Prediction of Abnormal Stem Elongation in Plant Factory Seedlings Based on Height Time-Series Variation

Abstract

This letter proposes a method to predict future abnormal stem elongation in sweet basil seedlings from height time-series data. A general growth model is constructed from normal plants, and a two-stage difference feature is derived. Experiments show that the method predicts etiolation one week in advance with 96.2% accuracy.