| 光谱学与光谱分析 |
|
|
|
|
|
| Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film |
| ZHOU Li-ping, ZHAO Yan-ru, YU Ke-qiang, HE Yong*, FANG Hui, YE Xu-jun |
| College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China |
|
|
|
|
Abstract In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380～1 030 nm) and NIR (874～1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.
|
|
Received: 2016-01-02
Accepted: 2016-04-28
|
|
|
|
Corresponding Authors:
HE Yong
E-mail: yhe@zju.edu.cn
|
|
[1] Lisiewska Z, Gebczyński P, Bernas E, et al. Journal of Food Composition and Analysis, 2009, 22(3): 218.
[2] Bergquist S M, Gertsson U E, Olsson M E. Journal of the Science of Food and Agriculture, 2006, 86(3): 346.
[3] Hu W Z, Jiang A L, Qi H P. Journal of Food Science and Technology, 2014, 51(12): 3862.
[4] Cozzolino R, Martignetti A, Pellicano M P, et al. Food Chemistry, 2016, 192: 603.
[5] Huang H, Liu L, Ngadi M O. Sensors, 2014, 14(4): 7248.
[6] Lara M A, Lleo L, Diezma-Iglesias B, et al. Journal of Food Engineering, 2013, 119(2): 353.
[7] HU Yao-hua, LIU Cong, HE Yong(胡耀华，刘 聪，何 勇). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2014, 34(4): 922.
[8] WANG Dan, LU Xiao-xiang, ZHANG Peng, et al(王 丹，鲁晓翔，张 鹏，等). Food and Fermentation Industries(食品与发酵工业), 2014, 40(2): 188.
[9] Xu L, Ye Z H, Cui H F, et al. Food Analytical Methods, 2012, 5(6): 1328.
[10] Xu L, Yan S M, Cai C B, et al. Journal of Spectroscopy, 2013, doi.org/10.1155/2013/797302.
[11] Wang N N, Yang Y C, Sun D W，et al. Food Analytical Methods, 2015, 8(5): 1173.
[12] Shao Y N, He Y. Journal of Food Engineering, 2007, 79(3): 1015.
[13] Gowen A A, O’Donnell C P, Esquerre C, et al. Applied Spectroscopy, 2010, 64(3): 304.
[14] Arnon D I. Plant Physiology, 1949, 24(1): 1.
[15] Davenport J J, Hodgkinson J, Saffell J R. Applied Optics, 2015, 54(27): 8135.
[16] Li X L，He Y, Wu C Q, et al. Journal of Food Engineering, 2007, 82(3): 316.
[17] Bagnasco L, Zotti M, Sitta N, et al. Talanta, 2015, 144: 1225.
[18] Serranti S, Cesare D, Marini F, et al. Talanta, 2013, 103: 276.
[19] Yu K, Zhao Y, Liu Z, et al. Food and Bioprocess Technology, 2014, 7(11): 3077.
[20] Maassen A, Erbersdobler H F, Busch-Stockfisch M. Ernahrungs-Umschau, 2006, 53(10): 390.
[21] Wu D, Wang S J, Wang N F, et al. Food and Bioprocess Technology, 2013, 6(11): 2943.
[22] Beghi R, Giovenzana V, Civelli R, et al. Journal of Food Engineering, 2016, 171: 145.
[23] Gitelson A A, Keydan G P, Merzlyak M N. Geophysical Research Letters, 2006, doi: 10.1029/2006GL026457.
[24] Downey G, Kelly J D. Journal of Agricultural and Food Chemistry, 2004, 52(2): 204.
[25] ZHANG Xiao-chao, WU Jing-zhu, XU Yun(张小超，吴静珠，徐 云). Near Infrared Spectroscopy Analysis Technology and Its Application in Modern Agriculture(近红外光谱分析技术及其在现代农业中的应用). Beijing: Publishing House of Electronics Industry(北京: 电子工业出版社), 2012.
