Farm Engineering and Automation Technology Journal

Development of a Semi-Automatic Pork Floss Shredding Machine for Community Enterprises

PIYAPONG SINGBUA — 2025-12-26

This study aimed to design and develop a semi-automatic shredded pork machine for the Krua Khao Kaeng community enterprise in Maha Sarakham Province to enhance production efficiency and reduce manual labor in traditional pork floss processing. The developed prototype measures 60×120×106 cm, is constructed from SUS 304 stainless steel compliant with GMP standards, and is powered by a 1-hp motor with adjustable roller speed and gap. Experimental results revealed that the optimal condition at a roller speed of 90 rpm and a roller gap of 3 mm achieved a maximum production rate of 49.8 ± 1.0 kg/h, compared with 2.5 kg/h from manual operation—representing a 1,892% increase or approximately 20 times higher productivity. The uniformity of shredded pork, as evaluated by experts, received an average score of 4.60 out of 5, while user satisfaction was rated at 4.53 out of 5, indicating a high level of acceptance. The findings confirm that the semi-automatic shredded pork machine effectively improves production capacity, maintains product quality, and provides a practical and hygienic solution for small-scale community food enterprises.

A Simple 3D Pet Food Pellet Measurement Application based on Intel RealSense and Streamlit

วิชิต เรือนชัย — 2025-12-26

Quality control of pet food pellet size is a critical factor in the manufacturing process. Currently, most inspections rely on manual labor, which leads to delays, high error rates, and the inability to perform real-time monitoring. This research proposes an automated 3D pet food pellet measurement system to replace manual inspection. The system applies image processing techniques, specifically thresholding and contour detection, utilizing an Intel RealSense D435i depth camera to analyze width, length, and thickness. To ensure convenient and fast access to the results, the system was developed as a web application using the Streamlit library. Experimental results comparing the system with a vernier caliper across three pellet shapes showed average accuracies of 93.55% for width, 93.93% for length, and 93.62% for thickness. This process is significantly faster than manual measurement. Consequently, this system demonstrates potential as an effective and simple-to-develop quality control tool for the pet food industry.

Self-Adjusting Greenhouse System for Black Oyster Mushroom Cultivation Using Automatic CO2 Responsive Ventilation Control

จาริณี จงปลื้มปิติ — 2025-12-26

This study aimed to develop an adaptive smart greenhouse system for oyster mushroom cultivation capable of automatically controlling ventilation based on carbon dioxide concentration. The system utilized a Non-Dispersive Infrared sensor integrated with a microcontroller and an Internet of Things (IoT) platform to collect real-time data and actuate the ventilation mechanism. Experiments were conducted in two identical mushroom houses: one without a ventilation system and another equipped with an automatic ventilation control system. A CO₂ sensor was installed at the central position of each house to monitor the environmental concentration under actual cultivation conditions. Statistical analysis using a paired sample t-test revealed that the average CO₂ concentration inside the greenhouse with automatic ventilation was 727.61 ppm, significantly lower than the 1,198.30 ppm measured in the unventilated house (p < 0.05) The system effectively reduced CO₂ accumulation by approximately 39.3% and decreased the standard deviation from 348.8 ppm to 85.5 ppm, indicating over fourfold improvement in environmental stability. Time-series analysis showed that the system consistently maintained CO₂ levels between 700–1,000 ppm, which is optimal for oyster mushroom growth throughout day and night cycles. These results confirm that the developed automated control system enhances environmental stability, reduces labor demand, and provides a reliable and sustainable solution for precision mushroom cultivation under the concept of smart agriculture.

