https://doi.org/10.4081/jae.2020.1028
Method of pump, pipe, and tank selection for aeroponic nutrient management systems based on crop requirements
Published: 18 June 2020
Abstract Views: 3222
PDF: 1306
HTML: 4905
HTML: 4905
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
The system-specific selection of aeroponic nutrient system components, specifically pumps, pipes, and tanks, is very important to improve system efficiency and minimize costs, as these components vary for different systems with different crop water requirements and design specifications. In this study, methods were suggested for determining the most suitable sizes of pumps, pipes, and tanks based on the plant water consumption and irrigation interval targeted to improve the usual procedures to design an aeroponic nutrient management system, and applied to a case. Factors affecting the size calculation are discussed, and calculation methods were suggested based on basic hydraulic principles. A recycle-type aeroponic nutrient management system, cultivating 500 plants in 21 plant beds, was considered for a case study. Application of the size calculation methods in the case study showed that an irrigation pump with a 37 Lmin–1 flow rate at 900 kPa capacity and nutrient pumps with a 5 Lmin–1 flow rate at 40 kPa capacity with 19-mmdiameter pipes were required to deliver the mixed nutrients and supply stock solutions into the mixing tank, along with nutrient mixing, stock nutrients, and distilled water tanks of 750, 40, and 685 L, respectively. Calculation was demonstrated to show the variations in the sizing of the pumps, pipes, and tanks by number of plants. Validation tests were performed for the selected irrigation pump capacity, and the results showed that the Nash-Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and root-mean-square error (RMSE) values were 0.410, 0.98, 0.109 Lmin–1 and 0.775, 0.99, 34.91 kPa for flow rate and pressure, respectively. The case study also showed that these sizing procedures increased the plant bed coverage efficiency of the irrigation pump by 33%, while increasing the nutrient mixing tank size by 133%. This study would provide useful information on the efficient sizing of pumps, pipes, and tanks for minimizing costs and maximizing crop production in aeroponic nutrient management systems.
Amalfitano C., Del Vacchio L., Somma S., Cuciniello, A., Caruso, G. 2017. Effects of cultural cycle and nutrient solution electrical conductivity on plant growth, yield and fruit quality of “Friariello†pepper grown in hydroponics. Horticu Sci 44(2): 91–98.
DOI: https://doi.org/10.17221/172/2015-HORTSCI
ASABE, 1999. Spray nozzle classification by droplet spectra. American Society of Agricultural and Biological Engineers, St. Joseph, USA.
Bankston J.D., Baker F.E. 1994. Selecting the proper pump. Southern Regional Aquaculture Center. https://wkrec.ca.uky.edu/files/selectingpumps.pdf.
Batchabani E., Fuamba M. 2012. Optimal tank design in water distribution networks: review of literature and perspectives. J Water Res Plan and Manag 140(2):136–145.
BETE. 2013. BETE engineering information – BETE spray nozzles. http://www.bete.com/pdfs/BETE_EngineeringInformation.pdf
BETE. 2018. Misting nozzles – BETE spray nozzles. https://www.bete.com /PDFs/BETE_0218Metric_Catalog.pdf
Bird J. (ed). 2007. Engineering mathematics. Elsevier Ltd., Netherlands.
DOI: https://doi.org/10.4324/9780080470955
Bos M.G., Kselik R.A., Allen R.G., Molden D. 2008. Water requirements for irrigation and the environment. Wageningen, Springer Science & Business Media, Netherlands.
Cho W.J., Kim H.J., Jung D.H., Kang C.I., Choi G.L., Son J.E. 2017. An embedded system for automated hydroponic nutrient solution management. Trans ASABE 60(4): 1083–1096.
DOI: https://doi.org/10.13031/trans.12163
Deb K., Pratap A., Agarwal S, Meyarivan T. 2002. A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE Trans Evol Comp 6(2): 182–197.
