OWSimu: an object-oriented and Web-based
simulator for plant growth
X. Pan
a, J.D. Hesketh
b, M.G. Huck
c,*
aBiotechnology Center, University of Illinois, 330 ERML, 1201 W. Gregory Drive, Urbana, IL 61801, USA bPhotosynthesis Research Unit, USDA-ARS, 190 ERML, 1201 W. Gregory Drive, Urbana, IL 61801, USA cDepartment of Natural Resources and Environmental Sciences, University of Illinois, 1102 S. Goodwin Avenue,
Urbana, IL 61801, USA
Received 15 December 1998; received in revised form 22 November 1999; accepted 23 November 1999
Abstract
OWSimu is a Java-based generic plant growth simulator. According to the principles of object-oriented design, Java classes were programmed for plant growth simulation as well as relevant input, output and user interfaces. The program was developed as a Java applet with a user-friendly graphical interface running on the Web. With a Java (JDK1.1)-embedded Web browser, users can link the run-time model and perform plant growth simulations at our website. OWSimu is a convenient tool for researchers, teachers and students to use in the general study of plant growth. It describes the growth of a typical plant that is free of pests and diseases. The program is currently able to simulate plant growth for more than a dozen crops and weeds under Illinois weather and three typical soil conditions. Additional data is needed to modify OWSimu so that it can have a better carbon balance model for dierent plant species and accommodate dierent varieties within a selected plant species for use in a speci®c crop production management system. The program source code is highly reusable for further development and for other crop modeling work.#2000 Published by Elsevier Science Ltd. All rights reserved.
Keywords:Java class; WWW; Interface; Crop simulation
1. Introduction
Plant growth refers to an increase in size, mass or complexity of cells or organs. Plant phenology (the timing of growth processes) and carbon balance (including
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* Corresponding author.
photosynthesis and respiration) are closely related to plant growth. Materials (C, N, H2O) stresses are important factors controlling plant growth. Leaf area expansion,
internode length extension, leaf area index (LAI) change and plant height growth can be predicted based upon the eects of accumulated degree days, materials stresses, etc., on leaf and internode phenological events (Pan, 1997). Leaf, stem and root weight increases can be calculated and simulated from materials balance, micro-environmental and phenological considerations (Jones et al., 1974; Baker et al., 1983; Reddy et al., 1997).
As shown in Fig. 1, plant growth is controlled by genetic and environmental fac-tors (e.g. weather, soil, water, nitrogen, agronomic practices, etc.). Genetic facfac-tors in¯uence variation in form and function of plant organs that lead to dierences among species, races or cultivars, the details of which can be inferred from experi-mental measurements. Weather components, including daily temperature measure-ments (maximum and minimum), solar radiation, rainfall, wind speed and humidity strongly aect plant growth. Soil, having unique physical and chemical properties, in¯uences both root and shoot growth. Water and nitrogen availability are also important factors in determining plant growth. Agronomic practices, including planting date, stand density, site location, irrigation and fertilizer application often have signi®cant eects.
Plant growth and micro-environmental variables such as water balance and nitrogen balance may also interact with one another. For example, leaf expansion and the distribution of leaves within a crop canopy aect the plant photosynthetic rate. On the other hand, nitrogen supply and photosynthetic rates have feedback eects upon events controlling phenological development such as leaf and internode growth rates, changes in LAI, or plant height growth. Plant water stress aects leaf expansion, while leaf growth, in turn, in¯uences both plant water stress and the amount of water transpired.
Plant growth can be described by a series of mathematical and logical models, which can be combined into a complex computer simulation model programmed
with one or more computer languages (Thornley and Johnson, 1990; Johnson, 1994). Such a computer simulation model can be used for plant growth prediction purposes and as a means of helping to understand how the plant growth system works. As a result, many computer-based models have been developed to simulate plant growth.