Development of a prototype device for automatic plant watering using a soil moisture detection system

กิตตินันท์ บุญศิริ — 2025-12-26

This research aims to develop a prototype automatic plant-watering system that operates based on soil moisture levels measured by a soil moisture sensor. The system is designed to reduce the users’ burden of plant care, particularly when regular watering is not possible. The prototype was tested using potted plants grown in loamy soil to evaluate the suitability of moisture thresholds for automatic control. The system consists of a soil moisture sensor, a microcontroller (e.g., Arduino or ESP32), and a water pump, all controlled automatically by predefined moisture thresholds. When soil moisture falls below the threshold, the system activates the water pump to irrigate the plant, and the pump stops once the moisture level reaches the upper limit. The experimental procedure included calibrating the sensor using the oven-dry method following ASTM D4959 and evaluating the prototype under real operating conditions for three consecutive days, with moisture data recorded every 30 minutes. The results show that the pump operated an average of three times per day, activating at moisture levels below approximately 12% and stopping at around 16%. Each activation delivered approximately 85–95 mL of water. Quantitative analysis indicates that the system reduced water usage by approximately 18–25% compared with manual watering while maintaining soil moisture within the desired range. The system also responded within 30 minutes of soil dryness detection. This prototype demonstrates strong potential for household or small-garden applications and can be further developed to support wireless networks or smartphone-based control for future smart farming implementations.

Comparative Performance Evaluation of Beater Blade Designs in a Banana Sheath Fiber Extraction Machine for Natural Fiber Applications

กวีพงษ์ หงษ์ทอง — 2025-12-26

This study evaluates the performance of three beater blade configurations—5-blade, 13-blade, and 32-blade designs—for banana fiber extraction, focusing on mechanical strength, production yield, fiber quality, and energy efficiency. Using standardized fresh banana sheaths, experiments were conducted with three replications per test group to ensure statistical reliability. The results demonstrate that the 5-blade configuration offers the superior engineering profile, exhibiting the lowest bending stress at 19.4 MPa and a minimum shear stress of 1.90 MPa, which is 33.5% lower than the alternative designs. This significantly enhances structural safety against fatigue and cracking. Regarding production performance, the 5-blade design achieved the highest fiber yield ($Y\%$) and Fiber Quality Index (FQI), particularly at a clearance of 0.8–0.9 mm with a 5-inch pulley. This setup optimized energy consumption, reaching a minimum specific energy of 0.06 kilowatt-hours per kilogram (kWh/kg), representing a 68.4% reduction in energy usage compared to the 32-blade model. While the 13-blade design yielded comparable quantities to the 5-blade version, it exhibited higher qualitative variability. Conversely, the 32-blade design performed poorly across all metrics due to extensive fiber damage during extraction. In conclusion, the 5-blade beater blade provides the optimal balance of material safety, yield quality, and energy efficiency, providing a definitive framework for enhancing the efficiency and sustainability of small-scale industrial banana fiber production.

The Analysis of Physical Properties and Textural of Fried Cricket Products for the Developing Automatic Frying Quality Control Systems

Wuttiphong Thonghaeo — 2025-12-26

This study aimed to investigate the physical and texture properties of crispy fried house cricket (Acheta domesticus) obtained from different sources, in order to provide fundamental data for designing an automatic frying control system to achieve consistent product quality. The samples were divided into three groups: Group A (general commercial products), Group B (top-selling online products), and Group C (products certified by the Food and Drug Administration). The results revealed significant physical differences among the three groups. Group A had an average size of 6.02 x 29.03 mm and an average weight of 0.2 g, Group B had 5.78 x 22.16 mm and 0.4 g, and Group C had 5.75 x 19.33 mm and 0.1 g. These results indicated that size is not the main factor determining product quality, which is more influenced by frying methods and oil absorption. The color values (L*) ranged from 28.9–30.7, with Groups A and C exhibiting lighter colors, while Group B was slightly darker. Group C had the highest Red - Green (a*) value (5.7), indicating a uniform reddish-brown color suitable for frying. Texture analysis showed that Group B had the highest hardness (230.980 N) and cohesiveness (0.482), indicating a firm and dense texture, whereas Group C had the lowest gumminess and chewiness (19.275 and 0.737), reflecting a light and crispy texture. In conclusion, Group A represented general products emphasizing value, Group B distinguished by its firmness and dense crispness preferred by consumers, and Group C shows uniform color and texture, making it suitable for industrial production and the development of automatic frying control systems in the future.