DYNAMIC MODEL OF CROP GROWTH SYSTEM AND NUMERICAL SIMULATION OF CROP GROWTH PROCESS UNDER THE MULTI-ENVIRONMENT EXTERNAL FORCE ACTION

According to the biomechanic theory and method, the dynamic mechanism of crop growth under the external force action of multi_environment factors (light, temperature,soil and nutrients etc.) was comprehensively explored.Continuous_time Markov(CTM) approach was adopted to build the dynamic model of the crop growth system and the simulated numerical method. The growth rate responses to the variation of the external force and the change of biomass saturation value were studied. The crop grew in the semiarid area was taken as an example to carry out the numerical simulation analysis, therefore the results provide the quantity basis for the field management. Comparing the dynamic model with the other plant growth model, the superiority of the former is that it displays multi_dimension of resource utilization by means of combining macroscopic with microcosmic and reveals the process of resource transition. The simulation method of crop growth system is advanced and manipulated. A real simulation result is well identical with field observational results.

Studies on crop growth modelling and simulation models in China

There is a close relationship between agricultural production and environmental meteorological conditions. In the study of the correlation between them, the simulation models are paid more attention to the crop growth. In this paper the development of the studies on the crop growth dynamic simulation model in China is briefly reviewed. The relationships between meteorological conditions and each process of crop growth (such as photosynthesis, respiration, accumulation and distribution of assimilation products and growth of leaf area) are studied and simulated basing on the results from field experiments. Preliminary models for rice, wheat, maize and soybean have been developed, and some investigations about modelling methods, procedures and parameters in simulation models are made.

Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops,thereby performing yield prediction,but not for fruit tree species such as jujube tree(Zizyphus jujuba).The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter.The model was established using data collected from dedicated field experiments performed in 2016-2018.Simulated growth dynamics of dry weights of leaves,stems,fruits,total biomass and leaf area index(LAI) agreed well with measured values,showing root mean square error(RMSE) values of 0.143,0.333,0.366,0.624 t ha^-1 and 0.19,and R2 values of 0.947,0.976,0.985,0.986 and 0.95,respectively.Simulated phenological development stages for emergence,anthesis and maturity were 2,3 and 3 days earlier than the observed values,respectively.In addition,in order to predict the yields of trees with different ages,the weight of new organs(initial buds and roots) in each growing season was introduced as the initial total dry weight(TDWI),which was calculated as averaged,fitted and optimized values of trees with the same age.The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI.The modelling performance was significantly improved when it considered TDWI integrated with tree age,showing good global(R2≥0.856,RMSE≤0.68 t ha^-1) and local accuracies(mean R2≥0.43,RMSE≤0.70 t ha^-1).Furthermore,the optimized TDWI exhibited the highest precision,with globally validated R2 of 0.891 and RMSE of 0.591 t ha^-1,and local mean R2 of 0.57 and RMSE of 0.66 t ha^-1,respectively.The proposed model was not only verified with the confidence to accurately predict yields of jujube,but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

Spatial-time continuous changes simulation of crop growth parameters with multi-source remote sensing data and crop growth model

本文将遥感信息与作物模型同化实现作物生长参数的时空域连续模拟,进而监测生长参数的时空域变化。首先将作物模型WOFOST(World food studies)与冠层辐射传输模型PROSAIL耦合构建WOPROSAIL模型,利用微粒群算法(PSO)通过最小化从CCD数据获取的土壤调节植被指数观测值SAVI(soil adjusted vegetation index)与耦合模型得到的模拟值SAVI’之间差值优化作物模型初始参数。通过MODIS数据反演实现参数的区域化,并将区域参数作为优化后作物模型输入参数驱动模型逐像元计算生长参数,实现生长参数的时空域连续模拟与监测,最终建立区域尺度遥感-作物模拟同化框架模型RS-WOPROSAIL。结果表明:同化模型解决了作物模型模拟空间域和遥感信息时间域的不连续问题。模型模拟的叶面积指数(LAI)、穗重(WSO)、地上总生物量(TAGP)等生长参数较好地体现了水稻生长状况时空域变化,研究区水稻模拟产量与实际产量的误差为27.4%。

Establishment of Winter Wheat Regional Simulation Model Based on Remote Sensing Data and Its Application

