Published

2018-01-01

Soymilk plant simulation to predict the formula of a new Hypothetical Product

Simulación de una planta de leche de soya para predecir la fórmula de un nuevo producto hipotético

Keywords:

Non-ideal Model Mixer, Soybean, Real Batch Mixer, Hypothetical Molecular formula. (en)
Modelo no ideal de mezclador, Semilla de soya, Mezclador batch real, Formula molecular Hipotética (es)

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Authors

  • Iacobi Boanerges Boanerges Industrial University of Santander
Ideal Patterns reactors alteration by real reactor patterns, for better accuracy was done using industrial software: Aspen Plus and Hysys Version 7.1 to represent the batch real mixer and soymilk production system. Fluid package for properties prediction was chosen from the software list. A feed steam of 41,67 Kg/h (Soybean) was taken; mass fractions were given by element since the Soybean has a wide blend of substances which cannot be described as a unique compound formula. The elements were C, N, H, O, S, Na, K, Mg, Ca, Fe, P, and Cu. Final flow of 8,333 Kg/h was used to achieve the objective of this study: the elemental analysis method for the hypothetical new product prediction (based only in presence of Amino-acids and other macro and multiple substances). The macromolecules described here are the onset for new specific soymilk compounds such as the concluded on this study. Fulminic Acid Family compound and the protein analysis may correspond to new proteins which are not well-known such as the ones found in studies by the Hospital de Rhode Island in 2014. Presence of Fe and Cu in soybean was ascribed to the micronutrients that could be present in the soil of crop cultivation and in soybeans by absorption.
La alteración de modelos de reactores ideales por modelos reales para mayor precisión fue hecha usando un software industrial: Aspen Hysys Versión 7.1 para representar el mezclador batch real y el sistema de producción de leche de soya. El paquete termodinámico de fluidos fue escogido de una de las listas del software. Una corriente de alimentación de 41,67 Kg/h (Soya) fue tomada; las composiciones en fracciones másicas fueron dadas por elemento puesto que las semillas de soya tienen una amplia mezcla de sustancias las cuales no pueden ser descritas como una formula molecular única y sencilla. Los elementos fueron: C, N, H, O, S, Na, K, Mg, Ca, Fe, P, y Cu. El flujo Final de 8,333 Kg/h fue usado para el objetivo de este estudio: El método de análisis elemental para la predicción de un Nuevo posible producto en la composición de la leche de soya (basado solamente en la presencia de amino ácido, y otras macro y múltiples substancias). Las macromoléculas descritas aquí son el inicio para nuevos y específicos componentes de la leche de soya tales como los concluidos en éste estudio. Componente de la familia del ácido fulmínico y el análisis de proteína puede corresponder a nuevas proteínas las cuales no son bien conocidas como la encontrada en los estudios por el hospital de Rhode Island en 2014. La Presencia de Fe y Cu en las semillas de soya fueron atribuidas a los micronutrientes presentes por absorción del suelo del cultivo.

References

Luz Stella Vanegas Pérez, Diego Alonso Restrepo Molina, Jairo Humberto López Vargas, Características de las bebidas con proteína de soya. (2009). Revista Facultad Nacional de Agronomía Medellín Vol. 62, Núm. 2

Benjamin Caballero Paul Finglas Fidel Toldra. Encyclopedia of food science, food technology and nutrition. (2007b). London: Academic Press.

Huisman, M. M. H. (2010). Elucidation of the chemical fine structure of polysaccharides from soybean and maize kernel Cell wall polysaccharides from soybean (Glycine max.) meal. Isolation and characterization. Carbohydrate Polymers, 37, 87– 95.

James, C. S. Determination of fat by the Soxhlet methods. In C. S. James (Ed.). (2010). Analytical chemistry of foods (91–92). London: Blackie Academic & Professional. Kumar, V., Rani, A., Solanki, S., & Hussain, S. M. (2009).

Kumar, V., Rani, A., Solanki, S., & Hussain, S. M. (2009). Influence of growing environment on the biochemical composition and physical characteristics of soybean seed. Journal of Food Composition and Analysis, 19, 188–195.

Liu, K. (2008). Chemistry and nutritional value of soybean components. Edited by Macrae, R., Robinson, R. K., & Sadler, M. J. Maeda, H. (2010). Soluble soybean polysaccharide. In G. O. Phillips & Williams PA (eds) Handbook of hydrocolloids, 2nd edn..)

Neusa SEIBE BJFT. v.12, n.2, p.113-122 (2009) The chemical characteristics and technological functionality of soybean based ingredients [Glycine Max (L.) Merrill]: carbohydrates and proteins

N.G. Stoforos, P.S. Taoukis. 2005. Pages 495-503A.C. Polydera, Food Chemistry, Volume 91, Issue 3. Plant pre-breeding for increased protein content in soybean Glycine max (L.) Merrill Journal: acta_agronomica Vol. 66, Núm. 4 (2017)

Ren, H., Liu, H., Endo, H., Takagi, Y., & Hayashi, T. Antimutagenic and anti-oxidative activities found in Chinese traditional soybean fermented products furu. Food Chemistry, 95, 71–76. (2011).

Rodriguez, R., Jimenez, A., Fernandez-Bolaños, J., Guille´n, R., & Heredia, A. (2011). Dietary fibre from vegetable products as source of functional ingredients. Trends in Food Science &Technology, 17,3–15.

Rostagno, M. A., Palma, M., & Barroso, C. G. (2011). Short-term Stability of soy isoflavones extracts: sample conservation aspects. Food Chemistry, 93, 557–564.

Scheppach, W., Luethrs, H., Melcher, R., Gostner, A., Schauber, J., Kudlich, T., et al. (2010). Anti-inflammatory and ant carcino geniceffects of dietary fiber. Clinical Nutrition Supplements, 1(2), 51–58.

Sosulski, F. W., Elkowicz, L., & Reichert, R. D. (2009). Oligosaccharides in eleven legumes and their air-classified protein and starch fractions. Journal Food Science, 47, 498– 502.

Tomasula, M.F. Kozempel, R.P. Konstance, D. Gregg, S. Boettcher, B. Baxt, L.L. Rodriguez. (2007). Journal of Dairy Science, Volume 90, Issue 7, Pages 3202-3211P.M.

How to Cite

Soymilk plant simulation to predict the formula of a new Hypothetical Product. (2018). Ingeniería E Investigación, 38(1), 46-51. https://doi.org/10.15446/ing.investig.v38n1.63781

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