Farm Production Research Articles

Assessment of Urban Farming Production, and Contribution to the Households’ Livelihood: A Case of Kigali City and Musanze District

Agriculture plays an important role in the economic growth and food security control in developing countries including Rwanda. This research study was carried out in Kigali and Musanze. Urban farming is one way to best use useless places closed inside household fences, resulting in high yields. Due to their short production cycle, Horticultural crops provide a quick response to emergency food needs, particularly in cities. These species have considerable yields that generate more income for farmers when used appropriately. The main objective of this study was to analyze the factors influencing urban farming production, profitability, and contribution to the households’ livelihoods in Rwanda. The population of interest for this research study constituted smallholder farmers of vegetables and fruits in Kigali and Musanze cities. The sampling unit was the garden household. A multistage sampling technique was employed involving purposive sampling of four districts Gasabo, Kicukiro, Nyarugenge, and Musanze. The study used a sample frame of 1085 population and a sample size of 112 respondents. The results from the study indicated that ten factors over fourteen have a positive influence on urban farming production while four have a negative influence in the study area. The results also showed that the productive fruits grown are classified into five classes indicated in Figure 1. The results of the study revealed different places/methods used to grow vegetables/species and fruits such as bags, baskets and basins, hanging baskets, old wheels, pallet gardens, open ground, trellises, arches, shelves, fences window box walls. The results displayed that the crops do well in small areas/places closed inside the household’s fences. The results proved that urban farming contributed to the social economy through different parts example malnutrition control, money saving, and food security. The results pointed out that urban farming production is constrained by some challenges such as small owned parcels, lack of urban farming knowledge, lack of technologies, period of crop maturity, lack of capital, lack of awareness, habitation system, and infrastructures. However, urban farming development should be enhanced to maintain national food security and improve income for farmers.

Relationship between Scientific Management Practices Followed by Fish Farmers with their Socio-economic Profile Characteristics

This study investigates the relationship between the adoption of scientific management practices by fish farmers and their socio-economic profile characteristics in the Raichur district of Karnataka, India. Using an ex-post-facto research design, data were collected from 120 fish farmers across eight villages. The results indicate that 36.28% of farmers adopted scientific management practices at a medium level, while 33.72% and 30.00% reported low and high adoption levels, respectively. Key socio-economic factors influencing adoption included education, social participation, extension orientation, and mass media utilization. These findings underscore the need for targeted interventions to enhance adoption rates and improve fish farming productivity, thereby supporting rural economies. This revised abstract maintains the essential details while improving clarity and focus.

Quantitative release assessment for beta-lactamase-producing Escherichia coli of dairy origin into vegetables

Abstract Outbreaks of food poisoning associated with vegetables contaminated with Escherichia coli have been reported globally. This study was conducted to assess the probability of releasing beta-lactamase-producing E . coli of dairy farm origin into vegetables in Japan. A release assessment model connecting dairy farms to vegetable farms was developed. Data on the indicated diseases and antimicrobial use in dairy cattle were obtained from the agricultural insurance program in Hokkaido Prefecture between 2016 and 2019. Data on bla -harboring E . coli in cattle were obtained from the Japan Veterinary Antimicrobial Resistance Monitoring System. Microbiological field sampling was conducted at dairy and vegetable farms. Inoculation experiments in vegetables were conducted. All processes in the model simulation were iterated for 1000 times. The estimated proportion of dairy farms holding cattle with bla -harboring E . coli was 6.00% (95% CI: 4.81–7.35%). Beta-lactams were used in 71.76% (333,098/464,204 average annual cases) of indicated diseases. The estimated concentration of bla -harboring E . coli in mixed fresh manure at affected farms was 3.33 log 10 CFU/g (95% CI: 3.33–3.34). The concentrations were reduced to 0.83 (95% CI: 0.34–1.25) and −0.54 log 10 CFU/g (95% CI: −1.04 to −0.05) in soil after immature manure, and slurry spraying, respectively. The estimated concentrations in the soil of fields of radish, leafy vegetables, tomato, and spring-seeded and autumn-seeded onions at harvest were −1.99 (95% CI: −2.48 to −1.57), −2.87 (95% CI: −3.36 to −2.42), −3.82 (95% CI: −4.32 to −3.40), −5.36 (95% CI: −5.85 to −4.93), and −5.94 (95% CI: −6.43 to −5.52) log 10 CFU/g, respectively. The concentrations in the bodies of leafy green spinach and lettuce were −9.88 (95% CI: −10.38 to −9.43) and −10.91 (95% CI, −11.52 to −8.05) log 10 CFU/g, respectively. The probability of ingesting bla -harboring E . coli of dairy origin with raw vegetables in Japan was thus assessed to be very low. One Health impact statement This study applied a release assessment in the World Organisation for Animal Health framework for antimicrobial resistance risk assessment to connect the antimicrobial use for dairy cattle, manure production and vegetable farming. As vegetable is often consumed raw, the assessment is directly associated with human health. Although the environmental continuum was not explored, the reduction of the hazard on the soil of vegetable farms was considered. The study involved the engagement with dairy and vegetable farmers and the agriculture industry in understanding farming behavior and value chain. The approach in this study can be applied to the complex problems across the animal-human-environment interface.

