Back close

Predictive modeling of allowable storage time of finger millet grains using artificial neural network and support vector regression approaches

Publication Type : Journal Article

Publisher : Elsevier BV

Source : Journal of Food Engineering

Url : https://doi.org/10.1016/j.jfoodeng.2024.112224

Keywords : Finger millet, Safe storage time, Levenberg–marquardt, Bayesian regularization, Scaled conjugated gradient, Support vector regression

Campus : Coimbatore

School : School of Physical Sciences

Department : Food Science and Nutrition

Year : 2024

Abstract : The study aimed to establish safe storage guidelines for long-term preservation of finger millet grains and to develop a model for predicting the allowable storage time. The experiment was conducted at various temperature (15, 25, 35 and 45 °C) and moisture contents (8, 11, 14, 17 and 20% wb). Changes in response variables such as germination, free fatty acid and mold growth were systematically monitored. Finger millet with a moisture content above 14% should be dried to safe moisture levels within 3–5 weeks at 30 °C or within 5–10 weeks at 15 °C to preserve grain quality. To maintain high quality and seed viability of finger millet, moisture content and storage temperature should be below 12% and 20 °C, respectively for up to 34 weeks. The study also assessed the use of artificial neural network and support vector regression models in predicting the safe storage period for finger millet grains.

Cite this Research Publication : Jayasree Joshi T, P. Srinivasa Rao, Predictive modeling of allowable storage time of finger millet grains using artificial neural network and support vector regression approaches, Journal of Food Engineering, Elsevier BV, 2024, https://doi.org/10.1016/j.jfoodeng.2024.112224

Admissions Apply Now