Crispness is a vitally significant factor to evaluate apple texture quality. This study explores quantitative prediction and kinetic models to determine the optimal preservation time of apple crispness during shelf life based on spectroscopy. The nonlinear iterative partial least squares algorithm was used to establish a quantitative prediction model based on the wavelength of 450–1000 nm. Kinetic models were developed to determine the preservation time of apple crispness at room and refrigeration temperatures. The results indicate that the determination coefficients of calibration and prediction sets were 0.8939 and 0.9206 respectively, and the root mean square errors of calibration and prediction sets were 0.1254 and 0.1669 kg, respectively. The determination coefficients of the kinetic models at room and refrigeration temperatures were 0.965 and 0.87, respectively. Consequently, the preservation time of the optimal freshness of Fuji apple crispness was five weeks at room temperature and eight weeks at refrigeration temperature.
Practical applications
This study provides a method for nondestructively and accurately detecting apple crispness via spectroscopy. This study also provides optimal freshness taste of apple crispness and how long apple crispness could retain under the conditions of room and refrigeration temperature during shelf life for customers and academics. The corporate could extend the preservation time according to this study to improve the profile.
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.