Effect of CPPU on optical properties of strawberry in near-infrared range during growth.

To investigate the effect of CPPU (forchlorfenuron) on optical properties of strawberry during growth, the optical properties (absorption coefficient (µa) and reduced scattering coefficient (µs')) of strawberry treated with CPPU solutions at different concentrations (0, 2.5, 5.0 and 7.5 mg/L) were measured in white, color turning and red stages by using a single integrating sphere system over near-infrared wavelength range of 900-1700 nm. The physicochemical properties, i.e., single fruit weight, soluble solids content, firmness and moisture content, as well as microstructure of strawberry were also investigated. The results showed that in white stage, the µa of strawberry treated with 7.5 mg/L CPPU was significantly (p ≤ 0.05) lower than that of untreated strawberry at absorption peak of 1411 nm. In color turning stage, the µs' of strawberry treated with 5 mg/L CPPU was significantly lower than that of treated with 2.5 mg/L at absorption peaks of 975, 1197 and 1411 nm. In red stage, the µa of strawberry treated with 2.5 mg/L CPPU was significantly (p ≤ 0.05) different from that of treated with 7.5 mg/L at 1197 nm. The study indicates that the optical properties of strawberry were affected by CPPU, and it provides useful information for identifying CPPU treated strawberry.

Non-destructive sugar content assessment of multiple cultivars of melons by dielectric properties.

BACKGROUND: Non-destructive determination of the internal quality of fruit with a thick rind and of a large size is always difficult and challenging. To investigate the feasibility of the dielectric spectroscopy technique with respect to determining the sugar content of melons during the postharvest stage, three cultivars of melon samples (160 melons for each cultivar) were used to acquire dielectric spectra over the frequency range 20-4500 MHz. The three cultivars of melons were divided separately into a calibration set and a prediction set in a ratio of 3:1 by a joint x-y distance algorithm. Partial least squares (PLS) and extreme learning machine (ELM) methods were applied to develop individual-cultivar and multi-cultivar models based on full frequencies (FFs) and effective dielectric frequencies (EDFs) selected by the successive projection algorithm (SPA). RESULTS: The results showed that ELM models demonstrated a better performance than PLS models for the same input dielectric variables. Most of the models built based on the EDFs selected by SPA had a slightly worse performance compared to those based on FFs. For both PLS and ELM methods, the models for multi-cultivars demonstrated a worse calibration and prediction performance compared to those for individual cultivars. When individual-cultivar and multi-cultivar samples were used to build sugar content determination models, the best model was FFs-ELM (Rp  = 0.887, RMSEP = 0.986), FFs-ELM (Rp  = 0.870, RMSEP = 1.028), FFs-PLS (Rp  = 0.882, RMSEP = 1.010) and FFs-ELM (Rp  = 0.849, RMSEP = 1.085) for 'Hongyanliang', 'Xinzaomi', 'Manao' and multi-cultivar melons, respectively. CONCLUSION: The present study indicates that it is possible to develop both individual-cultivar and multi-cultivar models for determining the sugar content of melons based on the dielectric spectroscopy technique. © 2021 Society of Chemical Industry.