DOI: https://doi.org/10.1109/4235.996017
dos Santos J.D., da Silva A.L.L., da Luz Costa J., Scheidt G.N., Novak A.C., Sydney E.B., Soccol C.R. 2013. Development of a vinasse nutritive solution for hydroponics. J Environ Manag 114: 8–12.
DOI: https://doi.org/10.1016/j.jenvman.2012.10.045
Fang H., Zhang J., Gao J.L. 2010. Optimal operation of multi-storage tank multi-source system based on storage policy. J Zhejiang Uni-Sci 11(8): 571–579.
DOI: https://doi.org/10.1631/jzus.A0900784
Fonseca C.M., Fleming P.J. 1993. Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of the 5th ICGA. pp. 416–423.
Frenning L. 2001. Pump life cycle costs: a guide to LCC analysis for pumping systems. https://www1.eere.energy.gov/manufacturing/tech_assistance/pdfs/pumplcc_ 1001.pdf
Giacomello C., Kapelan Z., Nicolini M. 2012. Fast hybrid optimization method for effective pump scheduling. J Water Res Plan and Manag 139(2): 175–183.
DOI: https://doi.org/10.1061/(ASCE)WR.1943-5452.0000239
Golmohammadi G., Prasher S., Madani A., Rudra R. 2014. Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT. Hydrology, 1(1): 20-39.
DOI: https://doi.org/10.3390/hydrology1010020
HDR Engineering. 2001. Handbook of public water systems. 2nd ed. John Wiley & Sons Inc., New York, USA.
Jadrnicek S., Jadrnicek S. 2016. The bio-integrated farm: a revolutionary permaculture-based system using greenhouses, ponds, compost piles, aquaponics, chickens, and more. Chelsea Green Publishing, White River Junction, USA.
Jones J.J.B. 2016. Hydroponics: a practical guide for the soilless grower. 2nd ed. CRC Press, New York, USA.
Jung D.H., Kim H.J., Choi G.L., Ahn T.I., Son J.E., Sudduth K.A. 2015. Automated lettuce nutrient solution management using an array of ion-selective electrodes. Trans ASABE 58(5): 1309–1319.
Kim H.J., Kim W.K., Roh M.Y., Kang C.I., Park J.M., Sudduth K. 2013. Automated sensing of hydroponic macronutrients using a computer-controlled system with an array of ion-selective electrodes. Comp Elect Agri 93: 46–54.
DOI: https://doi.org/10.1016/j.compag.2013.01.011
King H.W., Wisler C.O. 1974. Hydraulics, John Wiley and Sons, Inc., London, UK.
Kozai T. 2015. The state of Japanese CEA. Greenhouse Management. http://www.greenhousemag.com/article/gm0315-controlled-environment-agriculture-japan/.
Krause P., Boyle D P., Bäse F. 2005. Comparison of different efficiency criteria for hydrological model assessment. Adv. Geosci 5: 89-97.Kurek W., Ostfeld A. 2013. Multi-objective optimization of water quality, pumps operation, and storage size selection of water distribution systems. J Environ Manag 115: 189–197.
Lee S., Lee J. 2015. Beneficial bacteria and fungi in hydroponic systems: types and characteristics of hydroponic food production methods. Sci Hortic 195: 206–215.
DOI: https://doi.org/10.1016/j.scienta.2015.09.011
Lira R.M.D., Silva G.F.D., Santos A.N.D., Rolim M.M. 2015. Production, water consumption and nutrient content of Chinese cabbage grown hydroponically in brackish water. Revista Ciência Agronômica 46(3): 497–505.
DOI: https://doi.org/10.5935/1806-6690.20150031
Marchi A., Simpson A.R., Lambert M.F. 2017. Pump operation optimization using rule-based controls. Proc Eng 186: 210–217.
