激光斑点成像技术在苹果缺氧应力预测中的新应用

IF 4.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Piotr Mariusz Pieczywek, Artur Nosalewicz, Artur Zdunek
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引用次数: 0

摘要

背景:动态可控气氛(DCA)技术等水果贮藏方法可根据产品的生理状态调节贮藏室中的氧气水平,以减缓成熟过程。然而,DCA 的成功应用需要精确可靠的果实氧化应激传感器。在本研究中,在引入基于激光斑点成像技术(LSI)的苹果缺氧应力新型预测指标后,对呼吸速率和叶绿素荧光(CF)信号进行了评估:结果:原则上,叶绿素荧光和 LSI 信号在检测应激方面效果相同。然而,在基于机器学习模型的自动检测应用中,LSI 信号因其稳定性和测量重复性而被证明更胜一筹。此外,CF 信号的缺点似乎是无法显示叶绿素含量低的组织中的氧胁迫,但 LSI 却不存在这种情况。对不同的 LSI 信号处理方法进行比较后发现,基于图像内容动态变化的方法比基于像素亮度变化测量的方法(惯性矩或激光斑点对比度分析)更能显示压力。与红光激光相比,使用近红外激光获得的数据具有更好的预测能力:研究表明,激光散射现象产生的信号可以很好地预测苹果的氧化应激。结果表明,使用 LSI 可以进行有效预测,而且不需要额外的信号。所提出的方法作为水果氧化应激的替代指标具有很大的潜力,可应用于动态控制气氛的现代贮藏系统中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel application of laser speckle imaging technique for prediction of hypoxic stress of apples.

Background: Fruit storage methods such as dynamic controlled atmosphere (DCA) technology enable adjusting the level of oxygen in the storage room, according to the physiological state of the product to slow down the ripening process. However, the successful application of DCA requires precise and reliable sensors of the oxidative stress of the fruit. In this study, respiration rate and chlorophyll fluorescence (CF) signals were evaluated after introducing a novel predictors of apples' hypoxic stress based on laser speckle imaging technique (LSI).

Results: Both chlorophyll fluorescence and LSI signals were equally good for stress detection in principle. However, in an application with automatic detection based on machine learning models, the LSI signal proved to be superior, due to its stability and measurement repeatability. Moreover, the shortcomings of the CF signal appear to be its inability to indicate oxygen stress in tissues with low chlorophyll content but this does not apply to LSI. A comparison of different LSI signal processing methods showed that method based on the dynamics of changes in image content was better indicators of stress than methods based on measurements of changes in pixel brightness (inertia moment or laser speckle contrast analysis). Data obtained using the near-infrared laser provided better prediction capabilities, compared to the laser with red light.

Conclusions: The study showed that the signal from the scattered laser light phenomenon is a good predictor for the oxidative stress of apples. Results showed that effective prediction using LSI was possible and did not require additional signals. The proposed method has great potential as an alternative indicator of fruit oxidative stress, which can be applied in modern storage systems with a dynamically controlled atmosphere.

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来源期刊
Plant Methods
Plant Methods 生物-植物科学
CiteScore
9.20
自引率
3.90%
发文量
121
审稿时长
2 months
期刊介绍: Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences. There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics. Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.
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