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首页> 外文期刊>Journal of near infrared spectroscopy >Classification of maize kernel hardness using near infrared hyperspectral imaging
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Classification of maize kernel hardness using near infrared hyperspectral imaging

机译：利用近红外高光谱成像技术对玉米籽粒硬度进行分类

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摘要

Maize is an internationally important food crop that is usually milled before use. Milling yield is strongly influenced by maize hardness which, in turn, is controlled by the relative proportions of vitreous and floury endosperm within a single kernel. Current conventional near infrared (NIR) spectroscopic methods for determining maize hardness require reference data, which is obtained by destroying multiple kernels. In contrast, NIR hyperspectral imaging (NIR-HSI) has shown promise for determining the hardness of individual maize kernels without sample destruction or the need for reference data. This is possible due to the spatial dimension, in addition to the spectral dimension, offered by NIR-HSI. To illustrate this, NIR-HSI was used to characterise regions of germ, vitreous endosperm and floury endosperm from both the endosperm-rich (germ-down; GD) and endosperm-poor (germ-up; GU) surfaces of 155 single maize kernels. The proportions (expressed as % of whole image) of germ, vitreous and floury endosperm were determined from these images after principal component analysis was applied. Subsequent manual kernel dissection confirmed that the ratio of vitreous to floury endosperm was higher in kernels determined to be harder by NIR-HSI. The correlation coefficients between the manually obtained proportions (i.e. dissected) and proportions determined from NIR hyperspectral images (i.e. GU and GD images averaged) were 0.61, 0.59 and 0.11 for vitreous endosperm, floury endosperm and germ, respectively. The incongruence between the two types of determination reflects the surface-bias of reflectance spectroscopy. Irrespectively, NIR-HSI reflectance models could be developed without a reference method and applied to rapidly determine very hard from very soft kernels.
机译：玉米是国际上重要的粮食作物，通常在使用前进行碾磨。玉米硬度极大地影响了制粉的产量，而玉米的硬度又受单个籽粒中玻璃质和粉状胚乳的相对比例的控制。当前用于确定玉米硬度的常规近红外（NIR）光谱方法需要参考数据，该数据是通过破坏多个籽粒获得的。相比之下，NIR高光谱成像（NIR-HSI）已显示出确定单个玉米粒硬度的希望，而不会破坏样品或需要参考数据。由于NIR-HSI提供的空间尺寸以及光谱尺寸，这是可能的。为了说明这一点，使用NIR-HSI来表征155个单玉米粒的富含胚乳（胚芽降低; GD）和贫胚乳（胚芽; GU）的胚芽，玻璃质胚乳和粉状胚乳的区域。 。应用主成分分析后，从这些图像中确定胚芽，玻璃质和粉状胚乳的比例（表示为整个图像的百分比）。随后的人工籽粒解剖证实，通过NIR-HSI确定较硬的籽粒中玻璃质粉状胚乳的比例更高。对于玻璃质胚乳，粉状胚乳和胚芽，人工获得的比例（即解剖的）与从NIR高光谱图像（即GU和GD图像平均）确定的比例之间的相关系数分别为0.61、0.59和0.11。两种类型的测定之间的不一致反映了反射光谱的表面偏置。无论如何，无需参考方法即可开发NIR-HSI反射率模型，并将其应用于从非常软的内核中快速确定非常硬的内核。

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