Accurate crop growth monitoring and yield forecasting are significant to the food security and the sustainable development of agriculture. Crop yield estimation by remote sensing and crop growth simulation models have highly potential application in crop growth monitoring and yield forecasting. However, both of them have limitations in mechanism and regional application, respectively. Therefore, approach and methodology study on the combination of remote sensing data and crop growth simulation models are concerned by many researchers. In this paper, adjusted and regionalized WOFOST （World Food Study） in North China and Scattering by Arbitrarily Inclined Leaves-a model of leaf optical PROperties SPECTra （SAIL-PROSFPECT） were coupled through LAI to simulate Soil Adjusted Vegetation Index （SAVI） of crop canopy, by which crop model was re-initialized by minimizing differences between simulated and synthesized SAVI from remote sensing data using an optimization software （FSEOPT）. Thus, a regional remote-sensingcrop-simulation-framework-model （WSPFRS） was established under potential production level （optimal soil water condition）. The results were as follows： after re-initializing regional emergence date by using remote sensing data, anthesis, and maturity dates simulated by WSPFRS model were more close to measured values than simulated results of WOFOST; by re-initializing regional biomass weight at turn-green stage, the spatial distribution of simulated storage organ weight was more consistent with measured yields and the area with high values was nearly consistent with actual high yield area. This research is a basis for developing regional crop model in water stress production level based on remote sensing data.

Simulation and Validation of Rice Potential Growth Process in Zhejiang Province of China by Utilizing WOFOST Model

A crop growth model of WOFOST was calibrated and validated through rice field experiments from 2001 to 2004 in Jinhua and Hangzhou, Zhejiang Province. For late rice variety Xiushui 11 and hybrid Xieyou 46, the model was calibrated to obtain parameter values using the experimental data of years 2001 and 2002, then the parameters were validated by the data obtained during 2003. For single hybrid rice Liangyoupeijiu, the data recorded in 2004 and 2003 were used for calibration and validation, respectively. The main focus of the study was as follows： the WOFOST model is good in simulating rice potential growth in Zhejiang and can be used to analyze the process of rice growth and yield potential. The potential yield obtained from the WOFOST model was about 8100 kg/ha for late rice and 9300 kg/ha for single rice. The current average yield in Jinhua is only about 78% （late rice） and 70% （single rice） of their potential yield. The results of the simulation also showed that the currant practice of management at the middle and late growth stages of rice should be reexamined and improved to reach optimal rice growth.

A Method for Upscaling Genetic Parameters of CERES-Rice in Regional Applications

To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.

Applications of Decision Support System:A Case Study of Solanaceous Vegetables

Crop simulation models constitute the major proportion in decision support systems.A large number of crop models have been developed for potato and few for tomato and peppers.In the literature,thirty three crop models have been reported to simulate potato,nine for tomato and six for peppers.Some of these models dealt with the climate change scenario and others with the crop management practices such as sowing time,irrigation,nitrogen,and insect-pests management.The most evaluated and applied models for potato include;SUBSTOR,and LINTUL-Potato,whereas CROPGRO-tomato model is the most tested and applied for tomato.The AQUACROP is the most widely used model to simulate the water dynamics.The CROPGRO model has been tested for elevated temperatures and CO_(2) under greenhouse conditions for tomato.In tomato and peppers,almost similar models have been applied for field conditions as well as under greenhouse environments with some modifications.Nitrogen dynamics has been widely tested by employing the EU-Rotate-N model for tomato and peppers.Simulation studies dealing with changing climate conditions are rare in potato and are not found for tomato and peppers.To modify potato,tomato and peppers models for climate impact studies,it is required that they are(a)calibrated and evaluated with new cultivars under various agro-environmental conditions and(b)assessed under varying field conditions under changing climates and crop management practices,including temperature increases,water and nutrient management and their interactions.These comprehensive model studies and modifications need a collaborative international effort and a multi-year,large scale field research studies on potato,tomato and peppers.

Dynamic modeling of mineral contents in greenhouse tomato crop

Tomato is one the most important vegetables worldwide and mineral nutrition in tomato crops is considered as the second most important factor in crop management after water availability. Mathematical modeling techniques allow us to design strategies for nutrition management. In order to generate the necessary information to validate and calibrate a dynamic growth model, two tomato crop cycles were developed. Several mineral analyses were performed during crop development to determine the behavior of N, P, K, Ca, Mg and S in different organs of the plant. Regression models were generated to mimic the behavior of minerals in tomato plants and they were included in the model in order to simulate their dynamic behavior. The results of this experiments showed that the growth model adequately simulates leaf and fruit weight (EF > 0.95 and Index > 0.95). As for harvested fruits and harvested leaves, the simulation was less efficient (EF < 0.90 and Index < 0.90). Simulation of minerals was suitable for N, P, K and S as both, the EF and the Index, had higher values than 0.95. In the case of Ca and Mg, simulations showed indices below 0.90. These models can be used for planning crop management and to design more appropriate fertilization strategies.

