With increased climate-related challenges, beekeeping practices need to adopt climate-smart technologies to ensure high colonization rates and security against human and animal destruction. This study assessed beekeepers’ perception of the suitability of bee hive technologies for honey production. The study tested the hypothesis that improved bee hive technologies do not increase honey production. A multinomial Logit (MNL) regression model was used to analyze data from 428 randomly selected beekeepers in 2 sub-counties each of Kajiado and Nyandarua Counties where the Kenya Climate Smart Agriculture Project (KCSAP) is being implemented. Most beekeepers preferred the Kenya Top Bar hives (41%) and the Langstroth (36%). Based on the significant MNL at P < 0.01, this study concluded that honey productivity is influenced by the preference of the bee hive types. There is a need for enhanced training in beekeeping on climate-smart practices to increase the adoption of improved hive technologies and honey production.

L Martini, 'RFS Eswatini project and MTN empower youth through �??21 Days of Y�??ello Care�?? Beekeeping Initiative', p.1, 2019 | In Eswatini, Resilient Food Systems is working to improve the livelihoods of smallholder farmers through the promotion of diversified, climate-resilient agricultural practices. The RFS Eswatini project �??Climate-Smart Agriculture for Climate-Resilient Livelihoods�?? (CSARL) is closely linked with IFAD�??s Smallholder Market-Led Programme, which strengthens market linkages and scales up sustainable agricultural practices. Both projects focus on harnessing the sustainable use and management of natural resources for market-led economic growth in the agricultural sector. These objectives cannot be met without addressing the role of youth in reshaping the agricultural sector. In Eswatini, youth unemployment is roughly 44%. Youth and women are disproportionally impacted by developmental challenges and are particularly vulnerable to inequality, poverty, malnutrition, violence and poor health outcomes

The AI-Driven Climate-Smart Beekeeping (AID-CSB) for Women project worked with beekeepers in Uzbekistan and Ethiopia to co-design and localize the “Beekeeper’s Companion”, a climate-smart information communication technology for development (ICT4D) app designed to support beekeepers’ hive management practices and improve honey production. AID-CSB’s ambition is to work towards applying advanced machine learning models on standardized biodiversity data by mitigating bias and maintaining spatial and temporal accuracy. To do this, the project leverages the participation of women beekeepers and national experts and incorporates their traditional and local knowledge into the algorithms that will push information to the beekeepers. Recognizing the need for an agricultural solution that does not require more time from women, the app was designed so that uploading data points requires a minimal time investment. For example, recording information on a hive inspection can be done with a simple swipe gesture in under five seconds. The following report frames AID-CSB activities within the environmental, human rights, and digital contexts in Uzbekistan and Ethiopia; details the preliminary findings of a series of user-tests and iterative participatory application designs of the app; and provides recommendations for bringing the app to scale in Uzbekistan, Ethiopia, and beyond. Lessons learned include the limits of localization, and the careful communication and numerous iterations required to mitigate issues of language, scalability, bias, access and cultural norms around women and technology.

Honeybees are predominant and ecologically as well as economically important groupof pollinators in most geographical regions. As a result of analysing current situation in studiesand practices, a conclusion was drawn that beekeeping sector is in decline. The identified reasonsfor 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 harvestinglocation and use luring methods to attract bees to this location. Usually beekeepers choose theapiary location based on their own previous experience and sometimes the position is not optimalfor the bees. This can be explained by different flowering periods, variation of resources at theknown fields, as well as other factors. This research presents a model for evaluation of possibleapiary locations, taking into account resource availability estimation in different surroundingagricultural fields. Authors propose a model for real agricultural field location digitization andevaluation of possible apiary location by fusing information about available field resources. Toachieve this, several steps have to be completed, such as selection of fields of interest, convertingselection to polygons for further calculations, defining the potential values and coefficients foramount of resources depending on type of crops and season and calculation of harvestinglocations. As the outcome of the model, heat map of possible apiary locations are presented tothe end-user (beekeeper) in the visual way. Based on the outcome, beekeepers can plan theoptimal placement of the apiary and change it in the case of need. The Python language was usedfor the model development. Model can be extended to use additional factors and values to increasethe precision for field resource evaluation. In addition, input from users (farmers, agriculturalspecialists, etc.) about external factors, that can affect the apiary location can be taken intoaccount. This work is conducted within the Horizon 2020 FET project HIVEOPOLIS (Nr.824069– Futuristic beehives for a smart metropolis).

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).

Climate changes pose overwhelming impacts on primary production and, consequently, on agricultural and animal farming. Additionally, at present, agriculture still depends strongly on fossil fuels both for energy and production factors ,such as synthetized inorganic fertilizers and harmful chemicals such as pesticides. The need to feed the growing world population poses many challenges. The need to reduce environmental impacts to a minimum, maintain healthy ecosystems, and improve soil microbiota are central to ensuring a promising future for coming generations. Livestock production under cover crop systems helps to alleviate compaction so that oxygen and water can sufficiently flow in the soil, add organic matter, and help hold soil in place, reducing crusting and protecting against erosion. The use of organic plant production practices allied to the control of substances used in agriculture also decisively contributes to alleviating the pressure on ecosystems. Some of the goals of this new decade are to use enhanced sustainable production methodologies to improve the input/output ratios of primary production, reduce environmental impacts, and rely on new innovative technologies. This reprint addresses original studies and reviews focused on the current evolution and research novelty in agricultural sustainability. New developments are discussed on issues related to quality of soil, natural fertilizers, or the sustainable use of land and water. Also, crop protection techniques are pivotal for sustainable food production under the challenges of the Sustainable Development Goals of the United Nations, allied to innovative weed control methodologies as a way to reduce the utilization of pesticides. The role of precision and smart agriculture is becoming more pertinent as communication technologies improve at a rapid rate. Waste management, reuse of agro-industrial residues, extension of shelf life, and use of new technologies are ways to reduce food waste, all contributing to higher sustainability in food supply chains, leading to a more rational use of natural resources. The unquestionable role of bees as pollinators and contributors to biodiversity is adjacent to characterizing beekeeping activities, which in turn contributes, together with the valorization of endemic varieties of plant foods, to the development of local communities. Finally, the short circuits and local food markets have a decisive role in the preservation and enhancement of rural economies. | info:eu-repo/semantics/publishedVersion