Techno-Economic Analysis and Neuro-Fuzzy Production Rate Prediction of Sorghum (Sorghum bicolor) Leaf Shealth Colourant Extract Production

• Published in: Agricultural research (India : Online) Vol. 11; no. 3; pp. 579 - 589
• Main Authors: Oke, E. O., Adeyi, O., Nnaji, P. C., Okolo, B. I., Abam, F. I., Ude, C. J., Ayanyemi, J.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.09.2022; Springer Nature B.V
• Subjects: Artificial neural networks; Biodiversity; Biomedical and Life Sciences; Cell Biology; Coloring agents; Correlation coefficient; Correlation coefficients; Economic analysis; Economic forecasting; Energy balance; Full-Length Research Article; Fuzzy logic; Leaves; Life Sciences; Plant Biochemistry; Plant Ecology; Plant Genetics and Genomics; Plant Sciences; Production costs; Return on investment; Sensitivity analysis; Simulation; Sorghum; Sorghum bicolor; United States > US; Payback time; Biomass; Fixed Capital Investment (FCI); Biocolourant
• ISSN: 2249-720X; 2249-7218
• DOI: 10.1007/s40003-021-00596-2

In this work, process simulation, techno-economic study and Neuro-Fuzzy (NF) production rate prediction of colourant extract production from Sorghum ( Sorghum bicolor ) Leaf Shealth (SBLS) were studied. The Base Case Simulation (BCS) material and energy balance, economic and sensitivity analyses were carried out in Aspen Batch Process Developer (ABPD) V10® simulator. NF codes for the production rate forecasting were written and executed in MATLAB 9.2 software. For BCS, the plant was designed to process 683,000 kg of SBLS with 1,966 batches/annum at production rate of 1.81 kg/minute for 30 years lifetime. The BCS gave annual total capital investment US$ 1,279,078 and annual production cost US$ 18,391,821; while annual net profits US$ 658,960, Return on Investment (ROI) US$ 51% and Payback Time (PT) 1.94 years with US$ 19,124,000/yr as minimum selling price of the biocolourant. The sensitivity analysis revealed that increase in plant capacity and sales price increased ROI and decrease in PT to less than 365 days. NF results gave correlation coefficient 0.998 and root mean square error 0.000075 with linear output and triangular input membership function. The techno-economic analysis revealed that biocolourant production from the biomass is economically feasible and NF is capable of predicting the production rate