Simulating farm structural change dynamics in Thessaly (Greece) using a recursive programming model

Although the policy impacts on farms accumulate year by year, most farm decision models focus on short-term decisions, evaluating policies based on snapshots. Structural changes are gradually built; therefore, farm decision models should consider the sequences within the period under study. Multiyear data from the arable sector in Thessaly, Greece, have fed a newly developed recursive programming model mainly to simulate farm structural change dynamics. The proposed model incorporates new evidence on the strategic decision of arable crop farms regarding their remaining in the production system and farm expansion. Results reveal an evident gradual farmland concentration in relatively large farms, accompanied by a gradual expansion of the most profitable cropping activities, verifying the real-world survival strategy of farms.

Livelihood Transformation of The K’Ho Sre Ethnic Minority in Lam Dong Province

The K’Ho Sre people in Lam Dong province were the largest local group of the K’Ho ethnic group. Their traditional livelihood activities were farming, animal husbandry, making traditional handicrafts, and participating in predatory economic activities (hunting, gathering, fishing). Nowadays, the K’Ho Sre ethnic group has been adapting to converting their livelihoods from traditional agricultural production models to agricultural production models by applying science and technology. This economic transformation was manifested in many aspects, notably the strong introduction of new farm production methods completely different from traditional production methods regarding cultivation techniques, seedling structure, and forms of exploitation and product consumption. Besides, there were some relatively new activities such as services, buying and selling, hiring, etc. The research was conducted through the following methods: synthesis, observation, survey, and analysis of field data for 400 K’Ho Sre ethnic families in Lam Dong to point out changes in livelihood activities and propose recommendations to contribute to hunger eradication, poverty reduction, and sustainable development.

Effects of genetic and environmental trends from 1970 to 2020 on farm efficiency estimated with a whole farm modeling system

The objectives of this study were to evaluate associations of genetic, cow management and nutrition, inbreeding, and crop yields from 1970 to 2020 with measures of production and economic efficiency according to a whole farm model, and to evaluate effects of genetic change in individual traits on economic efficiency in comparison to expectations from economic selection indexes. Genetic and phenotypic performance metrics for Holsteins from 1970 and 2020 were retrieved and input into the Integrated Farm System Model (IFSM) for a 7000 cow TX herd and a 50 cow PA grazing herd. Crop yields estimates from 1970 and 2020 were retrieved and farm hectarage was altered so that forage and energy concentrate requirements were met through farm production; likewise, scenarios evaluating effects of atmospheric CO2 fertilization (CO2F) on crop yield were evaluated by altering farm hectarage. For single traits that could be dynamically modeled by IFSM, performance shifts and resulting change in product prices or management expenses were added to 1970 base models. Economic efficiency was evaluated as the per cow return to management and unpaid factors as compared with 1970 base models. As averaged across state scenarios, gains in economic efficiency were +$945 and -$76 for additive genetic and inbreeding effects, respectively, for a total gain from genetic change of +$869. Genetic gain in fat yield (+$549) and protein yield (+$524) were responsible for most of the genetic gain, whereas milk yield (-$128) and increased cow BW (-$129) depressed economic efficiency. Genetic change in productive life had a smaller effect (+$44) than predicted unless heifers were purchased and at double the default value. Gains due to cow management and nutrition increased efficiency by +$666 and crop yield increased efficiency by +$711, of which +$371 was attributed to CO2F across scenarios. Whole farm dry matter efficiencies derived as the ratio of fat and protein corrected milk yield to dry matter intake increased from 0.82 (PA) and 0.97 (TX) in 1970 to 1.20 in 2020 and could be higher if farms reduce the size of their replacement herd by producing beef calves. The landmass required in 2020 was 63% and 78% of the 1970 requirement for TX and PA, respectively. Changes in cow genetic merit, management and nutrition, and crop yields have all increased the economic and environmental sustainability of milk production, and systems such as IFSM could be a useful tool to help inform economic selection indices.

