Vegetable Commodity Organ Quality Formation Simulation Model (VQSM) in Solar Greenhouses

Chen Cheng, Liping Feng, Chaoyang Dong, Xianguan Chen, Feiyun Yang, Lu Wu (), Jing Yang, Chengsen Zhao, Guoyin Yuan and Zhenfa Li ()
Additional contact information
Chen Cheng: College of Ecology, Lishui University, Lishui 323000, China
Liping Feng: College of Resources and Environment Sciences, China Agricultural University, Beijing 100193, China
Chaoyang Dong: Tianjin Climate Center, Tianjin 300074, China
Xianguan Chen: College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Feiyun Yang: China Meteorological Administration Training Center, Beijing 100081, China
Lu Wu: China Meteorological Administration Training Center, Beijing 100081, China
Jing Yang: College of Ecology, Lishui University, Lishui 323000, China
Chengsen Zhao: College of Ecology, Lishui University, Lishui 323000, China
Guoyin Yuan: College of Ecology, Lishui University, Lishui 323000, China
Zhenfa Li: Tianjin Climate Center, Tianjin 300074, China

Agriculture, 2024, vol. 14, issue 9, 1-16

Abstract: Cucumber ( Cucumis sativus L.) and celery ( Apium graveolens L.) are among the most widely cultivated vegetable crops, belonging to the melon and leafy vegetable categories, respectively. This study aims to provide predictions for the quality formation of greenhouse cucumber and celery, as well as technical support for intelligent vegetable production management. Based on the light and temperature response characteristics of cucumber and celery growth and development and using the experimental varieties ‘Jinsheng 206’ for cucumber and ‘Juventus’ for celery, the observational data from a five-cropping season trial over 2 years were utilized. By analyzing the relationship between the growth and development of vegetables and key meteorological factors (radiation and temperature), simulation models for quality formation were constructed using the day–night temperature difference method ( ATD ) and the product of thermal effectiveness and the photosynthetically active method ( TEP ) as independent variables. The model parameters were determined and the model was validated using independent trial data. The results showed the following: (1) There exist quantifiable relationships between different quality indicators and ATD or TEP . These relationships are mainly presented through linear functions, exponential functions, logarithmic function, and logical functions. (2) The normalized root mean square error (NRMSE) of the cucumber quality model ranges from 1.13% to 29.53%, and the NRMSE of the celery quality model ranges from 1.63% to 31.47%. (3) Based on two kinds of normalization methods, the average NRMSE of the VQSM model is 13.72%, demonstrating a relatively high level of accuracy in simulation. These results demonstrate that the proposed model can dynamically and accurately simulate the quality formation process of vegetables, providing a theoretical basis and data support for the research on productivity and the economic benefits of greenhouse crops.

Keywords: cucumber; celery; day–night temperature difference; product of thermal effectiveness and photosynthetically active method; appearance quality; physicochemical quality (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/14/9/1531/pdf (application/pdf)
https://www.mdpi.com/2077-0472/14/9/1531/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:14:y:2024:i:9:p:1531-:d:1472053

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().