In this paper, apple crispness was evaluated by sensory evaluation and compared with non-destructive measurements of portable acoustic signal to discuss the feasibility of non-destructive evaluation for apple crispness based on portable acoustic signal. Acoustic eigenvalues from the acoustic signal were processed by time domain and Hilbert-Huang transform (HHT), followed by analysing the correlations with apple crispness that had been evaluated via sensory evaluation. Multiple linear regression (MLR) and artificial neural network (ANN) were applied to predict apple crispness. The results proved that crispness correlates significantly (P < 0.01) with four acoustic eigenvalues, including waveform index, sound intensity, energy of low frequency and energy of high frequency. The average relative error of apple crispness predicted by ANN was 1.42 AE 1.9%, remarkably lower (P < 0.01) that of MLR (6.79 AE 5.64%), implying that the model predicted by ANN is more accurate than that of MLR.
To discuss the feasibility of non-destructive determination method for carrot quality based on the acoustic signal, Pearson correlations between the acoustic eigenvalues and the main compositions of carrot were performed. It indicated that the water content, polysaccharide content and pectin content of carrot were all significantly (P<0.01) correlated with waveform index and sound intensity of acoustic eigenvalues in the timedomain and TE in the range of 2-3, 3-4, 4-5, 5-6, 6-7, 7-8 and 8-9 kHz. Through PCA analysis, 9 eigenvalues with good correlation can be reduced into two principal component factors. The acoustic signals knocked by the self-made signal collection platform could be a new nondestructive testing technology for quality evaluation of carrots. These results will provide essential information to determine the food attributes of agro-products through acoustic signals.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.