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2025 Vol.34, Issue 4 Preview Page

Original Articles

Differences in Growth after Transplanting of Kimchi Cabbage Seedlings Assessed using Image-Based Non-Destructive Grading

영상 기반 비파괴 등급화에 따른 배추 묘의 정식 후 생장 비교

Sehui Ban1
,
Yurina Kwack2*
반 세희1
,
곽 유리나2*
1Graduate Student, Department of Environmental Horticulture, College of Natural Science, University of Seoul, Seoul 02504, Korea
2Professor, Department of Environmental Horticulture, College of Natural Science, University of Seoul, Seoul 02504, Korea
1서울시립대학교 자연과학대학 환경원예학과 대학원생
2서울시립대학교 자연과학대학 환경원예학과 교수
*Corresponding Author
31 October 2025. pp. 476-484
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Abstract

Kimchi cabbage (Brassica rapa L. ssp. pekinensis) is the most widely consumed vegetable crop in Korea. The production of vigorous seedlings is essential in vegetable cultivation to ensure stable post-transplant growth, highlighting the need for technologies that enable rapid, objective, and non-destructive assessment. This study aimed to evaluate seedling growth of kimchi cabbage using image analysis and to determine differences in early growth after transplanting among image-based seedling grades. To induce variation in seedling growth, kimchi cabbage (cv. ‘Cheongmyeonggaeul’) seedlings were cultivated in plug trays with 72, 105, 128, 162, and 200 cells for 25 days after sowing, and then transplanted into pots. Before transplanting, images were acquired to calculate projected canopy size (PCS). PCS values allowed highly accurate prediction of leaf area and shoot fresh weight, and seedlings were subsequently classified into three grades (A－C). At 49 days after transplanting, growth responses differed by seedling grade: grade C seedlings exhibited delayed growth, whereas grades A and B showed comparable growth. These results suggest that PCS enables non-destructive estimation of seedling growth and that image analysis can be applied to select high-quality kimchi cabbage seedlings for transplanting.

Keywords
leaf area
projected canopy size (PCS)
seedling grade
shoot fresh weight

배추(Brassica rapa L. ssp. pekinensis)는 한국에서 가장 많이 소비되는 채소 작물로, 건강한 묘 생산은 정식 후 안정적인 생육을 보장하기 위해 필수적이다. 이에 따라 신속하고 객관적이며 비파괴적인 평가 기술의 필요성이 강조되고 있다. 본 연구는 영상 분석을 활용하여 배추 묘의 생장을 평가하고, 영상 기반 등급에 따른 정식 후 초기 생장 차이를 규명하고자 하였다. 청명가을 품종의 배추를 72, 105, 128, 162, 200구 플러그 트레이에서 파종 후 25일간 육묘한 뒤 포트에 정식하였으며, 정식 전 촬영한 영상을 통해 투영 캐노피 크기(PCS)를 계산하였다. PCS는 엽면적과 지상부 생체중을 높은 정확도로 예측하였고, 이를 바탕으로 묘를 A–C의 세 등급으로 분류하였다. 정식 후 초기에는 모종의 생장 차이가 그대로 반영되었으나, 정식 후 49일에는 A와 B등급 묘 간의 생장 차이는 사라졌고, C등급 묘는 지속적으로 생장이 지연되는 결과를 보였다. 이러한 결과는 PCS가 묘의 생육을 비파괴적으로 추정할 수 있음을 보여주며, PCS 기반의 기준을 설정하여 정식에 적합한 고품질 배추 묘를 선별하는 데 영상 분석이 효과적으로 활용될 수 있음을 시사한다.

