The growth of plants and their glucosinolate content largely depend on the cultivation environment; however, there are limited reports on the optimization of ambient environmental factors for kale grown in plant factories. This study was conducted to investigate the effects of temperature, relative humidity, and the carbon dioxide (CO2) concentration on kale growth and glucosinolate content in different growth stages of cultivation in a plant factory. Kale was grown under different temperatures (14, 17, 20, 23, and 26 °C), relative humidities (45, 55, 65, 75, and 85%), and CO2 concentrations (400, 700, 1000, 1300, and 1600 ppm) in a plant factory. Two and four weeks after transplantation, leaf samples were collected to evaluate the physical growth and glucosinolate contents. The statistical significance of the treatment effects was determined by two-way analysis of variance, and Duncan’s multiple range test was used to compare the means. A correlation matrix was constructed to show possible linear trends among the dependent variables. The observed optimal temperature, relative humidity, and CO2 range for growth (20–23 °C, 85%, and 700–1000 ppm) and total glucosinolate content (14–17 °C, 55–75%, and 1300–1600 ppm) were different. Furthermore, the glucosinolate content in kale decreased with the increase of temperature and relative humidity levels, and increased with the increase of CO2 concentration. Most of the physical growth variables showed strong positive correlations with each other but negative correlations with glucosinolate components. The findings of this study could be used by growers to maintain optimum environmental conditions for the better growth and production of glucosinolate-rich kale leaves in protected cultivation facilities.

A seedling picking device is an essential component for an automatic transplanter to automatically convey the seedling to the dibbling part. It is necessary to find the appropriate material and dimensions for the picking device gears to avoid mechanical damage and increase their durability. Therefore, the objectives of this research were to analyze the stress of a picking device gear mechanism in order to select suitable materials and dimensions, and to predict the fatigue life by considering the damage level. The picking device gear shaft divided the input power into two categories, i.e., crank and cam gear sets. Finite element analysis simulation and American Gear Manufacturers Association standard stress analysis theory tests were conducted on both of the crank and cam gear sets for different materials and dimensions. A test bench was fabricated to collect the load (torque) data at different gear operating speeds. The torque data were analyzed using the load duration distribution method to observe the cyclic load patterns. The Palmgren–Miner cumulative damage rule was used to determine the damage level of the picking mechanism gears with respect to the operating speed. The desired lifespan of the transplanter was 255 h to meet the real field service life requirement. Predicted fatigue life range of the picking mechanism gears was recorded as from 436.65 to 4635.97 h, making it higher (by approximately 2 to 18 times) than the lifespan of the transplanter. According to the analyses, the “Steel Composite Material 420H carbon steel” material with a 5 mm face width gear was suitable to operate the picking device for a 10-year transplanter service life. The analysis of stress and fatigue presented in this study will guide the design of picking device gears with effective material properties to maintain the recommended service life of the pepper transplanter.

The productivity of horticultural crops in an artificial light condition are highly influenced by the structure of plant and the area coverage. Accurate measurement of leaf area is very important for predicting plant water demand and optimal growth. In this paper, we proposed an image processing algorithm to estimate the ice-plant leaf area from the RGB images under the artificial light condition. The images were taken using a digital camera and the RGB images were transformed to grayscale images. A binary masking was applied from a grayscale image by classifying each pixel, belonging to the region of interest from the background. Then the masked images were segmented and the leaf region was filled using region filling technique. Finally, the leaf area was calculated from the number of pixel and using known object area. The experiment was carried out in three different light conditions with same plant variety (Ice-plant, Mesembryanthemum crystallinum). The results showed that the correlation between the actual and measured leaf area was found over 0.97 (R2:0.973) by our proposed method. Different light condition also showed significant impact on plant growth. Our results inspired further research and development of algorithms for the specific applications.

No abstract

Precision water management and crop growth monitoring are essential where water is a scarce, especially in desert soils. The purpose of the study was to control the irrigation and real-time image acquisition for monitoring the rice cultivation inside the net house under the UAE desert soil. An automated data acquisition system was constructed, installed, and tested in the experimental site at Al-Foah, Al-Ain. Soil water content sensors were placed in the different depths of desert soils, and an automatic irrigation logic was implemented to maintain the average of 30% desired water content level in desert soils. The irrigation rate was controlled based on the sensor data and the on/off of the pump and valves. When the average soil water content percentage level exceeds 30%, the pump and solenoid valve automatically turned off and vice versa. A Raspberry Pi operating system was used to control the irrigation, and a Raspberry Pi camera system was used to capture the real-time images for monitoring the rice growth and development. A web server was developed to upload and display the sensor values and images using python programing language through the embedded Wi-Fi network service. The web-based monitoring system was allowed to monitor the rice field situation from anywhere and download data from the site. The existing irrigation technique would help to grow the rice in UAE desert soil environments.