Determination of Upland Rice Cultivar Coefficient Specific Parameters for DSSAT (Version 4.7)-CERES-Rice Crop Simulation Model and Evaluation of the Crop Model under Different Temperature Treatments conditions

To develop basis for strategic or arranged decision making towards crop yield improvement in Thailand, a new method in which crop models could be used is essential. Therefore, the objective of this study was to measure cultivar specific parameters by using DSSAT (v4.7) Cropping Simulation Model (CSM) with five upland rice genotypes namely Dawk Pa-yawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm. Experiment was laid out in a Completely Randomized Design (CRD) with split plot design. Results showed that five upland rice genotypes had significantly affected each other by different temperature treatments (28°C, 30°C, 32°C) with grain yield, tops weight, harvest index, flowering, and maturity date. At the same time, all the phenological traits had highly significant variation with the genotypes. The cultivar specific parameters obtained by using a temperature tolerant cultivar (Basmati 385) with five upland genotypes involved in the DSSAT4.7-CSM. Model evaluation results indicated that utilizing the estimated cultivar coefficient parameters, model simulated well with varying temperature treatments as indicated by the agreement index (d-statistic) closer to unity. Hence, it was estimated that model calibration and evaluation was realistic in the limits of test cropping seasons and that CSM fitted with cultivar specific parameters can be used in simulation studies for investigation, farm managing or decision making. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.

A simulation of winter wheat crop responses to irrigation management using CERES-Wheat model in the North China Plain

To improve efficiency in the use of water resources in water-limited environments such as the North China Plain（NCP）, where winter wheat is a major and groundwater-consuming crop, the application of water-saving irrigation strategies must be considered as a method for the sustainable development of water resources. The initial objective of this study was to evaluate and validate the ability of the CERES-Wheat model simulation to predict the winter wheat grain yield, biomass yield and water use efficiency（WUE） responses to different irrigation management methods in the NCP. The results from evaluation and validation analyses were compared to observed data from 8 field experiments, and the results indicated that the model can accurately predict these parameters. The modified CERES-Wheat model was then used to simulate the development and growth of winter wheat under different irrigation treatments ranging from rainfed to four irrigation applications（full irrigation） using historical weather data from crop seasons over 33 years（1981–2014）. The data were classified into three types according to seasonal precipitation： 〈100 mm, 100–140 mm, and 〉140 mm. Our results showed that the grain and biomass yield, harvest index（HI） and WUE responses to irrigation management were influenced by precipitation among years, whereby yield increased with higher precipitation. Scenario simulation analysis also showed that two irrigation applications of 75 mm each at the jointing stage and anthesis stage（T3） resulted in the highest grain yield and WUE among the irrigation treatments. Meanwhile, productivity in this treatment remained stable through different precipitation levels among years. One irrigation at the jointing stage（T1） improved grain yield compared to the rainfed treatment and resulted in yield values near those of T3, especially when precipitation was higher. These results indicate that T3 is the most suitable irrigation strategy under variable precipitation regimes for stable yield of winter wheat with maximum water savings in the NCP. The application of one irrigation at the jointing stage may also serve as an alternative irrigation strategy for further reducing irrigation for sustainable water resources management in this area.

A simulation study on CO_2 assimilation and crop growth in agroforest ecosystems in the East China Plain

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Quantifying Responses of Winter Wheat Physiological Processes to Soil Water Stress for Use in Growth Simulation Modeling

