农业工程学报
農業工程學報
농업공정학보
2015年
12期
138-150
,共13页
姚宁%周元刚%宋利兵%刘健%李毅%吴淑芳%冯浩%何建强
姚寧%週元剛%宋利兵%劉健%李毅%吳淑芳%馮浩%何建彊
요저%주원강%송리병%류건%리의%오숙방%풍호%하건강
模型%作物%水分%冬小麦%DSSAT%CERES-Wheat
模型%作物%水分%鼕小麥%DSSAT%CERES-Wheat
모형%작물%수분%동소맥%DSSAT%CERES-Wheat
models%crops%moisture%winter wheat%DSSAT%CERES-Wheat
作物模型为人们认识旱区农业生境过程并对其进行调控提供了一种有效的工具。为了探讨小麦生长模拟模型DSSAT-CERES-Wheat能否准确模拟水分胁迫条件下旱区冬小麦的生长发育和产量形成过程，同时确定参数估计和模型验证的最优方案，该研究进行了连续两季（2012.10－2013.06和2013.10－2014.06）的冬小麦分段受旱田间试验。试验将冬小麦整个生育期划分为越冬、返青、拔节、抽穗和灌浆5个主要生长阶段，每相邻两个生长阶段连续受旱，形成4个不同的受旱时段水平（D1－D4），根据小麦生育期的需水量，设置灌水定额分别为40和80 mm 2个水平（I1和I2），共形成8个处理，每处理3次重复，在遮雨棚内采用裂区试验布置，此外在旁边设置1个各生育期全灌水的对照处理。文中设置了5套不同的参数估计和验证方案，利用DSSAT-GLUE参数估计模块得到不同的参数估计结果。通过对比分析冬小麦物候期、单粒质量、生物量、产量、以及土壤水分含量的模拟值和实测值之间的差异，以确定利用DSSAT-CERES-Wheat模型模拟旱区冬小麦生境过程的精度。结果表明，参数P1V（最适温度条件下通过春化阶段所需天数）和G3（成熟期非水分胁迫下单株茎穂标准干质量）具有较强的变异性，变异系数分别为19.07%和16.34%，受基因型-环境互作的影响较大，而其他参数的变异性则较弱，变异系数均小于10%；DSSAT-GLUE参数估计工具具有较好的收敛性，不同参数估计方案所得的参数值具有一定的一致性；不同的参数估计方案所得的模型输出结果有较大差异，其中参数估计方案1（利用两季试验中的充分灌溉处理 CK 数据进行参数估计，其他不同阶段受旱处理数据进行验证）的模型校正和验证精度最高，其中模型校正的绝对相对误差（absolute relative error，ARE）和相对均方根误差（relative root mean squared error, RRMSE）分别为4.89%和5.18%。在冬小麦抽穗期和灌浆期受旱时，DSSAT-CERES-Wheat模型可以较好地模拟小麦的生长发育过程以及土壤水分的动态变化，但是在越冬期和返青期受旱时，模拟结果相对较差，并且随着受旱时段提前和受旱程度的加重，模拟精度将变得更低。此外，该模型无法模拟由不同水分胁迫造成的冬小麦物候期差异，需要对模型进行相应的改进。交叉验证表明 DSSAT-CERES-Wheat 模型模拟该研究中不同水分胁迫条件下冬小麦生长和产量的总体性误差在15%～18%左右。总之，DSSAT-CERES-Wheat模型在模拟旱区冬小麦生境过程时存在着一定的局限性，若要更广泛地将该模型应用在中国干旱半干旱地区的冬小麦生产管理和研究，有必要对冬小麦营养生长阶段前期的水分胁迫响应机制和模拟方法进行进一步的深入研究。
作物模型為人們認識旱區農業生境過程併對其進行調控提供瞭一種有效的工具。為瞭探討小麥生長模擬模型DSSAT-CERES-Wheat能否準確模擬水分脅迫條件下旱區鼕小麥的生長髮育和產量形成過程，同時確定參數估計和模型驗證的最優方案，該研究進行瞭連續兩季（2012.10－2013.06和2013.10－2014.06）的鼕小麥分段受旱田間試驗。試驗將鼕小麥整箇生育期劃分為越鼕、返青、拔節、抽穗和灌漿5箇主要生長階段，每相鄰兩箇生長階段連續受旱，形成4箇不同的受旱時段水平（D1－D4），根據小麥生育期的需水量，設置灌水定額分彆為40和80 mm 2箇水平（I1和I2），共形成8箇處理，每處理3次重複，在遮雨棚內採用裂區試驗佈置，此外在徬邊設置1箇各生育期全灌水的對照處理。文中設置瞭5套不同的參數估計和驗證方案，利用DSSAT-GLUE參數估計模塊得到不同的參數估計結果。通過對比分析鼕小麥物候期、單粒質量、生物量、產量、以及土壤水分含量的模擬值和實測值之間的差異，以確定利用DSSAT-CERES-Wheat模型模擬旱區鼕小麥生境過程的精度。結果錶明，參數P1V（最適溫度條件下通過春化階段所需天數）和G3（成熟期非水分脅迫下單株莖穂標準榦質量）具有較彊的變異性，變異繫數分彆為19.07%和16.34%，受基因型-環境互作的影響較大，而其他參數的變異性則較弱，變異繫數均小于10%；DSSAT-GLUE參數估計工具具有較好的收斂性，不同參數估計方案所得的參數值具有一定的一緻性；不同的參數估計方案所得的模型輸齣結果有較大差異，其中參數估計方案1（利用兩季試驗中的充分灌溉處理 CK 數據進行參數估計，其他不同階段受旱處理數據進行驗證）的模型校正和驗證精度最高，其中模型校正的絕對相對誤差（absolute relative error，ARE）和相對均方根誤差（relative root mean squared error, RRMSE）分彆為4.89%和5.18%。在鼕小麥抽穗期和灌漿期受旱時，DSSAT-CERES-Wheat模型可以較好地模擬小麥的生長髮育過程以及土壤水分的動態變化，但是在越鼕期和返青期受旱時，模擬結果相對較差，併且隨著受旱時段提前和受旱程度的加重，模擬精度將變得更低。此外，該模型無法模擬由不同水分脅迫造成的鼕小麥物候期差異，需要對模型進行相應的改進。交扠驗證錶明 DSSAT-CERES-Wheat 模型模擬該研究中不同水分脅迫條件下鼕小麥生長和產量的總體性誤差在15%～18%左右。總之，DSSAT-CERES-Wheat模型在模擬旱區鼕小麥生境過程時存在著一定的跼限性，若要更廣汎地將該模型應用在中國榦旱半榦旱地區的鼕小麥生產管理和研究，有必要對鼕小麥營養生長階段前期的水分脅迫響應機製和模擬方法進行進一步的深入研究。
