Measurement of Plumpness for Intact Sunflower Seed Using Terahertz Transmittance Imaging
- 43 Downloads
The quality of sunflower seed usually influences the load and product quality. The plumpness, expressing as the percent of the kernel and shell (%), is a crucial indicator reflecting the vigor of the sunflower seed. Investigations were carried out to measure the plumpness of intact sunflower seed by the use of terahertz (THz) transmittance imaging. The THz data of the worms, defects, and sound sunflower seeds were scanned using a THz time-domain transmittance imaging system. Followed THz imaging, the shell and kernel of the sample were separated carefully and recorded RGB images as the reference. Compared with the shell, the absorption coefficients and time domain signals of the kernel showed a significant difference in 0.5–2.0 THz. The characteristic images in 0.5–2.0 THz and control groups of 0.5–1.0, 1.0–1.5, and 1.5–2.0 THz were extracted, and the defects, kernel, and shell could be discriminated clearly in 0.5–2.0 THz. The models of the plumpness were developed between the THz and RGB images processed by the threshold segmentation. The determination coefficient and root mean square error of prediction (RMSEP) were 0.91 and 4% for an independent prediction set, respectively. The results suggested that use of THz transmittance imaging in measurement of plumpness of the intact sunflower seed was feasible. In addition, THz imaging provided a novel quality assessment solution for the coated samples.
KeywordsTerahertz Transmission image Sunflower seed Plumpness spectroscopy
XS wrote this manuscript, and JL finished the data collection.
The work funded by Natural and Science Foundation of China (No. 31960497) and Outstanding Youth Program of Jiangxi Province (No. 20171BCB23060). XS acknowledges support of a China Scholarship Council travel award (No. 201808360317) and Jiangxi Association for Science and Technology (JAST).
Compliance with Ethical Standards
Conflict of Interests
The authors declare that they have no competing interests.
- 2.S. Aishwarya and V. Anisha, “Nutritional composition of sunflower seeds flour and nutritive value of products prepared by incorporating sunflower seeds flour,” International Journal of Pharmaceutical Research & Allied Sciences, vol. 3, pp, 45–49, 2014.Google Scholar
- 3.S. D. Tyag, “An analysis of the association factors influencing seed yield and oil percentage in sunflower,” Progressive Agriculture, vol. 11, pp. 149–155, 2011.Google Scholar
- 6.T. C. Pearson, J. Prasifka, D. Brabec, R. Haff and B. Hulke, “Automated detection of insect-damaged sunflower seeds by X-ray imaging,” Applied Engineering in Agriculture, vol. 30, pp, 125–131, 2014.Google Scholar
- 7.C. Xu and Q. Zhang, “Sunflower seed detection based on improved IVC model and gray feature,” Computer Engineering and Applications, vol. 53, pp, 221–225, 2017.Google Scholar
- 8.W. Wang and Q. Zhang, Identification and sorting system of wormhole sunflower seeds based on machine vision, Food & Machinery, vol. 30, pp. 109–113, 2014.Google Scholar
- 13.R. Gente, S. F. Busch, E. Stübling, L. M. Schneider, C. B. Hirschmann, J. C. Balzer and M. Koch, “Quality control of sugar beet seeds with THz time-domain spectroscopy,” IEEE Transactions on Terahertz Science and Technology, vol. 6, pp. 754–756, 2016.Google Scholar
- 16.H. Ge, Y. Jiang and Y. Zhang, THz spectroscopic investigation of wheat-quality by using multi-source data fusion, Sensors, vol.18, pp. E3945, 2018.Google Scholar
- 19.E. Hilscher, F. Friedhoff and C. Hirschmann, Method for classifying seeds, U.S. Patent No. 9857297B2, 2018.Google Scholar
- 20.M. Lu, Y. Zhang, J. Sun, S. Chen, N. Li, G. Zhao and J. Shen, “Identification of maize seeds by terahertz scanning imaging,” Chinese Optics Letters, vol.3, pp. S239-S241, 2005.Google Scholar
- 24.X. Shen, B. Li, X. Long and Y Long, Identification of transgenic and non-transgenic cotton seed based on terahertz range spectroscopy, Transactions of the CSAE, vol. 33, pp. 288–292, 2017Google Scholar
- 27.C. Cao, Z. Zhang, X. Zhao, H. Zhang, T. Zhang and Y Yu, Review of terahertz time domain and frequency domain spectroscopy, Spectroscopy and Spectral Analysis, vol. 38, pp. 2688–2699, 2018.Google Scholar
- 28.B. Cao, D. Hou, Z. Yan, P. Huang, G. Zhang and Z. Zhou, “Method for detection of pesticide residue based on terahertz time domain spectroscopy,” Journal of Infrared and Millimeter Waves, vol. 27, pp. 429–432, 2008.Google Scholar
- 30.S. Chen, Preparation of sunflower seed hull nanocrystalline cellulose and its application in soy-isolated protein-based edible film, PhD thesis, Jilin University, Changchun, 2016.Google Scholar
- 33.J. Ren, Study on aqueous enzymatic extraction of oil and the utilization of protein from sunflower seed, Ph.D thesis, Jiangnan University, Wuxi, 2008Google Scholar