Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

ABSTRACT: Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content. Three classification models, Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) were developed and validated in different scenarios with overall accuracy over 90% for all. SVM model had the highest value, but it required the longest training time. All models had accuracy over 8

SUBMITTER: Guo D 

PROVIDER: S-EPMC5557858 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature