The objective of this study was to investigate the growth and light-intercepting characteristics of tomatoes when movable benches are used in their cultivation. We cultivated tomatoes in a greenhouse (168 m2) during summer (9 July–9 September 2018) under different furrow distances (F1.0 = 1.0 m and F1.6 = 1.6 m) and movable benches (M indicates that the furrow distance = 0.4–0.8 m). Compared to the other treatments, when the movable bench was used to the change furrow distance depending on the plant growth stage (M treatment), the percentage of canopy light interception increased to ~90% at the early stage of plant growth (~20 days after transplanting). The percentage of canopy light interception for different treatments increased in the order of M > F1.0 > F1.6, and it increased towards the end of cultivation. In addition, the yield per unit area exhibited the same trend. Therefore, the solar radiation inside a greenhouse can be efficiently intercepted by plants when movable benches are used. This indicated that it was possible to increase plant yield per unit area using movable benches in plant cultivation.
Monitoring the growth of fruit vegetables is essential for the automation of cultivation management, and harvest. The objective of this study is to demonstrate that the current sensor technology can monitor the growth and yield of fruit vegetables such as tomato, cucumber, and paprika. We estimated leaf area, leaf area index (LAI), and plant height using coordinates of polygon vertices from plant and canopy surface models constructed using a three-dimensional (3D) scanner. A significant correlation was observed between the measured and estimated leaf area, LAI, and plant height (R2 > 0.8, except for tomato LAI). The canopy structure of each fruit vegetable was predicted by integrating the estimated leaf area at each height of the canopy surface models. A linear relationship was observed between the measured total leaf area and the total dry weight of each fruit vegetable; thus, the dry weight of the plant can be predicted using the estimated leaf area. The fruit weights of tomato and paprika were estimated using the fruit solid model constructed by the fruit point cloud data extracted using the RGB value. A significant correlation was observed between the measured and estimated fruit weights (tomato: R2 = 0.739, paprika: R2 = 0.888). Therefore, it was possible to estimate the growth parameters (leaf area, plant height, canopy structure, and yield) of different fruit vegetables non-destructively using a 3D scanner.
We constructed 3D models of the greenhouse 168 m 2 and tomato plants plant height: 150 cm . The point cloud data of tomato plants was acquired by a 3D scanner and converted to the 3D model, which was constructed using polygons. The canopy 3D model was installed in the greenhouse 3D model. In addition, the date, time, latitude, longitude, global solar radiation, and optical properties of objects, such as plants and covering material, were used as input values to estimate the amount of solar radiation received by canopy models using the ray tracing. The amount of solar radiation received by the canopy models at different layers under different furrow distances 60 -160 cm was calculated every 1 h. The lower layer and the middle layer of tomato plants were saturated with solar radiation at furrow distances of 120 cm and 100 cm, respectively. However, the radiation received by the upper layer of tomato plants did not change across the range 60 -160 cm of investigated furrow distances. This investigation has provided a visual demonstration of the relationship between the arrangement of cultivated fruit and vegetable plants, such as tomato, in the greenhouse and the amount of solar radiation received.
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