Abstract
BackgroundMangoes are fruits of nutritional importance in Kenya. The fruits vary in their sugars depending on cultivar type and ripening stage. Current methods of sugar content analysis are based on HPLC methods, which are accurate but expensive and time-consuming. We evaluated the potential of diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy as a rapid tool for quantitative prediction of fructose and glucose sugars in the pulp of Kenyan mangoes.MethodsPrincipal component analysis and partial least regression models were developed using the first derivative DRIFT spectra (400–4000 cm−1) to predict fructose and glucose sugars. A factorial analysis of variance compared effects of site (three locations), cultivar type (four cultivars), fruit position (inside/outside), and their interactions on fructose and glucose contents.ResultsThe principal component analysis scores plot using components 1 and 2 explained 75 and 8% of the variance, respectively, with no clear grouping either by sites or cultivars. The PLS range for glucose was R2 = 0.80, SECV = 0.55, and RPD = 11.52 and fructose R2 = 0.70, SECV = 0.28, and RPD = 11.52. Site (F (2, 265) = 18.12, p < 0.05, η2 = 0.02), cultivar type (F (3, 256) = 4.44, p < 0.05, η2 = 0.05), and fruit position (F (1, 259) = 7.62, p < 0.05, η2 = 0.03) had a significant effect on glucose content and not on fructose content. However, interactions between these three factors were not significant, p > 0.05. In general, fruits outside the canopy had higher fructose and glucose contents than those within the canopy.ConclusionsDRIFTS coupled with chemometric techniques showed potential for prediction of fructose and glucose contents of mango fruits.
Highlights
Mangoes are fruits of nutritional importance in Kenya
We evaluated the potential of diffuse reflectance infrared Fourier transform (DRIFT)-FTIR spectroscopy technique to predict fructose, glucose, sucrose, and maltose in two local (Apple and Ngowe) and two Floridian (Kent and Tommy Atkins) mango cultivars
Five (5) trees of Kent, Ngowe, Apple, and Tommy Atkins cultivars were randomly selected per Kenya Agricultural Research Institute (KARI) orchard and ten (10) mango fruits sampled per tree
Summary
DRIFTS spectral measurements were recorded on all the samples Out of this total, only 30% (N = 144) were subjected to wet analyses by HPLC and used to build a calibration model to predict the concentration of the remaining samples. 2 g of freeze-dried mango pulp was carefully weighed (± 0.0001 g) It was transferred into a 100 ml volumetric flask and homogenized with 40 ml distilled water and 25 ml HPLC grade acetonitrile. A factorial ANOVA was performed on predicted fructose and glucose concentrations to examine the effect of fruit position, cultivar type, and location of mango fruit sugars For both analyses, when a significant difference (p < 0.05) was detected in some variable, Tukey’s mean test was applied to evaluate the difference between the samples. Hierarchical component analysis (HCA) (minimum variance method; squared Euclidean distances) was carried out on the auto-scaled dataset of cultivars, in order to understand the variation within each cultivar
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