Occurrence prediction of pests and diseases in cotton on the basis of weather factors by long short term memory network.

Journal: BMC bioinformatics
PMID: 31874611

Abstract

BACKGROUND: The occurrence of cotton pests and diseases has always been an important factor affecting the total cotton production. Cotton has a great dependence on environmental factors during its growth, especially climate change. In recent years, machine learning and especially deep learning methods have been widely used in many fields and have achieved good results.

Authors

  • Qingxin Xiao
    Institutes of Physical Science and Information Technology, Anhui University, Hefei, 230601, China.
  • Weilu Li
    Institutes of Physical Science and Information Technology, Anhui University, Hefei, 230601, China.
  • Yuanzhong Kai
    School of Life Sciences, Anhui University, Hefei, 230601, China.
  • Peng Chen
  • Jun Zhang
    First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Bing Wang
    Computer Science & Engineering Department at the University of Connecticut.

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