키워드
모종 등급
엽면적
지상부 생체중
투영 캐노피 크기
References
1

Bae Y.H., H.C. Yang, Y.H. Kim, S.J. Hyeon, M.S. Choi, N.T. Vu, and D.C. Jang 2025, Seedling quality and early growth after the transplanting of tomato seedlings grown using different production methods. Hortic Sci Technol 43:275-285. doi: 10.7235/HORT.20250025

10.7235/HORT.20250025
2

Bar‐Tal A., B. Bar‐Yosef, and U. Kafkafi 1990, Pepper transplant response to root volume and nutrition in the nursery. Agron J 82:989-995. doi:10.2134/agronj1990.00021962008200050030x

10.2134/agronj1990.00021962008200050030x
3

Choi E.Y., T.C. Seo, S.G. Lee, I.H. Cho, and J. Stangoulis 2011, Growth and physiological responses of Chinese cabbage and radish to long-term exposure to elevated carbon dioxide and temperature. Hortic Environ Biotechnol 52:376-386. doi:10.1007/s13580-011-0012-0

10.1007/s13580-011-0012-0
4

Gallegos‐Cedillo V.M., C. Nájera, A. Signore, J. Ochoa, J. Gallegos, C. Egea‐Gilabert, N.S. Gruda, and J.A. Fernández 2024, Analysis of global research on vegetable seedlings and transplants and their impacts on product quality. J Sci Food Agric 104:4950-4965. doi:10.1002/jsfa.13309

10.1002/jsfa.13309
5

Ge Y., G. Bai, V. Stoerger, and J.C. Schnable 2016, Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging. Comput Electron Agric 127:625-632. doi:10.1016/j.compag.2016.07.028

10.1016/j.compag.2016.07.028
6

Hyeon S.J., H.C. Yang, Y.H. Kim, Y.H. Bae, and D.C. Jang 2024, Comparison of seedling quality of cucumber seedlings and growth and production after transplanting according to differences in seedling production systems. J Bio Enviro Con 33:88-98. doi:10.12791/KSBEC.2024.33.2.088 (in Korean)

10.12791/KSBEC.2024.33.2.088
7

Jeong H.W., H.R. Lee, H.M. Kim, H.M. Kim, H.S. Hwang, and S.J. Hwang 2020, Using light quality for growth control of cucumber seedlings in closed-type plant production system. Plants 9:639. doi:10.3390/plants9050639

10.3390/plants905063932429540PMC7284851
8

Jeong, J., Y. Ha, and Y. Kwack 2024, The selection of lettuce seedlings for transplanting in a plant factory by a non-destructive estimation of leaf area and fresh weight. Horticulturae 10:919. doi:10.3390/horticulturae10090919

10.3390/horticulturae10090919
9

Joalland S., C. Screpanti, A. Gaume, and A. Walter 2016, Belowground biomass accumulation assessed by digital image based leaf area detection. Plant and soil 398:257-266. doi:10.1007/s11104-015-2660-9

10.1007/s11104-015-2660-9
10

Kim C., and van M.W. Iersel 2022, Morphological and physiological screening to predict lettuce biomass production in controlled environment agriculture. Remote Sens 14:316. doi:10.3390/rs14020316

10.3390/rs14020316
11

Kim I.G., K.J. Park, and B.J. Kim 2013, Analysis of meteorological factors on yield of Chinese cabbage and radish in winter cropping system. Korean J Agric For Meteorol 15:59-66. doi:10.5532/KJAFM.2013.15.2.059 (in Korean)

10.5532/KJAFM.2013.15.2.059
12

Kim Y.S., Y.G. Park, and B.R. Jeong 2019, Seedling quality, and early growth and fruit productivity after transplanting of squash as affected by plug cell size and seedling raising period. J Bio Environ Con 28:185-196. doi:10.12791/KSBEC.2019.28.3.185 (in Korean)

10.12791/KSBEC.2019.28.3.185
13

Lazarević B., Z. Šatović, A. Nimac, M. Vidak, J. Gunjača, O. Politeo, and K. Carović-Stanko 2021, Application of phenotyping methods in detection of drought and salinity stress in basil (Ocimum basilicum L.). Front Plant Sci 12:629441. doi:10.3389/fpls.2021.629441

