Short-wavelength near-infrared (SW-NIR) (700–1100 nm) spectra of aqueous solutions of sucrose, d-glucose, and d-fructose were monitored with respect to change in temperature and sugar concentration. Sugar OH and CH related vibrations were identified by analysis of the spectra of sugar solutions in deuterium oxide (D ₂ O), and of sucrose- d ₈ solutions in D ₂ O. Absorption spectra were explained in terms of the second and third overtones of OH stretching vibrations and the third overtone of CH ₂ and CH stretchings. In deuterated solutions, CH and CH ₂ higher overtone vibration bands became apparent. The major spectral effect of decreased temperature or increased sugar concentration was a decrease in absorbance at 960 nm and an increase in absorbance at 984 nm, interpreted as an increase in the degree of H bonding. Partial least-squares (PLS) calibrations on sugar concentrations (with spectra collected at several sample temperatures) relied strongly on the 910 nm sugar CH related bands, whereas calibrations on temperature depended equally on all OH associated vibrations (750, 840, 960, and 985 nm).

In-field mango fruit sizing is useful for estimation of fruit maturation and size distribution, informing the decision to harvest, harvest resourcing (e.g., tray insert sizes), and marketing. In-field machine vision imaging has been used for fruit count, but assessment of fruit size from images also requires estimation of camera-to-fruit distance. Low cost examples of three technologies for assessment of camera to fruit distance were assessed: a RGB-D (depth) camera, a stereo vision camera and a Time of Flight (ToF) laser rangefinder. The RGB-D camera was recommended on cost and performance, although it functioned poorly in direct sunlight. The RGB-D camera was calibrated, and depth information matched to the RGB image. To detect fruit, a cascade detection with histogram of oriented gradients (HOG) feature was used, then Otsu’s method, followed by color thresholding was applied in the CIE L*a*b* color space to remove background objects (leaves, branches etc.). A one-dimensional (1D) filter was developed to remove the fruit pedicles, and an ellipse fitting method employed to identify well-separated fruit. Finally, fruit lineal dimensions were calculated using the RGB-D depth information, fruit image size and the thin lens formula. A Root Mean Square Error (RMSE) = 4.9 and 4.3 mm was achieved for estimated fruit length and width, respectively, relative to manual measurement, for which repeated human measures were characterized by a standard deviation of 1.2 mm. In conclusion, the RGB-D method for rapid in-field mango fruit size estimation is practical in terms of cost and ease of use, but cannot be used in direct intense sunshine. We believe this work represents the first practical implementation of machine vision fruit sizing in field, with practicality gauged in terms of cost and simplicity of operation.