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.

Growth and inhibition of zinc anode dendrites in Zn-air batteries:Model and experiment

Zinc(Zn)-air batteries are widely used in secondary battery research owing to their high theoretical energy density,good electrochemical reversibility,stable discharge performance,and low cost of the anode active material Zn.However,the Zn anode also leads to many challenges,including dendrite growth,deformation,and hydrogen precipitation self-corrosion.In this context,Zn dendrite growth has a greater impact on the cycle lives.In this dissertation,a dendrite growth model for a Zn-air battery was established based on electrochemical phase field theory,and the effects of the charging time,anisotropy strength,and electrolyte temperature on the morphology and growth height of Zn dendrites were studied.A series of experiments was designed with different gradient influencing factors in subsequent experiments to verify the theoretical simulations,including elevated electrolyte temperatures,flowing electrolytes,and pulsed charging.The simulation results show that the growth of Zn dendrites is controlled mainly by diffusion and mass transfer processes,whereas the electrolyte temperature,flow rate,and interfacial energy anisotropy intensity are the main factors.The experimental results show that an optimal electrolyte temperature of 343.15 K,an optimal electrolyte flow rate of 40 ml·min^(-1),and an effective pulse charging mode.

Optimizing Parameters of CSM-CERES-Maize Model to Improve Simulation Performance of Maize Growth and Nitrogen Uptake in Northeast China

Crop models can be useful tools ibr optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer （DSSAT）-CERES-Maize were optimized using a new method to provide a better simulation of maize （Zea mays L.） growth and N upfake in response to different nitrogen application rates. Field data were collected from a 5 yr field experiment （2006-2010） on a Black soil （Typic hapludoll） in Gongzhuling, Jilin Province, Northeast China. After cultivar calibration, the CERES-Maize model was able to simulate aboveground biomass and crop yield of in the evaluation data set （n-RMSE=5.0-14.6%）, but the model still over-estimated aboveground N uptake （i.e., with E values from -4.4 to -21.3 kg N ha-~）. By analyzing DSSAT equation, N stress coefficient for changes in concentration with growth stage （CTCNP2） is related to N uptake. Further sensitivity analysis of the CTCNP2 showed that the DSSAT model simulated maize nitrogen uptake more precisely after the CTCNP2 coefficient was adjusted to the field site condition. The results indicated that in addition to calibrating 6 coefficients of maize cultivars, radiation use efficiency （RUE）, growing degree days for emergence （GDDE）, N stress coefficient, CTCNP2, and soil fertility factor （SLPF） also need to be calibrated in order to simulate aboveground biomass, yield and N uptake correctly. Independent validation was conducted using 2008-2010 experiments and the good agreement between the simulated and the measured results indicates that the DSSAT CERES-Maize model could be a useful tool for predicting maize production in Northeast China.

Incorporation of intra-city human mobility into urban growth simulation:A case study in Beijing

The effective modeling of urban growth is crucial for urban planning and analyzing the causes of land-use dynamics.As urbanization has slowed down in most megacities,improved urban growth modeling with minor changes has become a crucial open issue for these cities.Most existing models are based on stationary factors and spatial proximity,which are unlikely to depict spatial connectivity between regions.This research attempts to leverage the power of real-world human mobility and consider intra-city spatial interaction as an imperative driver in the context of urban growth simulation.Specifically,the gravity model,which considers both the scale and distance effects of geographical locations within cities,is employed to characterize the connection between land areas using individual trajectory data from a macro perspective.It then becomes possible to integrate human mobility factors into a neural-network-based cellular automata(ANN-CA)for urban growth modeling in Beijing from 2013 to 2016.The results indicate that the proposed model outperforms traditional models in terms of the overall accuracy with a 0.60%improvement in Cohen’s Kappa coefficient and a 0.41%improvement in the figure of merit.In addition,the improvements are even more significant in districts with strong relationships with the central area of Beijing.For example,we find that the Kappa coefficients in three districts(Chaoyang,Daxing,and Shunyi)are considerably higher by more than 2.00%,suggesting the possible existence of a positive link between intense human interaction and urban growth.This paper provides valuable insights into how fine-grained human mobility data can be integrated into urban growth simulation,helping us to better understand the human-land relationship.