10.3389/fpls.2021.62944133679843PMC7929983
14

Lee J., B. Lee, K. Kim, and J. Son 2000, Growth of vegetable seedlings in decomposed expanded rice hull-based substrates. J Korean Soc Hortic Sci 41:249-253. (in Korean)

15

Lee J.E., Y.S. Shin, H.W. Do, J.D. Cheung, and Y.H. Kang 2016, Effect of seedling quality and growth after transplanting of Korean melon nursed under LED light sources and intensity. J Bio Environ Con 25:294-301. doi:10.12791/KSBEC.2016.25.4.294 (in Korean)

10.12791/KSBEC.2016.25.4.294
16

Lee J.S., H.I. Lee, and Y.H. Kim 2012, Seedling quality and early yield after transplanting of paprika nursed under light-emitting diodes, fluorescent lamps and natural light. J Bio Environ Con 21:220-227. (in Korean)

17

Lee S.G., S.K. Kim, H.J. Lee, C.S. Choi, and S.T. Park 2016, Impacts of climate change on the growth, morphological and physiological responses, and yield of kimchi cabbage leaves. Hortic Environ Biotechnol 57:470-477. doi:10.1007/s13580-016-1163-9

10.1007/s13580-016-1163-9
18

Leskovar D., and Y. Othman 2016, Low nitrogen fertigation promotes root development and transplant quality in globe artichoke. HortScience 51:567-572. doi:10.21273/HORTSCI.51.5.567

10.21273/HORTSCI.51.5.567
19

Liu A., and J.G. Latimer 1995, Root cell volume in the planter flat affects watermelon seedling development and fruit yield. HortScience 30:242-246. doi:10.21273/HORTSCI.30.2.242

10.21273/HORTSCI.30.2.242
20

Ma D., H. Maki, S. Neeno, L. Zhang, L. Wang, and J. Jin 2020, Application of non-linear partial least squares analysis on prediction of biomass of maize plants using hyperspectral images. Biosyst Eng 200:40-54. doi:10.1016/j.biosystemseng.2020.09.002

10.1016/j.biosystemseng.2020.09.002
21

Ministry of Agriculture, Food and Rural Affairs (MAFRA) 2024, Major statistics on agriculture, livestock, and food. MAFRA, Sejong, pp 343.

22

Nabwire S., C. Wakholi, M.A. Faqeerzada, M.A.A. Arief, M.S. Kim, I. Baek, and B.K. Cho 2022, Estimation of cold stress, plant age, and number of leaves in watermelon plants using image analysis. Front Plant Sci 13:847225. doi:10.3389/fpls.2022.847225

10.3389/fpls.2022.84722535251113PMC8895302
23

Nair A., and B. Carpenter 2016, Biochar rate and transplant tray cell number have implications on pepper growth during transplant production. HortTechnology 26:713-719. doi:10.21273/HORTTECH03490-16

10.21273/HORTTECH03490-16
24

NeSmith D.S., and J.R. Duval 1998, The effect of container size. HortTechnology 8:495-498.

10.21273/HORTTECH.8.4.495
25

Nomura K., E. Wada, M. Saito, H. Yamasaki, D. Yasutake, T. Iwao, I. Tada, T. Yamazaki, and M. Kitano 2022, Estimation of the leaf area index, leaf fresh weight, and leaf length of Chinese chive (Allium tuberosum) using nadir-looking photography in combination with allometric relationships. Hortscience 57:777-784. doi:10.21273/HORTSCI16569-22

10.21273/HORTSCI16569-22
26

Otoya P.E.L., and S.R.P. Gardini 2021, A machine vision system based on RGB-D image analysis for the artichoke seedling grading automation according to leaf area. 2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE) 176-181. doi:10.1109/ECICE52819.2021.9645676

