In greenhouses, computerized climate control systems can be used to dynamically and automatically regulate climatic and environmental parameters. To support such a mode of operation, a crop growth model that was developed for greenhouse tomato plants (TOMGRO) was chosen. The model describes the phenological development and increase in dry weight of various organs from planting till maturity under variable environmental conditions. The assimilate partitioning is based on sink strength. A FORTRAN version of TOMGRO was converted to the Smalltalk object-oriented programming environment. This model was integrated into GX, a dynamic climate management software system that was developed at Laval Univ. GX defines a general architecture that may accommodate different decision-making modules based on mathematical models and rule bases. The TOMGRO model is being used to evaluate different production scenarios and will be used to calculate and predict crop growth rates, development, and yields. The model can be used to perform real-time and seasonal cost–benefit analysis and for the dynamic optimization of greenhouse climatic parameters.
Hassan Zekki, André Gosselin, and Laurent Gauthier
Michel Carrier, André Gosselin, and Laurent Gauthier
A dynamic management strategy for supplemental lighting in greenhouses was developed. It makes use of a plant growth model and of a rule-based decisionmaking protocol within the framework of a generic greenhouse climate management software system. The model, an adapted version of SUCROS87, tracks plant growth and predicts dry weight production based on measured or estimated values of light intensity, temperature, and CO2 concentration. A set of logical predicates (rules) implements the strategy's behavior. Optimization of lamp use was conducted as a function of economic criteria that enable a comparison between the additional income associated with yield increases due to supplemental lighting and incurred cost increases. Although the model is not perfectly reliable in its predictions, the system can be used to simulate the effect of changes to economic parameters on the decisions of the management strategy. The dynamic strategy described here differs from conventional supplemental lighting scenarios in the sense that it increases the length of the period of supplemental lighting when the daily solar light integral is low, and reduces or eliminates the use of supplemental lighting when the weather forecast predicts that the daily solar light integral will exceed plant requirements.
Duane W. Greene, Alan N. Lakso, Terence L. Robinson, and Phillip Schwallier
model is most useful to predict possible thinner efficacy before thinner application, whereas our fruit growth model is a proposed tool to be used after has been applied. How to use the fruit growth model. Using this fruit growth model will require a
Thomas M. Kon, James R. Schupp, Keith S. Yoder, Leon D. Combs, and Melanie A. Schupp
complex and are dependent on maternal cultivar and temperature ( DeLong et al., 2016 ). Pollen source is not currently an input in pollen tube growth models (PTGM) and may be difficult to incorporate. The fungicide LS was one of the first chemical
Royal D. Heins
Environmental control computers allow regulation of greenhouse environments based on some model driven factor or factors other than fixed heating and cooling setpoints. A quantitative understanding of how environmental factors influence rate of plant development, flower initiation, and plant morphology is necessary to develop models for environmental control. The major limitation to the use of models for greenhouse climate and crop control is the lack of quantitative models. Examples of model development for environmental control will be discussed.
Douglas A. Hopper
One should choose the simplest form of a model as a tool that adequately represents the processes and relationships of interest. ROSESIM was first developed in SLAM II and FORTRAN to run on a mainframe computer, where it had few users and it was cumbersome to learn and use. As use of models on a personal computer (PC) has become more popular for instruction and simulation, ROSESIM was translated first into the American Standard Code for Information Interchange (ASCII) to run in the Beginner's All-purpose Symbolic Instruction Code (BASIC) language in the popular Microsoft Disk Operating System (MS-DOS). As graphical user interface (GUI) Windows applications have gained increased popularity, ROSESIM has been translated into C++ as object-oriented programming (OOP) to run inside Microsoft Windows 3.1. This makes ROSESIM for Windows readily available to virtually every PC user. Features of ROSESIM for Windows are listed and discussed.
Douglas A. Hopper, Troy T. Meinke, and Virginia S. Store
The computer simulation model ROSESIM is based on `Royalty' rose (Rosa hybrida L.) growth response to 15 unique treatment combinations of photosynthetic photon flux (PPF), day temperature (DT), and night temperature (NT) under constant growth chamber conditions. Environmental factors are assumed constant over an entire day, but set points may vary over the duration of the crop. Anticipated values for factors may be read from an ASCII file, allowing a variety of strategies to be modeled and compared.
A Valentine's Day crop senario compared 2 management strategies for crop development time and flower quality:  constant 24/17.1 DT/NT for the entire crop, or  15 days warm 30/20C DT/NT to promote bud break, 10 days 20/15C DT/NT to promote stem caliper and leaf size, 10 days 25/18C DT/NT to promote bud development, and remaining time to flower 20/15C DT/NT to enhance flower size and color. PPF was increased gradually over crop time as would occur naturally for Dec. to Feb. Strategy  had longer stems (63 vs. 50 cm), similar stem and leaf dry weights, but less flower bud dry weight (1.0 vs. 1.6 g), while flowering 2 days earlier (41 vs. 43 days after pinch). c:\pm4\ash94h.pm 4
George J. Wulster
A software application for the personal computer has been developed using the macro languages of Lotus l-2-3 Release 2.2 and the spreadsheet compiler Baler XE Release 1.0E to provide Easter lily (Lilium longiflorum Thunb.) growers with a tool to track and predict various developmental stages of the crop during greenhouse forcing.
Entin Daningsih, Laurie Hodges, and James R. Brandle
Experiments were conducted during summer seasons from 1991 to 1994 to find out the effect of winds on early growth of muskmelon. A randomized complete-block design with sheltered and exposed areas as treatments was used. Sensors for air temperature and relative humidity (model HMP35C or model XN217, Campbell Scientific) were placed at canopy height and 3-cup anemometers (model 12102, R.M. Young, Traverse City, Mich.) were 50 cm aboveground. All sensors were connected to CR10 automatic data loggers and recorded hourly average data. Using regression analysis, we found that the accumulative windspeed frequency below threshold (<4 m–s–1) can be used to predict both accumulative hourly heat units of air temperature (GDHT) with R2's more than 0.85 and total muskmelon fresh and dry weight and leaf area index at early growth. Predicted models using accumulative hourly windspeed frequency have R2's >0.80 in sheltered areas. Adding vapor pressure deficit to the model improves the prediction of muskmelon early growth, especially in exposed areas.