Plant Growth Simulation Model Research Articles

A bibliometric analysis of the literature on crop yield prediction: insights from previous findings and prospects for future research.

This research presents a bibliometric analysis of articles predicting crop yield using machine learning methods. While several systematic review articles exist, a comprehensive bibliometric analysis illustrating the knowledge structure and research trends, along with collaboration networks among authors, institutions, and countries in this field, has not been conducted. The study focused on 826 articles published over a 32-year period (1992 to 2023) and revealed a significant increase in publications, particularly in recent years. Zhang Zhao from China authored the majority of articles, while the highest number of citations was associated with articles by Zhu Yan and Lobell. Leading countries in article publications are the USA, China, India, Germany, Australia, and Canada, showing strong interconnections in citing each other's research. The Chinese Academy of Sciences and the US Department of Agriculture are the institutions with the highest number of articles and citations in this domain. The journals Agricultural and Forest Meteorology and Remote Sensing are recognized as top ranking journals in this field (Q1). Based on co-occurrence analysis, three main thematic domains were identified: weather and crop yield prediction, plant growth simulation models, and crop yield prediction using remote sensing data. The research suggests a focus on variables such as disease, pests, insects, and soil salinity when predicting yield. Additionally, greater attention should be given to discussions on food security and crop yield, especially in developing countries.

Метод автоматического распознавания сельскохозяйственных культур на основе спутниковых данных и имитационной модели развития растений

Метод автоматического распознавания сельскохозяйственных культур на основе спутниковых данных и имитационной модели развития растений

Simulating diverse native C4 perennial grasses with varying rainfall

Rainfall is recognized as a major factor affecting the rate of plant growth development. The impact of changes in amount and variability of rainfall on growth and production of different forage grasses needs to be quantified to determine how climate change can impact rangelands. Comparative studies to evaluate the growth of several perennial forage species at different rainfall rates will provide useful information by identifying forage management strategies under various rainfall scenarios. In this study, the combination of rainfall changes and soil types on the plant growth of 10 perennial forage species was investigated with both the experimental methods, using rainout shelters, and with the numerical methods using the plant growth simulation model, ALMANAC. Overall, most species significantly increased basal diameter and height as rainfall increased. Like measured volume, simulated yields for all species generally increased as rainfall increased. But, large volume and yield increases were only observed between 350 and 850 mm/yr. Simulating all species growing together competing agrees relatively well with observed plant volumes at low rainfall treatment, while simulating all species growing separately was slightly biased towards overestimation on low rainfall effect. Both simulations agree relatively well with observed plant volume at high rainfall treatment.

Statistical emulators of a plant growth simulation model

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 55:253-265 (2013) - DOI: https://doi.org/10.3354/cr01138 Statistical emulators of a plant growth simulation model Padmaja Ramankutty1,2,3,*, Megan Ryan1,2, Roger Lawes4, Jane Speijers3, Michael Renton1,2,4 1School of Plant Biology and Institute of Agriculture, and 2Future Farm Industries CRC, The University of Western Australia, 35 Stirling Hwy, Crawley, Western Australia 6009, Australia 3Department of Agriculture and Food, 3 Baron-Hay Court, South Perth, Western Australia 6151, Australia 4CSIRO Ecosystem Sciences, Private Bag 5, Wembley, Western Australia 6913, Australia *Email: ramanp01@student.uwa.edu.au ABSTRACT: A new methodology was developed to create statistical emulators from an existing complex plant growth simulation model, in order to provide simple models for predicting perennial pasture production based on meteorological data. The goal was to find emulators that could fit simulation data and provide reliable predictions of new simulation output. Four types of statistical emulators were compared—linear models, non-linear models, linear splines and cubic splines—which varied in complexity due to the use of different functional forms to fit main effects and different methods to determine model parameters. Two methods of model validation were used to ensure that the emulator selected provided good fits to the initial simulation output and gave adequate predictions of future simulation output. We illustrated the various techniques of model development and validation using the Agricultural Production Systems sIMulator (APSIM) plant growth model. The effects of rainfall amount, rainfall frequency, temperature and radiation on APSIM-generated biomass production of the perennial pasture species lucerne Medicago sativa were used as a case study. We conclude that, in this case, the best statistical emulator is the cubic spline. The novel approach illustrated here provides a rigorous, flexible and powerful means of developing and testing emulators for any complex simulation model. KEY WORDS: Statistical emulator · Linear mixed effects model · Model validation · Cubic splines · APSIM · Medicago sativa · Biomass production Full text in pdf format Supplementary material PreviousCite this article as: Ramankutty P, Ryan M, Lawes R, Speijers J, Renton M (2013) Statistical emulators of a plant growth simulation model. Clim Res 55:253-265. https://doi.org/10.3354/cr01138 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 55, No. 3. Online publication date: February 06, 2013 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2013 Inter-Research.