A preliminary study on simplified simulation model of spring wheat growth

In the model developed in this paper, taking the characters and requirements of meteorological services into account, some conventional meteorological observations which are easy to be obtained have been ch.osen, and mathematical equations describing micro-growth processes of crops have been established on the basis of the field experiments, laboratorial analysis and computer's modelling tests with time interval of ten-days for several years (1987-1989), in accordance with the known biological and physical rules and corresponding reference literatures. It is a preliminary simplified simulation model of spring wheat growth in optimal water and nutrient conditions. The field experiments show that simulation results of this simplified model are satisfactory. The potential operational application and theoretical sense are significant in the meteorological forecast of yield and in the assessment of influences of climatic change on agriculture.

Simulation of Dendritic Growth with Melt Convection in Solidification of Ternary Alloys

A cellular automaton-lattice Boltzmann coupled model is extended to study the dendritic growth with melt convection in the solidification of ternary alloys. With a CALPHAD-based phase equilibrium engine, the effects of melt convection, solutal diffusion, interface curvature and preferred growth orientation are incorporated into the coupled model. After model validation, the multi dendritic growth of the Al-4.0 wt%Cu-1.0 wt%Mg alloy is simulated under the conditions of pure diffusion and melt convection. The result shows that the dendritic growth behavior, the final microstructure and microsegregation are significantly influenced by melt convection in the solidification.

Numerical Simulation of the Multicomponent Mass Transfer during Bridgman Growth of CdZnTe Crystal Using Maxwell-Stefan Diffusion Model

To reveal the complicated mechanism of the multicomponent mass transfer during the growth of ternary compound semiconductors, a numerical model based on Maxwell-Stefan equations was developed to simulate the Bridgman growth of CdZnTe crystal. The Maxwell-Stefan diffusion coefficients in the melt were estimated. Distributions of Zn, Cd, and Te were calculated with variable ampoule traveling rate and diffusion coefficients. The experimental results show that Zn in melt near the growth interface decreases and diffuses from the bulk melt to the growth interface. For Cd, the situation is just the opposite. The coupling effects of Zn and Cd diffusions result in an uphill diffusion of Te at the beginning of the growth. Throughout the growth, the concentration of Te in the melt keeps low near the growth interface but high far from the growth interface. Increasing the ampoule traveling rate will aggravate the segregation of Zn and Cd, and hence deteriorate the uniformity of Te. We also find that not only the diffusion coefficients but also the ratios between them have significant influence on the species diffusions.

Monte Carlo simulation of asymmetrical growth of cube-shaped nanoparticles

We simulated the asymmetrical growth of cube-shaped nanoparticles by applying the Monte Carlo method.The influence of the specific mechanisms on the crystal growth of nanoparticles has been phenomenologically described by efficient growth possibilities along different directions（or crystal faces）.The roles of the thermodynamic and kinetic factors have been evaluated in three phenomenological models.The simulation results would benefit the understanding about the cause and manner of the asymmetrical growth of nanoparticles.

