Evaluation and Implementation of an Automatic Feeding System for Jariya Broiler Farm, Nakhon-Ratchasima, ThailandABSTRACT
This research aimed to design, fabricate, and test a prototype of a 1-feed-line automatic chicken feeder, determining the designed functionality and feeding time, and comparing the performance of an automatic feeding system applied to a closed-system broiler chicken farm (Jariya Farm, Nakhon Ratchasima, Thailand) with the traditional feeding method. On-site tests were conducted using both traditional and automatic methods, with 19,200 chickens subjected to each method. After installing the automatic feeder, the results showed that the total number of chicken deaths decreased from 599 to 490 (18% reduction) and the survival rate increased from 96.9% to 97.5%. Moreover, the feed conversion ratio (FCR) improved from 2.6 to 1.7. Test results indicate that the automatic chicken feeder is highly beneficial for managing feed distribution on the farm. Each pan was always full of food, and broiler chickens could eat at all times, avoiding the competition for food that occurs in the traditional system. This reduced congestion and the risk of chickens stepping on each other while feeding, leading to lower death levels, a noticeably higher survival rate, and an improved FCR. Hence, the system offers an effective method for broiler feeding and an opportunity for large-scale industrial applications. The installation of this system allows farmers to break even in less than two months.
Keywords:
Automatic feeding systems; broiler chicken farm; Feed Conversion Ratio; arduino; survival rate
INTRODUCTION
Livestock production in Thailand currently plays a crucial role in the country’s agricultural sector (Prathumchai et al., 2018) and contributes significantly to the national economy. The country is known for its diverse livestock industry, which includes cattle, pigs, poultry, goats, and other smaller animals. Livestock farming in Thailand not only provides for domestic food consumption, but also contributes to exports, especially in the form of pork, chicken, and various dairy products. Poultry farming is a highly efficient form of animal husbandry that plays a key role in ensuring nutritional security for a large portion of the global population. It offers a reliable source of protein, along with food and nutritional security for various populations in rural regions worldwide, particularly in developing nations (Vaarst et al., 2015; Gržinić et al., 2023). Poultry production in Thailand is a significant industry, with a focus on both broiler chicken production (for meat) and layer production (for eggs). Thailand is one of the major poultry producers and exporters in Southeast Asia (Santoso et al., 2018; Klaharn et al., 2024), and the industry plays a key role in the country’s food security, employment, and export economy.
A broiler chicken farm is a facility that specializes in the production of chickens raised for meat. The main goal of such a farm is to raise chickens to a marketable weight as efficiently as possible, typically within a 6-8-week period from hatching to market weight (approximately 1.8-2.3 kg per bird) (Tallentire et al., 2016; Mramba & Mapunda, 2024). Broiler chickens are specifically bred for rapid growth and meat production. The key aspects of a broiler chicken farm focus on the critical factors necessary for raising chickens efficiently and profitably. These aspects involve a combination of management, environmental conditions, nutrition, health, and economic planning (Dayyani, 2014). Some examples of the main aspects are farm infrastructure, breed selection, health management, environmental control, waste management, nutrition and feeding, and growth and production monitoring (Wongnaa et al., 2023; Wilcox et al., 2024).
Feeding is one of the most critical aspects of broiler production (Wongnaa et al., 2023; Mramba & Mapunda, 2024), as it directly impacts growth rates, feed conversion efficiency, and overall profitability (Martins et al., 2016; Kpomasse et al., 2021). Broiler chickens are raised primarily for meat production, and their growth is highly dependent on the quality and composition of their feed (Kpomasse et al., 2021). The goal is to ensure that they grow quickly, efficiently, and healthily. However, feeding costs are one of the largest expenses in poultry farming, accounting for 75% of the total production costs on a poultry farm (Olaniyi & Salami, 2014; Chinaeke-Ogbuka et al., 2021). Therefore, fluctuations in feed ingredient prices (often driven by global market conditions), and the cost of labor can have a direct impact on the profitability of poultry production (Fitrimawati et al., 2024) and lead to a low return on investment.
