Nondestructive Determination of Apple Internal Qualities Using Near-Infrared Hyperspectral Reflectance Imaging
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Nondestructive Determination of Apple Internal Qualities Using Near-Infrared Hyperspectral Reflectance Imaging Jinlei Dong 1 & Wenchuan Guo 1
Received: 2 January 2015 / Accepted: 30 March 2015 # Springer Science+Business Media New York 2015
Abstract Hyperspectral reflectance imaging technology in near-infrared regions (900–1,700 nm) was used to evaluate soluble solids content (SSC), firmness, moisture content (MC), and pH values of ‘Fuji’ apples during a 13-week storage period. Totally, 167 apples were divided into calibration set (125) and prediction set (42) based on the joint x-y distance sample set partitioning method. Mean spectrum of the regions of interest in the hyperspectral image of each apple was used for analysis. Two typical variable selection methods, i.e., successive projection algorithm (SPA) and uninformative variable elimination (UVE), were applied to extract the characteristic variables from full spectra (FS). The partial least squares (PLS) regression, least squares support vector machine (LSSVM), and backpropagation (BP) network modeling methods were used to establish models to predict SSC, firmness, MC, and pH of apples, respectively. The results showed that the SSC and MC could be predicted exactly by all developed models, and SPA-LSSVM and FS-BP could be used to predict pH value roughly. All models failed to predict firmness. The SPA-LSSVM model had better comprehensive ability in determining SSC, MC, and pH than others, with the correlation coefficient of prediction of 0.961, 0.984, and 0.882 and residual predictive deviation of 3.49, 5.51, and 2.06, respectively. The results demonstrated the feasibility of using near-infrared hyperspectral reflectance imaging technology as a non-invasive method for predicting SSC, MC, and pH of apples simultaneously.
* Wenchuan Guo [email protected] 1
College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
Keywords Apple . Hyperspectral imaging . Soluble solids content . Firmness . Moisture content . pH value
Introduction Apple is one of the most popular and the most important cash fruits in the world. It originated in Central Asia and Europe (Harris et al. 2002). Now, China is the largest cultivation country of apples, and it exported about 976 thousand tons of apples to the rest of the world in 2012 (National Bureau of Statistic of People’s Republic of China 2013). Sorting is an important process during fruit postharvest processing. At present, apples are usually sorted manually or automatically on the basis of size, shape, color, gloss, and surface defects and decay. However, some internal quality attributes, such as soluble solids content (SSC), firmness, moisture content (MC), and acidity (usually expressed as pH value), which directly contribute to the apples’ unique taste, are essential to meet different tastes of customers (Maniwara et al. 2014). Standard methods for these quality measurements are mostly destructive, inefficient, or time consuming. Developing nondestructive and efficient
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