THz Spectroscopic Investigation of Wheat-Quality by Using Multi-Source Data Fusion

Ge, Hongyi; Jiang, Yuying; Zhang, Yuan

doi:10.3390/s18113945

Cited by 15 publications

(5 citation statements)

References 39 publications

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“…Our data indirectly confirm this assumption. In addition, our data on a decrease in the absorption rate in wheat under Fusarium disease coincide with the literature data on a decrease in the absorption rate in seeds affected by mold compared to healthy seeds [ 56 ].…”

Section: Discussionsupporting

confidence: 89%

The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis

et al. 2021

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Fusarium and late blight (fungal diseases of cereals and potatoes) are among the main causes of crop loss worldwide. A key element of success in the fight against phytopathogens is the timely identification of infected plants and seeds. That is why the development of new methods for identifying phytopathogens is a priority for agriculture. The terahertz time-domain spectroscopy (THz-TDS) is a promising method for assessing the quality of materials. For the first time, we used THz-TDS for assessing the infection of seeds of cereals (oats, wheat and barley) with fusarium and potato tubers of different varieties (Nadezhda and Meteor) with late blight. We evaluated the refractive index, absorption coefficient and complex dielectric permittivity in healthy and infected plants. The presence of phytopathogens on seeds was confirmed by microscopy and PCR. It is shown, that Late blight significantly affected all the studied spectral characteristics. The nature of the changes depended on the variety of the analyzed plants and the localization of the analyzed tissue relative to the focus of infection. Fusarium also significantly affected all the studied spectral characteristics. It was found that THz-TDS method allows you to clearly establish the presence or absence of a phytopathogens, in the case of late blight, to assess the degree and depth of damage to plant tissues.

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Section: Discussionsupporting

confidence: 89%

The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis

et al. 2021

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“…The accuracy of 89% was close to this report of 90% when without scatter effect correction was applied. Our experiment was also slightly better than the THz-TDS application for wheat defect detection with an accuracy of 96% ( 22 ). The scatter effect is a common problem in THz-TDS measurement of solid state samples, especially for irregular granular samples ( 23 ).…”

Section: Resultsmentioning

confidence: 78%

Non-destructive Detection of Insect Foreign Bodies in Finishing Tea Product Based on Terahertz Spectrum and Image

Sun

Shen

2021

Front. Nutr.

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Non-destructive testing of low-density and organic foreign bodies is the main challenge for food safety control. Terahertz time-domain spectroscopy (THz-TDS) and imaging technologies were applied to explore the feasibility of detection for insect foreign bodies in the finishing tea products. THz-TDS of tea leaves and foreign bodies of insects demonstrated significant differences in terms of time domain and frequency signals in the range of 0.3–1.0 THz. These signals were corrected by the use of adaptive iteratively reweighted penalized least squares (AirPLS), asymmetric least squares (AsLS), and baseline estimation and de-noising using sparsity (BEADS) for reducing baseline drift and enhancing effective spectral information. The K-nearest neighbor (KNN) and partial least squares discrimination analysis (PLS-DA) models showed the best performance after AirPLS correction with the prediction accuracy of 98 and 100%, respectively. In addition, the locations and outlines of insect bodies could be clearly presented via the THz-TDS image. These results suggested that THz-TDS spectroscopy and imaging provide an alternative tool for the detection of insect foreign bodies in finishing tea products.

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“…In this part of the work, we use the TerraScan platform to assign the grayscale values of the pixels in the orthophoto with the corresponding coordinates to the point cloud based on the (x, y) position properties of the discrete points of the LiDAR data in the plane coordinate system, making it rich in spectral image texture information. Since the process does not have multiple LiDAR points within a pixel, this fusion method does not have overlap and interpolation problems [21][22][23].…”

Section: Accuracy Evaluationmentioning

confidence: 99%

Urban Llandscape Design and Maintenance Management Based on Multisource Big Data Fusion

Zhang

2022

Mathematical Problems in Engineering

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Data modeling based on the fusion of data from multiple sources can improve modeling accuracy compared to a single data source. A new modular information fusion model based on genetic neural networks is designed for the urban landscape design process. A digital elevation model is created using an ordered sequence of numbers based on preprocessed sensor images. A 3D orthophoto is then obtained to generate a 3D landscape using an artificial parallax-assisted mechanism. The scale and resources of the regional landscape are described by the three-dimensional geometric dimension after data processing, and a modular landscape model with a clear subject is constructed. Finally, a genetic algorithm based on real number coding optimizes the initial weights of the neural network and selects suitable learning factors to train the neural network to complete the data fusion task and error analysis. The maintenance situation is analyzed by introducing a multifactor landscape maintenance evaluation method. The simulation results show that the fusion process of the above model is stable and the energy consumption of information fusion is low, which can promote the efficient construction of the landscape and has important application value for improving the landscape design and maintenance management.

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THz Spectroscopic Investigation of Wheat-Quality by Using Multi-Source Data Fusion

Cited by 15 publications

References 39 publications

The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis

The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis

Non-destructive Detection of Insect Foreign Bodies in Finishing Tea Product Based on Terahertz Spectrum and Image

Urban Llandscape Design and Maintenance Management Based on Multisource Big Data Fusion

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