A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture

This paper presents a novel approach to address the essential challenge of accurately determining the total weight of shrimp within aquaculture ponds. Precise weight estimation is crucial in mitigating issues of overfeeding and underfeeding, thus enhancing efficiency and productivity in shrimp farming. The proposed system leverages image processing techniques to detect individual live shrimp and extract pertinent features for weight estimation within a clay pond environment. Specifically, an automated feed tray captures images of live shrimp, which are then processed using a combination of Detectron2, PyTorch, and CUDA (Compute Unified Device Architecture) for individual shrimp detection. Essential features such as area, perimeter, width, length, and posture are extracted through image analysis, enabling accurate estimation of shrimp weight. An Artificial Neural Network (ANN) model, utilizing these features, accurately predicts shrimp weight with a coefficient of determination (R2) of 94.50% when incorporating all extracted features. Furthermore, our system integrates a user-friendly web application that empowers farmers to monitor shrimp weight trends, facilitating precision feeding strategies and effective farm management. This study contributes a low-cost solution using a deep learning model to estimate the weight of live Pacific white shrimp in clay ponds, enabling daily weight calculations, helping farmers optimize feed quantities, providing shrimp size distribution insights, and reducing the Feed Conversion Ratio (FCR) for greater profitability. The procedure for shrimp feature extraction is also provided, including the calculation of shrimp length and width, as well as shrimp posture classification.

Assessment of Variants of Organic-Based Rice Production Systems in Negros Occidental, Philippines

A survey was conducted to determine information needs and assess variants of organic rice-based production among rice farmers in Negros Occidental, Philippines. Survey data were gathered from 199 out of 400 identified organic rice practitioners in the province, which accounts for a > 95% confidence level and 5% of margin of error. Among the respondents, only 20.1% had organic certification from third-party representatives, and 42.2% can be classified under a low-input farming system. Some (21.1%) were in transition for certification or were farmers intending to go into organic certification with third-party representatives. The remaining (16.6%) used organic inputs but were not certified nor in transition for certification. Results also showed that farmers' access to information and technologies was mainly from trainings and seminars facilitated by different organizations through their associations and cooperatives. Many of the farmers had practices based on cultural management, and their organic inputs were farm-produced. The average yield of organic farming systems of farmers in Negros Occidental ranged from 2.76 to 3.21 t/ha. The average net income of farmers was PhP 29 649.32. Well-informed farmers, active farmer associations, and available support from different organizations were among the identified elements of continued organic rice production of farmers in the province. Some of the constraints were low productivity and profit in organic rice farming and problems with market availability.

Financial impact of low pathogenic avian influenza virus subtype H9N2 on commercial broiler chicken and egg layer production systems in Pakistan