Generally, the types of feeders used depend on the size of the operation, varying between manual and automatic feeders. Manual feeders comprise manual feeding systems or simpler types of feeders in smaller operations, while automatic feeders are commonly used in larger commercial farms, where feed is delivered continuously or in set intervals to ensure the chickens always have access to fresh feed. Farming activities in broiler farms in Thailand are mostly dependent on human work. Recently, the broiler industry has been characterized by high levels of industrialization, with large commercial farms using modern methods for feeding, housing, and disease control. The use of new technologies in broiler chicken farms has been increasing dramatically. In this context, interest in automatic feeding systems (AFS) is increasing in order to supply diets with a high frequency and accuracy, and low labor input. Various researchers have proposed and evaluated several designs of automatic feeding systems.
Different kinds of feeders and their combinations utilized in broiler farms have been researched and developed. Researchers and farm owners have been turning to automatic feeding systems to avoid the use of manual labor to feed broiler chickens and to ensure precise and accurate feed distribution according to a set schedule, guaranteeing sufficient feed supply to meet the chickens’ needs. This in in line with the principles of precision feeding (PF) systems, which have rely on intelligent computer-controlled feeding systems to automatically feed individual broilers, breeders, or layers based on real-time measurements of body weight (BW) (Zuidhof et al., 2017; You et al., 2021). These smart poultry systems have been developed based on platforms including the intelligent fuzzy logic control (FLC) techniques (Olaniyi & Salami, 2014; Lahlouh et al., 2020), Arduino-embedded microcontrollers (Chinaeke-Ogbuka et al., 2021; Natho et al., 2023), wireless sensor network (WSN) (Sinduja et al., 2016), or Programmable Logic Controller (PLC) (Muttha et al., 2014; Dewanto et al., 2019).
The Internet of Things (IoT) has been utilized and applied to smart poultry farming worldwide. Through resource optimization and intelligent planning, this technology-driven farming solution helps farmers make informed agricultural decisions. The advancement of IoT-based smart farming with smart devices is transforming agricultural production by enhancing both quality and yield while also reducing farming costs. The primary objective of smart agriculture is to collect real-time data, such as temperature, soil moisture, and humidity, to monitor and manage poultry health, feeding, and environmental conditions (Vijaya et al., 2022), and to detect chicken behavior in poultry farms (Ahmed et al., 2024).
Lahlouh et al. (2020) studied and compared the performance of three control systems: a Multi-Input Multi-Output (MIMO) fuzzy logic controller (FLC) combined with a proportional-integral-derivative (PID) controller (called MFLPID), a standalone FLC, and a basic on/off controller. Their results showed that the proposed MFLPID control strategy worked more effectively for poultry farming applications. Moreover, Chinaeke-Ogbuka et al. (2021) designed an automatic feeding system for poultry farms to address the problem of requiring human labor for animal care. The results showed that the system was able to effectively detect and predict the levels of food and water in the farm with an accuracy of 98.79%. In addition to the application of automation, embedded systems technology was also applied for farm management, utilizing the UNO board and Arduino. Moreover, a wireless sensor network (WSN) combined with an Arduino ATmega2560 embedded microcontroller was studied by Sinduja et al. (2016), being able to monitor changes in environmental factors like temperature, food, and water levels. Additionally, it can analyze and display this data through a graphical user interface (GUI) for users.
Dewanto et al. (2019) have started to apply automatic control systems using PLC and HMI in poultry farms. These systems are more stable than control systems that use UNO boards and Arduino. The systems are capable of sending signals over longer distances and provide better protection against signal interference. Li et al. (2019) developed and introduced an ultra-high frequency radio frequency identification (UHF-RFID) system, a technology that offers a real-time solution to continuously monitoring feeding and drinking behaviors of individual broilers in group settings, and validating the performance of the system with video analysis to consider the instantaneous bird number (IBN) and time spent (TS) at feeders and drinkers. This system had crucial implications on farm management and animal well-being. Boonraksa & Boonraksa (2022) designed the automatic feeding system by using a DC gear motor to control the flow of chicken feed operated via the ESP-8266 board. When the conveyor thread reaches the last head of the chicken feed pan, the infrared photoelectric switch sensor will immediately cut off the motor. A timer can operate the chicken feeder to turn it on and off.