A deep understanding of crop-water eco-physiological relations is the basis for quantifying plant physiological responses to soil water stress. Pot experiments were conducted to investigate the winter wheat crop-water relations under both drought and waterlogging conditions in two sequential growing seasons from 2000 to 2002, and then the data were used to develop and validate models simulating the responses of winter wheat growth to drought and waterlogging stress. The experiment consisted of four treatments, waterlogging (keep 1 to 2 cm water layer depth above soil surface), control (70%-80% field capacity), light drought (40%-50% field capacity) and severe drought (30%-40% field capacity) with six replicates at five stages in the 2000-2001 growth season. Three soil water content treatments (waterlogging, control and drought) with two replicates were designed in the 2001-2002 growth season. Waterlogging and control treatments are the same as in the 2000-2001 growth season. For the drought treatment, no water was supplied and the soil moisture decreased from field capacity to wilting point. Leaf net photosynthetic rate, transpiration rate, predawn leaf water potential, soil water potential, soil water content and dry matter weight of individual organs were measured. Based on crop-water eco-physiological relations, drought and waterlogging stress factors for winter wheat growth simulation model were put forward. Drought stress factors integrated soil water availability, the sensitivity of different development stages and the difference between physiological processes (such as photosynthesis, transpiration and partitioning). The quantification of waterlogging stress factor considered different crop species, soil water status, waterlogging days and sensitivity at different growth stages. Data sets from the pot experiments revealed favorable performance reliability for the simulation sub-models with the drought and waterlogging stress factors.

Using CropSyst to Simulate Spring Wheat Growth in Black Soil Zone of Northeast China

Available water and fertilizer have been the main limiting factors for yields of spring wheat, which occupies a large area of the black soil zone in northeast China; thus, the need to set up appropriate models for scenario analysis of cropping system models has been increasing. The capability of CropSyst, a cropping system simulation model, to simulate spring wheat growth of a widely grown spring cultivar, 'Longmai 19', in the black soil zone in northeast China under different water and nitrogen regimes was evaluated. Field data collected from a rotation experiment of three growing seasons (1992-1994) were used to calibrate and validate the model. The model was run for 3 years by providing initial conditions at the beginning of the rotation without reinitializing the model in later years in the rotation sequence. Crop input parameters were set based on measured data or taken from CropSyst manual. A few cultivar-specific parameters were adjusted within a reasonable range of fluctuation. The results demonstrated the robustness of CropSyst for simulating evapotranspiration, aboveground biomass, and grain yield of 'Longmai 19' spring wheat with the root mean square errors being 7%, 13% and 13% of the observed means for evapotranspiration (ET), grain yield and aboveground biomass, respectively. Although CropSyst was able to simulate spring production reasonably well, further evaluation and improvement of the model with a more detailed field database was desirable for agricultural systems in northeast China.

Linking a farmer crop selection model(FCS) with an agronomic model(EPIC) to simulate cropping pattern in Northeast China

In this paper, authors established a farmer crop selection model（FCS） for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate model（EPIC）, the simulated results of FCS model for maize, rice and soybean were spatialized with 1 km×1 km grids to obtain cropping pattern. The reference map of spatial distribution for the three staple crops acquired by remote sensing imageries was applied to validate the simulated cropping pattern. The results showed that（1） the total simulation accuracy for the study area was 78.62%, which proved simulation method was applicable and feasible;（2） simulation accuracy for Jilin Province was the highest among the three provinces with a rate of 82.45% since its simple cropping system and not complex topography;（3） simulation accuracy for maize was the best among the three staple crops with a ratio of 81.14% because the study area is very suitable for maize growth. We hope this study could provide the reference for cropping pattern forecasting and decision-making.

Estimation of irrigation requirements for drip-irrigated maize in a sub-humid climate

