Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Control and Automation: Insmoaf (Integrated Smart Modern Agriculture and Fisheries) on The Greenhouse Model

A greenhouse is an agricultural management system that has shown the efficiency of food production. This system is an effective alternative to ensure maximum production results. Agriculture with greenhouse technology can create the desired environmental/climatic conditions. The rapid development of technology and science has led to the birth of communication between devices using IoT and AI. This technology can be applied to greenhouses in agriculture and fisheries. Research on greenhouse and microcontroller-based automation systems has been carried out, and it is interesting to be developed. Researchers make a more efficient system and can increase the quality and quantity of production. The measurement data of both modes are monitored using the web. The greenhouse prototype is supported by DHT22, DS18B20, a fan to control the greenhouse cooler, RFID as the key access to the greenhouse. DHT22 & DS18B20 sensor readings in the prototype greenhouse use an AI system with the fuzzy method. IoT and AI have been successfully implemented in models of rice fields, hydroponic farming, and fisheries using automatic modes of RTC devices and sensors. The fuzzy approach method is used to find the optimum temperature and humidity values. The fuzzy approach was successfully carried out until the temperature and humidity conditions were "ideal," "high," and "very high." This condition provides information to the microcontroller to activate which fan should turn on. In manual mode, the smartphone application controls the system properly.   Keywords: artificial intelegent, control and automation, fuzzy logic, greenhouse, Io

Automatic Fish Feeder and Telegram Based Aquarium Water Level Monitoring

An important factor in maintaining fish in an aquarium is the timeliness of feeding fish. Most fish keepers are worried about the aquarium's feeding and water conditions, which must be done every day. Therefore, an automatic fish feeding tool and telegram-based monitoring of aquarium water levels were made to make it easier for fish keepers and aquarium owners to provide and monitor fish feed automatically according to a predetermined schedule. Monitoring the remaining feed and water level in the aquarium is done via Telegram. The components used in this tool are Esp 8266 as a microcontroller, RTC as a timer for scheduling fish feed, Ultrasonic as a detector for remaining fish feed, JSN-SR04T as a water level detector, LCD to display time and date as well as notifications and a servo motor functions to open and close the fish feed. The conclusion from the results obtained from this device is that the device works well and helps the aquarium owner to monitor and feed efficiently, despite some challenges such as delay due to poor internet connection

Digital transformation of peatland eco-innovations (‘Paludiculture’): Enabling a paradigm shift towards the real-time sustainable production of ‘green-friendly’ products and services

The world is heading in the wrong direction on carbon emissions where we are not on track to limit global warming to 1.5 degrees C; Ireland is among the countries where overall emissions have continued to rise. The development of wettable peatland products and services (termed 'Paludiculture') present significant opportunities for enabling a transition away from peat-harvesting (fossil fuels) to developing 'green' eco-innovations. However, this must be balanced with sustainable carbon sequestration and environmental protection. This complex transition from 'brown to green' must be met in real time by enabling digital technologies across the full value chain. This will potentially necessitate creation of new green-business models with the potential to support disruptive innovation. This timely paper describes digital transformation of paludiculture-based eco-innovation that will potentially lead to a paradigm shift towards using smart digital technologies to address efficiency of products and services along with future-proofing for climate change. Digital transform of paludiculture also aligns with the 'Industry 5.0 -a human-centric solution'. However, companies supporting peatland innovation may lack necessary standards, data-sharing or capabilities that can also affect viable business model propositions that can jeopardize economic, political and social sustainability. Digital solutions may reduce costs, increase productivity, improve produce develop, and achieve faster time to market for paludiculture. Digitisation also enables information systems to be open, interoperable, and user-friendly. This constitutes the first study to describe the digital transformation of paludiculture, both vertically and horizontally, in order to inform sustainability that includes process automation via AI, machine learning, IoT-Cloud informed sensors and robotics, virtual and augmented reality, and blockchain for cyber-physical systems. Thus, the aim of this paper is to describe the applicability of digital transformation to actualize the benefits and opportunities of paludiculture activities and enterprises in the Irish midlands with a global orientation.info:eu-repo/semantics/publishedVersio

Aquatic Invasions: Causes, Consequences, And Solutions

Invasive species represent a global threat to ecosystems, human health, and the economy. A basic knowledge of invasive species biology is crucial to understand current and future impacts and implications. The purpose of this book is to provide a broad background on invasive species, and also details on specific examples through case studies. The students in the course Aquatic Invasive Species (MAR 442) at the University of New England in Biddeford, Maine, have researched and reviewed scientific literature to educate readers about these issues. The class, comprised of twelve junior and senior Marine Science, Marine Affairs, Applied Mathematics, and Environmental Sciences students, selected the different topics, presented the material, wrote the chapters, and assembled the final versions into this book. This book cannot be all inclusive, but we think this book will provide an excellent broad overview of the most important aspects of Invasive Species Biology and might stimulate the reader to dive deeper into the material.https://dune.une.edu/marinesci_studproj/1002/thumbnail.jp

Contribution of remote sensing technologies to a holistic coastal and marine environmental management framework: a review

Coastal and marine management require the evaluation of multiple environmental threats and issues. However, there are gaps in the necessary data and poor access or dissemination of existing data in many countries around the world. This research identifies how remote sensing can contribute to filling these gaps so that environmental agencies, such as the United Nations Environmental Programme, European Environmental Agency, and International Union for Conservation of Nature, can better implement environmental directives in a cost-e ective manner. Remote sensing (RS) techniques generally allow for uniform data collection, with common acquisition and reporting methods, across large areas. Furthermore, these datasets are sometimes open-source, mainly when governments finance satellite missions. Some of these data can be used in holistic, coastal and marine environmental management frameworks, such as the DAPSI(W)R(M) framework (Drivers–Activities–Pressures–State changes–Impacts (on Welfare)–Responses (as Measures), an updated version of Drivers–Pressures–State–Impact–Responses. The framework is a useful and holistic problem-structuring framework that can be used to assess the causes, consequences, and responses to change in the marine environment. Six broad classifications of remote data collection technologies are reviewed for their potential contribution to integrated marine management, including Satellite-based Remote Sensing, Aerial Remote Sensing, Unmanned Aerial Vehicles, Unmanned Surface Vehicles, Unmanned Underwater Vehicles, and Static Sensors. A significant outcome of this study is practical inputs into each component of the DAPSI(W)R(M) framework. The RS applications are not expected to be all-inclusive; rather, they provide insight into the current use of the framework as a foundation for developing further holistic resource technologies for management strategies in the future. A significant outcome of this research will deliver practical insights for integrated coastal and marine management and demonstrate the usefulness of RS to support the implementation of environmental goals, descriptors, targets, and policies, such as theWater Framework Directive, Marine Strategy Framework Directive, Ocean Health Index, and United Nations Sustainable Development Goals. Additionally, the opportunities and challenges of these technologies are discussed.Murray Foundation: 25.26022020info:eu-repo/semantics/publishedVersio

New fish product ideas generated by European consumers

Food lifestyles are changing; people have less time to spend on food purchase and preparation, therefore leading to increasing demand for new food products. However, around 76% of new food products launched in the market fail within the first year (Nielsen, 2014). One of the most effective ways to enhance new products’ success in the market is by incorporating consumers’ opinions and needs during the New Product Development (NPD) process (Moon et al., 2018). This study aimed to explore the usefulness of a qualitative technique, focus groups, to generate new aquaculture fish product ideas as well as to identify the most relevant product dimensions affecting consumers’ potential acceptance.Peer ReviewedPostprint (published version