According to the literature, the development of automatic chicken-feeding machines in the past has mostly focused on creating prototypes and testing them in a lab-scale setting (Boonraksa & Boonraksa, 2022; Natho et al., 2023). However, there has been limited progress in developing and applying these prototypes in the Thai industrial poultry farming sector. The objective of this research is to design and develop a prototype of a one-feed-line automatic chicken feeding machine, with the goal of applying and integrating the system into the poultry farming industry. Jariya broiler farm in Nakhon-Ratchasima province was used as the case study for this implementation.
Based on a field visit to Jariya Farm, which still utilized the traditional feeding method where workers manually distribute pellet feed into each pan, several issues were identified. This method not only resulted in high labor costs but also caused inconsistent feed quantities across the pans, with some receiving more feed than others. Additionally, pellet feed frequently spilled outside the pans, and since broiler chickens naturally did not eat pellet feed that had fallen on the floor, this led to food waste. Furthermore, when workers poured pellet feed pan by pan, the chickens crowded around and fought to eat from the first pans, causing pushing and trampling. This often led to injuries or even death, negatively impacting growth rates. Chickens that ate more feed grew faster than others, creating uneven growth within the flock. Therefore, the study aimed to assess the machine’s performance and compare the number of chicken deaths and the feed conversion ratio between the traditional and automatic feeding methods.
MATERIALS AND METHODS
Prototype and system design
The prototype of the 1-feed-line (FL) automatic chicken feeding system in this research was designed as shown in Figure 1. The design and installation of the feeding pan positions, based on past research (Boonraksa & Boonraksa, 2022; Natho et al., 2023), found that the pans should not be placed too close to each other to avoid overcrowding during feeding and to ensure that all chickens can access the feed. Each pan depicted in Figure 1(a) was designed to be 1 meter apart, and the first pan was positioned 1.5 meters away from the feed hopper. The 3D-CAD model of the system is depicted in Figure 1(b).
Prototype design of the 1-FL automatic chicken feeding system (a) schematic; and (b) 3D-CAD model.
The diet from the hopper marked as (1) was transported through the feed tube marked as (2) using spiral augers inside the tube, which conveyed the feed to the feeding pan marked as (3). The 2-inch diameter feed tube was also made of stainless steel 201. The hopper, which had a capacity of 290 kg, was made of stainless steel 304. The amount of diet in the hopper was detected by an ultrasonic sensor marked as (4), which monitored the diet level. If the amount of diet was lower than the specified level, the system would notify via a smartphone and stop the operation. The operation of the spiral auger placed inside the feed tube was controlled by a DC motor marked as (5) with a power rating of 80W, 24VDC, and 50RPM. An ultrasonic sensor marked as (6) was installed to detect the diet delivery at the last feeding pan. When the sensor at the final pan position detected that the pan was full, it indicated that the previous pans were also full. All parts of the system were controlled and processed to work in coordination as an automated system, with commands being issued from the control panel marked as (7).
In designing a system to fully automate the operation of all components, the process began with creating a flowchart, which illustrated the operation of the automatic feeding machine as shown in Figure 2. The operation started by checking the feed level in the hopper using the sensor installed at the top of the feed hopper. If the feed level was less than 10% of the hopper’s capacity, the system would send a notification via the Line application. Therefore, the user had to refill the hopper to more than 10% of its capacity before proceeding.
Then, the feeding time was scheduled into two periods: morning at 8:00 a.m. and evening at 5:00 p.m. When the set time arrived, the feed would be transported from the hopper through the tube using the spiral auger. The feed would first fill pan No. 1 until full, then continue to fill pan No. 2, 3, and 4 in order. The sensor was also installed at pan No. 4 to check the feed level. If the feed was full in pan No. 4, it indicated that the previous pans were also full. After that, the sensor would signal to the control panel to stop the motor and notify the user via the Line application. This marked the end of one complete feeding cycle.
