Support system for decision making in the management of the greenhouse environmental based on growth model for sweet pepper

Over recent years, intensive Mediterranean agriculture has been gradually changing from very low-technology greenhouses to those incorporating intermediate and, in some cases, advanced technology. The Decision Support System (DSS) can help growers, engineers and students learn about and manage the system dynamic and its influence on production. This work shows the calibration and validation of a pepper growth model based on physiological principles and on the works of several authors. The model gives good results on dry matter production estimation as well as partitioning between different plant organs. The promising results obtained in the model validation (tested with real data from the southeast of Spain) allowed us to design and implement the Graphical User Interface (GUI). This software tool, which predicts pepper crop growth using models based on climatic variables, permits the development of an optimum control system. The DSS final version is user-friendly and easily managed by growers.

[1]  J. Goudriaan,et al.  Modelling Potential Crop Growth Processes , 1994, Current Issues in Production Ecology.

[2]  J. L. Guzmán,et al.  GREENHOUSE DIURNAL TEMPERATURE CONTROL WITH NATURAL VENTILATION BASED ON EMPIRICAL MODELS , 2006 .

[3]  M. A. Scaife,et al.  The relationship between crop yield (or mean plant weight) of lettuce and plant density, length of growing period, and initial plant weight , 1976, The Journal of Agricultural Science.

[4]  Gerrit Hoogenboom,et al.  A web-based fuzzy expert system for frost warnings in horticultural crops , 2012, Environ. Model. Softw..

[5]  Francisco Rodríguez,et al.  Development of a biomass-based system for nocturnal temperature and diurnal CO2 concentration control in greenhouses , 2014 .

[6]  J. Porter,et al.  Effects of elevated CO2 and drought on wheat: testing crop simulation models for different experimental and climatic conditions , 2002 .

[7]  Pat Hanrahan,et al.  Rendering Techniques ’95: Proceedings of the Eurographics Workshop in Dublin, Ireland, June 12–14, 1995 , 1995, Eurographics.

[8]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[9]  Benoit Aubert,et al.  IT as enabler of sustainable farming: An empirical analysis of farmers' adoption decision of precision agriculture technology , 2012, Decis. Support Syst..

[10]  E. Heuvelink.  Evaluation of a Dynamic Simulation Model for Tomato Crop Growth and Development , 1999 .

[11]  R. Rabbinge,et al.  Simulation and systems management in crop protection , 1989, Plant Growth Regulation.

[12]  Francisco Rodríguez,et al.  Multiobjective hierarchical control architecture for greenhouse crop growth , 2012, Autom..

[13]  H. Cutforth,et al.  Crop growth models for decision support systems , 1996 .

[14]  Mateu Sbert,et al.  Global Monte Carlo. A Progressive Solution , 1995, Rendering Techniques.

[15]  Thierry Hoch,et al.  A mechanistic dynamic model to estimate beef cattle growth and body composition: 1. Model description , 2004 .

[16]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[17]  Jorge Antonio Sánchez-Molina,et al.  Virtual Sensors for Designing Irrigation Controllers in Greenhouses , 2012, Sensors.

[18]  L. Darrell Whitley,et al.  Genetic algorithms and neural networks: optimizing connections and connectivity , 1990, Parallel Comput..

[19]  M. M. González-Real,et al.  Influence of fruit load on dry matter and N-distribution in sweet pepper plants , 2008 .

[20]  M. M. González-Real,et al.  Influence of fruit sink strength on the distribution of leaf photosynthetic traits in fruit-bearing shoots of pepper plants (Capsicum annuum L.) , 2009 .

[21]  L. Marcelis,et al.  A simulation model for dry matter partitioning in cucumber. , 1994, Annals of botany.

[22]  Ep Heuvelink,et al.  Modelling biomass production and yield of horticultural crops: a review , 1998 .

[23]  C. Kempenaar,et al.  Analysis of the experimental variability in wheat responses to elevated CO2 and temperature , 2002 .

[24]  Francisco Rodríguez,et al.  Adaptive hierarchical control of greenhouse crop production , 2008 .

[25]  E. Nederhoff,et al.  Leaf conductance and rate of crop transpiration of greenhouse grown sweet pepper (Capsicum annuum L.) as affected by carbon dioxide , 1992 .

[26]  Octavio A. Castelán-Ortega,et al.  A Decision Support System for smallholder campesino maize-cattle production systems of the Toluca Valley in Central Mexico. Part I— Integrating biological and socio-economic models into a holistic system , 2003 .

[27]  P.H.B. de Visser,et al.  Modelling Dry Matter Production and Partitioning in Sweet Pepper , 2006 .

[28]  José Luis Guzmán,et al.  Water content virtual sensor for tomatoes in coconut coir substrate for irrigation control design , 2015 .

[29]  Francisco Rodríguez,et al.  Modeling and Control of Greenhouse Crop Growth , 2014 .