CAJ | 학술논문

目的：通过近红外漫反射光谱技术建立了柿子不同品种和贮藏期的快速判别方法。方法实验对贮藏冷库(0±0.5℃)20 d、40 d、60 d的磨盘柿和阳丰甜柿的近红外光谱(400~2500 nm)进行平滑、一阶倒数和标准正常化处理(SNV)处理，采用主成分分析法(PCA)建立判别模型。结果在全波长范围内，不同品种定标模型的正确分类率达到100%；阳丰甜柿不同贮藏期的正确分类率达到97.78%；磨盘柿不同贮藏期的正确分类率达到98.89%。3个预测模型的累积准确率达到96.67%。结论通过近红外漫反射光谱技术，判别不同品种的柿子并预测其贮藏期具有应用价值。
목적：통과근홍외만반사광보기술건립료시자불동품충화저장기적쾌속판별방법。방법실험대저장랭고(0±0.5℃)20 d、40 d、60 d적마반시화양봉첨시적근홍외광보(400~2500 nm)진행평활、일계도수화표준정상화처리(SNV)처리，채용주성분분석법(PCA)건립판별모형。결과재전파장범위내，불동품충정표모형적정학분류솔체도100%；양봉첨시불동저장기적정학분류솔체도97.78%；마반시불동저장기적정학분류솔체도98.89%。3개예측모형적루적준학솔체도96.67%。결론통과근홍외만반사광보기술，판별불동품충적시자병예측기저장기구유응용개치。
Objective A rapid method was developed for identification of different varieties and storage time of persimmon by near infrared diffuse reflectance spectroscopy(NIRS). Methods ‘Mopan’ permissions and‘Yangfeng’ sweet persimmons were collected and refrigerated at 0±0.5℃for 20 d、40 d and 60 d storage, and their spectra were acquired respectively by NIRS. After smooth processing, first derivative and standard normal variate (SNV), principal component analysis(PCA) was used to establish identification models. Results The calibration model for different varieties of persimmon, the correct classification rate was 100%. The cali-bration model for different storage time of ‘Yangfeng’ sweet persimmon, the correct classification rate was 97.78%. The calibration model for different storage time of mopan persimmon, the correct classification rate was 98.89%. Three prediction models cumulative accuracy rate was 96.67%. Conclusion The qualitative identification of different kinds of persimmon and their storage time by near infrared diffuse reflectance spec-troscopy has application value.