Komasilova Olvija, Komasilovs Vitalijs, Kviesis Armands, Zacepins Aleksejs
Department of Computer Systems, Faculty of Information Technologies, Latvia University of Life Sciences and Technologies, Jelgava, Latvia.
PeerJ. 2021 Sep 17;9:e12178. doi: 10.7717/peerj.12178. eCollection 2021.
Finding a proper location for a bee apiary is a crucial task for beekeepers and especially for travelling beekeepers. Normally beekeepers choose an appropriate apiary location based on their previous experience and sometimes the location may not be optimal for the bee colonies. This can be explained by different flowering periods, variation of resources at the known fields, as well as other factors. In addition it is very challenging to evaluate how many bee colonies should be placed in one geographical location for an optimal nectar foraging process. This research presents a model for finding the number of honey bee colonies needed for the optimal foraging process in the specific location, taking into account several assumptions. Authors propose to take into account potential field productivity, possible chemical contamination, surroundings of the apiary. To run the model, several steps have to be completed, starting from the selection of area of interest, conversion to polygons for further calculations, defining the roads in the selected area. The outcome of the model number of colonies that should be placed is presented to the user. The Python language was used for the model development. The model can be extended to use additional factors and values to increase the precision of the evaluation. In addition, input from users (farmers, agricultural specialists, etc.) about external factors that can affect the number of bee colonies in the apiary can be taken into account. This work is conducted within the Horizon 2020 FET project HIVEOPOLIS (Nr.824069).
为养蜂场找到合适的地点对养蜂人来说至关重要，对流动养蜂人而言更是如此。通常，养蜂人会根据以往经验选择合适的养蜂场地点，但有时该地点对蜂群来说可能并非最佳。这可以通过不同的花期、已知场地资源的变化以及其他因素来解释。此外，评估在一个地理位置应放置多少蜂群才能实现最佳采蜜过程极具挑战性。本研究提出了一个模型，用于确定特定地点最佳觅食过程所需的蜜蜂蜂群数量，同时考虑了几个假设。作者建议考虑潜在的田间生产力、可能的化学污染以及养蜂场的周边环境。要运行该模型，必须完成几个步骤，从选择感兴趣的区域开始，转换为多边形以便进一步计算，确定所选区域内的道路。模型得出的应放置的蜂群数量结果会呈现给用户。该模型开发使用了Python语言。该模型可以扩展以使用其他因素和值来提高评估的精度。此外，可以考虑用户（农民、农业专家等）提供的关于可能影响养蜂场蜂群数量的外部因素的输入。这项工作是在“地平线2020”未来新兴技术项目HIVEOPOLIS（编号824069）中开展的。
