An accurate irrigation volume prediction method based on an optimized LSTM model.

Precise prediction of irrigation volumes is crucial in modern agriculture. This study proposes an optimized long short-term memory (LSTM) model-based irrigation prediction method that combines bidirectional LSTM networks. The model provides farmers with more precise irrigation management decisions, facilitating optimal utilization of water resources and effective crop production management.

Distinct mechanisms govern the phosphorylation of different SR protein splicing factors.

Serine-arginine (SR) proteins are essential splicing factors containing a canonical RNA recognition motif (RRM), sometimes followed by a pseudo-RRM, and a C-terminal arginine/serine-rich (RS) domain that undergoes multisite phosphorylation. Phosphorylation regulates the localization and activity of SR proteins, and thus may provide insight into their differential biological roles. The phosphorylation mechanism of the prototypic SRSF1 by serine-arginine protein kinase 1 (SRPK1) has been well-studied, but little is known about the phosphorylation of other SR protein members.