Automatic control of drip irrigation on hydroponic agriculture: Daniela tomato production

The irrigation control and monitoring of the involved variables in the plant growth are actions that farmers must implement in their crops to save water resources and assessing the growth of the Daniela tomato plant. This work presents the control drip is applied to hydroponic farming in which is developed an interface between human and machine in a free software allowing continuous monitoring of moisture, pH, temperature and electrical conductivity of soil through the sensors housed in the crop root zone also, the controller performs the conditioning sensors, actuator control resource to irrigate water, and nutrient solution, and monitoring via web. The field implementation of the system is carried out in a tunnel-type greenhouse designed under the requirements of a hydroponic system. Finally to show the results we evaluate two experiments: Experiment one: determining hydric resourses, and nutritional requirements needed by the culturing based on monitoring of physical variables. Experiment 2; assess how media type tomato fruit have more weight and diameter.

[1]  A. Bleicher Farming By The Numbers , 2013, IEEE Spectrum.

[2]  Miguel Ángel Porta-Gándara,et al.  Automated Irrigation System Using a Wireless Sensor Network and GPRS Module , 2014, IEEE Transactions on Instrumentation and Measurement.

[3]  J. L. Dávila,et al.  Contaminación enteroparasitaria de lechugas expendidas en mercados del estado Lara. Venezuela , 2004 .

[4]  W. Zheng,et al.  Greenhouse humidity system modeling and controlling based on mixed logical dynamical , 2014, CCC 2014.

[5]  Mario Jimenez,et al.  Strawberries collecting robot prototype in greenhouse hydroponic systems , 2013, Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013.

[6]  Howard Resh,et al.  Hydroponic food production : a definitive guidebook for the advanced home gardener and the commercial hydroponic grower , 1978 .

[7]  F. Capraro,et al.  Intelligent Irrigation in Grapevines: A Way to Obtain Different Wine Characteristics , 2008 .

[8]  Martha Ramírez-Martinez,et al.  Hábitos alimenticios en estudiantes de Nutrición de la Universidad Autónoma de Aguascalientes en el periodo enero- junio de 2015 , 2018 .

[9]  Matías L. Marote Agricultura de Precisión , 2010 .

[10]  Laurent Lefort,et al.  Farming the Web of Things , 2013, IEEE Intelligent Systems.

[11]  C J Rutten,et al.  Invited review: sensors to support health management on dairy farms. , 2013, Journal of dairy science.

[12]  Naim Karasekreter,et al.  Developing agricultural irrigation technology compatible with national energy efficiency policy , 2013, 2013 IEEE INISTA.