However, most published plant simulation models (e.g. McKinion et al., 1975; Jones et al., 1980; Baker et al., 1983; Mutsaers, 1984; Ritchie et al., 1985; Hoogen-boom and Huck, 1987; Acock and Trent, 1991; Marani and Phene, 1993), are pro-grammed in FORTRAN (a procedural computer language), rather than in object-oriented code. Although some models (Fu and Hesketh, 1996; Lemmon and Chuck, 1998; Caldwell and Fernandez, 1998), coded in C++, are object-oriented, they are computer platform-dependent and cannot be used on the Web.
Object-oriented programming (OOP) has now reached the mainstream of pro-gramming. Its code is encapsulated in objects, which have both a public interface and a private implementation, so programmers can rapidly develop prototypes and group code into manageable chunks Ð even for very complex systems. In OOP, objects can inherit the characteristics of other objects and override inherited char-acteristics, so programmers can easily reuse code, make their codes more compact, and ®x or update codes in one place, which saves time and reduces bugs.
The World Wide Web (WWW or Web) is transforming our society. It provides people with a very handy way to access information through the Internet.
The Java language (Cornell and Horstmann, 1996; Sridharan, 1997), developed by Sun Microsystems, is thoroughly object-oriented. It mimics the object orientation of C++ and includes extensions from Objective C for dynamic method resolution. Creating network connections is easier in Java than in C or C++ because Java has built-in routines for dealing with Internet Protocols. These routines make it as easy to open and access objects over the Internet through URLs as it is to access a local ®le system. Java applets make it possible for a website to include a strong ability to interact with data on the Web in real time.
PHENAPP, developed by Pan et al. (1997), is a Java program. It simulates the eects of accumulated degree-days upon plant leaf and internode phenological events of var-ious plant species (including ®eld crops, horticultural crops and weeds) that are free of pests and diseases. Following the basic outline established for PHENAPP, we devel-oped carbon balance, water balance and nitrogen balance models and combined them into the more complex model described here: OWSimu, which is an object-oriented generic plant growth simulator intended for research and educational purposes.
2. Object-oriented design for plant growth
2.1. Java classes with inheritance relationships
(Evapotranspiration), NBalance, SoilN and PlantN were designed and programmed as a set of Java classes to describe plant growth. The relationships among these classes are illustrated in Fig. 2.
Class Agroecosystem is the super class of all the other classes. This class contains common member data declarations such as simulation dates, agronomic data, weather data, etc., and methods for data setting and computations.
Growth, H2OBalance, and NBalance are abstract classes which inherit class
Agroecosystem and then extend it, separately. These three classes also represent the super classes of Phenology, CBalance, ET, SoilWater, PlantWater, PlantN and SoilN, respectively. Furthermore, the properties of Phenology and CBalance are inherited and extended by SizeGrowth and MassGrowth, separately.
2.2. Plant phenological model
The plant phenological model is described by classes Phenology and SizeGrowth, which represent solutions to a set of regression-based models based upon the experimental data sets described by Pan et al. (1998a,b). Output from class Phenol-ogy represents the in¯uence of heat units (expressed as degree-days) upon leaf and internode phenological events. These events include leaf appearance, expansion and death rates, as well as internode appearance and extension rates. Class SizeGrowth, on the other hand, estimates the dynamics of leaf area, LAI and plant height based upon the eects of accumulated heat measurement values and population density on leaf expansion and internode extension. In class SizeGrowth, light interception is also estimated from computed LAI and plant height.
Classes PlantWater, CBalance and PlantN are called to provide estimates of plant water, carbohydrate and nitrogen stress, respectively, for estimating such stress eects on plant leaf and stem growth and development rates in class SizeGrowth.
Class SizeGrowth is called to provide estimates of current LAI and light inter-ception for use in estimating transpiration in class ET and in predicting photo-synthetic rate in class CBalance, respectively.
The algorithm for calculating plant leaf area in class SizeGrowth is given below to illustrate a series of steps by which OWSimu arrives at an estimate for plant phe-nology and size growth.
First, the eect of plant density on leaf growth (DE) is calculated based on the algorithm of Marani (1996) in CALGOS, using the following equation:
DE1ÿP75 1ÿeP76 5ÿplants row=row spacing
ÿ
ÿ
; 1
whereP75andP76are the 75th and 76th data, read from a table in the plant
data-base and denote genotype parameters, plants_row represents the number of plants per meter of row, and row_spacing denotes the distance (in meters) between two adjacent rows.
