Modeling and prediction of dry matter production by tomato plants in year-round production based on short-term, low-truss crop management
2020
A:PS
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Title
Modeling and prediction of dry matter production by tomato plants in year-round production based on short-term, low-truss crop management
Publication Date
2020
Call Number
A:PS
Summary
We investigated dry matter (DM) and fruit production of tomato plants, the effects of CO2 levels on DM production, and light-use efficiency (LUE) in a tomato production system based on short-term, low-truss crop management during six consecutive periods over one year in a commercial greenhouse. The CO2 concentration, total dry matter production (TDM), and LUE differed significantly among the periods. Since LUE was significantly correlated with the mean daytime CO2 concentration, we modeled LUE empirically from that. We developed a model to predict LUE and DM production of tomato plants and validated the model using data from the six periods. We accurately predicted LUE and TDM within a range of ca. 400 to 650 µmol·mol−1 daytime CO2 concentration. However, when daytime CO2 concentration was beyond this range, or when a management failure such as inadequate irrigation occurred, predicted values differed significantly from observed values.
Journal Citation
89(4):417-424, THE HORTICULTURE JOURNAL
Contact Information
harvest@worldveg.org
Record Appears in
Research > Published Articles