不同矿化度水源膜下滴灌棉田土壤水盐动态和作物生长模拟

为构建适用于干旱区膜下滴灌条件的土壤水盐动态分布和棉花生长模型,基于2020—2021年的田间试验,经过对SWAP模型的土壤、土壤水力功能和作物生长等模块进行率定和验证,对灌溉水矿化度为1、2、3、4、5、6 g·L^(-1)时的土壤水盐分布特征、作物生长过程和干物质累积分配进行数值模拟。结果表明:(1)土壤含水率与土壤含盐量的模拟精度以20~100 cm土层较好,0~20 cm土层模拟精度较差,其中土壤含水量的模拟效果优于土壤含盐量;随着灌溉水源矿化度的增加,土壤含水率和含盐量的模拟误差逐渐变小。(2)不同矿化度水源膜下滴灌棉花叶面积指数模拟效果较好(R2=90.72%,RMSE=0.35 cm^(2)·cm^(-2),NRMSE=8.73%,IOA=0.98)。(3)不同矿化度水源膜下滴灌棉花茎干物质累积量模拟效果较好(R2=89.08%,RMSE=6.12 g,NRMSE=23.16%,IOA=0.96)。研究结果表明,SWAP模型可以较好地对不同矿化度水源膜下滴灌的土壤水盐动态分布和棉花生长过程进行模拟。

Research in Agrometeorolgy on Fodder Crops in Central India—An Overview

Livestock rearing is one of the major occupations in India and is making significant contribution to the country GDP. The regional and seasonal variations in the teperature and rainfall distribution have been the major factors influencing the economy of a region. It is a matter of serious concern that out of 11 districts of central India, 9 districts are showing increasing trend in maximum temperature with a rate of 0.01°C to 0.15°C/year. A significant long-term decreasing trend (Slope = -4.26) was found in annual rainfall series at Jhansi. At Jhansi, moderate to severe drought occurs once in five years. But in the last decade, 7 years experienced moderate to disastrous drought in Jhansi region, wherein rainfall deficiency ranged between 40% and 60% from normal value. Of special mention was the year, 2006, which experienced a worst drought ever recorded for this region. Studies related to crop simulation model was carried out for fodder sorghum and its application for agronomic management and assessing the impact of climate change. Crop modeling studies on forage sorghum (C4) and cowpea (C3) showed increased dry matter biomass by 3% in sorghum but more prominent in cowpea by 46% under elevated CO2 from 330 ppm to 770 ppm. The interaction study of enhanced CO2 and temperature showed prominent negative impact on yields of both the crops. Evapotranspiration and crop coefficient (Kc) of several fodder crops i.e. berseem, lucerne, oat, sorghum, teosinte, maize + cowpea, guinea + berseem were worked out. In berseem, the highest Kc (1.81) was found during 2nd cutting followed by 3rd and 4th cuts. Estimates on irrigation scheduling for the guinea grass + berseem showed that the cropping system requires 7 irrigations at an interval ranging from 13 to 30 days to fulfill the 567.6 mm of water per season as net irrigation under mar soil (black) type whose actual water holding capacity (AWHC) is 175 mm. Similarly, if the cropping system is grown under kabar (AHWC = 140 mm) soil, then it requires nine irrigation with a total water requirement of 591.5 mm at an interval ranging from 10 to 24 days. For integrated pest management (IPM) scheme of lucerne, degree day based model was developed to monitor the lucerne weevil population in central region.

作物生长模型研究综述

作物生长模型的构建有利于既有科研成果的综合集成 ,也是作物种植管理决策现代化的基础 ,还是辅助决策的有力工具。本文以荷兰Wageningen ,美国DSSAT ,澳大利亚APSIM和中国CCSODS等作物生长模型研究流派为例 ,回顾了作物生长模型的发展历程 ,论述了作物生长模型的主要功用 。

数字植物及其技术体系探讨

数字植物是数字农业的基础,是利用数字化方法研究植物,并为植物生命系统和农业生产过程的数字化表达、生长建模、过程模拟、可视化计算分析、协同科研实验、成果共享及集成应用提供信息服务和技术支撑平台。探讨数字植物及其技术体系对数字农业有重要的意义。本文介绍了数字植物的概念和内涵,分析了数字植物的基本研究问题,在此基础上探讨了数字植物的科学内涵和技术支撑体系,并讨论了该技术体系建设的重点和应采取的对策方法,以期为数字植物的进一步发展提供有益参考。

