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Modern digital technologies have the great potential to improve the sustainability of fish farming in artisanal fisheries. However, in spite of the popularity of these technologies for fish farming in other parts of the world, Brazil still lags behind. To fill this gap, this study has conducted the first field study in implementing the IoT sensor technologies in Southern Brazil and documents the experiences in this paper. More specifically, it discusses developing sustainable artisanal fisheries infrastructure using these technologies with reference to southern Brazil, where the study explores the use of sensor technology in aquaculture and its effectiveness in reducing waste and improving productivity. The overarching goal of the project is to demonstrate how simple data collection using IoT sensors and its analysis can support artisanal freshwater fish farms in Brazil and beyond to increase production, reduce waste, and thereby improve their sustainability. The pilot implementation of these technologies has demonstrated the potential of increasing the productivity of the artisanal fisheries, reducing waste (e.g., loss of farmed fish, optimised feeding to reduce waste of feeds), and improving the sustainability of aquaculture. This paper documents the valuable firsthand experiences of selecting, adapting, and implementing the IoT sensor technologies with close cooperation from local research institutions and artisanal fish farmers. The paper describes the different implementation stages and use interviews with stakeholders as a testimony of the effectiveness of the IoT technology adoption.

Food waste is a serious problem worldwide, including in Europe. Research efforts are being carried out to reduce food waste. In this paper, we focus on using modern digital technologies (also known as Industry 4.0 technologies) to reduce waste in food supply chains. Based on interactions with a number of food companies in Europe over the last four years using Action Research, we provide new insights on the motivations and challenges for food companies when they are engaged in the use of technologies for reducing food waste in their supply chains. Motivations for firms include improved food quality of their produce, improved reliability, support in meeting legal requirements, a green image, and improved revenues from selling the food that has been saved. However, data security issues and trust issues posed challenges in using these technologies. Since this is an emerging area of research, we look at potential business models for technology companies for working with food companies in reducing food waste, identify value propositions and value capture, and look at how these investments in technologies can improve the sustainability of food businesses. We believe technology companies can leverage the opportunities, develop new business models with value propositions around the use of technologies, and support food companies via timely alerts in case of potential quality issues. Value capture occurs via the sale of hardware and subscriptions.

To develop one porous additive material that can be assembled on cigarette filter, and achieve both functions of reducing hazard substances like tar and providing special aroma and moisture, this study innovatively selects the raw materials like baking-carbonized functional flavors with special aroma and konjac glucomannan (KGM) with properties of water absorption, gelling and film-forming, following the steps of casting into membrane shape, thermostatic crosslinking for strength enhancement and freeze-drying for pore creating to prepare 5 porous composite membranes based on baked-carbonized functional flavors and konjac glucomannan (KGM) were prepared. The composite structure, morphologies on the surface and the cross section, porosity structures including mesoporous and macropore of the porous composite membranes were characterized, the tensile performance and aroma constituents through solid phase microextraction and hazardous substances adsorption as packed into the commercial cigarette were also studied. Results showed that all baked-carbonized functional flavors were carbonized into amorphous, and contained the groups of aromatic components like ≡C-H, C=O, C-O-C (aldehydes, esters), cross-linking achieved the entanglement of KGM segments by deacetylation. When compounded, KGM acted as the framework to build the 3D porous network structure, and the functional flavor powders were wrapped into the KGM layer. All porous composite membranes owned some mechanical strength and the internal porosity over 90%, the mesopores and the macropores were ranged with 5–50 nm and 20–255 µm, respectively, which was satisfied for gas flowing and harmful substances adsorption. Aroma and resulting abundance of extracted constituents changed with timing, which equipped the membranes with a comprehensive aroma feeling. Among them, the membrane prepared with the raw material of dark plum showed a better comprehensive performance, especially it could significantly reduce the contents of harmful HCN and phenol in cigarette during smoking.

Persulfate has been applied extensively for waste activated sludge (WAS) decomposition due to the strong oxidizing sulfate radical generated as a product. However, the efficiency is not improved without activation to produce free radicals. In this study, a novel coupling strategy of heat-activated persulfate (Heat_PS) pretreatment and sulfate-reducing bacteria (SRB) triggering was explored to enhance short-chain fatty acids (SCFAs) produced by WAS fermentation. The remaining sulfate acts as an essential acceptor of electrons for the metabolism of synergistic SRB, thereby boosting WAS acidification by energetic cooperation with anaerobic fermenters. The results showed that SCFAs yield in the Heat_PS + SRB group peaked at 431.89 mg COD/gVSS, with the proportion of acetate reaching 57.8 %. This was 6.33 and 1.75 times higher than that in raw and single Heat_PS treated WAS, respectively. Carbon balance revealed a conversion rate of 26.1 % of carbon content in WAS to SCFAs, with 4.5 % lower CO

Food waste reduction, as a major application area of the Internet of Things (IoT) and big data technologies, has become one of the most pressing issues. In recent years, there has been an unprecedented increase in food waste, which has had a negative impact on economic growth in many countries. Food waste has also caused serious environmental problems. Agricultural production, post-harvest handling, and storage, as well as food processing, distribution, and consumption, can all lead to food wastage. This wastage is primarily caused by inefficiencies in the food supply chain and a lack of information at each stage of the food cycle. In order to minimize such effects, the Internet of Things, big data-based systems, and various management models are used to reduce food waste in food supply chains. This paper provides a comprehensive review of IoT and big data-based food waste management models, algorithms, and technologies with the aim of improving resource efficiency and highlights the key challenges and opportunities for future research.

The desk rejection of submitted articles can be a hugely frustrating and demotivating process from the perspective of the researcher, but equally, a time-consuming and vital step in the process for the Editor, tasked with selecting appropriate articles that meet the required criteria for further review and scrutiny. The feedback from journal Editors within this editorial, highlights the significant gaps in understanding from many academics of the journal assessment process and acceptance criteria for progression to the review stage. This editorial offers a valuable “lived-in” perspective on the desk rejection process through the lens of the Editor, via the differing views of nine leading journal Editors. Each Editor articulates their own perspectives on the many reasons for desk rejection, offering key insight to researchers on how to align their submissions to the specific journal requirements and required quality criteria, whilst demonstrating relevance and contribution to theory and practice. This editorial develops a succinct summary of the key findings from the differing Editor perspectives, offering a timely contribution of significant value and benefit to academics and industry researchers alike.

Gibbons are a family (Hylobatidae) of ape species endemic to the rainforests of the mainland and islands of Southeast Asia, including four well-recognized genera (Hylobates, Nomascus, Symphalangus, and Hoolock). Most gibbon species are known as considered “endangered” or “critically endangered” (IUCN 2009). This present article gives a review on the research progress of phylogenetic relationships between gibbon species and closely related genera utilizing a range of different traits (e.g., vocalization, morphology, karyotype, mtDNA, Y chromosomes, Autosomes, Alu, and whole genome). Our aim held great potential to clarify more directions in researches on identification of genetic relationship, to provide reference for molecular biology research and useful information for further gibbon research.

Based on the mathematical description and biological parameters of three nonlinear growth models (Logistic, Gompertz, Bertalanffy), the recent advance of growth curve fitting analysis in goose have been reviewed briefly in this paper in order to provide some basic information for future goose research and breeding work.