Prediction of Growth and Quality of Chinese Cabbage Seedlings Cultivated in Different Plug Cell Sizes via Analysis of Image Data Using Multispectral Camera

Sehui Ban, Inseo Hong, Yurina Kwack

Research output: Contribution to journalArticlepeer-review

Abstract

In recent times, there has been an increasing demand for the development of rapid and non-destructive assessment of the growth and quality of seedlings before transplanting. This study was conducted to examine the growth and quality of Chinese cabbage seedlings that can be determined via the image data acquired using a multispectral camera. Chinese cabbage seedlings were cultivated in five different plug trays (72, 105, 128, 162, and 200 cells/tray) for 30 days after sowing (DAS). The growth of seedlings had no significant difference in the early stage of cultivation; however, it decreased with increasing the number of cells in the plug tray due to the restricted root zone volume in the mid to late stages. Individual leaf area was predicted by analyzing of image data with high accuracy (R2 > 0.8) after 15 DAS; however, the accuracy of leaf area prediction per tray decreased due to overlapping and twisting leaves. Among six different vegetation indices, mrNDVI showed a high correlation (R2 > 0.6) with the dry weight of seedlings at 25 and 30 DAS. We confirmed that the leaf area of seedlings can be predicted non-destructively by analyzing the acquired image data per seedling and tray and suggested the applicability of vegetation indices for predicting the growth and quality of vegetable seedlings.

Original languageEnglish
Article number1288
JournalHorticulturae
Volume9
Issue number12
DOIs
StatePublished - Dec 2023

Keywords

  • dry weight
  • leaf area
  • mrNDVI
  • tray
  • vegetation index

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