DOI: https://doi.org/10.1016/j.proeng.2017.03.229
Miranda J.L.H., López L.A.A. 2011. Piping design: the fundamentals. https://orkustofnun.is/gogn/unu-gtp-sc/UNU-GTP-SC-12-36.pdf
Moran S. 2016. Pump size selection: bridging the gap between theory and practice. Chem Eng Prog 112(12): 38–44.
Morgan L. 2003. Hydroponics substance. Growing Edge 15(2): 54–66.
Moriasi D.N., Arnold J.G., Van Liew M.W., Bingner R.L., Harmel R.D., Veith, T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3): 885-900.
DOI: https://doi.org/10.13031/2013.23153
Pagliarulo C.L., Hayden A.L. 2000. Potential for greenhouse aeroponic cultivation of medicinal root crops. Controlled Environment Agriculture Center, Department of Plant Sciences, University of Arizona, Tucson, USA.
Paulus D., Paulus E., Nava G.A., Moura C.A. 2012. Growth, water consumption and mineral composition of lettuce in hydroponic system with saline water. Revista Ceres 59(1): 110–117.
DOI: https://doi.org/10.1590/S0034-737X2012000100016
Pignata G., Casale M., Nicola S. 2017. Water and nutrient supply in horticultural crops grown in soilless culture: resource efficiency in dynamic and intensive systems. In: Advances in Research on Fertilization Management of Vegetable Crops. Springer, Cham, Switzerland. pp. 183–219.
Raza A. 2013. Size selection, specifying and selecting centrifugal pumps. Chem Eng 120(2): 43.
Reddy P.P. 2016. Sustainable crop protection under protected cultivation. Springer, Singapore.
DOI: https://doi.org/10.1007/978-981-287-952-3
Resh H.M. 2016. Hydroponic food production: a definitive guidebook for the advanced home gardener and the commercial hydroponic grower. CRC Press. New York, USA.
DOI: https://doi.org/10.1201/b12500
Samsuri S.F.M., Ahmad R., Hussein M. 2010. Development of nutrient solution mixing process on time-based drip fertigation system. In: Mathematical/Analytical Modelling and Computer Simulation (AMS), 2010 Fourth Asia International Conference on IEEE. pp. 615–619.
Santamaria P., Campanile G., Parente A., Elia A. 2003. Subirrigation vs drip-irrigation: effects on yield and quality of soilless grown cherry tomato. J Hortic Sci Biotech 78(3): 290–296.
DOI: https://doi.org/10.1080/14620316.2003.11511620
Savic D., Kapelan Z., Farmani R., Giustolisi O. 2007. Optimal design and management of water distribution systems. In: Numerical Modelling of Hydrodynamics for Water Resources. CRC Press, Washington, DC, USA. pp. 37–58.
Srivastava R.C. 1996. Methodology for optimizing design of integrated tank irrigation system. J Water Resou Plan Manag 122(6): 394–402.
DOI: https://doi.org/10.1061/(ASCE)0733-9496(1996)122:6(394)
Tolvanen, J. 2007. Life cycle energy cost savings through careful system design and pump selection. World Pumps 2007(490): 34–37.
DOI: https://doi.org/10.1016/S0262-1762(07)70253-5
Trimmer, W.L., Hansen H.J. 1997. Size selection irrigation mainlines and fittings. A Pacific Northeast extension publication, Washington, USA.
Vamvakeridou-Lyroudia, L.S., Savic, D.A. Walters G.A. 2007. Tank simulation for the optimization of water distribution networks. J Hydr Eng 133(6): 625–636.
DOI: https://doi.org/10.1061/(ASCE)0733-9429(2007)133:6(625)
Van Liew, M.W., Arnold, J.G. and Garbrecht, J.D., 2003. Hydrologic simulation on agricultural watersheds: Choosing between two models. Trans. ASAE, 46(6): 1539.
DOI: https://doi.org/10.13031/2013.15643
Van Zyl, J.E., D.A. Savic, Walters G.A. 2004. Operational optimization of water distribution systems using a hybrid genetic algorithm. J Water Res Planning and Manag 130(2): 160–170.
