Microclimate control is increasingly widespread in limited agricultural environments. This is especially important for the cultivation of plants that tolerate significantly different thermal and hygrometric conditions. Nevertheless, there is much to be done in automation and control technology in this area to achieve the best results in both quantitative and qualitative terms of the product. This applies especially to horticultural crops that are sensitive to the cultivation environment and microclimate. This work aims to characterize the microclimate parameters in a confined agricultural environment with perforated ducts for air conditioning supply. For this work, a microclimate control unit was used instead of a lettuce crop. It was placed into a confined agricultural environment at different locations in the space to obtain the main microclimate parameters. After setting the input of the microclimate environment, the instrument measured a series of physical quantities (temperature, radiant temperature, humidity, and air velocity). Tests were carried out by taking the optimum day temperature constant for growing lettuce and by varying the supply airflow rate by setting the fan speed at 30%, 50%, and 80%. The results of these tests are essential for performing real-time control of the microclimate environment and for managing parameters for optimization of the entire system. In addition, the air velocity test showed adequate velocity reduction and good air mixing. The values obtained are generally acceptable for indoor cultivation and the conditions created are suitable for growing plants in such an environment. Light is an essential need for plants so that plants can carry out the photosynthesis process properly. In indoor DWC hydroponics system, the source of UV light is LED lights for plants. Some of the advantages of using LED light include a small light spectrum, less heat production, low power consumption, and wavelengths of 660 m and 450 m that are needed by plants. This research project aims to create a DWC hydroponic system for growing red lettuce in an indoor hydroponics and see the effect of LED grow light on the growth of red lettuce. DWC hydroponics uses AB-Mix nutrients that are channeled through inch PVC pipes using pump power. The hydroponic rack used has a height of 1.7 m and a width of 40 cm and has 3 shelves, where each shelf has 9 nutrient containers. The red lettuce plants in the DWC system were provided with different light treatments by installing shading nets with different percentages of light penetration, namely, 75%, 50%, and 0%. From the results of these treatments, the average yield of red lettuce was 300 grams on the top shelf, 400 grams on the middle shelf, and 600 grams on the bottom shelf.
Plants can be identified using several variables, such as seeds’ shapes, colors, and sizes. However, several types of plants have close similarities to seed shapes. Therefore, additional characteristics are necessary to support the identification process. This study applied machine learning with the PCA method to identify plant species from seed shapes. The PCA simplifies the observed variables by reducing data dimensions and storing 75% of the information. The procedure did not eliminate too much important information while reducing data size and processing time. We collected 100 images of plant seeds similar to one another, such as sapodilla seeds, soursop, cucumber, star fruit, grape, melon, apple, lime, watermelon, and chili. A measurement system was designed using the K-Fold Cross Validation, and 10 tables of experimental results discovered a good level of accuracy of 83%. The Omission error occurred in the seeds of soursop, starfruit, grape, apple, lime, and watermelon while the most commission errors occurred in apple seeds (8 times).
This research aimed to design a plant fertilizing and watering system that can be controlled and observed through a smartphone and use the solar electric energy source. The results of this study can ease the work of farmers in terms of energy and cost because they allow the fertilizing and watering processes to run automatically. The system is assembled using the following components: 100WP solar module, 30A solar charge controller, deep-cycle battery, Arduino Uno, ESP8266WiFi, DHT11 sensor, soil moisture sensor, and 12V DC electric solenoid valve. This system works in the following way: if the soil moisture sensor reads that the soil is dry and if the air temperature sensor reads that the air is cool, then the microcontroller will order electric faucets to drain water containing fertilizer to the ground until the soil becomes wet. This system is supported by connection to the Internet so it can be controlled and observed from an Android-based smartphone. The calculation conducted in an economic analysis of the system yielded cost principal of Rp47.6/l and BEP for production of 11,389 l/year.
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