Then, the area of thenth leaf (An) is calculated [Eq. (2)]:
AnAmax n DDÿDD0 n =DDd n ; 2
whereAmax(n) represents the maximum area of thenth leaf expansion, DD is the number of degree-days accumulated from emergence until current day, DD0(n)
denotes the growing degree-days required for thenth leaf appearance, DDd(n) is the
growing degree-days required for duration of the nth leaf expansion. All of these values are obtained by inheritance from class Phenology's methods.
The area of thenth leaf can then be adjusted using the result calculated from Eq. (1) and the methods called from classes PlantWater, PlantN and CBalance based upon Eq. (2) in the following manner:
AnAnDEH2O:plantWaterStress N:plantNStress
C:plantCStress ; 3
where H2O.plantWaterStress() represents the current value of plant water stress,
which is obtained from the instance (H2O) of class PlantWater, N.plantNStress()
denotes the current value of plant nitrogen stress, derived from the instance (N) of class PlantN, C.plantCStress() is the current value of plant carbon stress, calculated from the instance (C) of class CBalance.
Therefore, the total leaf area (TA) for a plant at a speci®c accumulated growing degree-day value (GDD) can be calculated as Eq. (4):
TAX
ne
nn0
An; 4
wheren0 andnerepresent the number of dead leaves and the total number of leaves
2.3. Plant carbon balance model
The plant carbon balance model consists of classes CBalance and MassGrowth, describing plant photosynthesis and respiration, carbohydrate partitioning between shoot and root systems, plant biomass accumulation, leaf weight, stem weight, root weight and the ratio of shoot/root.
For these two classes, programming for the plant photosynthesis and respiration methods were based on two cotton models (Baker et al., 1983; Marani, 1996) and were adjusted using the simulated results of the phenological model. The carbohy-drate partitioning method was coded according to the algorithm in the ROOTSIMU model of Hoogenboom and Huck (1987). Other methods were programmed based upon the simulated results of the photosynthesis and carbohydrate partitioning fac-tor methods.
Class CBalance calls classes PlantWater and PlantN to obtain estimates for plant water and nitrogen stresses, required for calculating photosynthesis.
Class MassGrowth, in turn, is called by class PlantWater to obtain an estimate for root weight growth, required to compute plant water uptake. It is also called by class PlantN for biomass accumulation prediction, needed to simulate plant nitrogen content and nitrogen stress.
An example of class MassGrowth calculations is given below to estimate cotton plant root weight:
First, daily gross photosynthesis rate is estimated for the cotton plant by Eqs. 5 and 6:
pstand2:3908WATTSM 1:37379ÿWATTSM0:00054136; 5
where pstand represents the potential for gross photosynthesis in energy units for a standing non-stressed full canopy. This equation represents an empirical function of WATTSM as used by Baker et al. (1972), in which the average daily global radiation is expressed in units of (W mÿ2).
Then, the plant gross photosynthesis is adjusted by light interception (INT), plant population density factor (popfac), CO2eect (CO2_eect), H2O eect (H2O_eect),
and N-nutrition eect (N_eect):
pplant0:10pstandINTpopfacCO2 effectH2O effect
N effect; 6
where pplant represents gross photosynthesis for each individual cotton plant, pop-fac is a plant population pop-factor (poppop-fac = row_spacing/plants_row).
Cotton plant daily net photosynthesis (net_photo1) can be computed by
subtract-ing photo-respiration and maintenance respiration (Marani, 1996) from pplant.
1 For other plant species, net_photo must currently be adjusted by the following equation:
net photocotton net photoleaf area=cotton leaf area; 70
Then, daily net photosynthesis partitioned by the root weight (root_weight1) is
computed as shown in Eq. (7):
root weight1net photoTQ10pw:root partitioning factor ; 7
where TQ10is the biological Q-10, which implies a doubling of the reaction rate for
each 10 degree (C) soil temperature change. The pw.root_partitioning_factor() represents the value of root partitioning factor which is simulated in class Plant-Water.
