可见/近红外光谱技术无损检测果实坚实度的研究  

Nondestructive measurement of firmness of pear using visible and near-infrared spectroscopy technique

作　　者：曾一凡[1] 刘春生[1] 孙旭东[1] 陈兴苗[1] 刘燕德[1] 

机构地区：[1]江西农业大学工学院,南昌330045

出　　处：《农业工程学报》2008年第5期250-252,共3页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金项目(60468002)

摘　　要：该研究的目的是建立可见/近红外光谱与梨果实坚实度之间的数学模型,评价可见/近红外光谱技术无损测量梨果实坚实度的应用价值。在可见/近红外光谱区域(350～1800 nm),试验对比分析了不同测量部位、不同光谱预处理方法和不同校正建模算法的梨果实坚实度校正模型。结果表明:赤道部位吸光度一阶微分光谱的偏最小二乘回归所建梨果实坚实度校正模型的预测性能较优,其校正和预测相关系数分别为0.8779和0.8087,校正和预测均方误差分别为1.0804 N和1.4455 N。研究表明:可见/近红外光谱技术无损检测梨果实坚实度是可行的。The objectives of this study are to establish mathematical relationship between visible and near-infrared （Vis/NIR） spectroscopy and firmness of pear, and to evaluate the applicability of VIS/NIR spectroscopy technique for nondestructive measurement of firmness of pear. In the spectral region between 350 and 1800 nm, calibration results for firmness of pear were compared with those at different measurement positions, with different spectral pretreatment methods and different calibration modeling algorithms. The results show that the partial least square regression （PLSR） model, with respect to the first derivative spectra （Dllog （I/R）） at equatorial position, provides better prediction performance for firmness of pear, with correlation coefficient （r） of calibration and prediction, root mean standard error of calibration （RMSEC） and root mean standard error of prediction （RMSEP） of 0.8779, 0.8087, 1.0804 N and 1.4455 N, respectively. The research results show that nondestructive measurement of firmness of pear using VIS/NIR spectroscopy technique is feasible.

关 键 词：可见/近红外光谱技术 无损检测 测量部位 光谱预处理方法 校正建模算法 果实坚实度 梨 

分 类 号：O433.5[机械工程—光学工程]