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Statistical Analysis for LowField Nuclear Magnetic Resonance Batch Data of Sweet Corn
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SHAO Xiaolonga,b,ZHU Jiangweib,LI Yunfeib
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(a. Institute of Refrigeration and Cryogenic Engineering; b. School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 200240, China )
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Abstract To obtain the effect and quantitative information of water components in sweet corn by different blanching temperature, Statistical analysis system (SAS) was applied to deal with lowfield nuclear magnetic resonance (LFNMR) data of blanched sweet corn. Statistic analysis on batch raw data of LFNMR was performed by SAS system, including exponential fitting, principal component analysis (PCA) and partial least squares regression (PLSR). The corresponding SAS codes were provided. The fitting result of multiexponential model indicates that the percentages of two components with relaxation times (405-750 ms) and (50-70 ms) change distinctly. Three blanching temperature ranges: 20-40, 50-70 and 80-100 °C are roughly discriminated by PCA. PLSR does well in prediction of bound water in blanched sweet corn (determined coefficient is 0.974, root mean square error of crossvalidation is 0.32%). From the whole data processing, SAS programming performs efficiently on data management and analysis and gives valuable reference for LNNMR application.
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Received: 07 January 2010
Published: 27 January 2011
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