The next step was to build the control system based on the flowchart that had been designed. The control system would consist of various components, as shown in Figure 3. The operation of the control system began by supplying 220V power to the breaker, which served as the on/off switch for the system, with a controller to manage the operation via the internet. The power was then sent to the switching regulator to adjust the voltage and reduce it to a level that was suitable for the output used. The processing unit would utilize an Arduino NodeMCU Baseboard to receive the necessary data from the ultrasonic sensor, with a delay function to control the operation as instructed by the processing board before sending commands to the output, which included the DC motor. Additionally, the control panel included a cooling fan, an operation control button, and an indicator light to illustrate the system’s operational status.
1-FL Experimental setup
The prototype of the 1-FL automatic chicken feeder, as shown in Figure 4, was designed, constructed, and tested at the laboratory of the Department of Mechanical Engineering, Faculty of Technology and Engineering, Udon Thani Rajabhat University, Thailand. The key components illustrated in Figure 4 that were employed in the experiment included a 290-kilogram feed hopper made from stainless steel sheets, a feed tube line that contained a spiral auger inside the tube, and 4 feeding pans. The ultrasonic sensors were installed inside the hopper and at pan No. 4. The control box with the Arduino NodeMCU-Base board was placed on the hopper wall. A smartphone application to control the system was installed and demonstrated. The testing of the prototype machine aims to evaluate the overall performance of the system. The assessment was divided into two main parts: the time taken to deliver feed to each pan and the amount of feed provided per pan, using both powdered and pellet feed types. The data of each experiment were repeated 5 times. The results from these tests were analyzed to determine the efficiency and reliability of the system in different feeding conditions. Additionally, the responsiveness of the ultrasonic sensors was evaluated to ensure accurate feed detection and distribution. The smartphone application was tested for its user-friendliness and real-time control capabilities, allowing operators to monitor and adjust the feeding process remotely. Overall, the performance of the prototype was found to meet the expected requirements for a fully automated poultry feeding system.
Application and data collection
The automatic feeding system was modified for the traditional Jariya broiler farm. The broiler farm located in Sikhio, Nakhon-Ratchasima, was utilized in the current study. All experimental procedures were carried out in accordance with the guidelines of the Institute of Animal for Scientific Purposes Development (IAD), with application number for Animal Use License (U1-02292-2558), and were approved by the UDRU ethics committee (AREC.UDRU 03/2025). The commercial broiler closed house was 15 m × 150 m, with controlled temperature and humidity. The internal temperature was set between 28 - 34oC by ventilation fans and evaporative cool cells. The farm’s humidity and temperature control system was operated independently from the automatic feeding system, with each functioning as a separate, standalone system.
A feed container (75,000 kg capacity) was placed outside a broiler house as depicted in Figure 5(a). Pelleted diets were conveyed from a feed container through a 2-inch PVC pipe - as shown in Figure 5(b) - using a spiral auger placed inside the pipe - as illustrated in Figure 5(c) - and a 3-phase motor located at the end of the pipe to four small hoppers depicted in Figure 5(d) that were installed inside the house. The automatic feeding system was installed in the house to replace the traditional system. There were four 120-m-long feed lines in the broiler house. Each feed hopper supplied one line, and each line had 100 feed pans, as shown in Figure 5(e). In each line, the spiral auger was also placed inside the feed tube and driven by a 3-phase motor, which was installed together with an ultrasonic sensor at the end of the feed line, as illustrated in Figure 5(f).
The key components of the automatic feeding system used in Jariya broiler farm; (a) a feed container, (b) a 2-inch PVC pipe conveyor, (c) a spiral auger, (d) a small hopper, (e) feed pans, and (f) a 3-phase motor.
Data were collected weekly from week 1 to week 7 from two broiler closed house systems: one using traditional feeding and the other using the applied automatic feeding system. The initial number of chickens in each farming system was the same, with a total of 19,200 chickens. Each system had 4 feeding lines. The alignment of the broiler closed houses and the feeding system sampling diagram applied for the Jariya farm is depicted in Figure 6.
Schematic diagram of automatic and traditional feed systems used in the Jariya broiler house.
Feed Conversion Ratio
The Feed Conversion Ratio (FCR), as indicated in Eq (1), is defined as a ratio of total feed intake (TFI) by the body weight gain (BWG) of broiler chickens, and is the conventional measure of livestock production efficiency. It represents the amount of feed required to produce a given amount of live weight.