DOI: https://doi.org/10.1061/(ASCE)0733-9496(2004)130:2(160)
Washington State Department of Health. 2009. Water system design manual. Office of Drinking Water, Constituent Services Section, Department of Health, Washington, USA.
How to Cite
Chowdhury, M. (2020) “Method of pump, pipe, and tank selection for aeroponic nutrient management systems based on crop requirements”, Journal of Agricultural Engineering, 51(2), pp. 119–128. doi: 10.4081/jae.2020.1028.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Daniele Torreggiani, Alberto Barbaresi, Francesca Dallacasa, Patrizia Tassinari, Effects of different architectural solutions on the thermal behaviour in an unconditioned rural building. The case of an Italian winery , Journal of Agricultural Engineering: Vol. 49 No. 1 (2018)
- José Luis Morales-Reyes, Héctor-Gabriel Acosta-Mesa, Elia-Nora Aquino-Bolaños, Socorro Herrera Meza, Aldo Márquez Grajales, Anthocyanins estimation in homogeneous bean landrace (Phaseolus vulgaris L.) using probabilistic representation and convolutional neural networks , Journal of Agricultural Engineering: Vol. 54 No. 2 (2023)
- Simone Pascuzzi, Giovanni Russo, Giacomo Scarascia-Mugnozza, Giuseppe Verdiani, Sanitary risk analysis for farm workers exposed to environmental pollutants , Journal of Agricultural Engineering: Vol. 43 No. 4 (2012)
- Claudia Arcidiacono, Simona M.C. Porto, IMPROVING PER-PIXEL CLASSIFICATION OF CROP-SHELTER COVERAGE BY TEXTURE ANALYSES OF HIGH-RESOLUTION SATELLITE PANCHROMATIC IMAGES , Journal of Agricultural Engineering: Vol. 42 No. 4 (2011)
- Bhola Paudel, Jayanta Kumar Basak, Seong Woo Jeon, Gun Ho Lee, Nibas Chandra Deb, Sijan Karki, Hyeon Tae Kim, Working speed optimization of the fully automated vegetable seedling transplanter , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Aldo Calcante, Francesco M. Tangorra, Measuring oxygen saturation and pulse rate in dairy cows before and after machine milking using a low-cost pulse oximeter , Journal of Agricultural Engineering: Vol. 52 No. 2 (2021)
- Xingye Zhu, Jing Konng, Alexander Fordjour, Joseph Kwame Lewballah, Frank Agyen Dwomoh, Samuel Anim Ofosu, Junping Liu, Hydraulic performance assessment on dynamic fluidic and complete fluidic sprinklers under indoor and outdoor conditions , Journal of Agricultural Engineering: Vol. 55 No. 3 (2024)
- Ernest Ekow Abano, Livingston Kobina Sam-Amoah, Ato Bart-Plange, Variation in ultrasonic frequency and time as pre-treatments to air-drying of carrot , Journal of Agricultural Engineering: Vol. 43 No. 4 (2012)
- Senanur Durgut Malçok, Azime Özkan Karabacak, Ertürk Bekar, Cüneyt Tunçkal, Canan Ece Tamer, Influence of a hybrid drying combined with infrared and heat pump dryer on drying characteristics, colour, thermal imaging and bioaccessibility of phenolics and antioxidant capacity of mushroom slices , Journal of Agricultural Engineering: Vol. 54 No. 3 (2023)
- Maria Luisa Amodio, Antonio Derossi, Giancarlo Colelli, Modelling sensorial and nutritional changes to better define quality and shelf life of fresh-cut melons , Journal of Agricultural Engineering: Vol. 44 No. 1 (2013)
<< < 27 28 29 30 31 32 33 34 35 36 > >>
You may also start an advanced similarity search for this article.
