Non-destructive Detection of Aspergillus ochraceus in Corn Based on Multispectral Imaging Technology
CSTR:
Author:
Affiliation:

(1.School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009;2.Intelligent Control and Compute Vision Lab, Hefei University, Hefei 230601)

  • Article
  • | |
  • Metrics
  • |
  • Reference [29]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    Corn is easily infected by Aspergillus ochraceus, which is severely hazardous to human health. As the traditional methods for Aspergillus ochraceus detection are time-consuming and destructive, it is necessary to develop a rapid and non-destructive method for monitoring the growth of Aspergillus ochraceus in corn during storage. In this study, multispectral imaging technology combined with chemometric methods was used to obtain the optimal model for predicting the count of Aspergillus ochraceus quantitively and classifying the infection degree qualitatively. The results showed that compared with partial least square (PLS) and least square-support vector machine (LS-SVM), back propagation neural network (BPNN) showed the best prediction performance with correlation coefficient of prediction (Rp) value of 0.9494, and the lowest root-mean-square error of calibration (RMSEC) and root-mean-square error of prediction (RMSEP) values of 2.6693 and 2.2743 CFU/g, respectively. In addition, for the classification experiment of the infective degree, BPNN was also the best prediction model with the accuracy of calibration(Ac) and the accuracy of prediction(Ap) both reached 100%. The results indicated that multispectral imaging combined with chemometric methods provided a promising technique to evaluate the infection of Aspergillus ochraceus in corn.

