A deep learning method for the long-term prediction of plant electrical signals under salt stress to identify salt tolerance

no code implementations • Computers and Electronics in Agriculture 2021 • Jie-Peng Yao, Zi-Yang Wang, Ricardo Ferraz de Oliveira, Zhong-Yi Wang, Lan Huang

Furthermore, we developed a quantitative model, named the NaCl stress concentration discrimination model (SCDM), to investigate the relationship between the electrical signals, NaCl stress concentration, and time dependence, and used a salt tolerance classification model (STCM) to discover the most appropriate NaCl stress concentration for distinguishing the salt tolerance of wheat.

Using a one-dimensional convolutional neural network with a conditional generative adversarial network to classify plant electrical signals

no code implementations • Computers and Electronics in Agriculture 2020 • Xiao-Huang Qin, Zi-Yang Wang, Jie-Peng Yao, Qiao Zhou, Peng-Fei Zhao, Zhong-Yi Wang, Lan Huang

This paper proposes a model, based on a one-dimensional convolutional neural network (1D-CNN) with a conditional generative adversarial network (CGAN), which can quickly and effectively identify the salt tolerance of the seedlings using plant electrical signals at the early seedling stage.

Data Augmentation Generative Adversarial Network