多光谱成像和X光图像在鉴别麻风树种子品质与种子表...
多光谱成像和X光图像在鉴别麻风树种子品质与种子表型研究的应用
最近，来自Aarhus大学以及丹麦理工大学的科学家利用多光谱成像设备以及X光设备发表了题为Multispectral and X-ray Images for Characterization of Jatropha Curcas L. Seed Quality的文章，结论显示MSI多光谱成像技术以及X光图像在麻风树的种子生理性能研究上有强相关性。 此类技术可作为未来替代方法用于快速、有效、可持续、无损鉴别麻风树种子品质，克服传统种子品质分析内在主观性。
研究中使用了Videometer开发的多光谱成像系统，该系统是种子品质以及种子表型组学研究的利器，目前为止，利用该设备已经发表了多达250多篇文章。
Multispectral and X-ray Images for Characterization of Jatropha Curcas L. Seed Quality
seed viability, non-destructive analysis, machine vision, artificial intelligence
Jean M Carstensen
Danmarks Tekniske Universitet
Birte Boelt
Aarhus Universitet
Background: Jatropha curcas
is an oilseed plant with great potential for biodiesel
production. In agricultural industry, the seed quality
is still estimated by manual inspection, using
destructive, time-consuming and subjective tests
that depend on the seed analyst experience. Recent advances in machine vision
combined with
artificial intelligence algorithms can provide spatial and spectral information for characterization
of biological images, reducing subjectivity and optimizing the analysis process.
Results: We present a new method for automatic characterization of jatropha seed quality, based
on multispectral imaging (MSI) combined with X-ray
imaging. We propose an approach along with X-ray images in order
to investigate
internal problems such as damages in the embryonic axis and endosperm, considering the fact
that seed surface profiles can be negatively affected, but without reaching important internal
regions of the seeds. Our studies included the application of a normalized canonical discriminant analyses (nCDA)
algorithm as a supervised transformation building method to classify spatial and spectral patters according to
the classes of seed quality. Spectral reflectance signatures in a range
of 780 to 970 nm and the X-ray images can efficiently
predict quality traits such as normal seedlings,
abnormal seedlings and dead seeds.
Conclusions: MSI and X-ray images have a strong relationship with physiological performance of Jatropha curcas L. These techniques can be alternative methods for rapid, efficient, sustainable and non-destructive characterization of jatropha seed quality in the future, overcoming the intrinsic subjectivity of the conventional seed quality