    Reference
    [1] 戴海蓉, 梁思慧, 王春民, 等.同时检测食品中多种类真菌毒素的研究进展[J].中国粮食学报, 2022, 22(8): 389-414.DAI H R, LIANG S H, WANG C M, et al.Research progress of simultaneous detection of mycotoxins in food[J].Journal of Chinese Institute of Food Science and Technology, 2022, 22(8): 389-414.
    [2] 孙嘉笛, 徐洪文, 徐一达, 等.食用植物油中黄曲霉毒素和赭曲霉毒素的污染状况及特征分析[J].中国油脂, 2022, 47(9): 35-43.SUN J D, XU H W, XU Y D, et al.Analysis of contamination status and characteristics of aflatoxin and ochratoxin in edible vegetable oils[J].China Oils and Fats, 2022, 47(9): 35-43.
    [3] PARK S, LIM W, YOU S, et al.Ochratoxin A exerts neurotoxicity in human astrocytes through mitochondria-dependent apoptosis and intracellular calcium overload[J].Toxicol Letters, 2019, 313: 42-49.
    [4] KHALIL O A A, HAMMAD A A, SEBAEI A S.Aspergillus flavus and Aspergillus ochraceus inhibition and reduction of aflatoxins and ochratoxin A in maize by irradiation[J].Toxicon, 2021, 198: 111-120.
    [5] JIARPINIJNUN A, OSAKO K, SIRIPATRAWAN U.Visualization of volatomic profiles for early detection of fungal infection on storage jasmine brown rice using electronic nose coupled with chemometrics[J].Measurement, 2020, 157: 107561.
    [6] 李爱华, 岳思君, 马海滨.真菌孢子三种计数方法相关性的探讨[J].微生物学杂质, 2006, 26(2): 107-110.LI A H, YUE S J, MA H B.Correlativity of three counting methods of fungal spore[J].Journal of Microbiology, 2006, 26(2): 107-110.
    [7] 余凡, 苏欣, 安兰芳, 等.氮碳纳米酶联合近红外光抗真菌体外试验研究[J].中国麻风皮肤病杂质, 2020, 36(12): 707-717.YU F, SU X, AN L F, et al.Antifungal effect of nitrogen-doped carbon nanozyme combined with near infrared in vitro[J].China Journal of Leprosy and Skin Diseases, 2020, 36(12): 707-717.
    [8] JOUBERT A, CALMES B, BERRUYER R, et al.Laser nephelometry applied in an automated microplate system to study filamentous fungus growth[J].Biotechniques, 2010, 48(5): 399-404.
    [9] Di LUCA M, KOLISZAK A, KARBYSHEVA S, et al.Thermogenic characterization and antifungal susceptibility of candida auris by microcalorimetry[J].Journal of Fungi, 2019, 5(4): 103-105.
    [10] SIRIPATRAWAN U, MAKINO Y.Monitoring fungal growth on brown rice grains using rapid and non-destructive hyperspectral imaging[J].International Journal of Food Microbiology, 2015, 199: 93-100.
    [11] BAURIEGEL E, GIEBEL A, GEYER M, et al.Early detection of fusarium infection in wheat using hyper-spectral imaging[J].Computers and Electronics in Agriculture, 2011, 75(2): 304-312.
    [12] DACHOUPAKAN SIRISOMBOON C, PUTTHANG R, SIRISOMBOON P.Application of near infrared spectroscopy to detect aflatoxigenic fungal contamination in rice[J].Food Control, 2013, 33(1): 207-214.
    [13] HE H J, SUN D W.Hyperspectral imaging technology for rapid detection of various microbial contaminants in agricultural and food products[J].Trends in Food Science & Technology, 2015, 46(1): 99-109.
    [14] 张宏蕊, 刘长虹, 张九凯, 等.多光谱成像的玛咖掺伪定性鉴别和定量分析[J].光谱学与光谱分析, 2020, 40(1): 152-156.ZHANG H R, LIU C H, ZHANG J K, et al.Qualitative identification and quantitative analysis of Maca admixture in multispectral imaging[J].Spectroscopy and Spectral Analysis, 2020, 40(1): 152-156.
    [15] 张华锋, 王武, 白玉荣, 等.多光谱成像无损识别冻融猪肉中危害级碎骨[J].光谱学与光谱分析, 2020, 41(9): 2892-2897.ZHANG H F, WANG W, BAI Y R, et al.Nondestructive identification of hazardous bone fragments in freeze-thawing pork by multispectral imaging[J].Spectroscopy and Spectral Analysis, 2020, 41(9): 2892-2897.
    [16] 金涛, 刘伟, 刘长虹, 等.基于多光谱成像技术的牛肉干水分含量快速无损检测研究[J].安徽农业科学, 2021, 49(2): 204-205.JIN T, LIU W, LIU C H, et al.Research on rapid nondestructive detection of moisture content of beef jerky based on multispectral imaging technology[J].Journal of Anhui Agricultural Sciences, 2021, 49(2): 204-205.
    [17] 杨培培, 蔡莉萍.多光谱成像技术在食品营养品质检测方面的应用方法[J].现代食品, 2021, 1: 127-129.YANG P P, CAI L P.Application of multispectral imaging technology in food nutrition quality detection[J].Food Science and Technology, 2021, 1: 127-129.
    [18] ORINA I, MARENA M, WILLIAMS P J.Non-destructive techniques for the detection of fungal infection in cereal grains[J].Food Research International, 2017, 100: 74-86.
    [19] LIU C H, LIU W, CHEN W, et al.Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit[J].Food Chemistry, 2015, 173: 482-488.
    [20] MENESATTI P, ANTONUCCI F, PALLOTTINO F, et al.Laboratory vs.in-field spectral proximal sensing for early detection of Fusarium head blight infection in durum wheat[J].Biosystems Engineering, 2013, 114(3): 289-293.
    [21] EBRAHIMI P, VAN DEN BERG F, AUNSBJERG S D, et al.Quantitative determination of mold growth and inhibition by multispectral imaging[J].Food Control, 2015, 55: 82-89.
    [22] REGO C H Q, FRAN?覶A-SILVA F, GOMES-JUNIOR F G, et al.Using multispectral imaging for detecting seed-borne fungi in cowpea[J].Agriculture, 2020, 10(8): 361.
    [23] LIU W, HE L, XIA Y M, et al.Monitoring the growth of Fusarium graminearum in wheat kernels using multispectral imaging with chemometric methods[J].Analytical Methods, 2022, 14(2): 106-113.
    [24] LIU C H, LIU W, LU X Z, et al.Potential of multispectral imaging for real-time determination of colour change and moisture distribution in carrot slices during hot air dehydration[J].Food Chemistry, 2016, 195: 110-116.
    [25] LIU C H, LIU W, YANG J B, et al.Non-destructive detection of dicyandiamide in infant formula powder using multi-spectral imaging coupled with chemometrics[J].Journal of the Science of Food and Agriculture, 2017, 97(7): 2094-2099.
    [26] SU W H, SUN D W.Multispectral imaging for plant food quality analysis and visualization[J].Comprehensive Reviews in Food Science and Food Safety, 2018, 17(1): 220-239.
    [27] SHAHIN M A, SYMONS S J, HATCHER D W.Quantification of mildew damage in soft red winter wheat based on spectral characteristics of bulk samples: A comparison of visible-near-infrared imaging and near-infrared spectroscopy[J].Food and Bioprocess Technology, 2013, 7(1): 224-234.
    [28] ZELAZNY W R, CHRPOVA J, HAMOUZ P.Fusarium head blight detection from spectral measurements in a field phenotyping setting - A pre-registered study[J].Biosystems Engineering, 2021, 211: 97-113.
    [29] ZHANG D Y, CHEN G, YIN X, et al.Integrating spectral and image data to detect Fusarium head blight of wheat[J].Computers and Electronics in Agriculture, 2020, 175: 105588.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation
Share
Article Metrics
  • Abstract:105
  • PDF: 203
  • HTML: 58
  • Cited by: 0
History
  • Received:June 25,2023
  • Online: July 22,2024
Article QR Code
Copyright :Journal of Chinese Institute of Food Science and Technology     京ICP备09084417号-4
Address :9/F, No. 8 North 3rd Street, Fucheng Road, Haidian District, Beijing, China      Postal code :100048
Telephone :010-65223596 65265376      E-mail :chinaspxb@vip.163.com
Supported by : Beijing E-Tiller Technology Development Co., Ltd.
Firefox, Chrome, IE10, IE11 are recommended. Other browsers are not recommended.