Therefore, accumulated root weight (root_weight) can be obtained (Eq. (8)):
root weightroot weight0root weight1; 8
where root_weight0is the accumulated root weight from the previous day.
2.4. Water balance model
Class ET was developed by entirely transferring GOSSYM (Baker et al., 1983) subroutine ET, which was in turn adapted from the Ritchie (1972) model. It extends class H2OBalance and mainly calculates water losses from both soil and plant by
evaporation and transpiration. In this class, SoilWater is called to use its soil water potential method in computing evaporation. Then SizeGrowth is called to use its LAI and light interception methods in calculating plant transpiration.
Classes SoilWater and PlantWater were programmed by translation of the FOR-TRAN source code of ROOTSIMU (Hoogenboom and Huck, 1987). They also inherit and extend class H2OBalance. Class SoilWater estimates soil water potential
and soil water content for each component of the soil pro®le. Class PlantWater describes plant canopy water potential and plant water stress.
Class PlantWater is called to estimate water uptake rate per soil layer, needed to adjust soil water balance method in class SoilWater, whereas class SoilWater is called to estimate soil water potential, required to compute plant water potential in class PlantWater. Class PlantWater calls class MassGrowth for obtaining root weight to estimate the total length of active roots, needed for predicting H2O
uptake.
2.5. Nitrogen balance model
Classes PlantN and SoilN were coded to estimate plant nitrogen content, soil nitrogen content (in class SoilN) and plant nitrogen stress (in class PlantN) for each system component.
3. System input and output
3.1. Plant, weather and soil data input
Class DBMS was programmed to input plant, weather and soil data. OWSimu can obtain these data from two possible alternative sources: databases or ¯at ®les accessible to the operating systems.
3.1.1. Input from plant, weather and soil databases
Plant, weather and soil database development and their connection to the Java programs have been described in another paper by Pan et al. (1998c).
In class DBMS, method ``connectDB()'' was coded to connect with the three databases through JDBC-ODBC (Java Database Connectivity and Open Database Connectivity) served by dbANYWHERE Server (Symantec, 1997). Methods ``readPlantDB()'', ``readWeatherDB()'' and ``readSoilDB()'' were programmed to get data from the three databases. Methods ``setPlantData()'', ``setWeatherData()'' and ``setSoilData()'' were written to set the three types of data to the simulation models, separately.
3.1.2. Input from ¯at ®le system
Data in each table of the databases were converted and stored in a ¯at ®le. All of these ®les were classi®ed and stored in plant, weather and soil directories, respec-tively. Then, the plant, weather and soil directories were made publicly accessible by the Web server which publishes Java applet Simulator.
In Java class DBMS, methods ``readPlantFile()'', ``readWeatherFile()'' and ``readSoilFile()'' were coded to obtain the three types of data from the relevant ®les. The ``setPlantData()'', ``setWeatherData()'' and ``setSoilData()'' mentioned above can also be used to set these data to the simulation models.
3.2. Agronomic data input
Class Agronomy was programmed to facilitate user input of agronomic data. This class cannot only transfer data for speci®c agronomic variables (e.g. latitude, plant-ing date, plants per meter of row, row spacplant-ing, simulation start and simulation stop dates) from the text ®elds which were built in the main graphical user interface (GUI), but it also presents a graphical interface (Fig. 3) from which the user can edit and apply the time and rate of irrigation or fertilization practices.
3.3. Output simulated results
Classes PlotItem, Plot and Text were programmed to display the simulated results. Class PlotItem serves to display the simulated results in a time interval.
Text functions to show the output in text format.
The output content can be any of those listed in Table 1 as the users' choices. Class GUI was programmed to generate the main user graphical interface for OWSimu. As shown in Fig. 4, the upper part of the interface was designed for data input, whereas the central section displays model output. The ``User Guides'' and ``Run'' buttons at the bottom of the interface permit the user to execute operations to learn how to use OWSimu and to run the model. Menu choices in the upper-left section allow the user to choose a target plant species, site-speci®c weather and typical soil types, respectively. Data to describe agronomic practices can be entered on the upper-middle and upper-right part. The graphical output is displayed in the dark area to the left of center, whereas text-formatted output is displayed to the right of the central section.