Study on simulation models of tomato fruit quality related to cultivation environmental factors

Plant growth simulation models are valuable tools for optimizing the environmental factors and managing crop cultivation in cultural facilities. Researches presently on tomato simulation models have mainly focused on the plant growth and development, growth stages, dry matter production and distribution, however, no report on modeling of tomato fruit quality has been published yet. In this study, the method of accumulated Thermal Effectiveness and PAR (TEP) was employed to model the dynamic relationship between the major quality indicators and the environmental factors. Data of both indicators of tomato fruit quality and environmental factors, temperature and solar radiation of the cultivation environment, were collected under multiple protected structures like solar greenhouse and plastic tunnel for tomato production. The variety of simulation models were established based on the effects of temperature and solar radiation on tomato quality formation, and independently tested with the modeling data. The results show that the dynamic changes of the indicators of fruit quality after fruit set are accorded with the amount of accumulated TEP and individual indicators of fruit quality are suitable to its specific models. The fruit hardness is well accorded with a formula of generalized least squares FHi=k1+k2×TEPi+k3×TEPi2; Fruit soluble sugar content is in a formula of Logistic model SSCi=b11+eb2+b3×TEPi. Fruit organic acid content is in a formula of generalized least squares OACi=n1+n2×TEPi+n3×TEPi2. Fruit tannin content is in a formula of Johnson Schumacher model TCi=q1×e-q2TEPi+q3. According to the established fruit hardness model, the determination coefficient R2 values based on the 1:1 beeline between the simulated values and the measured values of the first, second, third and the fourth truss of fruit are 0.9396, 0.9181, 0.8910 and 0.9523, respectively and values of root mean square error (RMSE) are 0.833kg/cm2, 0.942kg/cm2, 0.628kg/cm2 and 0.738kg/cm2, respectively. Based on the established fruit soluble sugar content model, the determination coefficient R2 values based on the 1:1 beeline between the simulated values and the measured values of the first, second, third and the fourth truss of fruit are 0.8596, 0.9420, 0.9027 and 0.9473, respectively and the values of RMSE are 1.011%, 0.710%, 0.771% and 0.608%, respectively. On the basis of the established fruit organic acid content model, the determination coefficient R2 values based on the 1:1 beeline between the simulated values and the measured values of the first, second, third and the fourth truss of fruit are 0.8856, 0.9025, 0.9183 and 0.8768, respectively and the values of RMSE are 0.029%, 0.030%, 0.024% and 0.023%, respectively. According to the established fruit tannin content model, the determination coefficient R2 values based on the 1:1 beeline between the simulated values and the measured values of the first, second, third and the fourth truss of fruit are 0.9481, 0.9219, 0.9521 and 0.8911, respectively and the values of RMSE are 13.41mg/kg, 14.04mg/kg, 13.92mg/kg and 16.78mg/kg, respectively. All of the coefficients of determination R2 are higher than 0.85, and the values of RMSE are generally smaller, which means the modeling is accurate and well accordance. This study will form a theoretic basis and provide technical support for the management of tomato production and environment control under plastic tunnel and solar greenhouse cultivation.

植物成長シミュレーションによる緑地設計・環境評価ツールの開発

In this research, a Simple Landscape Gardening Design-Environmental Evaluation tool was developed using Vector Works and general 3D-CAD of a plant growth simulation model AMAP. When you design forested land in a city, such as the Namiki Park, tools like this can be used to compile the environmental map of the forested land. Thermal environmental measurement was done inside the government-managed Showa Kinen Park, from the result, we led the expression to calculate MRT and CSE of the environmental Index by using greenery. In addition, it drew up the surface temperature file every of material from the infrared ray thermal imagery, converted to a database and it constructed the kind of system which can do environmental appraisal simultaneously with the design. The forested land was actually designed with the developed tool and an environmental map was drawn up. With sands in the land, we obtained CSE with negative number, the urban area compared to air temperature was 2 degree C or more higher and the forest area with have been converted CSE being correct, the urban area compared to 4 degree C or lower were obtained.