10.1109/ECICE52819.2021.9645676
27

Qin K., and D.I. Leskovar 2020, Humic substances improve vegetable seedling quality and post-transplant yield performance under stress conditions. Agriculture 10:254. doi:10.3390/agriculture10070254

10.3390/agriculture10070254
28

Rossi R., S. Costafreda-Aumedes, L. Leolini, C. Leolini, M. Bindi, M. Moriondo 2022, Implementation of an algorithm for automated phenotyping through plant 3D-modeling: A practical application on the early detection of water stress. Comput Electron Agric 197:106937. doi:10.1016/j.compag.2022.106937

10.1016/j.compag.2022.106937
29

Rural Development Administration (RDA) 2021, Hydroponics. Rural Development Administration, Jeonju, Korea, pp 160. (in Korean)

30

Statistics Korea 2024, Survey of agricultural production. Available via https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1ET0028&conn_path=I2 Accessed 13 September 2025

31

Tian S., Z. Wang, J. Yang, Z. Huang, R. Wang, L. Wang, and J. Dong 2017, Development of an automatic visual grading system for grafting seedlings. Adv Mech Eng 9:1687814016686265. doi:10.1177/1687814016686265

10.1177/1687814016686265
32

Tong J.H., J.B. Li, and H.Y. Jiang 2013, Machine vision techniques for the evaluation of seedling quality based on leaf area. Biosyst Eng 115:369-379. doi:10.1016/j.biosystemseng.2013.02.006

10.1016/j.biosystemseng.2013.02.006
33

Tremblay N., and M. Senécal 1988, Nitrogen and potassium in nutrient solution influence seedling growth of four vegetable species. HortScience 23:1018-1020. doi:10.21273/HORTSCI.23.6.1018

10.21273/HORTSCI.23.6.1018
34

Walters S.A., H.A. Riddle, and M.E. Schmidt 2005, Container cell volume and transplant age influences muskmelon development and yield. J Veg Sci 11:47-55. doi:10.1300/J484v11n01_05

10.1300/J484v11n01_05
35

Wenneck G., R. Saath, R. Rezende, V. Vila, A.F.B.A. Andrean, and D. Terassi 2022, Cucumber seedlings production: Tray size impact on development. Braz J Biosyst Eng 16:1079. doi:10.18011/bioeng.2022.v16.1079

10.18011/bioeng.2022.v16.1079
36

Wi S.H., H.J. Lee, S. An, and S.K. Kim 2020, Evaluating growth and photosynthesis of kimchi cabbage according to extreme weather conditions. Agronomy 10:1846. doi:10.3390/agronomy10121846

10.3390/agronomy10121846
37

Xiao Z., Y. Tan, X. Liu, and S. Yang 2019, Classification method of plug seedlings based on transfer learning. Appl Sci 9:2725. doi:10.3390/app9132725

10.3390/app9132725
38

Yuan F., G. Ma, Q. Zeng, J. Liu, Z. Xiao, Z. Zou, and X. Wang 2025, RGB and point cloud-based intelligent grading of pepper plug seedlings. Agronomy 15:1568. doi:10.3390/agronomy15071568

10.3390/agronomy15071568
39

Zhang L., Z. Xu, D. Xu, J. Ma, Y. Chen, and Z. Fu 2020, Growth monitoring of greenhouse lettuce based on a convolutional neural network. Hortic Res 7:124. doi:10.1038/s41438-020-00345-6

10.1038/s41438-020-00345-632821407PMC7395764
Information
  • Publisher :The Korean Society for Bio-Environment Control
  • Publisher(Ko) :(사)한국생물환경조절학회
  • Journal Title :Journal of Bio-Environment Control
  • Journal Title(Ko) :생물환경조절학회지
  • Volume : 34
  • No :4
  • Pages :476-484
  • Received Date : 2025-09-29
  • Revised Date : 2025-10-14
  • Accepted Date : 2025-10-20
  • DOI :https://doi.org/10.12791/KSBEC.2025.34.4.476
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