农业机械学报2018，Vol.49Issue(2)：339-344,357,7.DOI:10.6041/j.issn.1000-1298.2018.02.044
马铃薯干物质空间分布状态可视化研究
Visualization Spatial Assessment of Potato Dry Matter
摘要
Abstract
In order to visualize the spatial distribution of potato dry matter,the internal dry matter content of potato was studied by using visible/near-infrared hyperspectral imaging (HSI) and a detection model of dry matter of potato was established.The reflectance spectra of sliced potatoes which were extracted from the regions of interest of HIS were performed with different pretreatments.The standard normal variable (SNV) combined with Savitzky-Golay smoothing (SG) and the first derivative (SNV-SG-FD) was the optimal pretreatment.Based on optimal pretreatment,competitive adaptive reweighted sampling (CARS) combined with successive projections algorithm (SPA) was used to select variables of the spectrum and obtained 22 variables.Three regression models based on principal component regression (PCR),support vector regression (SVMR) and partial least squares regression (PLSR) were established.The best performance was achieved by PLSR model,its determination coefficient (R2p),root mean square error for prediction and relative percent difference were 0.849,0.878％ and 2.312,respectively.The PLSR model based on 22 variables was superior to the full-spectrum model.An imaging processing algorithm was developed to transfer each pixel in potato dry matter content with the SNV-SG-FD-CARS-SPA-PLSR model.The imaging showed the distribution of dry matter within the potatoes.It showed that the potato dry matter was mainly distributed between the inner pith and vascular bundle and the inner pith had the lowest dry matter content.It was gradually increased from the inner pulp to the outer.Dry matter content was 12.16％ in inner pith and the outer layer reached up to 24.62％.The results show that the visible near infrared hyperspectral imaging is a useful tool for rapidly and effectively visualizing detecting spatial distribution of potato dry matter.关键词
马铃薯/干物质/空间分布/可视化/高光谱Key words
potato/dry matter/spatial distribution/visualization/hyperspectra分类
数理科学引用本文复制引用
许英超,王相友,印祥,胡周勋,岳仁才..马铃薯干物质空间分布状态可视化研究[J].农业机械学报,2018,49(2):339-344,357,7.基金项目
国家重点研发计划项目(2016YFD0701603-02)和山东省农机装备研发创新计划项目(2017YF056) （2016YFD0701603-02）