3D ORCHARD CANOPY ARCHITECTURAL MODELLING FOR USE IN AIRFLOW AND DRIFT PREDICTIONS

The current trend in studying the interaction of vegetation canopies with their environment and numerical prediction of drift is mainly based on porous media approaches. The methods involve several approximations and estimations that give the global effect of the canopies to airflow and drift without investigating the detailed local effects of the vegetation elements. These approaches also require precise estimation of certain parameters such as drag coefficient and leaf area density. To make some advances in the field and to address some of the above problems a new approach needed to be developed, where real canopy architecture was modelled and linked to a computational Fluid Dynamics (CFD) software to model airflow through the canopies. This helped to investigate the real effects of the vegetation elements on atmospheric airflow which directly affects drift and drift prediction. In this work, 3D orchard canopy architecture was modelled using a combined discrete-continuous plant growth simulation model, which considered the phenomenological plant growing behaviour and the effect of temperature. Two canopy geometries were introduced into a fluid domain and the domain was meshed. Airflow around and through the canopy was simulated using the Reynolds-averaged Navier-Stokes (RANS) equations and k-H turbulence model. The airflow simulation results agreed both qualitatively with wind tunnel validation experiment and quantitatively with previous works done in the area, ensuring the prospect of the architectural modelling for further application. It was also possible to show the detailed effects of canopy elements on airflow.

Analysis of Competition Effects in Mono‐ and Mixed Cultures of Juvenile Beech and Spruce by Means of the Plant Growth Simulation Model PLATHO

Inter- and intra-specific competition between plants for external resources is a critical process for plant growth in natural and managed ecosystems. We present a new approach to simulate competition for the resources light, water, and nitrogen between individual plants within a canopy. This approach was incorporated in a process-oriented plant growth simulation model. The concept of modelling competition is based on competition coefficients calculated from the overlap of occupied crown and soil volumes of each plant individual with the occupied volumes of its four nearest neighbours. The model was parameterised with data from a two-year phytotron experiment with juvenile beech and spruce trees growing in mono- and mixed cultures. For testing the model, an independent data set from this experiment and data from a second phytotron experiment with mixed cultures were used. The model was applied to analyse the consequences of start conditions and plant density on plant-plant competition. In both experiments, spruce dominated beech in mixed cultures. Based on model simulations, we postulate a large influence of start conditions and stand density on the outcome of the competition between the species. When both species have similar heights at the time of canopy closure, the model suggests a greater morphological plasticity of beech compared with spruce to be the crucial mechanism for competitiveness in mixed canopies. Similar to the experiment, in the model greater plasticity was a disadvantage for beech leading to it being outcompeted by the more persistent spruce.

Verification and Validation of Ceres-Wheat Model Under Çukurova Conditions

Plant Growth models have been presently used extensively by engineers and planners in order to evaluate various management alternatives. Plant growth models are tools for predicting crop growth parameters by using mathematical equation of complex environmental dynamics. In this study, CERES-Wheat V2. 1 plant growth simulation model was verified and validated on PANDA wheat variety under Çukurova conditions. Different amounts of irrigation water were applied to wheat. For this purpose a line-soruce sprinkler irrigation system was utulized in the experiment. Wheat rows adjacent to the lateral were denoted as nonwater stress treatment (I1), rows outside the wetted area were denoted as non-irrigated treatment (I5); the plant rows in between the I1 and I5 treatments were taken as the deficit irrigation treaments with linearly decreasing amount. Meteorological data required by the model were obtained from the automatic recording type weather station in the experimental area of the Department of Agricultural Structures and Irrigation of the Çukurova University and from the Meteorological station of Adana province. Throughout the experiment, soil water, phenological growth stages, and leaf area index (LAI), kernel weight, etc. were determined. The simulated results were compared with the observed parameters. Model under predicted the grain yields in fully irrigated treatment and non-irrigated treatment. On the other hand, the predicted yields in other treaments were higher than the actual grain yields. Predicted and observed accumulated dry matter were very similar. Simulated and observed LAI values had similar trend however the time for reaching the maximum LAI was about one month before the observed maximum LAI. The reason for the time delay could be attributed to the genetic coefficients used in the model for PANDA might not represent this variety. Sensitivity analysis were done in this study and a 10% increase in the field capacity and permanent wilting point water contents resulted in no change in the grain yields from the I1, I2, I3 treatments, however caused a 23% grain yield increase in yield of I5 treament. The same changes resulted in 7% increase in the plant biomass.