Simulation of Desert-Scrub Growth: A Forcing to Warmer and More Pluvial Climate

Desert-fringe vegetation growing over bright, sandy soils reduces the surface albedo from above 0.4 to well below 0.3. Called desert-scrub, these shrubs form a predominantly vertical clumps protruding from the soil-level, thereby significantly increasing the coefficient of turbulent heat transfer from the surface. The impact on global and desert-belt climate of changes in these two surface characteristics was simulated by a multi-layer energy balance tnodel. Evaluated only as a forcing to a further climatic change (that is, without accounting for any possible feedbacks) the results are: if vegetation (such as apparently existed under the warmer climate of 6,000 BP ) grows over large areas in the arid, currently bare-soil regions, the annual Northern Hemisphere surface temperature increases by 0.7t (by 0.6'C in July ), the surface temperature over land in the 20-30°N zone increases by 0.9℃ in both the annual and the July means, and the land-ocean annual temperature contrast in this zone increases by 0.25℃(0.2° in July). These results represent the combined influence of the reduction in the surface albedo and of the increase in the coefficient of turbulent heat transfer. In the desert-belt zones, the increase in the transfer coefficient sharply reduces the land temperature and the land-ocean temperature contrast from the values produced by the albedo change alone. This reduction must be attributed to the increased land-to-ocean circulation (which our model does not evaluate explicitly). Considering that a stronger circulation (resulting from land-ocean temperature contrast) generally forces a higher rainfall, the vegetation which emerged in the arid regions during the post-glacial optimum should be considered a significant positive feedback towards a still warmer, and also a more pluvial, climate. Our study may have implications for the 21st century, if the global warming expected from the enhanced greenhouse effects is accompanied by increased precipitation over the continents.

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

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Optimized interval 2-tuple linguistic aggregation operator based on PGSA and its application in MAGDM

This study proposes a multiple attribute group decisionmaking(MAGDM)approach on the basis of the plant growth simulation algorithm(PGSA)and interval 2-tuple weighted average operators for uncertain linguistic weighted aggregation(ULWA).We provide an example for illustration and verification and compare several aggregation operators to indicate the optimality of the assembly method.In addition,we present two comparisons to demonstrate the practicality and effectiveness of the proposed method.The method can be used not only to aggregate MAGDM problems but also to solve multi-granularity uncertain linguistic information.Its high reliability,easy programming,and high-speed calculation can improve the efficiency of ULWA characteristics.Finally,the proposed method has the exact characteristics for linguistic information processing and can effectively avoid information distortion and loss.

A New Method for Comprehensive Evaluation of Air Quality in Urban Agglomeration

In this study, a new method for a comprehensive evaluation of air quality in urban agglomerations was developed based on a prototype used to solve the spatial Steiner-Weber point. With this method, the air quality information of each city in the city group is aggregated into an optimal gathering point, and then the air quality of the city group is then dynamically evaluated each year. According to the relevant data of the China Statistical Yearbook 2018, we applied this method to aggregate the air quality indices of the major cities in the Beijing-Tianjin-Hebei urban agglomeration from 2014 to 2017. Using the plant growth simulation algorithm (PGSA), the optimal assembly points were calculated to be of a higher accuracy, compared to the traditional mean value aggregation method. Finally, the air quality of the Beijing-Tianjin-Hebei urban agglomeration during each year was evaluated dynamically based on the obtained assembly points. The results show that the air quality of the urban agglomeration is ranked as follows: Y2016Y2015Y2017Y2014.

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.

Evaluation of mixed mode-Ⅰ/Ⅱ criteria for fatigue crack propagation using experiments and modeling

In this study, in-plane mixed mode-Ⅰ/Ⅱ fatigue crack growth simulations and experiments are performed for the Al 7075-T651 aluminum alloy which is widely used in the aerospace industry. Tests are carried out under different mode mixity ratios to evaluate the applicability of a fracture criterion developed in a previous study to mixed mode-Ⅰ/Ⅱ fatigue crack growth tests.Results obtained from the analyses and experiments are compared with existing and developed criteria in terms of crack growth lives. Compact Tension Shear（CTS） specimens, which enable mixed mode loading with loading devices under different loading angles, are used in the simulations and experiments. In an effort to model and simulate the actual conditions in the experiments, crack surfaces of fractured specimens are scanned, crack paths are modeled exactly, and contacts are defined between the contact surfaces of a specimen and the loading device for each crack propagation step in the analyses. Having computed the mixed mode stress intensity factors from the numerical analyses, propagation life cycles are predicted by existing and the developed mixed mode-Ⅰ/Ⅱ criteria and then compared with experimental results.