Class MenuMaker extends the PopupMenu from Sun Java standard library. It produces the ``Run'' menu which contains choices needed to generate output con-tents.
4. System management
4.1. System organization
OWSimu system has been organized in a structure, as shown in Fig. 5.
The MAIN directory contains MODEL and IO packages (a package is a group of related Java classes organized and packaged in a directory) as well as Java applet Simulator and some Java classes for designing GUI. A simple HTML program tagging the Java applet Simulator is also in this directory.
Java classes Agroecosystem, Growth, SizeGrowth, MassGrowth, Phenology, CBalance, H2Obalance, SoilWater, PlantWater, ET (Evapotranspiration),
NBa-lance, SoilN and PlantN, simulating plant growth and its environmental eects, were packaged in the MODEL.
The IO package, serving to deal with I/O problems, contains classes DBMS, Agronomy, Plot, PlotItem, Text and Utility.
4.2. Object class management
Class Simulator was programmed to manage the entire OWSimu system. It calls classes GUI and MenuMaker to show the graphical user interface, the classes in the
Table 1
List of output contents
Category Sub-category Output contents (simulation targets)
Size growth Leaf area (cm2/ plant)
LAI (cm2/ cm2)
Internode length (cm) Plant height (cm)
Mass growth Plant biomass (g / plant)
Leaf weight (g / plant) Stem weight (g / plant) Root weight (g / plant) Shoot/root
Phenology Leaf expansion
Internode extension Leaf and internode events
Carbon balance Gross photosynthesis (g / plant / day) Net photosynthesis (g / plant / day) Respiration (g / plant / day)
H2O balance Soil water Soil water potential (bar)
Soil water content (cm3/cm3)
Plant water Plant water potential (bar) Plant water stress
Evapotranspiration Evaporation (mm/day) Transpiration (mm/day) Evapotranspiration (mm/day)
Nitrogen balance Soil nitrogen Soil nitrogen content (mg/cm3)
Soil nitrate N content (mg/cm3)
MODEL package to simulate plant growth, and the classes in the IO package to deal with system I/O problems.
4.3. Web publication
Class Simulator also inherits the characteristics of class Applet in the SUN Java standard library. Thus, class Simulator can be used as an applet which can be tagged into a HTML program and published on the Web.
Fig. 4. Main graphical user interface.
5. Program operation and simulation
OWSimu can be run on a user's client machine by using a Java (JDK1.1)-embed-ded Web browser and linking our website: http://th190-50.agn.uiuc.edu. OWSimu will ®rst generate a GUI as described earlier when a user link to the Web page tag-ging Java applet Simulator.
He/she may wish ®rst to read the user guides by clicking the ``User Guides'' but-ton on the GUI and link into the ``OWSimu User Guides'' Web page.
When the user has chosen a plant species from the menu choice marked with ``Plant Species'' for a plant growth simulation study, he/she may also wish to choose environmental conditions from each of the other two databases containing site-spe-ci®c weather and a set of soil characteristic values in the ``Weather Data'' and ``Soil Type'' menu. The user must also specify relevant agronomic data, such as planting date, row spacing, etc., in the text ®elds provided by the interface.
The buttons marked ``Irrigation'' and ``Fertilization'' are intended for use with irrigation and fertilization application schedules. When users click either the ``Irri-gation'' or ``Fertilization'' button, a window will be popped up so that users can schedule the timing and rate of irrigation or nitrogen fertilization, and then input the scheduled data into the system by clicking the ``Apply'' button in this popup window. Output can be displayed in either graphical and/or text format after clicking the ``Run'' buttons and choosing the simulation targets (Table 1) from a popup menu with submenu choices including Size Growth, Mass Growth, Phenology, C Balance, H2O Balance and Nitrogen Balance. In its default mode, the output is displayed in
both ®gure and text formats.
