Application of Multivariate Statistical Techniques in Bioprocess Optimization and Production Yield Improvement

Journal Of Biochemical Technology 2026 Open access

Read full text
Authors: Bernabé Canqui Flores, Percy Huata Panca, Juan Reinaldo Paredes Quispe, Charles Mendoza Mollocondo, Godofredo Quispe Mamani, Juan Carlos Juarez Vargas, Fred Torres-Cruz
DOI: 10.51847/q27bv1w51d
Cited by: 1
References: 59

Abstract

Bioprocess optimization depends on understanding many interacting variables that rarely change independently. Temperature, pH, dissolved oxygen, aeration, agitation, substrate feed, and base addition often move together across a batch, creating strongly correlated process trajectories rather than simple one-factor effects. Multivariate techniques such as principal component analysis and partial least squares regression are therefore natural tools for reducing dimensionality, monitoring deviation

Fields of Study & Subjects

Viral Infectious Diseases and Gene Expression in Insects Fault Detection and Control Systems Spectroscopy and Chemometric Analyses

Publication details

Journal / source
Journal Of Biochemical Technology
Publisher
Polaris
Volume
17
Issue
2
Pages
19–29
Publication date
1 January 2026