Growth and nitrogen relations in reciprocal grafts of wild-type and nitrate reductase-deficient mutants of pea (Pisum sativumL. var. Juneau)

Plants growing on NO 3 - differ in the proportion of NO 3 - reduced in their roots and leaves. Using a version of a two-compartment, two-resource plant growth simulation model, the possible effects of changing the N assimilation site on plant growth were explored. Subsequently, using an experimental system designed to vary the site of NO 3 - reduction; chimeras (reciprocal grafts) of Pisum sativum var. Juneau and its mutant, A317, deficient in nitrate reductase. Plant growth and N metabolism at varying NO 3 - levels were examined in a hydroponic system. In what is thought to be the first direct plant manipulation of this kind, total dry weight, root:shoot ratio, total N and NO 3 - concentrations, in vitro nitrate reductase activity, NO 3 - in xylem exudates, and leaf chlorophyll content were compared. It was found that changing the location of nitrate reduction did not change growth significantly and caused only subtle changes in N concentration. These indifferences occurred in spite of marked changes in growth associated with NO 3 - availability and useability. To achieve this kind of plasticity the plants must have dramatically altered the flow and storage of NO 3 - , and reduced N. The results are compared with existing views of biomass partitioning and regulation of N assimilation.

Estimating the temperature of a maize apex during early growth stages

When the leaf area index is low at the early stages of growth, the temperature of a maize apex can be much higher than the air temperature measured at screen level. In order to account for temperature effects in plant growth simulation models, it would be better to use plant temperature rather than air temperature. We propose a model to estimate the apex temperature for both day-time and night-time averages from a small number of readily available meteorological data: solar radiation, wind speed, air temperature and humidity. It is based on an energy balance of a maize apex under field conditions. It performs a radiation balance that separates diffuse and direct components, and assumes a similarity between the apex and soil surface temperature evolutions. In the absence of any references, the apex stomatal resistance was parameterized as a simple linear function of water vapour deficit, deduced from experimental data. The calculated temperatures were compared with those measured for two sets of experimental data collected in 1989 and 1990. The agreement was quite satisfactory, the average absolute error being in all cases less than 1.0°C. Furthermore, the empirical relationship between stomatal resistance and water vapour deficit was shown to be valid for both sets of data. We should now confirm this relation under different soil or climatic conditions, as well as the similarity between the apex and soil surface temperatures.

Predicting soil water retention characteristics from soil physical and chemical properties

Abstract Knowledge of soil water availability for plant growth is vital for the development of plant growth simulation models. Data on soil water availability are often not available because field and laboratory measurements of soil water content are time‐consuming and tedious. The objective of this study was to develop alternative procedures to predict water content at ‐10 kPa (UL10), ‐33 kPa (U133), ‐1500 kPa (LL), and the potential available water capacity (AWC) from easily and routinely available soil properties. Multiple regression equations for soil orders of Soil Taxonomy were developed using a database containing information of about 12,000 pedons of the continental U.S., Hawaii, Puerto Rico, and some foreign countries. Regression equations with bulk density, sand, silt, clay, and organic carbon contents accounted for up to 83% of the variation in UL10 for all orders except Ultisols. For Ultisols, sand content accounted for up to 90% of the variation in UL10. Equations with clay and organic carbon contents accounted for up to 75% of the variability in UL33 for all except Aridisols, Oxisols, Vertisols, and Spodosols. For these four orders, equations with bulk density, clay, silt, and sand contents accounted for up to 81% of the variation in UL33. LL was linearly related to clay content. Clay content accounted for up to 91% of the variation in LL for all but Oxisols and Vertisols. More accurate predictions of AWC resulted when AWC was computed from UL10 and LL water content data. Equations with bulk density alone or bulk density plus silt and/or sand contents accounted for up to 83% of the variation in AWC for all except Entisols, Inceptisols, and Spodosols.

