Chapters authored
Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed
Pig farming is largely characterized by closed, large-scale housing technology. These systems are driven by resource efficiency. In intensive technologies, humans control almost completely. However, there are pig farming systems where humans have just little control. These free-range technologies are called organic pig farming systems in which the quality characteristics of the produced meat sold on a premium price are primary. We present the practical difficulties that are challenging in implementing precision pig farming. We characterize the data science methods that determine the reliability of our conclusions. This chapter describes the literature on the behavior and production results of pigs, social aspects, and the possibilities of the certified meat supply chain. Digital solutions can be implemented to verify and trace the origin of meat products. In our project, Mangalica breeding sows were tagged with passive Radio Frequency Identification (RFID) tags, and a research zone was established at wallowing area. RFID readers record the presence of sows in this zone. In addition, temperature, humidity, and air pressure are recorded hourly for 24 hours a day. Data are analyzed using visualization and data science techniques. We present our interim results and conditions of the experiment in this chapter.
Part of the book: Tracing the Domestic Pig
Information Technology Drivers in Smart Farming Management Systems
The chapter describes the possibilities of collecting digital data on crop and livestock production and their use in “smart farming” systems. Earth drone and spectral mobile mapping technologies can provide plant production-related measures with high temporal and spatial resolution. Remote sensing helps better understand farming patterns and crop management. Improving understanding of the link between remotely sensed data and risk assessment and management in “smart farming” is very important. Controlled-environment agriculture takes advantage of light recipes, related to spectral light-emitting diode (LEDs) and sensors. In livestock farming, analyzing a database of digital data on the environment and livestock individuals can help farmers make decisions better. The heterogeneous digital data from plant and livestock production are collected into a Data Lake. Then the data are processed to transform the data into the proper format for data analytics. Data Warehouse should be integrated into an ERP system that is dedicated to the agricultural environment.
Part of the book: Smart Farming