• EI
  • Scopus
  • 中国科技期刊卓越行动计划项目资助期刊
  • 北大核心期刊
  • DOAJ
  • EBSCO
  • 中国核心学术期刊RCCSE A+
  • 中国精品科技期刊
  • JST China
  • FSTA
  • 中国农林核心期刊
  • 中国科技核心期刊CSTPCD
  • CA
  • WJCI
  • 食品科学与工程领域高质量科技期刊分级目录第一方阵T1
中国精品科技期刊2020
江梦薇,兰维杰,屠康,等. 冬枣黑斑病的光学特性检测方法建立[J]. 食品工业科技,2023,44(18):321−330. doi: 10.13386/j.issn1002-0306.2022100082.
引用本文: 江梦薇,兰维杰,屠康,等. 冬枣黑斑病的光学特性检测方法建立[J]. 食品工业科技,2023,44(18):321−330. doi: 10.13386/j.issn1002-0306.2022100082.
JIANG Mengwei, LAN Weijie, TU Kang, et al. Method Establishment for the Detection of Black Spot Disease on Winter Jujubes Based on Optical Properties[J]. Science and Technology of Food Industry, 2023, 44(18): 321−330. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022100082.
Citation: JIANG Mengwei, LAN Weijie, TU Kang, et al. Method Establishment for the Detection of Black Spot Disease on Winter Jujubes Based on Optical Properties[J]. Science and Technology of Food Industry, 2023, 44(18): 321−330. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022100082.

冬枣黑斑病的光学特性检测方法建立

Method Establishment for the Detection of Black Spot Disease on Winter Jujubes Based on Optical Properties

  • 摘要: 本研究旨在探究冬枣果实黑斑病过程中光学特性的变化,并筛选出病害检测的特征波长。采用单积分球检测系统结合反向倍加(IAD)算法测定冬枣果实在黑斑病过程中短-中波近红外区域(900~1650 nm)内光学吸收和散射特性,通过光学特性与品质指标间的相关性分析获得特征波长,最后通过近红外光谱对特征波长的有效性进行了验证。研究结果表明,随着黑斑病的发展,冬枣果实的失重率和a*呈现明显的上升趋势,L*、可溶性固形物及叶绿素含量则随贮藏时间下降。冬枣果实的吸收系数(μa)和约化散射系数(μs')均表现出明显的下降趋势。μaμs'分别在1400~1650和900~1360 nm与病害程度(病斑面积)和部分品质指标(失重率、L*a*、可溶性固形物和叶绿素)呈现高度相关。与全波长和基于算法获得的特征波长模型相比,基于光学特性优选的10个特征变量建立的冬枣黑斑病判别模型效果最佳,建模集和预测集总体正确率分别达到92.53%和92.35%,证明了短-中波近红外光学信号识别不同病害程度冬枣果实的潜力及基于光学特性优选的特征波长的有效性。

     

    Abstract: The objective of this study is to investigate the variations of optical properties during the progression of black spot disease and select the characteristic wavelengths for disease detection. The optical absorption and scattering properties were measured on winter jujubes using a single integrating sphere detection system in the band range of 900~1650 nm combined with inverse adding-doubling (IAD) algorithm in this study. The characteristic wavelengths were obtained depending on the correlation analysis between optical properties absorption and physicochemical indicators. Finally, the effectiveness of characteristic wavelengths was verified using near-infrared spectroscopy. The results indicated that a* and weight loss increased with storage time, while L*, soluble solids content and chlorophyll showed a consistent decrease. Both the absorption coefficient (μa) and the reduced scattering coefficient (μs') of the winter jujubes showed a significant downward trend with the development of black spot disease. The μa and μs' curves were highly correlated with disease extent (spot area) and some quality indicators (weight loss, L*, a*, soluble solids content and chlorophyll) in the 1400~1650 and 900~1360 nm, respectively. The discriminant models built based on the 10 characteristic variables selected by optical properties performed best compared with the models based on full wavelengths and algorithm-based characteristic wavelengths, with an overall accuracy of 92.53% and 92.35% for the calibration and prediction set, respectively. This study demonstrated the potential of the short- and mid-wave infrared optical signal in the disease detection on winter jujubes and the effectiveness of characteristic wavelengths on the basis of optical properties.

     

/

返回文章
返回