In commercial broiler chicken production, an FCR of 1.5 to 1.8 is considered good (Santoso et al., 2018), meaning that for every 1.5 to 1.8 kg of feed, a broiler chicken will gain 1 kg of body weight. The lower the FCR, the more efficient the farm is at converting feed into meat. According to the literature (Santoso et al., 2018), the FCR in the closed-house system for 7 raising periods was 1.49 on average, and the average FCR for broilers raised in the semi-closed house was 1.56. Furthermore, the broilers raised in the stilt-house system had 1.83 FCR for broilers raised in the first floor, and 1.77 for broilers raised in the third floor. The FCR score for broilers raised in the closed-house system was lower than in the semi-closed-house or in the stilt-house.
Survival Rate
The survival rate (SR) of broilers depends on several factors, including the age of the broiler, the quality of the hatching eggs, and hygiene, and disease prevention. The survival rate can be calculated by Eq (2) below, where N t is the broiler number at week-t, and N o is the initial broiler number.
RESULTS AND DISCUSSION
Prototype testing
The results of the 1-feed-line prototype test on the average time to deliver feed to each pan, using both powdered and pellet feed, from a total of 5 repeated experiments, are shown in Figure 7.
Comparison of the average time for feeding each pan (No.1 - 4) using pellet and powdered feed.
Figure 7 shows that the average time to fill pan 1 until full was 1:21 minutes and 1:25 minutes for pellet feed and powdered feed, respectively. Meanwhile, filling the remaining pans takes less than 1 minute on average. This was because the distance between the feed hopper and pan 1 was longer than the distance between each subsequent pan. Moreover, the experimental results showed that the time to fill the pans with both pellet and powdered feed was nearly the same. The pellet feed takes slightly less time than the powdered feed, with an average time of 4:11 minutes for pellets and 4:19 minutes for powdered feed. One of the main reasons pellet feeds filled the pan faster was due to the shape and the gaps between the pellets. Additionally, the amount of feed in each pan when using pellet feed was clearly about 25% heavier per pan compared to powdered feed, as shown in Figure 8. The main reason for this was the higher density of the pellet feed. From the prototype testing of the automatic chicken feeder, it was found that the machine performed well according to the preset parameters. In terms of the time taken for transportation and the amount of feed in each pan, the amounts were consistent with the machine’s design specifications. Using pellet feed was more suitable than powdered feed, as both types of feed took a similar time to fill the pans, but pellet feed had a higher weight per pan. The investigation of the effects of feed shape (pellet vs. powder) on system performance, along with the corresponding statistical analysis, will be addressed in future studies. Besides, if faster feed delivery is desired, it would be necessary to increase the size of the motor, spiral auger, and feed tube. Additionally, if a higher amount of feed per pan is required, it would be necessary to increase the size of the feeding pan.
On-site testing
The comparison of the automatic feeding system installed at the farm and the traditional feeding system using manual labor will be based on factors such as the number of chicken deaths, survival rate, total feed intake, and feed conversion ratio (FCR).
The number of chicken deaths and the survival rates at each week for each system are respectively shown in Figure 9 and Figure 10.
The graphs show that the number of chicken deaths was highest in the first week, and the lowest in week 7, which was the final week before broiler sale. Moreover, the number of chicken deaths in the traditional feeding system was significantly higher than in the automatic feeding system each week. This difference arose from several factors, but observations of the chickens’ behavior revealed that the primary cause was overcrowding and the chickens stepping on each other while eating. In the traditional feeding system, workers poured food into pans one at a time, and chickens rushed to feed from the same pan, causing overcrowding and trampling. Some chickens experienced injury, while others died. As a result, the number of chicken deaths was higher, and the survival rate was lower.
The comparison of TFI and FCR between traditional and automatic feeding systems is shown in Figure 11. The results show that the total feed intake (TFI) of the traditional feeding systems is significantly higher than the automatic system, with a maximum difference of around 25,650 kg at week 7. FCR is also calculated and presented in the secondary axis of Figure 11, revealing that the automatic system could improve the FCR, which decreased by approximately 34.6% (from 2.6 to 1.7).
