This paper studied the feasibility of using rapid and non-invasive method to measure Fuji apple firmness by FT-NIR spectra techniques. Techniques of spectral analysis and pre-processing including multiplicative scatter correction (MSC), standard normal variate (SNV) and first deviate (FD) were used. The result shows that the MSC technique can effectively remove the base shift and deviation and remove the signal to noise ratio of absorbance spectrum greatly. The best statistical model was developed using partial least square (PLS) with respect to multiplicative scatter correction (MSC) in wavelength range of 1408~2355nm. The correlation coefficient (R2) of the model was 0.9852, the root mean square error of cross validation (RMSECV) was 0.0398kg/cm2 and the root mean square error of prediction (RMSEP) was 0.0166kg/cm2. Then the model was optimized by weeding out outliers. Using the model to validate 25 samples, the results show that R2 is 0.9908 and RMSEP is 0.0147kg/cm2. It is concluded that the model is reliable and the predicted result is effective. The method can meet the requirement of quick measuring of apple’s firmness.
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李桂峰,赵国建,刘兴华,肖春玲.苹果硬度的傅里叶变换近红外光谱无损检测[J].农业机械学报,2009,40(1):120-123.[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(1):120-123.