Drip-irrigation is increasingly applied in maize （Zea mays L.） production in sub-humid region. It is cdtical to quantify irrigation requirements during different growth stages under diverse climatic conditions. In this study, the Hybrid-Maize model was calibrated and applied in a sub-humid Heilongjiang Province in Northeast China to estimate irrigation requirements for drip- irrigated maize during different crop physiological development stages and under diverse agro-climatic conditions. Using dimensionless scales, the whole growing season of maize was divided into diverse development stages from planting to maturity. Drip-irrigation dates and irrigation amounts in each irrigation event were simulated and summarized in 30-year simulation from 1981 to 2010. The maize harvest area of Heilongjiang Province was divided into 10 agro-climatic zones based on growing degree days, arid index, and temperature seasonality. The simulated results indicated that seasonal irrigation requirements and water stress during different growth stages were highly related to initial soil water content and distribution of seasonal precipitation. In the experimental site, the average irrigation amounts and times ranged from 48 to 150 mm with initial soil water content decreasing from 100 to 20% of the maximum soil available water. Additionally, the earliest drip-irrigation event might occur during 3- to 8-leaf stage. The water stress could occur at any growth stages of maize, even in wet years with abundant total seasonal rainfall but poor distribution. And over 50% of grain yield loss could be caused by extended water stress during the kernel setting window and grain filling period. It is estimated that more than 94% of the maize harvested area in Heilongjiang Province needs to be irrigated although the yield increase varied （0 to 109%） in diverse agro-climatic zones. Consequently, at least 14% of more maize production could be achieved through drip-irrigation systems in Heilongjiang Province compared to rainfed conditions.

Air flow characteristics of an air-assisted sprayer through horizontal crop canopy

Artificially induced air currents or air-assistance to droplet spectrum produced by hydraulic nozzles not only facilitate in transporting and depositing the droplets in different parts of canopy but also reduce the application rate of chemicals.The air streams increase the velocity of smaller droplets so that extra momentum would increase impaction and improve penetration into the crop as well as mitigating the influence of wind on drift.It is necessary to quantify the airflow characteristics.But,control of climatic and other conditions in the field is very difficult.Thus,airflow characteristics study was done under controlled conditions on a horizontal simulated crop canopy.Based on this study,an airflow distribution model was developed and airflow characteristics for vegetable crops,namely,eggplant,chilli and bittergourd were predicted.The differences between predicted and actual field study values were not statistically significant.Kinetic energy of air stream dissipated with its movement from top to bottom of the canopy.The rate of kinetic energy dissipation was higher in denser canopies.Higher air velocity 15 m/s was the best as it produced maximum turbulence throughout the canopy.

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.

Assessment of the influence of global dimming on the photosynthetic production of rice based on three-dimensional modeling

Observations indicate that global radiation reaching the Earth's surface has gradually decreased over the past several decades(i.e.,the "global dimming" phenomenon),while the fraction of diffuse radiation in global radiation has increased.It has been found that the increase in diffuse fraction significantly increases photosynthetic production in the canopy,but the mechanism has not been clarified.A three-dimensional light distribution model considering the geometry of incident radiation was employed in this study.This model was used to simulate the light distribution and potential photosynthetic production of rice canopy.The results indicate that the potential photosynthetic production of rice significantly increases in response to an increase in the diffuse fraction as long as global radiation does not decline greatly.The "fertilization effect" of diffuse radiation results from the reduction of leaf area with photosynthetic photon flux density(PPFD) below the light compensation point in response to an increasing diffuse fraction,and an increase in the leaf area with PPFD on the linear part of the light response curve.The increase in the diffuse fraction results in a significant increase in the photosynthetic rate of the upper canopy.High-performance computation is an easy-to-use and economic approach to overcome the computational constraints of the model.

Agricultural Risk Modeling Challenges in China:Probabilistic Modeling of Rice Losses in Hunan Province

This article summarizes a joint research projec undertaken under the Risk Management Solutions, Inc(RMS) banner to investigate some of the possible approaches for agricultural risk modeling in China. Two modeling approaches were investigated—the simulated weather crop index and the burn yield analysis approach. The study was limited to Hunan Province and a single crop—rice. Both modeling approaches were dealt with probabilistically and were able to produce probabilistic risk metrics. Illustrative model outputs are also presented. The article discusses the robustness of the modeling approaches and their dependence on the availability, access to, and quality of weather and yield data. We offer our perspective on the requirements for models and platforms for agricultural risk quantification in China in order to respond to the needs of all stakeholders in agricultural risk transfer.