Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2014, Article ID 602647, 12 pages
Research Article

Use of a Digital Camera to Monitor the Growth and Nitrogen Status of Cotton

1The Key Laboratory of Oasis Ecological Agriculture, Xinjiang Production and Construction Group/College of Agriculture, Shihezi University, Shihezi, Xinjiang 832000, China
2Xinjiang Shida Sender Technology Co. Ltd, Shihezi, Xinjiang 832000, China

Received 24 November 2013; Accepted 16 January 2014; Published 27 February 2014

Academic Editors: Y. I. Kuk and B. Uzun

Copyright © 2014 Biao Jia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [4 citations]

The following is the list of published articles that have cited the current article.

  • Ri-Xian Cui, Jin-Dong Fu, and Ya-Dong Liu, “Estimation of winter wheat leaf nitrogen accumulation using machine learning algorithm and visible spectral,” Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis, vol. 36, no. 6, pp. 1837–1842, 2016. View at Publisher · View at Google Scholar
  • Biao Jia, and Fuyu Ma, “Design and experiment of nitrogen nutrition diagnosis system of cotton based on machine vision,” Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, vol. 47, no. 3, pp. 305–310, 2016. View at Publisher · View at Google Scholar
  • Ping Yang, Biao Jia, and Zhong Zheng, “Modeling cotton growth and nitrogen status using image analysis,” Agronomy Journal, vol. 109, no. 6, pp. 2630–2638, 2017. View at Publisher · View at Google Scholar
  • Salah Elsayed, Gero Barmeier, and Urs Schmidhalter, “Passive Reflectance Sensing and Digital Image Analysis Allows for Assessing the Biomass and Nitrogen Status of Wheat in Early and Late Tillering Stages,” Frontiers in Plant Science, vol. 9, 2018. View at Publisher · View at Google Scholar