Comparing weight dynamics between urban and rural honey bee colonies in Latvia

Received: January 16th, 2023 ; Accepted: April 8th, 2023 ; Published: April 17th, 2023 ; Correspondence: [email protected] is an important agricultural industry in Latvia, which has an area of 64,589 km2 and is largely mixed forest. The natural foraging base does not provide the honey yield evenly throughout the whole season, thus the average honey yield in Latvia is about 20 kg per colony. The objective of this research was to compare the weight dynamics of colonies placed in rural and urban environments. As urban beekeeping is becoming more popular, it is important to understand whether there are enough foraging resources within the city for the bee colonies. To do this, the weight changes of ten honey bee colonies was remotely monitored and analysed during the summer period. Five colonies were located in the rural environment in Vecauce and five in the urban environment in Jelgava city. Colonies were assessed using the precision beekeeping approach and developed scale systems. It was concluded that for rural colonies in Vecauce, the main weight increase occurred in June - from 41.02 to 54.68 kg - which resulted in 94% of the total increase for the summer period. Data analysis from the urban apiary revealed that colonies increase weight during the entire monitoring period, indicating that there are foraging resources available throughout the summer period within the city

Modular sensory hardware and data processing solution for implementation of the precision beekeeping

ArticleFor successful implementation of the Precision Apiculture (Precision Beekeeping) approach, immense amount of bee colony data collection and processing using various hardware and software solutions is needed. This paper presents standalone wireless hardware system for bee colony main parameters monitoring (temperature, weight and sound). Monitoring system is based on Raspberry Pi 3 computer with connected sensors. Power supply is granted by the solar panel for reliable operation in places without constant source for power. For convenient data management cloud based data warehouse (DW) is proposed and developed for ease data storage and analysis. Proposed data warehouse is scalable and extendable and can be used for variety of other ready hardware solutions, using variety of data-in/data-out interfaces. The core of the data warehouse is designed to provide data processing flexibility and versatility, whereas data flow within the core is organized between data vaults in a controllable and reliable way. Our paper presents an approach for linking together hardware for bee colony real-time monitoring with cloud software for data processing and visualisation. Integrating specific algorithms and models to the system will help the beekeepers to remotely identify different states of their colonies, like swarming, brood rearing, death of the colony etc. and inform the beekeepers to make appropriate decisions/actions. This research work is carried out within the SAMS project, which is funded by the European Union within the H2020-ICT-39-2016-2017 call. To find out more visit the project website https://sams-project.eu/

Evaluation of the honey bee colonies weight gain during the intensive foraging period

Received: March 5th, 2022 ; Accepted: April 1st, 2022 ; Published: April 13th, 2022 ; Correspondence: [email protected] in Latvia has a long tradition and it is a classical branch of agriculture. In Latvia, there is no traditional beekeeping region, and beekeeping is performed in all regions. Honey yield is influenced by various factors - variety of crops (nectar plants) around the apiary, man-made changes in land/forests (deforestation), climate change, beekeepers’ actions, etc. Application of information and communication technologies (ICT) in the field of beekeeping can bring benefits to the beekeepers. To be more specific, continuous remote monitoring of certain bee colony parameters can improve beekeeper’s apiary management, by informing timely about the nectar flow (or even provide information on bee colony states, e.g., swarming). In such a way, beekeepers can plan their next actions - prepare supers or even choose to move the apiary to a different geographical location. Within this research, weight gain of the ten honey bee colonies was remotely monitored and analysed during two-week period at the beginning of the summer 2021 in Vecauce, Latvia, using the precision beekeeping approach. This monitoring period corresponded to intensive flowering of the winter rapeseed and field beans. Colonies were equipped with the automatic scales. In addition, colony and environmental temperature was monitored. Measurements were taken every thirty minutes. Analysing the obtained data, weight increase can be observed in all colonies, from 17 to 48 kg. As well, based on weight data, swarming event can be identified. Constant monitoring of weight change can also help to identify daily patterns in honey bee activity

Model for the bee apiary location evaluation

Honeybees are predominant and ecologically as well as economically important group of pollinators in most geographical regions. As a result of analysing current situation in studies and practices, a conclusion was drawn that beekeeping sector is in decline. The identified reasons for this are land-use intensification, monocropping, pesticide poisoning, colony diseases, parasites and adverse climate. One of the solutions is to find a proper bee colony harvesting location and use luring methods to attract bees to this location. Usually beekeepers choose the apiary location based on their own previous experience and sometimes the position is not optimal for the bees. This can be explained by different flowering periods, variation of resources at the known fields, as well as other factors. This research presents a model for evaluation of possible apiary locations, taking into account resource availability estimation in different surrounding agricultural fields. Authors propose a model for real agricultural field location digitization and evaluation of possible apiary location by fusing information about available field resources. To achieve this, several steps have to be completed, such as selection of fields of interest, converting selection to polygons for further calculations, defining the potential values and coefficients for amount of resources depending on type of crops and season and calculation of harvesting locations. As the outcome of the model, heat map of possible apiary locations are presented to the end-user (beekeeper) in the visual way. Based on the outcome, beekeepers can plan the optimal placement of the apiary and change it in the case of need. The Python language was used for the model development. Model can be extended to use additional factors and values to increase the precision for field resource evaluation. In addition, input from users (farmers, agricultural specialists, etc.) about external factors, that can affect the apiary location can be taken into account. This work is conducted within the Horizon 2020 FET project HIVEOPOLIS (Nr.824069 – Futuristic beehives for a smart metropolis)

