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Advances in pig-specific sensors
YANG Liang, WANG Hui, CHEN Ruipeng, SHENG Qingkai, YUAN Zhen, XIONG Benhai
Journal of Intelligent Agricultural Mechanization 2023, 4 (2): 22-34. DOI:
10.12398/j.issn.2096-7217.2023.02.003
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265
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Traditional pig farming has disadvantages such as high labor costs, low breeding efficiency, and high work intensity, which restrict the development of agricultural modernization. The scale, intensive and digital-oriented breeding model has become an inevitable requirement for the development of precision animal husbandry, and individual farming and health monitoring technology based on professional sensors has become the main direction of research. This paper introduces the research progress of pig-specific sensors from three aspects: behavioural sensors, growth and physiological sensors, and disease detection sensors. The outbreak of African swine fever has increased the demand for sensor technology and accelerated the development of new sensing methods. In assessing the adaptive physiology of livestock, sensor technology is essential for measuring physiological parameters of livestock due to its ability to capture time series of behavioural and physiological data. Biosensors and wearable technologies, based on advanced statistical and computer science methods, are used to predict and assess adaptive responses and resilience of livestock. Real-time analysis of animal body condition data such as sound, images and video can improve the biological indicators of livestock. Future developments in sensor technology will facilitate farmers to gain a comprehensive understanding of the health and welfare of their animals. Sensor devices will gradually move from contact to non-contact, so as to reduce he psychological stress on the animals. In terms of behavioural monitoring, video monitoring avoids the problem of traditional wearable devices affecting animals through long-distance target tracking. In terms of the reliability of individual animal identification algorithms, achieving accurate identification of multiple target individuals will be the focus of research. In terms of the applicability of animal behaviour detection algorithms, the study of the complex behaviour of individual animals will be a key research direction. In terms of individual animal disease prediction, the focus will be on achieving early identification of physiological responses in pigs and improving animal health and welfare. This study introduces the purpose of pig sensors to create value for society by improving animal health and welfare, increasing animal productivity, reducing production costs, and minimizing environmental pollution.
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Research progress on the monitoring methods of the separating loss in grain combine harvester
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Yang Li, Zhen Xue, Lizhang Xu, Yaoming Li, Jie Qiu, Yingfeng Wang
Journal of Intelligent Agricultural Mechanization (in Chinese and English) 2020, 1 (1): 13-23. DOI:
10.12398/j.issn.2096-7217.2020.01.003
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193
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The grain loss during the operation of combine harvester is directly related to the economic benefits of farmers. Mastering the accurate real-time grain loss information not only provide intuitive basis for the manipulator to adjust the working parameters of combine harvester that ensures the operation quality and improves the operation efficiency but also facilitate farmers or relevant government departments to track, supervise and measure the harvest loss of each region. The grain loss mainly includes the header loss, the unthreshed grain, the separating loss, the cleaning loss and leakage loss. The cleaning loss and separating loss account for a large proportion of grain loss. Therefore, it is necessary to monitor them in real time. Chinese researches on the monitoring methods of the separating loss are still at the theoretical and experimental stage, which is different from the researches oversea. Methods to improve the accuracy, reliability and adaptability of the separating loss sensors are difficult and essential in the information developing process of the grain combine harvester in our country. This paper summarizes the research progress of the monitoring methods and devices of grain combine harvester's separating loss at home and abroad from the aspects of the monitoring principles of the separating loss, the sensor signal processing system, the sensor damping method, the probability distribution model of separating loss. In addition, the developing trend will be analyzed. This will contribute to the continuous improving and upgrading of separation loss sensor and lay a solid foundation for the completion of information harvest in China .
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