Articles

Prediction of yield based on fruit set and dry matter production in greenhouse tomato

Article number
1404_173
Pages
1249 – 1256
Language
English
Abstract
This study aimed to predict the yield of high-Brix tomatoes in a large-scale commercial greenhouse with our dry matter distribution to fruits (DDF) fluctuation model.
The greenhouse area was 1944 m2, and 11593 plants were grown from February 25, 2017, to February 16, 2018. First, we identified average number of fruit set at n DAT (aNFSn). aNFSn fluctuated from 1.52 to 6.5 fruits m‑2 day‑1 throughout the experiment.
Second, we predicted the fluctuation of dry matter distribution to fruits at n DAT (DDFn) based on number of fruits on the plant (NFPn). The relationship between NFPn and DDFn follows the linear regression function.
To set the maximum DDFn to 0.75 g g‑1, we adjusted the coefficient by adjusting the light use efficiency (LUE; g MJ‑1), which was used for the total dry matter production (TDM) calculation, to 1.65. When the LUE was 1.65, the coefficient a was 0.0042 and the coefficient of determination (R2) was 0.87. DDFn reached the highest of 0.75 g g‑1 in June and then it decreased continuously to 0.39 g g‑1 in August.
The fluctuations in DDFn occurred later than those in TDMn and aNFSn Then, we predicted fresh yield at n DAT (FYpn) and compared it with observed one (FYon). FYon and FYpn reached more than 70 g m‑2 before September.
Both FYon and FYpn decreased from the first of August to the middle of September.
After mid-October, FYon and FYpn did not match well for timing and amount.
MAPE between FYon and FYpn was 19.6 and 25.4% when using our DDF fluctuation model or previous DDF constant model, respectively.
These results suggest that we succeeded to predict DDF based on fruit set data and improved the accuracy of yield prediction using our DDF fluctuation model with unintended changes in the fruit set condition.

Publication
Authors
M. Itoh, Y. Muramatsu, D.H. Ahn, T. Higashide
Keywords
high Brix, hydroponics, dry matter distribution, dry yield, light use efficiency, maturation, number of fruits
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