Break-even point analysis
The break-even point (BEP), which is a ratio of total initial investment (fixed costs) and monthly cost savings, was determined to estimate how long it takes to recover the investment in an automatic feeding system based on the fixed costs and the reduced monthly expenses at the Jariya broiler farm. Fixed Costs (Initial Investment) consisted of five three-phase motors used to drive the feeding mechanism. These motors were highly durable and suitable for continuous operation on the farm. In addition, accessories and additional parts, including spiral augers, ultrasonic sensors, feed pans, structural supports, control panels, and other necessary components, were required to complete the installation. The total fixed costs were about THB 69,750. The installation of the automatic feeding system enabled the farm to reduce feed loss from spillage by an average of 95 kilograms per month, and decrease labor requirements by two workers. This represents a cost reduction of approximately 49,300 baht per month. By installing this automatic feeding system, the farmers would recover their investment in just under 2 months, after which the system starts generating net monthly savings of over THB 49,300, improving efficiency, reducing waste, and cutting labor costs.
Adoption Challenges
This one-feed-line (1-FL) prototype system was implemented to control a three-phase electric motor at Jariya broiler farm by connecting the motor to a frequency-controlled Voltage Source Inverter (VSI). The inverter adjusted both voltage and frequency to match the desired motor speed and operated via a relay module that governed power delivery. The control system functioned through the collaboration between a microcontroller (NodeMCU) and a power supply unit. The NodeMCU served as the central processing unit, monitoring conditions such as feeding times or feed levels. When the preset criteria were met, it sent a signal to the relay to activate the inverter circuit. Upon activation, the inverter supplied three-phase power to the motor, driving the feeding mechanisms, including spiral augers. When the ultrasonic sensor detected that the feed level had reached a specified threshold, the NodeMCU sent a signal to deactivate the relay, thereby stopping the inverter and halting motor operation. This system demonstrated an effective application of microcontroller and automation technologies in the agricultural sector. It helped reduce labor requirements and operational errors while enhancing efficiency and effectiveness in livestock feeding operations. Furthermore, to ensure the success of the automatic feeding system, farmer training and maintenance support are essential. Proper training helps farmers operate, adjust, and troubleshoot the system effectively, maximizing efficiency and minimizing errors. Regular maintenance, including cleaning, mechanical checks, and software updates, ensures long-term reliability and reduces downtime. Providing farmers with clear maintenance guidelines or access to technical support further enhances system performance and protects the investment.
CONCLUSION
In this study, a prototype of a 1-feed-line automatic chicken feeder controlled by an Arduino microcontroller system was designed, fabricated, and tested in a laboratory. The prototype was fully functional. To achieve faster feed delivery, it would be essential to upgrade the motor, spiral auger, and feed tube. Moreover, if a larger quantity of feed per pan is needed, the size of the feeding pan would also need to be increased. Besides, an automatic feeding system was implemented in a sample closed-system broiler chicken farm, Jariya broiler farm, Sikhio, Nakhon-Ratchasima province. The comparison between the automatic feeding system and the traditional feeding method showed that the total number of chicken deaths decreased by 18% from 599 to 490. The survival rate was also 0.6% higher, from 96.9% to 97.5%. FCR was improved from 2.6 to 1.7. The automatic chicken feeder offered significant advantages in managing feed distribution on the farm. Each pan remained consistently filled with food, allowing broiler chickens to eat at any time, preventing the competition for food typically seen in traditional systems. This helped reduce overcrowding and the likelihood of chickens stepping on one another during feeding, leading to lower death levels, a noticeable increase in survival rates, and an improved FCR. With the implementation of the automatic feeding system, the investment is expected to be recovered in under two months.
ACKNOWLEDGEMENTS
The authors would like to express gratitude to the Department of Mechanical Engineering, Faculty of Technology and Engineering, Udon Thani Rajabhat University, for providing funding, tools, and equipment to fabricate and test the prototype of a 1-feed-line automatic chicken feeder. Special thanks are also extended to Jariya Farm for permitting and facilitating the installation and testing of the automatic chicken feeder system at the farm.
