溴均出现向上运移的现象。本研究证实了种植填闲作物糯玉米具有有效利用菜田土壤残留氮与阻控氮淋洗风险的作用,为北方日光温室典型种植模式氮素优化管理提供了科学参考。