작물모형위인문인식한구농업생경과정병대기진행조공제공료일충유효적공구。위료탐토소맥생장모의모형DSSAT-CERES-Wheat능부준학모의수분협박조건하한구동소맥적생장발육화산량형성과정，동시학정삼수고계화모형험증적최우방안，해연구진행료련속량계（2012.10－2013.06화2013.10－2014.06）적동소맥분단수한전간시험。시험장동소맥정개생육기화분위월동、반청、발절、추수화관장5개주요생장계단，매상린량개생장계단련속수한，형성4개불동적수한시단수평（D1－D4），근거소맥생육기적수수량，설치관수정액분별위40화80 mm 2개수평（I1화I2），공형성8개처리，매처리3차중복，재차우붕내채용렬구시험포치，차외재방변설치1개각생육기전관수적대조처리。문중설치료5투불동적삼수고계화험증방안，이용DSSAT-GLUE삼수고계모괴득도불동적삼수고계결과。통과대비분석동소맥물후기、단립질량、생물량、산량、이급토양수분함량적모의치화실측치지간적차이，이학정이용DSSAT-CERES-Wheat모형모의한구동소맥생경과정적정도。결과표명，삼수P1V（최괄온도조건하통과춘화계단소수천수）화G3（성숙기비수분협박하단주경수표준간질량）구유교강적변이성，변이계수분별위19.07%화16.34%，수기인형-배경호작적영향교대，이기타삼수적변이성칙교약，변이계수균소우10%；DSSAT-GLUE삼수고계공구구유교호적수렴성，불동삼수고계방안소득적삼수치구유일정적일치성；불동적삼수고계방안소득적모형수출결과유교대차이，기중삼수고계방안1（이용량계시험중적충분관개처리 CK 수거진행삼수고계，기타불동계단수한처리수거진행험증）적모형교정화험증정도최고，기중모형교정적절대상대오차（absolute relative error，ARE）화상대균방근오차（relative root mean squared error, RRMSE）분별위4.89%화5.18%。재동소맥추수기화관장기수한시，DSSAT-CERES-Wheat모형가이교호지모의소맥적생장발육과정이급토양수분적동태변화，단시재월동기화반청기수한시，모의결과상대교차，병차수착수한시단제전화수한정도적가중，모의정도장변득경저。차외，해모형무법모의유불동수분협박조성적동소맥물후기차이，수요대모형진행상응적개진。교차험증표명 DSSAT-CERES-Wheat 모형모의해연구중불동수분협박조건하동소맥생장화산량적총체성오차재15%～18%좌우。총지，DSSAT-CERES-Wheat모형재모의한구동소맥생경과정시존재착일정적국한성，약요경엄범지장해모형응용재중국간한반간한지구적동소맥생산관리화연구，유필요대동소맥영양생장계단전기적수분협박향응궤제화모의방법진행진일보적심입연구。
Crop growth simulation models are useful tools to help us understand and regulate the agro-ecological systems in arid areas. In this study, the CERES-Wheat, a wheat growth simulation model in the DSSAT (decision support system for agrotechnology transfer) software, was investigated for its ability to simulate the growth and yield of winter wheat (Triticum aestivum L.) in arid areas and to find the optimal plan for the estimation of genetic parameters and the model verification. Field experiments were conducted under a rainout shelter for winter wheat growing under water stresses at different growth stages in 2 growth seasons (from October 2012 to June 2013 and from October 2013 to June 2014). The whole growth season of wheat was divided into 5 growing stages (wintering, greening, jointing, heading and grain filling). Water stress occurred every 2 continuous stages while irrigations were applied at other stages, which resulted in 4 different levels of water stress period (D1-D4). Two irrigation levels of 40 mm (I1) and 80 mm (I2) were applied. There were a total of 8 treatments, with 3 replicates for each, and the split-plot experiment was designed. An extra control treatment with irrigation in all 5 stages was arranged near. The experimental data were used to run the model. A total of 5 different plans for model calibration and verification were designed and the DSSAT-GLUE, a program package for parameter estimation in DSSAT, was used to estimate the relevant genetic coefficients. Then the 5 plans were compared for the discrepancies between corresponding simulated and observed values of phenological phase, single grain weight, biomass, yield and soil moisture so as to