Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality.
Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality.
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自体荧光光谱成像技术是一种快速、无损、可靠评价大豆种子品质的新方法。
DOI：
10.1038/s41598-021-97223-5
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发表时间：
2021-09-08
影响因子：
4.6
通讯作者：
Dos Reis AR
中科院分区：
文献类型：
--
作者：
Barboza da Silva C;Oliveira NM;de Carvalho MEA;de Medeiros AD;de Lima Nogueira M;Dos Reis AR
在农业方面，基于快速和非破坏性方法的光学成像技术的进步促进了不断增长的人口的粮食生产。本研究利用自体荧光光谱成像和机器学习算法，建立了人工老化后不同生理品质大豆种子的分类模型。来自365/400 nm激发-发射组合的自发荧光信号(与胚胎中的总酚显示出完美的相关性)能够有效地分离处理。此外，还有可能证明自发荧光光谱数据与几个质量指标之间存在很强的相关性，例如早期萌发和种子对胁迫条件的耐受性。基于人工神经网络、支持向量机或线性判别分析建立的机器学习模型对不同质量水平的种子分类具有较高的性能(0.99正确率)。综上所述，我们的研究表明，大豆种子的生理潜力随着自体荧光化合物浓度的变化而降低，可能还伴随着结构的变化。此外，种子自身荧光性质的改变也会影响幼苗的光合作用装置。从实用的角度来看，基于自体荧光的成像可以用来检查大豆种子组织的光学性质的变化，并一致地区分高活力和低活力的种子。
In the agricultural industry, advances in optical imaging technologies based on rapid and non-destructive approaches have contributed to increase food production for the growing population. The present study employed autofluorescence-spectral imaging and machine learning algorithms to develop distinct models for classification of soybean seeds differing in physiological quality after artificial aging. Autofluorescence signals from the 365/400 nm excitation-emission combination (that exhibited a perfect correlation with the total phenols in the embryo) were efficiently able to segregate treatments. Furthermore, it was also possible to demonstrate a strong correlation between autofluorescence-spectral data and several quality indicators, such as early germination and seed tolerance to stressful conditions. The machine learning models developed based on artificial neural network, support vector machine or linear discriminant analysis showed high performance (0.99 accuracy) for classifying seeds with different quality levels. Taken together, our study shows that the physiological potential of soybean seeds is reduced accompanied by changes in the concentration and, probably in the structure of autofluorescent compounds. In addition, altering the autofluorescent properties in seeds impact the photosynthesis apparatus in seedlings. From the practical point of view, autofluorescence-based imaging can be used to check modifications in the optical properties of soybean seed tissues and to consistently discriminate high-and low-vigor seeds.
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影响因子：
5.6
作者：
Galletti PA;Carvalho MEA;Hirai WY;Brancaglioni VA;Arthur V;Barboza da Silva C
通讯作者：
Barboza da Silva C
影响因子：
4.2
作者：
Groot SP;Surki AA;de Vos RC;Kodde J
通讯作者：
Kodde J
影响因子：
2.1
作者：
Caverzan, Andreia;Giacomin, Rafael;Chavarria, Geraldo
通讯作者：
Chavarria, Geraldo
影响因子：
6.1
作者：
Fukushima, Romualdo S.;Kerley, Monty S.
通讯作者：
Kerley, Monty S.
影响因子：
4.3
作者：
Cui, Meng;Wu, Dong;Luo, Liping
通讯作者：
Luo, Liping