Data-driven management of greenhouse high-wire fruiting vegetables using 3D scanning

Original paper: Ohashi, Y., Y. Ishigami, and E. Goto. 2020. Monitoring the growth and yield of fruit vegetables in a greenhouse using a three-dimensional scanner. Sensors. 20: 5270. doi:10.3390/s20185270

Controlled environment agriculture (CEA) for food crop production allows high productivity and efficient resource use. Applications of CEA have been expanding rapidly worldwide. However, the current limitation that slows the expansion is shortage of experienced human workers. In addition, increasing costs of labor are serious problem that slows the potential growth of CEA. More automation is needed to lower the labor input in various tasks of crop management. Automated monitoring of plant growth and morphology (structure) can allow growers to make more science-based, data-driven decisions for crop management and minimize labor, energy, water, and other resource usage.

Three-dimensional scanning technologies have developed rapidly to create a digital twin (model) for various measurements and computational analyses. There are affordable technologies and various data processing software.  The authors of this paper are a team of horticultural engineers at Chiba University (Matsudo, Japan) and demonstrated usage of 3D scanning for greenhouse crop management. Their specific objective was to estimate key metrics of plant growth and productivity, such as leaf area, plant height, biomass, and fruit yield for three major fruiting crops grown in greenhouse (tomato, cucumber, and sweet (bell) pepper).

The tests were conducted in a greenhouse located in Chiba University. Different ages (sizes) of tomato, cucumber and pepper plants of selected cultivars are used for the tests. A hand-held 3D scanner (DPI-8X, Opt Technologies, Tokyo) was used to scan individual plants as well as a group (canopy) of six plants grown using a typical soilless cultivation method with a common density applied in commercial greenhouses. The scan generated a set of many data points with xyz coordinates (point cloud) which are then converted to a digital ‘surface model’ for finding leaf area and a digital ‘solid model’ for finding fruit yield. The leaf areas were then used for finding biomass (dry weight) of leaves and whole plants using predetermined correlation between these variables. However, accuracy of estimation of leaf area and plant biomass for tomato was less than that for cucumber and pepper, due to more complex leaf morphology (compound leaves with many leaflets) of tomato than the other crops.

The authors also estimated the leaf areas at different heights of canopy, demonstrating the capacity of quantifying leaf distributions inside the canopy.  This information is especially useful for finding levels of available light at various heights inside the canopy. The information of light distribution in the canopy will help growers use more data-driven crop management practices including leaf pruning, plant density management, so that light use efficiency can be maximized.

Yield prediction based on 3D scans showed reasonable correlation with measured yield (R2 > 0.7) for tomato and pepper. The RGB data obtained by the scanner was used for detecting ripe fruit, whose point cloud data were converted to sold (voxel) models. Fruit volume estimated by the solid model was then converted to fruit mass (grams) by a predetermined fruit density (ratio of mass and volume). Cucumber was not scanned for fruit analysis as fruit shapes were extracted based on colors (red or yellow) and fruit color of cucumbers is green (difficult to distinguish from leaf images).  Similarly, immature (unripe) fruits of tomato and pepper were not extracted either for the same issue of color-based recognition.  Overall, fruit yield estimate was least accurate compared with leaf area and other metrics. The inaccuracy is based on the difficulty to scan the opposite side of fruit.

Although dense canopy and overlapping leaves add difficulty in achieving high accuracy, this preliminary effort to demonstrate the potential use of a 3D scanner for crop management was successful. Coefficient of determination (R2) was almost always high (>0.8) except LAI for tomato.  The tools (hardware and software) that they used for scanning and data conversions were commercially available. Although more work will need to be done to improve the accuracy and perhaps to streamline the logistics of measurement and data processing, this is a valuable demonstration of what we can do with a simple handheld 3D scanner or similar tool in future greenhouse crop production.


Welcome to 2021 HCS 8830, ‘Current research topics on controlled environment plant physiology and technology’!

A small amount of UV radiation is needed for tomato plant health

Original paper: Kubota, C., T. Eguchi, and M. Kroggel. 2017. UV-B radiation dose requirement for suppressing intumescence injury on tomato plants. Scientia Horticulturae. 226:366-371.


UV-B radiation (300-320 nm) has the shortest wavelength of the sunlight spectrum in the natural environment. Too strong UV radiation can cause issues such as leaf burn, but too little UV radiation also becomes problematic for certain species of plants including tomato. The sensitivity varies among varieties of tomato and a particular rootstock tomato used for grafting, for example, is a very sensitive one that must be grown under light including UV-B.  A typical disorder caused by lack of UV-B radiation are leaf tumors called intumescence (or oedema). In severe cases, plants cannot grow and usually die. This becomes problematic when plants are grown under protected environments (such as tunnels) covered with UV-blocking plastic material or under sole source electric lighting that does not emit UV radiation (such as LEDs). A research group led by Chieri Kubota (currently at the Ohio State University) identified the needed amount of UV radiation to maintain plants without causing such disorder.  This group also worked on other innovative approaches to mitigate intumescence injury, including a discovery of an effective LED lighting protocol to mitigate the intumescence injury.


In their experiment, they grew rootstock tomato ‘Beaufort’ plants as their experimental plant material for its high sensitivity to induce intumescence under UV-B deficient light environment.  The lamps that they tested were red and blue LEDs or cool-white T5 fluorescent lamps. While red and blue LEDs do not emit UV radiation at all, T5 fluorescent lamps do emit small amount of UV-B radiation. When ‘Beaufort’ plants were grown under LEDs, plants developed massive amounts of intumescence, but the injury was less severe under T5 fluorescent lamps due to the UV radiation.  UV-B supplementation was examined for the plants under LEDs at varied hours of UV-B exposure (1.5, 3.0 and 6.0 hours) at a very low intensity of UV-B of 0.12 W m-2 (or 0.31 μmol m-2 s-1). The UV-B exposure was conducted during the night time (every night), rather than day time. Kubota’s group showed that an increasing amount (dose) of UV-B exposure drastically improved ‘Beaufort’ tomato plant health.  The highest daily dose of UV-B they examined was 2.6 kJ m-2 (or 6.7 mmol m-2). This UV-level is less than one-tenth of what you can expect outdoors during the summer.  Under this dose of 2.6 kJ m-2, plants still exhibited a minor injury of intumescence. So the group used a mathematical approach (linear regression) to estimate the dose of UV-B that would have eliminated the intumescence injury, which was 5 kJ m-2 (or 14 mmol m-2), about twice of the highest examined dose in this study, but still far below the natural UV level of sunlight.


The impact of this study includes possible contributions to the design of plant growing facilities that use LED lighting.  The linear dose response they described in this study is particularly useful as one can choose a combination of UV-B intensity and exposure time suitable for their production setting.  A lower intensity for long exposure and a higher intensity for shorter exposure could yield the same effective dose.  Kubota group also showed that night-time application of UV-B is effective and this is helpful for growers who do not want to expose workers to UV-B light while they are in the facility.  The known/Knowing the dose response also makes the application methods more flexible, including using a movable light source over the plant canopy. The finding will be helpful for Indoor farming as well as greenhouse crop production.