Fig 1.
Mandarin images at different ripening stages.
Fig 2.
Tomato images at different ripening stages.
Table 1.
Index abbreviations, formulae, and references of selected RGB indices for digital image analysis.
Fig 3.
Contour maps (Correlation matrices) illustrating the R2 for two sets wavelength pairings in the 302–1148 nm range (as a ratio index) with (a) chlorophyll a (Chl a), (b) chlorophyll b (Chl b), (c) total soluble solids (TSS), (d) titratable acidity (TA), (e) TSS/TA, and (f) carotenoids of mandarin fruits at different ripening degrees.
Fig 4.
Contour maps (Correlation matrices) illustrating the R2 for two sets wavelength pairings in the 302–1148 nm range (as a ratio index) with (a) chlorophyll a (Chl a), (b) chlorophyll b (Chl b), (c) total soluble solids (TSS), (d) titratable acidity (TA), (e)TSS/TA, (f) carotenoids (car), (g) lycopene and (h) firmness of tomato fruits at different ripening degrees.
Table 2.
Index abbreviations, formulae, and references of new and published spectral indices used in the present study.
Fig 5.
Flowchart for predicting eight fruit parameters of mandarin and tomato using spectral and RGB indices with decision tree (DT) and random forest (RF) models.
Table 3.
Statistical summary of six biochemical parameters, twelve RGB indices, and twelve spectral reflectance indices for mandarin fruits.
Table 4.
Maximum, minimum and mean values of eight biochemical parameters of tomato fruits, twelve RGB indices derived from digital image analysis and sixteen spectral reflectance indices.
Table 5.
Correlation coefficients among physiological parameters in mandarin fruits: chlorophyll a (Chl a), chlorophyll b (Chl b), total soluble solids (TSS), titratable acidity (TA), TSS/TA ratio, and carotenoids (Car).
Table 6.
Correlation coefficients between eight parameters, chlorophyll a (Chl a), chlorophyll b (Chl b), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (Car), lycopene, and firmness of tomato fruits.
Table 7.
Coefficient of determination values of linear regression models of six mandarin fruit parameters including chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (car) with twelve RGB indices.
Table 8.
Coefficient of determination values of linear regression models of eight tomato fruit attributes, chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (car), lycopene and firmness with twelve RGB indices.
Table 9.
Coefficient of determination values of linear regression models of six mandarin attributes, chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (car) with twelve spectral reflectance indices.
Table 10.
Coefficient of determination values of linear regression models of eight tomato attributes, chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (car), lycopene and firmness with spectral reflectance indices.
Table 11.
Results of Random Forest (RF) and Decision Tree (DT) models incorporate distinct features retrieved spectral reflectance indices (SRIs) and RGB indices (RGBI) to predict chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, and carotenoids (car) of mandarin fruits.
Table 12.
Shows the results of Random Forest (RF) and Decision Tree (DT) models incorporate distinct features retrieved spectral reflectance indices (SRIs) and RGB indices (RGBI) to predict chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), TSS/TA, carotenoids (car), lycopene and firmness of tomato fruits.
Table 13.
Displays the results from the Random Forest (RF) and Decision Tree (DT) models, using the superior hybrid features of both spectral reflectance indices (SRIs) and RGB indices (RGBIs) together to predict various characteristics of mandarin fruits.
These characteristics include chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), the TSS/TA ratio, and carotenoids (car).
Table 14.
Presents the results of the Random Forest (RF) and Decision Tree (DT) models, which utilize advanced hybrid features from both spectral reflectance indices (SRIs) and RGB indices (RGBIs) together to predict various properties of tomato fruits.
These properties include chlorophyll b (Chl b), chlorophyll a (Chl a), total soluble solids (TSS), titratable acidity (TA), the TSS/TA ratio, carotenoids (Car), lycopene, and firmness.