光谱成像和化学计量学在种子科学表型研究中的应用:系统综述

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
T. B. Michelon, Elisa Serra Negra Vieira, Maristela Panobianco
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引用次数: 0

摘要

对种子批次遗传质量的评价对于其生产和商业化的质量控制过程,以及在植物育种计划中鉴定优良基因型和核实正确杂交都是至关重要的。目前的技术是基于种子形态特征的鉴定,需要熟练的分析人员,而生化方法既耗时又昂贵。光谱成像分析作为一种快速、准确、无损的分析方法,将数字成像与光谱学相结合,正在得到越来越广泛的应用。该技术的成功与化学计量学技术密切相关,化学计量学技术在数据处理中使用统计和数学工具。本文的目的是评价光谱图像分析和化学计量学方法在种子表型及其实际应用中的主要应用。使用PRISMA方法进行了系统评价,其中共鉴定和筛选了1304篇文章,其中包括44篇与范围有关的文章。结果表明,光谱图像分析对不同基因型的种子具有较高的分类能力(93.33%):在不同品种之间;杂交种和祖先;以及杂交种和品系,以及包皮种子的分离。在物种特征的指导下,通过不同的策略,如选择设备类型、频谱范围和额外特征,以及在数据量大时选择算法和降维程序来优化模型,都可以获得准确的分类。尽管该技术在种子表型分析中的实际应用仍然需要开发,以便在具有大量分析,批次,基因型和收获的实验室中使用。研究已经加速,以克服这种方法的实际挑战,如使用模型更新算法,在线分类系统和实时分类地图的工作。因此,有强烈的迹象表明,多光谱图像分析的应用将达到常规的种子分析实验室。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectral imaging and chemometrics applied at phenotyping in seed science studies: a systematic review
The evaluation of the genetic quality of a seed lot is crucial for the quality control process in its production and commercialization, as well as in the identification of superior genotypes and the verification of the correct crossing in plant breeding programmes. Current techniques, based on the identification of seed morphological characteristics, require skilled analysts, while biochemical methods are time-consuming and costly. The application of spectral imaging analysis, which combines digital imaging with spectroscopy, is gaining ground as a fast, accurate and non-destructive method. The success of this technique is closely linked to chemometric techniques, which use statistical and mathematical tools in data processing. The aim of the work was to evaluate the main procedures in terms of spectral image analysis and chemometric procedures applied in seed phenotyping and its practical application. A systematic review was conducted using the PRISMA methodology, in which a total of 1304 articles were identified and screened to the inclusion of 44 articles pertaining to the scope. It was concluded that spectral image analysis has a high ability to classify seeds of different genotypes (93.33%) in a range of situations: between cultivars; hybrids and progenitors; and hybrids and lines, as well as in the separation of coated seeds. Accurate classification can be obtained by different strategies, such as the choice of the equipment type, the spectrum range and extra features, guided by the characteristics of the species, as well as in the choice of algorithms and dimensionality reduction procedures for the optimization of models when there is a large amount of data. Despite the fact that the practical application of this technique in seed phenotyping still needs to be developed for use in laboratories with large volumes of analyses, lots, genotypes and harvests. Research has been accelerated to overcome the practical challenges of this method, as seen in works using model update algorithms, online classification systems, and real-time classification maps. Thus, there are strong indications that the application of multispectral image analysis will reach the routine of seed analysis laboratories.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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