REFERENCES
-
Ahmed MM, Hassanien EE, et al. A smart IoT-based monitoring system in poultry farms using chicken behavioural analysis. Internet of Things 2024;25:101010. https://doi.org/10.1016/J.IOT.2023.101010
» https://doi.org/10.1016/J.IOT.2023.101010 -
Boonraksa P, Boonraksa T. The design of automatic chicken feeders machine controlled by a smartphone. International Journal of Science and Innovative Technology 2022;5 (1):74-82. Available from: https://ph01.tci-thaijo.org/index.php/IJSIT/article/view/248462
» https://ph01.tci-thaijo.org/index.php/IJSIT/article/view/248462 -
Chinaeke-Ogbuka, I;Anoliefo, E;Ajibo, A. Design and implementation of an automated feeding system for poultry farms. Proceedings of the 4th International Conference on Industrial Engineering and Operations Management; 2021 Aug 2-5; Rome, Italy; 2021. p.532-9. https://doi.org/10.46254/EU04.20210336
» https://doi.org/10.46254/EU04.20210336 - Dayyani N. The principles of poultry husbandry. International Journal of Advanced Biological and Biomedical Research 2014;2 (5):1344-9.
- Dewanto P, Munadi M, Tauviqirrahman M. Development of an automatic broiler feeding system using PLC an HMI for closed house system. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) 2019;58 (1):139-49.
-
Fitrimawati;Nurhayati;Indrayani, I;et al. The analysis of broiler price fluctuations in Indonesia. Jurnal Ilmiah Peternakan Terpadu 2024;12 (1):23-35. https://doi.org/10.23960/JIPT.V12I1.P23-35
» https://doi.org/10.23960/JIPT.V12I1.P23-35 -
Gržinić G, Piotrowicz-Cieślak A, Klimkowicz-Pawlas A, et al. Intensive poultry farming:A review of the impact on the environment and human health. Science of the Total Environment 2023;853:160014. https://doi.org/10.1016/j.scitotenv.2022.160014
» https://doi.org/10.1016/j.scitotenv.2022.160014 -
Klaharn K, Ngampak R, Chudam Y, et al. Analyzing and forecasting poultry meat production and export volumes in Thailand:a time series approach. Cogent Food & Agriculture 2024;10(1). https://doi.org/10.1080/23311932.2024.2378173
» https://doi.org/10.1080/23311932.2024.2378173 -
Kpomasse CC, Oke OE, Houndonougbo FM, et al. Broiler production challenges in the tropics:A review. Veterinary Medicine and Science 2021;7 (3):831-842. https://doi.org/10.1002/vms3.435
» https://doi.org/10.1002/vms3.435 -
Lahlouh I, Rerhrhay F, Elakkary A, et al. Experimental implementation of a new multi input multi output fuzzy-PID controller in a poultry house system. Heliyon 2020;6(8):e04645. https://doi.org/10.1016/J.HELIYON.2020.E04645
» https://doi.org/10.1016/J.HELIYON.2020.E04645 -
Li G, Zhao Y, Hailey R, et al. An ultra-high frequency radio frequency identification system for studying individual feeding and drinking behaviors of group-housed broilers. Animal 2019;13(9):2060-9. https://doi.org/10.1017/S1751731118003440
» https://doi.org/10.1017/S1751731118003440 -
Martins JMS, Carvalho CMC, Litz FH, et al. Productive and economic performance of broiler chickens subjected to different nutritional plans. Brazilian Journal of Poultry Science 2016;18(2):209-16. https://doi.org/10.1590/1806-9061-2015-0037
» https://doi.org/10.1590/1806-9061-2015-0037 -
Mramba RP, Mapunda PE. Management factors associated with the survival and market weight of broiler chickens among small-scale farmers in the Dodoma City of Tanzania. Heliyon 2024;10(13):e33907. https://doi.org/10.1016/J.HELIYON.2024.E33907
» https://doi.org/10.1016/J.HELIYON.2024.E33907 -
Muttha RI, Deshpande SN, Chaudhari MA, et al. PLC based poultry automation system. International Journal of Scientific Research 2014;3(6):149-52. https://www.doi.org/10.36106/ijsr
» https://www.doi.org/10.36106/ijsr -
Natho P, Chamuthai L, Boonying S, et al. A prototype platform for automated chicken feeding control with an embedded system. International Journal of Advanced Science Computing and Engineering 2023;5 (1):66-74. https://doi.org/10.62527/ijasce.5.1.106
» https://doi.org/10.62527/ijasce.5.1.106 - Olaniyi OM, Salami AF, Adewumi OO, et al. Design of an intelligent poultry feed and water dispensing system using fuzzy logic control technique. Control Theory and Informatics 2014;4(9):61-72.