基于遥感信息的华北冬小麦区域生长模型及模拟研究

卫星遥感估产和作物生长模拟在作物监测和产量预测方面有各自不可替代的优势。但是,遥感估产难以揭示作物生长发育和产量形成的内在机理,作物模拟在区域应用时初始值的获取和参数的区域化遇到很多困难。如何利用二者的互补性使其相互结合受到人们关注。该文在Wofost模型本地化和区域化的基础上,首次利用同化法的思路探讨了MODIS遥感信息与华北冬小麦生长模拟模型结合的可行性和方法,初步建立了潜在生产水平(水分适宜条件)下区域遥感-作物模拟框架模型(WSPFRS模型)。模拟结果显示:WSPFRS模型对区域尺度的出苗期重新初始化后,模拟的开花期、成熟期空间分布的准确性比Wofost模拟结果有所改进;利用遥感信息对区域尺度上返青期生物量重新初始化后,模拟贮存器官干重的空间分布更接近实际单产的分布,贮存器官干重的高值区与实际高产区基本相符。该研究将为下一步实际水分供应条件下基于遥感信息的冬小麦区域生长模拟研究奠定了基础。

气候变化情景下东北地区玉米产量变化模拟

WOFOST作物模型在东北地区玉米适应性验证的基础上,结合气候模型BCC-T63输出的未来60年(2011～2070年)气候情景资料,模拟分析了未来气候变化情景下我国东北地区玉米生育期和产量变化情况。模拟结果显示:未来气候变化情景下,玉米生育期将缩短,其中,中熟玉米平均缩短3.4 d,晚熟玉米平均缩短1.1 d;玉米产量将相应下降,中熟玉米平均减产3.5%,晚熟玉米平均减产2.1%。

作物生长模拟模型及其应用

论述了作物生长模型在国内外的研究及其发展过程，作物模型的机理及在农业生产中的作用。

灌溉水量对网纹甜瓜基质苗生长的影响

研究了非胁迫条件下不同灌溉水量对网纹甜瓜基质苗生长及部分生理指标的动态变化,并采用REF-98模型对干物质生产和累积进行了模拟。结果表明,T80%处理(平均基质水分体积分数为0.177 2 m3/m3)的幼苗因具较高的根系活力、叶绿素含量和光合面积等,其生长量明显高于其它处理,在成苗后干物重和壮苗指数最大;REF-98模型可很好地模拟甜瓜幼苗的干物质生长动态和幼苗生长速度,但在光截获等参数上仍需进一步校正。

运用WOFOST模型对浙江水稻潜在生长过程的模拟与验证

通过2001～2003年在金华市和2004年在杭州市的水稻田间试验，应用WOFOST模型对浙江水稻潜在生长进行了模拟和验证。对于常规晚稻秀水11和杂交晚稻协优46，用2001年和2002年的试验数据作参数校正，得到一套参数后，用2003年试验数据作模型验证；对于单季稻两优培九，则以2004年试验数据用于校正，2003年的用于验证。通过对几种水稻品种模拟结果的综合分析，主要结论如下：WOFOST模型可以成功地用于浙江主要水稻品种潜在生长过程的模拟，可以较好地分析浙江水稻的生长过程和产量潜力。由WOFOST模型计算得到浙江中部地区连作晚稻的生产潜力为8100kg／hm^2左右，中稻为9300kg／hm^2左右。目前两种水稻的实际平均产量分别为模拟产量的78％和70％。判断结果表明，有必要对目前水稻中、后期的田间管理措施进行重新审视。

对计算机模拟在作物生长发育研究中应用的评价

为促进计算机模拟在作物生长发育研究中的应用,从作物模拟在农业系统学中的地位、模拟的分类与最新发展趋势、模型与模拟的异同、模拟的步骤、认识论价值及其在实际应用中的一些问题等视角评述了计算机模拟在作物生长发育研究中的应用价值。作物模拟技术增加了作物系统可观察量,提高了人们对自然界"实践-认识-实践"的认知速度,其过程和步骤体现了认识论思想,具有深刻的认识论价值。应进一步加大其研究和应用力度,使之在粮食安全与现代农业中发挥技术支撑作用。

ALMANAC模型对大豆产量的模拟

本文使用ALMANAC作物生长模型对黑龙江省嫩江县鹤山农场的大豆产量进行了模拟,并探讨了影响大豆模拟产量与实际产量差异的原因。研究结果发现,1991年~2003年鹤山农场大豆的平均实际产量和模拟产量分别为2·75t/hm2和3·00t/hm2左右,误差为8·9%左右;大豆的实际产量与模拟产量趋势一致,均呈降低的趋势,说明模型能够用于模拟大豆的生产。造成差异的主要原因可能是某些突发的自然灾害。模拟得到的温度和水分的胁迫日数与该地区的气候变化有较一致的关系,即温度胁迫有减少的趋势,水分胁迫有增加的趋势。模拟结果还发现,提高大豆的出苗密度可以增加大豆的产量,但增加值与生长季的降水量有一定的关系。