[26] Galvo R K H, Araujo M C U, José G E, et al. Talanta, 2005, 67(4): 737. |
| [1] |
ZHANG Yue1, 3, ZHOU Jun-hui1, WANG Si-man1, WANG You-you1, ZHANG Yun-hao2, ZHAO Shuai2, LIU Shu-yang2*, YANG Jian1*. Identification of Xinhui Citri Reticulatae Pericarpium of Different Aging Years Based on Visible-Near Infrared Hyperspectral Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3286-3292. |
| [2] |
LI Bin, SU Cheng-tao, YIN Hai, LIU Yan-de*. Hyperspectral Imaging Technology Combined With Machine Learning for Detection of Moldy Rice[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2391-2396. |
| [3] |
ZHANG Zi-hao1, GUO Fei3, 4, WU Kun-ze1, YANG Xin-yu2, XU Zhen1*. Performance Evaluation of the Deep Forest 2021 (DF21) Model in
Retrieving Soil Cadmium Concentration Using Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2638-2643. |
| [4] |
PIAO Zhao-jia, YU Hai-ye, ZHANG Jun-he, ZHOU Hai-gen, LIU Shuang, KONG Li-juan, DANG Jing-min*. Hyperspectral Inversion Model of Pectin Content in Wheat Under Salt and Physical Damage Stresses[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2935-2940. |
| [5] |
WANG Yan1, 2, 3, WANG Bao-rui1, 2, 3*, WANG Yue1, 2, 3. Study on Radical Characteristics of Methane Laminar Premixed Flame Based on Hyperspectral Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2403-2410. |
| [6] |
BAI Xue-bing, MA Dian-kun, ZHANG Meng-jie, MA Rui-qin*. Hyperspectral Non-Destructive Analysis of Red Meat Quality: A Review[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 1993-1998. |
| [7] |
CHEN Yuan-zhe1, WANG Qiao-hua1, 2*, TIAN Wen-qiang1, XU Bu-yun1, HU Jian-chao1. Nondestructive Determinations of Texture and Quality of Preserved Egg Gel by Hyperspectral Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1985-1992. |
| [8] |
LIU Yan-de, WANG Shun. Research on Non-Destructive Testing of Navel Orange Shelf Life Imaging Based on Hyperspectral Image and Spectrum Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1792-1797. |
| [9] |
JIANG Qing-hu1, LIU Feng1, YU Dong-yue2, 3, LUO Hui2, 3, LIANG Qiong3*, ZHANG Yan-jun3*. Rapid Measurement of the Pharmacological Active Constituents in Herba Epimedii Using Hyperspectral Analysis Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1445-1450. |
| [10] |
LI De-hui1, WU Tai-xia1*, WANG Shu-dong2*, LI Zhe-hua1, TIAN Yi-wei1, FEI Xiao-long1, LIU Yang1, LEI Yong3, LI Guang-hua3. Hyperspectral Indices for Identification of Red Pigments Used in Cultural Relic[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1588-1594. |
| [11] |
MA Ling-kai, ZHU Shi-ping*, MIAO Yu-jie, WEI Xiao, LI Song, JIANG You-lie, ZHUO Jia-xin. The Discrimination of Organic and Conventional Eggs Based on
Hyperspectral Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1222-1228. |
| [12] |
WANG Guo-liang1, 2, YU Ke-qiang3, CHENG Kai2, LIU Xin2, WANG Wen-jun1, LI Hong2, GUO Er-hu2, LI Zhi-wei1*. Hyperspectral Technique Coupled With Chemometrics Methods for Predicting Alkali Spreading Value of Millet Flour[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3189-3193. |
| [13] |
YANG Chong-shan1,2, DONG Chun-wang2*, JIANG Yong-wen2, AN Ting1,2, ZHAO Yan1*. A Method for Judging the Fermentation Quality of Congou Based on Hyperspectral[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(04): 1320-1328. |
| [14] |
LIU Qun-wei, SHAO Yong-ni, CHEN Xiao-wan, JIANG Lin-hua*. Study on the Changes of Material in Scenedesmus Obliquus Based on Fourier Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3890-3894. |
| [15] |
SHAO Yuan-yuan1, 2, WANG Yong-xian1, XUAN Guan-tao1, 3*, GAO Zong-mei4, LIU Yi1, HAN Xiang1, HU Zhi-chao2*. Hyperspectral Imaging Technique for Estimating the Shelf-Life of Kiwifruits[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(06): 1940-1946. |
|
|
|
|