A regional agricultural model using a plant growth simulation program as activities generator— an application to a region in Argentina

This paper presents a regional agricultural model using a plant growth simulation model (EPIC) as generator of activities. Its objective is to develop a simple tool which determines the possible effects of economic changes on regional supply and revenue as well as at the level of farm structure and farm relationships. Erosion trends can also be observed. The use of a physiological model allows us to utilize real activities of the region as well as some potential ones (such as irrigation or different fertilizer doses). Thus, if economic changes are produced, these activities may become more profitable and, so, will appear in the solution. The predictive capability of the model then, becomes more accurate. In this work the authors develop a model prototype of this kind for a region in Argentina, which considers three types of farms, including land market (sale and rent) and the market for rented machinery. The results obtained on cropping pattern are close to the actual ones with the present economic environment. When price and interest rate simulations are done, differences inter and intra farms are observed as well as in the total regional output. The sensitivity analysis shows that changes in wheat and soybean prices would induce the most important changes at the regional level, which is not the case for corn or cattle prices. On the other hand, erosion trends will generally be aggravated (except when wheat price increases), if no specific measures are taken to counterbalance the tendency.

Orthogonal Central Composite Designs of the Third Order in the Evaluation of Sensitivity and Plant Growth Simulation Models

Abstract The U.S. Department of Agriculture has used response-surface techniques as applied by Baker and Bargmann (1981) to plant process simulation models as an aid in the identification of interrelationships among yield and various single-valued and functional parameters. Orthogonal cubic surfaces have provided insight into higher order relationships as well as a measure of the relative sensitivity of yield to experimentally determined parameter values. Several examples investigate the effectiveness of those higher order surfaces and illustrate how less precise (and less costly) measurements may be possible in building and using these simulation models.

Orthogonal Central Composite Designs of the Third Order in the Evaluation of Sensitivity and Plant Growth Simulation Models

Abstract The U.S. Department of Agriculture has used response-surface techniques as applied by Baker and Bargmann (1981) to plant process simulation models as an aid in the identification of interrelationships among yield and various single-valued and functional parameters. Orthogonal cubic surfaces have provided insight into higher order relationships as well as a measure of the relative sensitivity of yield to experimentally determined parameter values. Several examples investigate the effectiveness of those higher order surfaces and illustrate how less precise (and less costly) measurements may be possible in building and using these simulation models.

Morphological Development and Water Use in Clonal Lines of Four Forage Grasses1

A need exists for information on the morphogenesis and water use by forage species to use as a basis to improve management and grazing practices, varietal improvement, and for development of plant growth simulation models. Our objectives were to evaluate morphological development and water use in clonal lines of crested wheatgrass [Agropyron desertorum (Fisch. ex Link) Schult.], western wheatgrass [Pascopyrum smithii (Rhdb.) Löve Syn: A. smithii Rydb.], intermediate wheatgrass [Elytrigia intermedia (Host) Nevsk: Syn: A. intermedium (Host) Beauv.], and reed canarygrass (Pharlaris arundinacea L.). We also defined the relationship between morphological development, water use, and air temperature expressed as growing‐degree days (GDD) with a base temperature of O°C. The study was conducted during 1981 and 1982 in the field on a Parshall sandy loam soil (coarse‐loamy, mixed Pachic Haploboroll) with two clones of each of two cultivars per species. Number of leaves developed in the spring and GDD per phyllochron varied among species and among clones within a species. Reproductive (spike forming) tillers of clonal lines of crested wheatgrass and western wheatgrass developed six leaves with 557 and 778 GDD, respectively; intermediate wheatgrass, seven leaves with 780 GDD; reed canarygrass, eight leaves with 706 GDD. Number of GDD required to develop a single leaf was 84 for reed canarygrass, 104 for crested wheatgrass, 125 for intermediate wheatgrass, and 147 for western wheatgrass. Western wheatgrass extracted soil water from a deeper soil depth and to a lower content than the other species. Dry matter yields were highest in intermediate wheat‐grass and lowest in western wheatgrass. Water‐use‐efficiency (WUE) was highest in crested wheatgrass and lowest in western wheatgrass. There were no difference in total water used among clones within any species. Among the three wheatgrasses, earlier morphological development corresponded to higher WUE. Differences were observed for yield and WUE among crested and western wheatgrass clones.

Using a crop growth simulation model for evaluating irrigation practices

Water management decisions are dependent on crop variety, soil and climatic conditions. A properly structured plant growth simulation model which takes these factors into account can be successfully used to quantify the effects of irrigation practices on crop yields. The use of such a simulation model will be considerably less expensive and time consuming than conducting field experiments. This paper reports the results of using such a model for making important water management decisions, such as determining: (a) optimum soil moisture depletion and replenishment levels; and (b) timing and amount of irrigation during different crop growth stages.