Low Pathogenic Avian Influenza (LPAI) subtype H9N2 is endemic in Pakistan and impacts poultry farming through disease related mortality, poor weight gain and reduced egg production. This study aims to estimate the farm-level financial impact of LPAI H9N2 infection on commercial broiler and layer production systems in Pakistan.A questionnaire based cross-sectional survey of 138 broiler farms and 136 layer farms in Pakistan was conducted in 2019. Primary data collected by cross-sectional survey along with expert opinion and published literature were used to parameterize five stochastic production and gross margin models for three broiler and two layer production systems: fully integrated production (FIP), partially integrated production (PIP) and independent farming production (IP) systems. Partial budget analysis were then carried out to estimate the financial impact of LPAI H9N2.Results indicate that in broiler production systems, starting with 35,000 day old chicks (DOC) per batch, the net cost of disease (million PKR/production cycle) was estimated at 4.10 (14,862 USD), 4.62 (16,747 USD) and 2.46 (8917 USD) for IP, PIP and FIP systems, respectively. The disease produced a negative gross margin (defined here as revenue minus replacement and variable costs) in IP (-53 PKR (-0.19 USD)/DOC bought) and PI (-25 PKR (-0.091 USD)/DOC bought) systems, while remained positive for FIP systems (87 PKR (0.32 USD)/DOC bought). For layer production systems, (mean flock size as 48,000 DOCs) the net cost (million PKR/production cycle) was 29.75 (107,095.21 USD) and 29.51 (106,223.45 USD) IP and PIP systems, respectively, and produced negative gross margin in both systems.The outcomes of the study highlight the vulnerability of independent and partially integrated production systems to the disease. These findings also offer a decision-making tool to the farmers and policy makers to evaluate avian influenza surveillance systems and control interventions in Pakistan.

The ripple effects of climate change on agricultural sustainability and food security in Africa

AbstractClimate change results in lower agricultural outputs, disruption of food supply chains, and widening of the social gap between poor and rich in developing countries, with more vulnerable groups being pushed into untold poverty. This review aims to investigate the consequences of climate change on food insecurity in Africa in the context of environmental degradation. This review emphasizes the complexity of demands on food security systems due to changing climatic conditions under the four pillars (availability, accessibility, utilization, and stability). This review demonstrated the susceptibility of farm production to changes in temperature, precipitation, and weather patterns generated by climate change. In addition, this review investigated the factors shaping food insecurity, such as increasing population growth, poverty, inadequate early warning systems, and weak agricultural infrastructure. Furthermore, the review points out how climate change affects food prices and availability and the widening income gap, potentially leading to social unrest and political instability in Africa. Vulnerable populations, including impoverished, elderly, and physically challenged individuals, are at increased risk due to climate‐related health impacts. Women who face gender inequalities and socioeconomic limitations are particularly susceptible. We posit that there is a need for comprehensive strategies that address health disparities and consider vulnerable subgroups within society alongside broader measures to enhance food security in the face of climate change.

Vaccinated Atlantic salmon (Salmo salar L.) maintain a specific antibody response throughout the seasonal fluctuations of a full commercial production cycle in sea: a case study

Vaccination is a critical prophylactic measure to prevent disease outbreaks in Atlantic salmon (Salmo salar L.) and multivalent oil-adjuvanted vaccines administered intraperitoneally (IP) are widely used for this purpose. The Atlantic salmon in this observational study were sampled during commercial production in a salmon farm in Northern Norway. Fish were sampled in the hatchery prior to vaccination, and further every 6 weeks after sea transfer up until slaughter. The key findings revealed that Atlantic salmon vaccinated IP with a commercial multivalent oil-based vaccine developed specific and long-lasting antibody responses against A. salmonicida, V. anguillarum, Y. ruckeri, and IPNV for up to 20 months post-vaccination. However, there was variation in the measured specific antibody response to the different antigens. Notably, the antibody responses against A. salmonicida and V. anguillarum antigens were higher and more prolonged compared to the antibody responses against Y. ruckeri and IPNV antigens. Histological examination showed presence of vaccine-induced granulomas in the pancreas at the injection site for up to 50 weeks post-vaccination and V. anguillarum antigens were found in the granulomas up to 44 weeks post-vaccination. There were also individual IgM-positive cells present in these vaccine-induced granulomas, and qPCR confirmed increased gene expression of membrane-bound and secretory IgM up to 37 weeks post-vaccination. Altogether the qPCR data of membrane and secretory IgM suggests local production of IgM in the vaccine-induced granulomas, while the head kidney might be responsible for the long-term secretion of IgM. Neither the low temperature the fish experienced for two winter seasons (below 5 °C) nor the seasonal changes in photoperiod affected the vaccine-induced specific antibody responses.