For example, to simulate soybean plant height growth on clay loam soil under Urbana weather conditions as recorded in 1996, ``Soybean'', ``Urbana 96'' and ``Clay Loam'' were selected from the three menu choices, presented. Then, ``40.1'', ``15'', ``0.76'', ``05/25/96'', ``06/05/96'', ``08/15/96'' might be typed into the text ®elds marked ``Latitude'', ``Plants/m of Row'', ``Row Spacing (m)'', ``Emergence Date'', ``Simu. Start Date'', and ``Simu.Stop Date'', respectively. After that, 20, 15 and 15 mm water are scheduled for irrigation on ``7/15/96'', ``7/25/96'' and ``8/05/96'', separately, in a popup window by clicking the ``Irrigation'' button. When running OWSimu by pressing the ``Run'' button and choosing ``Plant Height'' from ``Size Growth'' category in the popup menu, the output is displayed with both text and graphical formats (Fig. 6). If the ``Text Output'' is not checked, the result would be shown only with graphical format. Or if the ``Figure Output'' is not checked, OWSimu will only display the simulation results in text format.
6. Discussion
OWSimu is a convenient tool for researchers, teachers and students to use in the study of plant growth since it is Web-based facilitating communication and giving access to a wide variety of potential users. It can be shared over the Web while studying plant phenological events and growth of vegetative canopy in response to micro-environmental variables.
OWSimu is an object-oriented plant growth simulator. Fundamental plant growth processes, state-variables, environmental factors and cultural practices were coded as objects into Java classes, which were packaged in the MODEL directory. These classes can be inherited and extended by other newly programmed classes, facilitat-ing easy update or reuse of code. New functions to the plant growth model can easily be added by coding some new methods in the classes presented here, or by programming a new class to extend the most relevant class in the MODEL. Other model developers may wish to use the code by importing package MODEL and then calling or extending its classes while writing their own Java programs for plant growth or relevant ®elds. The IO package provides with powerful techniques and rich resources to input data from databases and to output simulated results. In extending these Java classes to their own Java code, other programmers may reuse source code from this IO package and share these techniques and resources by importing the existing IO package and overriding a few methods of the DBMS and Plot classes.
varieties within a selected plant species, and extended for use in a speci®c crop pro-duction management.
At present, the photosynthesis and respiration estimations in the carbon balance model of OWSimu are based upon the cotton models GOSSYM and CALGOS. So OWSimu may not be able to simulate plant biomass accumulation accurately for most other plant species, though we have done some preliminary work in adjusting the carbon balance model by using plant leaf area and plant leaf weight from the phenological model simulation results [e.g. Eq. (70)]. We must continue to explore
better algorithms, and to collect experimental data needed for adjusting the carbon balance model applicable for use with other plant species.
7. System requirements
OWSimu requires a Java (JDK1.1 or above)-embedded Web browser such as Netscape Communicator 4.07 or newer version, Microsoft Internet Explorer 4.0 or higher version, HotJava BrowserTM1.1 or newer version, etc.
Because OWSimu was developed under Windows 95 and 98, it has optimal per-formance when running under Windows 95/98/NT. OWSimu can also run under UNIX, but its graphical user interface usually does not show well. OWSimu runs well with Microsoft Internet Explorer 4.5 or higher version, but does not work with current Netscape Communicator under Macintosh because JDK1.1 still has not been fully embedded into the Netscape Communicator for Macintosh.
References
Acock, B., Trent, A., 1991. GLYCIM: the Soybean Crop Simulator. Idaho Agricultural Experimental Station, Mis. Series Bulletin. No. 145, Moscow, ID, USA.
Baker, D.N., Hesketh, J.D., Duncan, W.G., 1972. The simulation of growth and yield in cotton: I. Gross photosynthesis, respiration and growth. Crop Sci. 12, 431±435.
Baker, D.N., Lambert, J.R., McKinion, J.M., 1983. GOSSYM: A Simulator of Cotton Crop Growth and Yield. South Carolina Agricultural Experimental Station Technical Bulletin No. 1089, Clemson, SC, USA.
Caldwell, R.M., Fernandez, A.A.J., 1998. A generic model of hierarchy for systems analysis and simula-tion. Agricultural Systems 57 (2), 197±225.
