|
|
|
|
|
|
| The Discrimination of Blackheart Pears Research Based on Visible/Near-Infrared Diffuse Transmission Spectrum On-Line Detector |
| LIU Yan-de, LI Yi-fan, GONG Zhi-yuan, SUN Xu-dong |
| School of Mechanical Engineering, East China Jiaotong University, Nanchang 330013, China |
|
|
|
|
Abstract Pears which suffer from the main physiological disease as blackheart directly affected the export of pears, so fast and accurate identification of blackheart pears for pear export is of practical significance. Vis/NIR spectroscopy combining new online technique was proposed to identify exterior and interior properties of objects in the present study. The purpose of this paper is to have a research on the feasibility of using visible/near-infrared diffuse transmission spectrum on-line detector to detect blackheart pears. 80 normal pears and 70 pears in disease are taked as modeling set. All samples were divided into the calibration set and prediction set for developing optimal results and assessing their performance. The visible/near-infrared diffuse transmission spectrum was collected under the speed of 5 pears per minute. Energy spectrum processed by the standard orthogonal transformation (SNV) and multiple scatter correction (MSC) respectively established the model of blackheart pears by partial least-squares discriminant model(DPLS) , peak area discriminant model (DPA) and PCA discriminant model(DPCA). 30 normal pears and 20 blackheart pears were taken as prediction set was used to evaluate the ability to predict. By comparison, the model of DPLS has the highest accuracy. All the blackheart pears were recognised correctly. The experiment shows that visible/near-infrared diffuse transmission spectrum with DPLS discriminant method realized the on-line detection of blackheart pears which provided technical support and reference for export trade of ‘Yali’ pear products. In comparison to destruction and time-consuming chemical methods, the results in the feasibility study may provide technical support and scientific reference in testing blackheart pears.
|
|
Received: 2015-06-17
Accepted: 2015-12-29
|
|
|
|
[1] WANG Wen-hui, LI Zhen-ru, WANG Zhi-hua, et al(王文辉，李振茹，王志华，等). China Fruit(中国果树), 2005，9: 13.
[2] LIN Lin, JIANG Wei-bo, CAO Jian-kang, et al(林 琳，姜微波，曹健康，等). Farm Products Processin(农产品加工), 2006，8: 4.
[3] HAN Dong-hai, LIU Xin-xin, LU Chao, et al(韩东海，刘新鑫，鲁 超，等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报)，2006, 37(6): 86.
[4] LIU Xin-xin, HAN Dong-hai, TU Run-lin, et al(刘新鑫，韩东海，涂润林，等). Transactions of the Chinese Society of Agriculture Engineering(农业工程学报), 2004, 20(1): 211.
[5] HAN Dong-hai, TU Run-lin, LIU Xin-xin, et al(韩东海，涂润林，刘新鑫，等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2005, 36(3): 71.
[6] YING Yi-bin, RAO Xiu-qin, MA Jun-fu(应义斌，饶秀勤，马俊福). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2004, 20(2): 144.
[7] FU Xia-ping(傅霞萍). Zhejiang University(浙江大学)，2008, 4.
[8] Mouazen A M，Karoui R, De Baredemaeker J, et al. Written for Presentation at the 2006 ASABE Annual International Meeting Sponsored by ASABE, Oregon Convention Center, Portland, Oregon, 2006.
