Chinese Journal of Agrometeorology ›› 2023, Vol. 44 ›› Issue (07): 611-623.doi: 10.3969/j.issn.1000-6362.2023.07.006

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Construction of A Tomato Growth Rate Simulation Model Based on Climate Suitability Index

GUO Shen-bo,LIU Fu-hao,WANG Di,HUANG Bo,CAO Yan-fei   

  1. College of Horticulture, Northwest A&F University/Key Laboratory of Northwest Facility Horticulture Engineering, Ministry of Agriculture and Rural Affairs, Yangling 712100, China
  • Received:2022-08-20 Online:2023-07-20 Published:2023-07-17

Abstract: The microclimate of the facility is an important influencing factor for tomato growth and is characterized by complex parameters and rapid changes. In order to scientifically grasp the microclimate characteristics and explore the relationship between microclimate suitability index and tomato growth rate, two experiments were conducted in 2021 using tomatoes as the test material in insulated plastic greenhouses, with ‘Provence’ as the test tomato variety for the spring crop (January 18-May 24, 2021) and ‘Baolufuqiang’as the test tomato variety for the autumn crop (August 27-December 31, 2021), both in substrate bags. Authors adopt conventional field management methods. Microclimate including temperature, relative humidity, solar radiation, CO2 concentration and vapor pressure deficit (VPD) were monitored in the facility, and tomato morphological indicators and growth rate were measured every 7 days. Authors proposed a method for calculating the microclimate suitability index for facilities using factor analysis, and constructed a tomato growth rate simulation model based on the microclimate suitability index using multiple linear regression method to simulate and verify tomato growth rate in autumn crop. The results showed that the microclimate suitability identified based on the computational method matched 75% with that based on manual empirical judgment, and the correlation between microclimate suitability and the growth amounts of fresh tomato weight (r=0.690), dry weight (r=0.623), and plant height (r=0.748) reached significant levels (P<0.05). In the simulation results of the growth rate of autumn crop, the fitting degree and accuracy of the growth rate simulation were better. The results of autumn crop tomato growth rate simulations showed good fit and accuracy, with simulated relative growth rate at seedling stage with measured values R2=0.875 and RMSE=0.048d−1, and simulated absolute growth rate at flowering and fruiting stage with measured values R2=0.785 and RMSE=0.877g·d−1. In summary, this study provides a new method for quantitative facility microclimate analysis, which is more comprehensive than temperature determination, and also provides a new way of thinking for the construction of tomato growth rate model.

Key words: Tomato, Factor analysis, Microclimate suitability, Growth rate