Ghanaian farmers suffer from a decline in cocoa production partly due to damages and diseases from insect pests. To increase predation by bats on insects on the cocoa plantations we installed two different types of bat boxes on 15 plantations around the village of Buoyem. Bat activity, bat species composition (numbers of insectivorous and frugivorous bats) and insect abundance were measured before and after bat box installation. Insectivorous bats were present on all ofthe sampled plantations, namelyleaf-nosed bats (Hipposideros sp.), slit-faced bats (Nycteridae sp.), horseshoe bats (Rhinolophus sp.) and vesper bats (Vespertilionidae sp.). Furthermore, no correlation between insect abundance and bat activity could be detected. The bat boxes were not occupied yet during the research period since rainy season started in the second half of the measurements and bat activity decreases with increasing precipitation which is supported by our Un dings. Additionally, the available time period between in stallation and measuring of the effects of the boxes was very short when compared to similar researches. Bats alsohave different preferences per species for size and shape of bat boxes and the number of naturally available roosting sites also influences bat box occupancy. Our results suggest that bats are abundant above cocoa plantations in Buoyem and therefore bat boxes have the potential to be ahelpful tool in insect pest control.
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Agriculture and horticulture are essential for ensuring safe food to the growing global population, but they also contribute significantly to climate change and biodiversity loss due to the extensive use of chemicals. Integrated pest management is currently employed to monitor and control pest populations, but it relies on labor-intensive methods with low accuracy. Automating crop monitoring using aerial robotics, such as flapping-wing drones, presents a viable solution. This study explores the application of deep learning algorithms, You Only Look Once (YOLO) and Faster region-based convolutional neural network regions with convolutional neural networks (R-CNN), for pest and disease detection in greenhouse environments. The research involved collecting and annotating a diverse dataset of images and videos of common pests and diseases affecting tomatoes, bell peppers, and cucumbers cultivated in Dutch greenhouses. Data augmentation and image resizing techniques were applied to enhance the dataset. The study compared the performance of YOLO and Faster R-CNN, with YOLO demonstrating superior performance. Testing on data acquired by flapping-wing drones showed that YOLO could detect powdery mildew with accuracy ranging from 0.29 to 0.61 despite the shaking movement induced by the actuation system of the drone’s flapping wings.
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Control methods are applied worldwide to reduce predation on livestock by European red foxes (Vulpes vulpes). Lethal methods can inflict suffering; however, moral debate about their use is lacking. Non-lethal methods can also inflict suffering and can unintentionally lead to death, and yet both the welfare consequences and ethical perspectives regarding their use are rarely discussed. The aim of this study was to investigate the animal welfare consequences, the level of humaneness, the ethical considerations and the moral implications of the global use of fox control methods according to Tom Regan’s animal rights view and Peter Singer’s utilitarian view. According to Regan, foxes ought not to be controlled by either lethal or potentially harmful non-lethal methods because this violates the right of foxes not to be harmed or killed. According to Singer, if an action maximises happiness or the satisfaction of preferences over unhappiness or suffering, then the action is justified. Therefore, if and only if the use of fox control methods can prevent suffering and death in livestock in a manner that outweighs comparable suffering and death in foxes is one morally obligated t
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Diverse partijen, zowel marktpartijen als kennisinstellingen, gaan in 2020 samenwerken in een pilot om te toetsen in hoeverre zij de plant kardoen (familie van de artisjok distel) in haar volle potentieel kunnen gebruiken voor diverse commerciële doeleinden, zoals bloemen, voedsel, composiet en een lamp. Er wordt in deze pilot onderzoek gedaan naar: - Gebruik van reststromen als bodemverbeteraar - Teelt van kardoen - Verwerking van kardoen
Inleiding en praktijkvraag De groeiende wereldbevolking gecombineerd met de klimaatverandering zorgt voor een de noodzaak tot een duurzame voedselvoorziening (KIA missie Landbouw, voedsel & water). Een significante reductie van gewasbestrijdingsmiddelen is daarbinnen een belangrijke doelstelling. Robotica maakt als technologie motor van de precisielandbouw plant specifieke precisie-bestrijding mogelijk. Het projectconsortium onderzoekt een semiautonoom samenwerkend grond-luchtrobot platform voor de precisielandbouw. Projectdoelstelling De doelstelling van het project AGRobot Platform is dan ook: “Onderzoek de mogelijkheden van een semi-autonoom samenwerkend grond-lucht robotplatform voor de precisielandbouw”. De hoofddoelstelling wordt binnen dit project beantwoordt door de deliverables uit de volgende subdoelstellingen: 1. Case studie onderzoek naar de mogelijke voordelen van het grond-luchtrobotplatform 2. Onderzoek naar de benodigde technologieën voor een grond-luchtrobotplatform 3. Ontwikkelen van een eerste (mogelijk case-specifieke) demonstrator 4. Ontwikkelen van (nieuwe) samenwerkingsvormen. Vraagsturing & Netwerkvorming Riwo Engineering is een industriële automatiseeerder die met zijn grondrobots en control-besturingssytemen actief is in de veeteelt. DRONEXpert gebruikt hyperspectrale camera’s onder drones voor het bemeten van gewassen. Saxion mechatronica onderzoekt met de onderzoekslijn unmanned robotic systems hoe de nieuwste robotica technologieën systemen mogelijk maakt voor ongestructureerde omgevingen. De partners bezitten gezamenlijk een enorm netwerk (TValley, Space53, euRobotics) en klanten om via de case studies de kansen te achterhalen en te realiseren. Innovatie Nergens ter wereld is een samenwerkend grond-luchtrobot platform actief in de precisielandbouw. Voor OostNederland, met naast veel robotica kennis ook veel Agro-kennis, zal het project letterlijk de KIEM zijn voor nieuwe projecten waaruit de valorisatie kansen richting heel Europa gaan. Activiteitenplan & Projectorganisatie Het project wordt geleid door de lector Dr. Ir. D.A.Bekke en uitgevoerd door Abeje Mersha en Mark Reiling samen met het deelnemend MKB. Het project bestaat uit 4 werkpakketten die achtereenvolgens antwoordt geven op de gestelde subdoelstellingen. Aan elk werkpakket zijn deliverables gekoppeld.
Flying insects like dragonflies, flies, bumblebees are able to couple hovering ability with the ability for a quick transition to forward flight. Therefore, they inspire us to investigate the application of swarms of flapping-wing mini-drones in horticulture. The production and trading of agricultural/horticultural goods account for the 9% of the Dutch gross domestic product. A significant part of the horticultural products are grown in greenhouses whose extension is becoming larger year by year. Swarms of bio-inspired mini-drones can be used in applications such as monitoring and control: the analysis of the data collected enables the greenhouse growers to achieve the optimal conditions for the plants health and thus a high productivity. Moreover, the bio-inspired mini-drones can detect eventual pest onset at plant level that leads to a strong reduction of chemicals utilization and an improvement of the food quality. The realization of these mini-drones is a multidisciplinary challenge as it requires a cross-domain collaboration between biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. Moreover a co-creation based collaboration will be established with all the stakeholders involved. With this approach we can integrate technical and social-economic aspects and facilitate the adoption of this new technology that will make the Dutch horticulture industry more resilient and sustainable.