[9] HAO Yong, SUN Xu-dong, GAO Rong-jie, et al(郝 勇，孙旭东，高荣杰，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2010, 26(12): 373. |
| [1] |
YANG Wen-feng1, LIN De-hui1, CAO Yu2, QIAN Zi-ran1, LI Shao-long1, ZHU De-hua2, LI Guo1, ZHANG Sai1. Study on LIBS Online Monitoring of Aircraft Skin Laser Layered Paint Removal Based on PCA-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3891-3898. |
| [2] |
ZHU Hua-dong1, 2, 3, ZHANG Si-qi1, 2, 3, TANG Chun-jie1, 2, 3. Research and Application of On-Line Analysis of CO2 and H2S in Natural Gas Feed Gas by Laser Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3551-3558. |
| [3] |
HUANG Hua1, LIU Ya2, KUERBANGULI·Dulikun1, ZENG Fan-lin1, MAYIRAN·Maimaiti1, AWAGULI·Maimaiti1, MAIDINUERHAN·Aizezi1, GUO Jun-xian3*. Ensemble Learning Model Incorporating Fractional Differential and
PIMP-RF Algorithm to Predict Soluble Solids Content of Apples
During Maturing Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3059-3066. |
| [4] |
HUANG Chao1, 2, ZHAO Yu-hong1, ZHANG Hong-ming2*, LÜ Bo2, 3, YIN Xiang-hui1, SHEN Yong-cai4, 5, FU Jia2, LI Jian-kang2, 6. Development and Test of On-Line Spectroscopic System Based on Thermostatic Control Using STM32 Single-Chip Microcomputer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2734-2739. |
| [5] |
CAI Jian-rong1, 2, HUANG Chu-jun1, MA Li-xin1, ZHAI Li-xiang1, GUO Zhi-ming1, 3*. Hand-Held Visible/Near Infrared Nondestructive Detection System for Soluble Solid Content in Mandarin by 1D-CNN Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2792-2798. |
| [6] |
LI Wen-xia1, DU Yu-jun2, WANG Yue1, LIU Zheng-dong3*, ZHENG Jia-hui1, DU Wen-qian1, WANG Hua-ping4. Research on On-Line Efficient Near-Infrared Spectral Recognition and Automatic Sorting Technology of Waste Textiles Based on Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2139-2145. |
| [7] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
| [8] |
YAN Zhong-wei1, 2, 3, TIAN Xi2, 3, ZHANG Yi-fei2, 3, LI Lian-jie2, 3, LIU San-qing1, 2, 3, HUANG Wen-qian2, 3*. Online Detection of Soluble Solids Content in Different Parts of
Watermelons Based on Full Transmission Near Infrared
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1800-1808. |
| [9] |
ZHANG Fan1, WANG Wen-xiu1, ZHANG Yu-fan1, HU Ze-xuan1, ZHAO Dan-yang1, MA Qian-yun1, SHI Hai-yan2, SUN Jian-feng1*. Hyperspectral and Ensemble Learning Method for Rapid Identification of Black Spot in Yali Pear at Gley Stage[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1541-1549. |
| [10] |
ZHANG Fu1, 2, 3, CAO Wei-hua1, CUI Xia-hua1, WANG Xin-yue1, FU San-ling4*, ZHANG Ya-kun1. Non-Destructive Detection of Soluble Solids in Cherry Tomatoes by
Visible/Near Infrared Spectroscopy Based on SG-CARS-IBP[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 737-743. |
| [11] |
JIANG Xiao-gang1, ZHU Ming-wang1, YAO Jin-liang1, LI Bin1, LIAO Jun1, LIU Yan-de1*, ZHANG Jian-yi2, JING Han-song2. Research on Parameter Optimization of Apple Sugar Model Based on Near-Infrared On-Line Device[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 116-121. |
| [12] |
TIAN Xi1, 2, 3, CHEN Li-ping2, 3, WANG Qing-yan2, 3, LI Jiang-bo2, 3, YANG Yi2, 3, FAN Shu-xiang2, 3, HUANG Wen-qian2, 3*. Optimization of Online Determination Model for Sugar in a Whole Apple
Using Full Transmittance Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1907-1914. |
| [13] |
ZHANG Fu1, 2, 3, CUI Xia-hua1, DING Ke4*, ZHANG Ya-kun1, WANG Yong-xian1, PAN Xiao-qing5. Study on the Influence of Different Pretreatment Methods on Gender Determination of Multiposition[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 434-439. |
| [14] |
LI Qing-bo1, WEI Yuan1, CUI Hou-xin2, FENG Hao2, LANG Jia-ye2. Quantitative Analysis of TOC in Water Quality Based on UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 376-380. |
| [15] |
REN Shuang-zan1, WANG Jing-wei2, GAO Liang-liang2, ZHU Hong-mei1, WU Hao1, LIU Jing1, TANG Xiao-jun2*, WANG Bin2. A Novel Compensation Method of Gas Absorption Spectrum Based on Time-Sharing Scanning Spectra and Double Gas Cell Switching[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(11): 3438-3443. |
|
|
|
|