Cornell, G., Horstmann, C.S., 1996. Core Java. 1st Edition. The Sunsoft Press: Java Series, Upper Saddle River, NJ.
Fu, H., Hesketh, J.D., 1996. A crop phenology simulator for windows. Proceedings of the 6th Interna-tional Conference on Computers in Agriculture, pp. 1013±1021.
Hoogenboom, G., Huck, M.G., 1987. ROOTSIMU: model simulating root and shoot growth. In: Hillel, D. (Ed.), Advances in Irrigation, Vol. 4. Academic Press, Orlando, FL, USA, pp. 331±376.
Johnson, I.R., 1994. PLANTMOD 2.1: Exploring the Physiology of Plant Communities. Greenhat Soft-ware, Armidale, NSW, Australia.
Jones, J.W., Hesketh, J.D., Kamprath, E.J., Bowen, H., 1974. Development of a nitrogen balance for cotton growth: a ®rst approximation. Crop Sci. 14, 541±546.
Lemmon, H., Chuk, N., 1998. CottonPlus: A Cotton Crop Model and Expert System to Support On-Farm Management. I. Theory and Equations of the Crop Model (http://home.earthlink.net/lemmon/ _private/papers/thry.htm).
Lemmon, H., Chuk, N., Reddy, V., Acock, B., Pachepsky, Y. 1997. Sigma Plus: A Cotton Crop Model. The 27th Crop Simulation Workshop, Gainesville, FL.
Marani, A., 1996. CALGOS Cotton Simulation Model (http://asset.arsusda.gov/ WMRL/calgos.html). Marani, A., Phene, C.J., 1993. ABSTRACT. CALGOS Ð a model of irrigated cotton. Agronomy
Abstracts, 1993 Annual Meetings, 7±12 November, Cincinnati, OH
McKinion, J.M., Baker, D.N., Hesketh, J.D., Jones, J.W., 1975. SIMCOT II: A Simulation of Cotton Growth and Yield. USDA, ARS, Southern Series Bull. ARS S-52, 27±82.
Mutsaers, H.J.W., 1984. KUTUN: a morphogenetic model for cotton (Gossypium hirsutumL.). Agri-cultural Systems 14, 229±257.
Pan, X., 1997. Modeling Degree Day Eects on Plant Leaf and Internode Phenological Events. MSc. thesis, University of Illinois, Urbana-Champaign, IL, USA.
Pan, X., Hesketh, J.D., Huck, M.G., 1997. PHENAPP: A Java Applet and Application for Plant Phe-nological Events. The 27th Crop Simulation Workshop, Gainesville, FL, USA
Pan, X., Begonia, G.B., Hesketh, J.D., 1998a. Quantifying Crop-Weed Competition (http://th190-50.agn.uiuc.edu/).
Pan, X., Hesketh, J.D., Huck, M.G., 1998b. A database for scaling up from the leaf to the canopy. PHOTOSYNTHETICA 35 (3), 329±334.
Pan, X., Hesketh, J.D., Huck, M.G., 1998c. A Web interface to databases associated with a plant simu-lator. Computers and Electronics in Agriculture 21 (3), 207±217.
Reddy, K.R., Hodges, H.F., McKinion, J.M., 1997. Crop modeling and applications: a cotton example. In: Advances in Agronomy Vol. 59. Academic Press, pp. 225±290.
Ritchie, J.T., 1972. Model predicting evaporation from a row crop with incomplete cover. Water Resources Research 8, 204±1213.
Ritchie, J.T., Godwin, D.C., Otter-Nacke, S., 1985. CERES-Wheat: A Simulation Model of Wheat Growth and Development. Texas A&M University Press, College Station, TX, USA.
Sridharan, P., 1997. Advanced Java Networking. Prentice Hall, Upper Saddle River, NJ, USA. Symantec, 1997. Visual Cafe for Java 2.0. Database Development. Symantec, Cupertino, CA, USA. Thornley, J.H.M., Johnson, I.R., 1990. Plant and Crop Modelling: A Mathematical Approach to Plant