determine the accuracy of CERES-Wheat model to simulate the agro-ecological processes of winter wheat farming system in arid areas. The results showed that 2 genetic coefficients P1V (days required to complete vernalization at optimum vernalizing temperature) and G3 (standard dry weight of a single tiller without stress at maturity) varied remarkably under different scenarios of water stress. The coefficients of variation were 19.07% and 16.34%, respectively. It suggested that the values of these 2 parameters were influenced heavily by genotype-environment interactions. The rest of parameters were relatively independent of water stress scenarios since the coefficients of variation were all less than 10%. The DSSAT-GLUE package was proved to have good convergence since the estimated values of most genetic coefficients converged into narrow ranges. For output variables, the different plans of model calibration and verification showed great discrepancy. Plan 1 (model calibration used the data from the CK treatments with sufficient irrigation and model verification used the data from the rest of treatments in the 2 growth seasons) was proved to be the optimal one since its absolute relative error (ARE) and relative root mean squared error (RRMSE) for model calibration were the lowest, only 4.89% and 5.18%, respectively. When water stresses occurred during the heading and grain-filling stages, CERES-Wheat model was able to correctly simulate the dynamic changes in growth and development of wheat as well as the soil moisture content. However, when water stresses occurred during the wintering and greening stages, there were relatively large simulation errors. When water stress occurred earlier and severer, the simulation accuracy was lower. In addition, CERES-Wheat model could not correctly simulate the phenological discrepancies caused by different water stress scenarios because current algorithm for phenology estimation was only based on temperature and photoperiod but neglecting the secondary effects by water stress. Thus an improvement on current phenology algorithm of winter wheat was needed. The results of leave-one-out cross validation showed that the overall error was about 15%-18% for CERES-Wheat model to simulate winter wheat growth and yield under different scenarios of water stress designed in this study. In general, there were some limitations for CERES-Wheat model to simulate winter wheat growth under arid conditions. It was necessary to research into the mechanism and simulation method of winter growth responding to water stresses in early vegetative stage, if CERES-Wheat was expected to be applied more widely in the management and research of winter wheat production in arid and semi-arid areas in China.
