Maize Root Phenotypic Detection Based on Thermal Imaging and Root Gap Repair Algorithm

Wei Lu, Zhao Han, Xing Liang Jian, Ji Zhou, Yan Feng Ding

Research output: Contribution to journalArticlepeer-review

Abstract

Aiming at the problem of incomplete root image information because of blocking by the soil, the paper proposed a root phenotypic method by using thermal image combined with improved Criminisi algorithm for root image repair and studied the relationship between the root phenotype and seed vigor. First, an annular double-layer quartz culture device adapted to maize root configuration was designed to push maize roots to grow along the inner wall of the device, and the maize seeds aged 0, 1, 3 and 6 d were planted in the annular culture device respectively. Base on the significant difference of heat capacity between soil and water, water was used to irrigate the seedling along their stems followed by short-time hot air thermal excitation, and then infrared thermal images were captured based on the temperature difference between the soil and interstitial water flow around the roots. Secondly, the endpoints of the root thermal images after preprocessed were selected and matched for connecting using improved Criminisi algorithm to repair the root image. Finally, different aged-day maize seeds were applied for seeding root phenotyping detection to verify the mentioned method which results show that the proposed thermal infrared imaging method can help to enhance the root phenotypic image information which improves the precision of phenotypic parameters about 0.5%~10% comparedwith color image. The was no significant difference of Root Total Length (RTL) and Root Total Number (RTN) after 1 d aging, but there was remarkable difference of RTL and RTN after 3 and 6 d aging which decreased about 20%~35% and 10%~55% respectively. In general, the maize root phenotypic parameters such as RTN and RTL were significantly negative with the aging-day, which can be used as important index parameters of seed vigor. Furthermore, RTN is more sensitive to impress a seed vigor. Root number of 1 d/3 d and 6 d aging days increasing delayed about 1day and 2 day compared with 0 aging-day seeds respectively. The proposed root phenotypic detection method based on the thermal infrared imaging combined with improved Criminisi algorithm for root image repair can be used in root high throughput non-destructive detection, which has a broad application prospect.

Translated title of the contributionMaize Root Phenotypic Detection Based on Thermal Imaging and Root Gap Repair Algorithm
Original languageChinese (Simplified)
Pages (from-to)2845-2850
Number of pages6
JournalGuang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis
Volume40
Issue number9
DOIs
Publication statusPublished - 1 Sep 2020
Externally publishedYes

Keywords

  • Image restoration
  • Nondestructive detection
  • Root phenotype
  • Seed
  • Thermal infrared imaging

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