Comparative Study of Productivity of Organic and Conventional Agriculture in Maize Crops in East Java

This study provides a comparative analysis of the productivity of organic and conventional maize farming in East Java, employing a quantitative approach with 40 sample farms. Utilizing a Likert scale from 1 to 5, data were collected and analyzed using SPSS version 26. The findings indicate that while conventional farming demonstrates higher average yields, the difference in productivity between the two systems is statistically significant but not substantial. Organic farming shows competitive productivity, particularly in the long term, due to its positive impact on soil health and sustainability. The study highlights the potential of organic farming as a viable alternative to conventional practices in maize cultivation, offering valuable insights for policymakers and farmers in East Java.

Greenhouse farming: Hydroponic vertical farming- Internet of Things (IOT) Technologies: An updated review

This review paper of literature highlights the importance of greenhouse urban farming technology, hydroponics, aeroponics, aquaponics, vertical farming and applications of Internet of Things (IOT) technologies. The greenhouse farming is a well known modern agriculture technology for optimal plant growth. Hydroponics, a soilless cultivation technique using nutrient solutions under controlled conditions, is used for growing vegetables, high-value crops, and flowers. Vertical farming is a popular trend in hydroponics that involves stacking multiple layers of plants in a vertical arrangement. This farming method saves space, reduces water usage, and increases yields per square foot of growing area. In comparison to conventional greenhouse cultivation, hydroponics requires less fertilizer, pesticides, and water due to the precise control over their distribution. The term “Internet of Things (IOT)” is a system of interconnected computing devices, sensors, objects, microcontrollers, and cloud servers that can transmit data across a network and control other devices remotely without human intervention. A better management of nutrient solution in hydroponic systems requires optimum pH, electrical conductivity (EC), or ions concentration. The three main greenhouse farming gases (GHGs) emissions in hydroponics hi-tech urban farming are nitrous oxide, methane and carbon dioxide (CO2). To measure the levels of CO2 in hydroponics, the more intermediate to advanced grower can use a CO2 monitoring and controllers system. Hydroponic vertical farming is in infancy in India. Although hydroponic vertical farming units for production of crops like strawberry, lettuce and other leafy vegetables, foliage and flowers are functioning in major metros of India. However, the organized hydroponic vertical farms for production of food crops are not available in India. Therefore, only a few successful hydroponic vertical farms have been built in India mainly due to the initial high price tag on construction and the cost of maintaining them afterwards. Another disadvantage is carbon footprint of hydroponic vertical farming is very high, and discourages its applications.

Identification of factors affecting fattening efficiency of commercial pig herds and analysis of their impact at different performance levels

Improving fattening efficiency is an important goal of breeding commercial pigs, especially for the large-scale pig farms. Fattening efficiency index (FEI) can be used to evaluate the fattening efficiency. The aim of this study was to identify the factors affecting the fattening efficiency of commercial pigs in large-scale pig farms and further study the impact of these factors on the production performance of commercial pig batches at different production levels. The data of 9,570 batches was mainly consisted of four parts (farm facilities, general information of piglets, production performance of nursery pigs and finishing pigs). A total of 28 variables were evaluated by the multi-variable linear regression models. The differences in production factors significantly correlated with FEI at piglets-finishing stage were compared among high-performing (HP), moderate-performing (MP), and low-performing (LP) batches of commercial pigs during the nursery and finishing stage. Among the 28 variables, 18 were significantly correlated with fattening efficiency (P < 0.05), including 11 continuous variables and seven discrete variables. The significant differences among the 11 consecutive variables in the HP, MP, and LP batches of commercial pigs mostly persisted from the piglets-nursery stage to the growing-finishing stage, ultimately affecting the FEI at piglets-finishing stage. For the seven significant discrete variables, the HP batches had a lower proportions in owned source of piglets, number of the purchasing piglets in spring and winter, number of batches in the East and North regions and five-way crossbred pigs, while a higher proportions in the use of closed circuit television video (CCTV) and wastes treatment system. The fattening efficiency of commercial pigs in large-scale pig farms was comprehensively affected by farm facilities, piglets, and production performance at nursery and finishing stage. The low fattening efficiency may have started at the end of nursery stage.