Solution for remote real-time visual expertise of agricultural objects

ArticleIn recent years automated image and video analyses of plants and animals have become important techniques in Pre cision Agriculture for the detection of anomalies in development. Unlikely, machine learning (i.e., artificial neural networks, support vector machine, and other relevant techniques) are not always able to support decision making. Nevertheless, experts can use these techniques for developing more precise solutions and analysis approaches. It is labour - intensive and time - consuming for the experts to continuously visit the production sites to make direct on - site observations. Therefore, videos from the site n eed to be made available for remote viewing and analysis. In some cases it is also essential to monitor different parts of objects in agriculture and animal farming (e.g., bottom of the plants, stomach of the animal, etc.) which are difficult to access in standard recording procedures. One possible solution for the farmer is the use of a portable camera with real - streaming option r ather than a stationary camera. The aim of this paper is the proposition of a solution for real - time video streaming of agricultural objects (plants and/or animals) for remote expert evaluation and diagnosis. The proposed system is based on a Raspberry Pi 3, which is used to transfer the video from the attached camera to the YouTube streaming service. Users will be able to watch the video stream from the YouTube service on any device that has a web browser. Several cameras (USB, and Raspberry Pi camera) and video resolutions (from 480p till 1 , 080p) are compared and analysed, to find the best option, taking into account video quality, frame rates, and latency. Energy consumption of the whole system is evaluated and for the chosen solution it is 645 mA

Development of the Digital Matchmaking Platform for international cooperation in the biogas sector

Received: January 12th, 2021 ; Accepted: March 27th, 2021 ; Published: March 31st 2021 ; Correspondence: [email protected] demand for sustainable, renewable and clean energy sources has been increasing in the past decade in order to combat global warming by reducing greenhouse gas emissions. Biogas has proven to be a versatile energy carrier which can be used for heating purposes, power and fuel. Having acknowledged the high potential for the use of biogas energy and having researched the demand and supply markets, the Digital Global Biogas Cooperation (DiBiCoo) project aims to link European biogas and biomethane technology providers with emerging and developing markets. To achieve this goal the development and application of innovative digital support tools is necessary - a digital matchmaking platform (DMP) with bi-directional partnership architecture. DMP can be used as means to build trust-based business relationships, share information on available European technologies and serve as an additional marketing option for EU and non-EU companies and industries. This article presents the developed platform prototype and demonstrates its basic functionality and the development process. Basic business and functional requirements were defined and then refined into functional, user-interface and performance requirements for implementation. User requirements were defined using user centred design approach in collaboration with potential platform end-users, considering their specific needs. During the development process Agile methodology was used. In the future digital platform functionality will be extended based on discussions and feedback of the stakeholders and end-users during local workshops and other events, where the DiBiCoo platform will be presented

Usability improvements of the Thermipig model for precision pig farming

Pig livestock farming systems encounter several economic and environmental challenges, connected with meat price decrease, sanitary norms, emissions etc. To deal with these issues, methods and models to assess the performance of a pig production system have been developed. For instance, Thermipig model represents the pig fattening room and simulates performances of pigs at the batch level, taking into account interactions between the individual variability of pigs, farmer's practices, room characteristics and outdoor climate conditions. The model requires some static basic inputs fulfilled in several spreadsheets (such as rooms, pigs, and dietary characteristics) but also data files for voluminous variable inputs (such as outdoor temperature or climate control box parameters) for further modelling and outcome producing. This leads to challenges in data providing by the farmers and have to be improved. This paper deals with the implementation of the separate modules of the developed data warehouse system for usability improvements of the Thermipig model. The idea is to substitute input from the data files with online data input and automated variable processing by the model using the python script for connection to the remote data warehouse. The data warehouse system is extended with ‘Property Sets’ section dealing with all the operations that can be performed to a set of input variables. This approach demonstrates the ability of the data warehouse to act as data supplier for the remote model. As well the outcome of the model is also transferable back to the data warehouse for evaluation. This work is done within the Era-Net SuSan PigSys project - Improving pig system performance through a whole system approach