Nukasani Sagarika
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Nukasani Sagarika has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Anil Kumar
Department of Food Science and Technology, College of Agriculture, G.B. Pant University of Agriculture and Technology, Pantnager 263145, India
1 shared publication - Anjineyulu Kothakota
Agro and Food Processing Technology Division CSIR‐National Institute for Interdisciplinary Science and Technology (CSIR‐NIIST) Thiruvananthapuram India
1 shared publication - Anupama Singh
Department of Food Engineering, National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonipat, India
1 shared publication - Chintada H. Sai Srinivas
Foods Business Division, ITC Limited, Visakhapatnam 530001, Andhra Pradesh, India
1 shared publication - Jai Prakash Pandey
Department of Post-Harvest Process and Food Engineering, College of Technology, G.B. Pant University of Agriculture and Technology, Pantnagar 263145, Uttarakhand, India
1 shared publication - Kaliramesh Siliveru
Department of Grain Science and Industry, Kansas State University, Manhattan, KS 66506, USA
1 shared publication
Latest Publications
- Open Access
Modeling and Optimization of Process Parameters for Nutritional Enhancement in Enzymatic Milled Rice by Multiple Linear Regression (MLR) and Artificial Neural Network (ANN)
This study involves information about the concentrations of nutrients (proteins, phenolic compounds, free amino acids, minerals (Ca, P, and Iron), hardness) in milled rice processed with enzymes; xylanase and cellulase produced by Aspergillus awamori, MTCC 9166 and Trichoderma reese, MTCC164. Brown rice was processed with 60–100% enzyme (40 mL buffer -undiluted) for 30 to 150 min at 30 °C to 50 °C followed by polishing for 20–100 s at a safe moisture level. Multiple linear regression (MLR) and artificial neural network (ANN) models were used for process optimization of enzymes. The MLR correlation coefficient (R2) varied between 0.87–0.90, and the sum of square (SSE) was placed within 0.008–8.25. While the ANN R2 (correlation coefficient) varied between 0.97 and 0.9999(1), MSE changed from 0.005 to 6.13 representing that the ANN method has better execution across MLR. The optimized cellulase process parameters (87.2% concentration, 80.1 min process time, 33.95 °C temperature and 21.8 s milling time) and xylanase process parameters (85.7% enzyme crude, 77.1 min process time, 35 °C temperature and 20 s) facilitated the increase of Ca (70%), P (64%), Iron (17%), free amino acids (34%), phenolic compounds (78%) and protein (84%) and decreased hardness (20%) in milled rice. Scanning electron micrographs showed an increased rupture attributing to enzymes action on milled rice.
Open AccessModeling and Optimization of Process Parameters for Nutritional Enhancement in Enzymatic Milled Rice by Multiple Linear Regression (MLR) and Artificial Neural Network (ANN)
This study involves information about the concentrations of nutrients (proteins, phenolic compounds, free amino acids, minerals (Ca, P, and Iron), hardness) in milled rice processed with enzymes; xylanase and cellulase produced by Aspergillus awamori, MTCC 9166 and Trichoderma reese, MTCC164. Brown rice was processed with 60–100% enzyme (40 mL buffer -undiluted) for 30 to 150 min at 30 °C to 50 °C followed by polishing for 20–100 s at a safe moisture level. Multiple linear regression (MLR) and artificial neural network (ANN) models were used for process optimization of enzymes. The MLR correlation coefficient (R2) varied between 0.87–0.90, and the sum of square (SSE) was placed within 0.008–8.25. While the ANN R2 (correlation coefficient) varied between 0.97 and 0.9999(1), MSE changed from 0.005 to 6.13 representing that the ANN method has better execution across MLR. The optimized cellulase process parameters (87.2% concentration, 80.1 min process time, 33.95 °C temperature and 21.8 s milling time) and xylanase process parameters (85.7% enzyme crude, 77.1 min process time, 35 °C temperature and 20 s) facilitated the increase of Ca (70%), P (64%), Iron (17%), free amino acids (34%), phenolic compounds (78%) and protein (84%) and decreased hardness (20%) in milled rice. Scanning electron micrographs showed an increased rupture attributing to enzymes action on milled rice.