Insect community structure in young and productive coffee farms under leucaena shade of Jember Regency, East Java, Indonesia

The developmental phase of Robusta coffee plantations with agroforestry systems exhibits varying ecosystem characteristics (biotic and abiotic), therebyinfluencing the dynamics of insect community composition within them. One of the major coffee-producing centers in East Java is Jember Regency, where coffeecultivation commonly employs agroforestry systems with various shade trees. Understanding the abundance of insect species in agroforestry coffee plantations is important for determining insect pest control measures. This research aims to study the insect community structure in young coffee and productive coffee farms. Insect sampling was conducted in young coffee farms and productive coffee farms at the Kaliwining Experimental Station, Indonesian Coffee and Cocoa Research Institute (ICCRI), by using road sampling methods with insect nets and pitfall traps. Both types of plantations utilize Leucaena sp. var L2 as shade trees, forming agroforestry coffee plantation systems. Data analysis was performed by calculating the Shannon-Wiener diversity index (H’) to assess insectdiversity and the independent sample t-test to determine differences in insect abundance based on functional roles between the two farms. The results indicatethat the composition and abundance of insects in productive coffee farms are higher than in young coffee farms, resulting in a higher insect diversity index valuefor productive coffee farms (categorized as high), while young coffee farms fall into the moderate category. Furthermore, based on their functional roles, productive coffee farms positively influence the abundance of herbivorous, predatory, parasitoid, and detritivorous insects.

Matlab-Simulink Model of CHMT for Internal Climate in Greenhouses

Over the past twenty years, Kenya&amp;apos;s food security has been threatened by the sub-division of land into tiny areas and the clearance of forests to make way for settlement. These actions have an impact on soil moisture, rainfall patterns, and regional temperature changes. Clear response plans and adaption techniques have been required to address the threats that have arisen. Greenhouse farming, where warmer temperatures are attained and the impact of unfavourable weather conditions on plants is mitigated by the enclosure, is one strategy being used to combat the production of food and climate change. Nevertheless, crop production and quality are negatively impacted by traditional techniques of regulating temperature and humidity through arbitrary opening and closing of the greenhouse walls. In light of this, the goal of this research was to enhance greenhouse farming as it exists today by implementing a dynamic, adjustable system that would create ideal climate conditions for plant growth. This mostly entailed controlling the greenhouse&amp;apos;s humidity, temperature, and vapour pressure deficit to the ideal ranges needed by various plants. The humidity and air temperature within the greenhouse were the controlled microclimate conditions. These were accomplished by simulating the convectional heat transfer and mass transfer that occur inside the greenhouse to control the temperature and humidity, and by developing mathematical model utilizing differential equations. Proportional Integral Derivative (PID) was utilized to automatically modify SIMULINK, a block-based modelling and simulation tool. Regardless of the different external conditions, the numerical values for internal temperature and humidity were calculated and graphically depicted. The model made it possible to modify the outcomes according to the needs of the plant. To increase crop productivity in greenhouse farming, it was suggested that a physical prototype model be constructed and integrated into the greenhouse construction.

Public-Private Partnerships in driving Sustainable Agricultural Growth for Addressing Poverty and Food Insecurity in Nigeria

Poverty and food insecurity have become a concern in various parts of the world including Nigeria which are regarded as impediments for achieving sustainable development goals (SDGs). Overwhelming studies have explored the roles and contributions of public-private partnerships (PPP) in driving various aspects of the economy in general and gross domestic product (GDP) in particular. However, less focus of attention is given to public-private partnerships (PPP) in fostering the sustainable agricultural growth in Nigeria in order to addressing poverty and food insecurity in Nigeria. Content and critical analysis is used in this study as a methodological approach. Secondary data were used which were sourced through academic databases such as journals from google scholar. The result demonstrated that the current hike in the price of commodities in the country contribute to the proliferation of poverty among the households and the challenges of kidnapping and banditry immensely contribute to the challenge of food security in the country. The challenge of funds identified among the farmers contribute immensely to high level of poverty and prevalence of food insecurity in the country. It is therefore suggested that the government should encourage provision of funds through an effective collaboration of public-private partnerships (PPP) in driving sustainable agriculture growth in the country. In so doing, it would strengthen the income of households through farming and sustainable agricultural productivity for poverty alleviation and food security will be achieved.

Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence

This paper proposes an automated approach to the technology selection of High-Voltage Alternating Current (HVAC) Offshore Substations (OHVS) for the integration of Oil &amp; Gas (O&amp;G) production and Offshore Wind Farms (OWF) based on Artificial Intelligence (AI) techniques. Due to the complex regulatory landscape and project diversity, this is enacted via a cost decision-model which was developed based on Knowledge-Based Systems (KBS) and incorporated into an optioneering software named Transmission Optioneering Model (TOM). Equipped with an interactive dashboard, it uses detailed transmission and cost models, as well as a technological and commercial benchmarking of offshore projects to provide a standardized selection approach to OHVS design. By automating this process, the deployment of a technically sound and cost-effective connection in an interactive sandbox environment is streamlined. The decision-model takes as primary inputs the power rating requirements and the distance of the offshore target site and tests multiple voltage/rating configurations and associated costs. The output is then the most technically and economically efficient interconnection setup. Since the TOM process relies on equivalent models and on a broad range of different projects, it is manufacturer-agnostic and can be used for virtually any site as a method that ensures both energy transmission and economic efficiency.

The increasing influence of oyster farming on sedimentary organic matter in a semi-closed subtropical bay

Oyster farming activities play a pivotal role in the biogeochemical cycles of coastal marine ecosystems, particularly in terms of sedimentary carbon cycling. To gain deep insights into the influence of expanding oyster culture on the sedimentary carbon cycle, surface sediments were collected from the Maowei Sea, which is the largest oyster farming bay in south China, based on six filed surveys between July 2010 and December 2022. The sediment samples were analyzed for total organic carbon (TOC), total nitrogen (TN), stable carbon and nitrogen isotopes (δ13C and δ15N) to evaluate the inter-annual variations in the source contribution to sedimentary organic matter (SOM). The results revealed that the average contents of sedimentary TOC and TN were 0.67 ± 0.41 % and 0.06 ± 0.03 %, respectively. Fluctuations in the C/N molar ratios ranged from 5.8 to 23.6, with an average of 12.6 ± 2.9, indicating a significant terrestrial input contribution to SOM in the study area. Furthermore, the integration of stable isotope analysis and Bayesian mixing model demonstrated a gradual increase in the mean proportion of shellfish biodeposition to SOM, from 12.0 ± 5.6 % in July 2010 to 21.1 ± 7.3 % in December 2022, consistent with the progressive expansion of oyster aquaculture along this coastal area, thereby emphasizing the substantial influence of oyster farming on SOM composition. With the anticipated expansion of oyster farming scale and production in the future, shellfish biodeposition is expected to assume a more important role in shaping SOM dynamics and sedimentary organic carbon cycling in coastal waters. Overall, this study provided an important perspective for better assessing the impact of expanding mariculture scale on coastal biogeochemical cycles, thereby making valuable contributions to future policy formulation concerning mariculture and ecological conservation.

Upgrading hazelnut skins: Green extraction of polyphenols from lab to semi-industrial scale

Hazelnut skins (HS) are usually managed as waste; however, this by-product is a source of bioactive compounds, with potential applications in feed and food sectors. Phenolic compounds can be extracted using green protocols combining enabling technologies and green solvents. This work investigates subcritical water extraction (SWE) of bioactive compounds from HS. A laboratory-scale study was performed on four different batches, with significant batch-to-batch heterogeneity. The evaluation of polyphenolic profiles and antioxidant activities afforded promising results compared to the benchmark of reflux maceration. To evaluate process effectiveness, the extraction protocol was replicated on a semi-industrial plant that processed 8 kg of matrix. Downstream processes have been optimized for scale-up, demonstrating the effectiveness of SWE in retaining product concentration and bioactivity avoiding excipients in spray-drying phase. Hazelnut extracts exhibited antibacterial properties against animal- and food-borne pathogens, supporting their potential use as sustainable feed ingredients for improved hazelnut production and animal farming practices.