https://scholars.lib.ntu.edu.tw/handle/123456789/438622
標題: | Evaluation of nitrogen content in cabbage seedlings using hyper-spectral images | 作者: | Chen S. Chen C.-T. Wang C.-Y. Yang I.-C. SUMING CHEN |
公開日期: | 2007 | 卷: | 6761 | 來源出版物: | Proceedings of SPIE - The International Society for Optical Engineering | 摘要: | Monitoring of nutrient status of crops is essential for better management of crop production. Nitrogen is one of the most important elements in fertilizer for the growth and yield of vegetable crops. In this study, nitrogen content of cabbage seedlings was evaluated using hyper-spectral images. Cabbage seedlings, cultured at five nitrogen fertilization levels, were planted in the 128-cell plug trays and grown in a phytotron at National Taiwan University. The images, ranged from 410 to 1090 nm, of cabbage seedlings were analyzed by a hyper-spectral imaging system consisting of CCD cameras with liquid crystal tunable filters (LCTF), which was developed in this study. The digital images of seedling canopies were processed including image segmentation, gray level calibration and absorbance conversion. Models including modified partial least square regression (MPLSR), step-wise multi-linear regression (SMLR) and artificial neural network with cross-learning strategy (ANN-CL) were developed for the determination of the nitrogen content in cabbage seedlings. The three significant wavelengths derived from SMLR model are 470, 710, and 1080; and the best result is obtained by ANN-CL model, in which rc=0.89, SE06.41 mg/g, rv=0.87, and SEV=6.96 mg/g. The ANN-CL model is more suitable for the remote sensing in precision agriculture applications because not only its model accuracy but also only 3 wavelengths are needed. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/438622 | ISBN: | 9780819469212 | ISSN: | 0277786X | DOI: | 10.1117/12.733079 | SDG/關鍵字: | Crops; Neural networks; Nitrogen; Spectrum analyzers; Hyper-spectral images; Nitrogen content; Seedlings; Food products |
顯示於: | 生物機電工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。