English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Quantification of sugars is considered to be a key factor in the assessment of honey quality. Standard chromatographic methods for sugar quantification in honey may be unsuitable for routine analysis due to the associated time, cost, and complexity. Herein, a comparison between non-genetic and genetic algorithm–partial least squares (GA-PLS) chemometric and infrared spectroscopic approaches is reported for the direct quantification of glucose, fructose, and sucrose in Philippine honeys. A full factorial set (n = 61) was designed to predict Box-Behnken test set (n = 16) sugar concentrations. First derivative (FD) signal processing followed by PLS of the 1500–800 cm −1  spectral region harboring the analytes provided optimum results with  R2average  = 0.943 in the training set and a mean root mean square error of prediction (RMSEP average ) of 0.049 across fructose, glucose, and sucrose. Applying GA-PLS after FD processing across the spectral region from 3700 to 700 cm −1  did not further improve the results (R 2average  = 0.926, RMSEP average  = 0.077). FD followed by PLS (1500–800 cm −1 ) provided minimal differences between the actual and predicted sugar content in training and testing values, implying that the probe produced developmental avenues to directly quantify these sugars. When applied to real samples (n = 26), the method potentially differentiated real honey from non-honey and adulterated samples.

Comparison of Genetic and Non-genetic Algorithm Partial Least Squares for Sugar Quantification in Philippine Honeys