-
Prathumchai N, Polprasert C, Englande Jr AJ. Phosphorus distribution and loss in the livestock sector - the case of Thailand. Resources, Conservation & Recycling 2018;136:257-66. https://doi.org/10.1016/J.RESCONREC.2018.04.027
» https://doi.org/10.1016/J.RESCONREC.2018.04.027 -
Santoso SI, Sarjana TA, Setiadi A. Income analysis of closed house broiler farm with partnership business model. Bulletin of Animal Science 2018;42 (2):164-9. https://doi.org/10.21059/buletinpeternak.v42i2.33222
» https://doi.org/10.21059/buletinpeternak.v42i2.33222 - Sinduja K, Jenifer SS, Abishek MS, et al. Automated control system for poultry farm based on embedded system. International Research Journal of Engineering and Technology 2016;3 (3):620-4.
-
Tallentire CW, Leinonen I, Kyriazakis I. Breeding for efficiency in the broiler chicken: a review. Agronomy for Sustainable Development 2016;36(66). https://doi.org/10.1007/s13593-016-0398-2
» https://doi.org/10.1007/s13593-016-0398-2 -
Vaarst M, Steenfeldt, S;Horsted, K. Sustainable development perspectives of poultry production. World's Poultry Science Journal 2015;71 (4):609-620. https://doi.org/10.1017/S0043933915002433
» https://doi.org/10.1017/S0043933915002433 -
Vijaya, SR;Sridharani, J;Saranya CP;et al. Smart farming:the IoT based future agriculture. In Proceedings of the 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli, India, 20-22 January 2022;150-5. https://doi.org/10.1109/ICSSIT53264.2022.9716331
» https://doi.org/10.1109/ICSSIT53264.2022.9716331 -
Wilcox, CH;Sandilands, V;Mayasari, N;et al. A literature review of broiler chicken welfare, husbandry, and assessment. World's Poultry Science Journal 2023;80 (1):3-32. https://doi.org/10.1080/00439339.2023.2264824
» https://doi.org/10.1080/00439339.2023.2264824 -
Wongnaa, CA;Mbroh J;Mabe, FN;et al. Profitability and choice of commercially prepared feed and farmers' own prepared feed among poultry producers in Ghana. Journal of Agriculture and Food Research 2023;12:100611. https://doi.org/10.1016/J.JAFR.2023.100611
» https://doi.org/10.1016/J.JAFR.2023.100611 -
You, J;Lou, E;Afrouziyeh, M;et al. A supervised machine learning method to detect anomalous real-time broiler breeder body weight data recorded by a precision feeding system. Computers and Electronics in Agriculture 2021;185:106171. https://doi.org/10.1016/J.COMPAG.2021.106171
» https://doi.org/10.1016/J.COMPAG.2021.106171 -
Zuidhof MJ;Fedorak MV;Ouellette CA;et al. Precision feeding:innovative management of broiler breeder feed intake and flock uniformity. Poultry Science 2017;96 (7):2254-63. https://doi.org/10.3382/PS/PEX013
» https://doi.org/10.3382/PS/PEX013
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FUNDING
This work was supported by the Department of Mechanical Engineering, Faculty of Technology and Engineering, Udon Thani Rajabhat University.
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DATA AVAILABILITY STATEMENT
Data will be available upon request.
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DISCLAIMER/PUBLISHER’S NOTE
The published papers’ statements, opinions, and data are those of the individual author(s) and contributor(s). The editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.
Data will be available upon request.
