Development of Prediction Model for the Na Content of Leaves of Spring Potatoes Using Hyperspectral Imagery
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Park, Jun-Woo
(Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science))
Kang, Ye-Seong (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Ryu, Chan-Seok (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Jang, Si-Hyeong (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Kang, Kyung-Suk (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Kim, Tae-Yang (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Park, Min-Jun (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Baek, Hyeon-Chan (Department of Bio-System Engineering, GyeongSang National University (Institute of Agriculture & Life Science)) Song, Hye-Young (National Institute of Agricultural Sciences, Rural Development Administration) Jun, Sae-Rom (Hortizen Co. Ltd.) Lee, Su-Hwan (National Institute of Crop Science, Rural Development Administration) |
1 | Phatak, A., and S. De Jong, 1997: The geometry of partial least squares. Journal of Chemometrics: A Journal of the Chemometrics Society 11(4), 311-338. DOI |
2 | Ruffin, C., and R. L. King, 1999: The analysis of hyperspectral data using Savitzky-Golay filtering-theoretical basis. 1. In IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No. 99CH36293) 2, 756-758. |
3 | Onoyama, H., C. Ryu, M. Suguri, and M. Iida, 2015: Nitrogen prediction model of rice plant at panicle initiation stage using ground-based hyperspectral imaging: Growing degree-days integrated model. Precision Agriculture 16(5), 558-570. DOI |
4 | Jensen, J. R., 2015: Introductory digital image processing: a remote sensing perspective. Prentice Hall Press. |
5 | Lewis, C. D., 1982: Industrial and business forecasting methods: A practical guide to exponential smoothing and curve fitting. Butterworth-Heinemann. |
6 | Hamzeh, S., A. A. Naseri, S. K. Alavipanah, B. Mojaradi, H. M. Bartholomeus, J. G. Clevers, and M. Behzad, 2013: Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices. International Journal of Applied Earth Observation and Geoinformation 21, 282-290. DOI |
7 | Hasegawa, P. M., R. A. Bressan, J. K. Zhu, and H. J. Bohnert, 2000: Plant cellular and molecular responses to high salinity. Annual Review of Plant Physiology and Plant Molecular Biology 51(1), 463-499. DOI |
8 | Huang, M., M. S. Kim, S. R. Delwiche, K. Chao, J. Qin, C. Mo, and Q. Zhu, 2016: Quantitative analysis of melaminein milk powders using near-infrared hyperspectral imaging and band ratio. Journal of Food Engineering 181, 10-19. DOI |
9 | Parida, A. K., and A. B. Das, 2005: Salt tolerance and salinity effects on plants: a review. Ecotoxicology and Environmental Safety 60(3), 324-349. DOI |
10 | Williams, P., 2003: Near-infrared Technology-Getting the Best Out of Light. PDK Grain., 8-10. |
11 | Zygielbaum, A. I., A. A. Gitelson, T. J. Arkebauer, and D. C. Rundquist, 2009: Non-destructive detection of water stress and estimation of relative water content in maize. Geophysical Research Letters 36(12). |
12 | Richter, M., and J. Beyerer, 2014: Optical filter selection for automatic visual inspection. In IEEE Winter Conference on Applications of Computer Vision, 123-128. |
13 | Savitzky, A., and M. J. Golay, 1964: Smoothing and differentiation of data by simplified least squares procedures. Analytical chemistry 36(8), 1627-1639. DOI |
14 | Vaiphasa, C., 2006: Consideration of smoothing techniques for hyperspectral remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing 60(2), 91-99. DOI |
15 | Chen, S., X. Hong, C. J. Harris, and P. M. Sharkey, 2004: Sparse modeling using orthogonal forward regression with PRESS statistic and regularization. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34(2), 898-911. DOI |
16 | Kang, Y. S., S. H. Jang, J. W. Park, H. Y. Song, C. S. Ryu, S. R. Jun, and S. H. Kim, 2020: Yield prediction and validation of onion (Allium cepa L.) using key variables in narrowband hyperspectral imagery and effective accumulated temperature. Computers and Electronics in Agriculture 178, 105667. DOI |
17 | Berni, J. A., P. J. Zarco-Tejada, L. Suarez, and E. Fereres, 2009: Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on geoscience and Remote Sensing 47(3), 722-738. DOI |
18 | Kang, K. S., C. S. Ryu, S. H. Jang, Y. S. Kang, S. R. Jun, J. W. Park, H. Y. Song, and S. H. Lee, 2019: Application of hyperspectral imagery to decision tree classifier for assessment of spring potato (Solanum tuberosum) damage by salinity and drought. Korean Journal of Agricultural and Forest Meteorology 21(4), 317-326. DOI |
19 | Ayers, R. S., and D. W. Westcot, 1985: Water quality for agriculture. Rome: Food and Agriculture Organization of the United Nations, 174pp. |
20 | Carter, G. A., 1993: Responses of leaf spectral reflectance to plant stress. American journal of botany 80(3), 239-243. DOI |
21 | Choi, C. H., K. C. Kim, D. R. Lee, S. H. Cho, D. H. Cho, S. Y. Lee, and I. S. Lee, 2018: Evaluation of various characteristics of high quality rice varieties that could potentially be grown on reclaimed land in Jellabuk Province, Korea. Korean Journal of Crop Science 63(3), 196-204. DOI |
22 | Ekelof, J., 2007: Potato yield and tuber set as affected by phosphorus fertilization. |
23 | GRI (Gyeonggi Research Institute), 2007: Analysis and utilization of west coast reclamation. 2007 Report of Gyeonggi Research Institute. |
24 | Lee, S., R. NICS, H. Bae, R. NICS, S. H. Lee, R. NICS, and R. NICS, 2016: Effect of irrigation on soil salinity and corn (Zea mays) growth at coarse-textured tidal saline soil. The Journal of the Korean Society of International Agriculture 28(4), 526-532. DOI |
25 | Kang, Y. S., C. S. Ryu, S. H. Kim, S. R. Jun, S. H. Jang, J. W. Park, and T. K. Sarkar, 2018: Yield prediction of Chinese cabbage (Brassicaceae) using broadband multispectral imagery mounted unmanned aerial system in the air and narrowband hyperspectral imagery on the ground. Journal of Biosystems Engineering 43(2), 138-147. DOI |
26 | Koo, J. W., J. K. Choi, and J. G. Son, 1998: Soil properties of reclaimed tidel lands and tidelands of western sea coast in Korea. Korean Journal of Soil Science and Fertilizer 31(2), 120-127. |
27 | Lee, S. H., S. H. Yoo, S. I. Seol, Y. An, Y. S Jung, and S. M. Lee., 2000: Assessment of salt damage for upland-crop in Dae-Ho reclaimed soil. Korean Journal of Environment Agriculture 19(4), 358-363. (in Korean with English abstract). |
28 | Medjahed, S. A., T. A. Saadi, A. Benyettou, and M. Ouali, 2016: Gray wolf optimizer for hyperspectral band selection. Applied Soft Computing 40, 178-186. DOI |
29 | Nigon, T. J., D. J. Mulla, C. J. Rosen, Y. Cohen, V. Alchanatis, J. Knight, and R. Rud, 2015: Hyperspectral aerial imagery for detecting nitrogen stress in two potato cultivars. Computers and Electronics in Agriculture 112, 36-46. DOI |
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