Search Results (23)

The paper examines the current landscape, as well as the promises and pitfalls, of the digital transition in agricultural production and rural areas in Greece. It questions whether digitalisation is a viable option given the demographic dynamics, gaps in digital infrastructure, and heavy reliance on migrant labour in rural Greece. The methodological approach employs a mixed-methods design, integrating statistical and cartographic analyses of available census data with qualitative methods (semi-structured interviews, ethnographic observations, and a focus group). The main research question is grounded in a brief theoretical framework that addresses critiques of the inevitability of technological innovation and highlights the need to understand the complex dynamics of digital change. The paper analyses the dynamics and challenges of digital change in rural Greece, examining how demographic change and ageing, the structure and size of farms, and dependence on migrant labour relate to gaps and inequalities in digital infrastructure and skills. A critique of the prevailing discourse on digital transformation is supported by a discussion of the recently collected qualitative empirical material. The concluding section highlights the key findings and provides policy recommendations. Full article

Women’s reproductive decisions and life trajectories are shaped by an interplay of biological, social, and ecological factors. While Life History Theory (LHT) has traditionally been applied in biological sciences to examine reproductive trade-offs, its integration with Life Course Theory (LCT) and empowerment frameworks offers a novel approach to understanding how structural and environmental conditions shape women’s reproductive behaviours and household roles. This study applies Categorical Principal Component Analysis (CATPCA) to identify key profiles of women’s lives in two ecologically distinct rural communities in Timor-Leste—Ossu and Natarbora—and examines how these patterns relate to early life conditions. Building on a longitudinal study conducted in these communities, our findings reveal four distinct profiles: (1) Tech and Sanitation, linked to household labour-saving technology and higher education; (2) Traditional, reflecting large household size and livestock ownership; (3) Contraception, associated with fertility control, particularly among younger cohorts; and (4) High Fertility, characterised by more births, greater child mortality, and being born in high-altitude regions. By combining LHT, LCT, and the empowerment framework, this study analyses how reproductive strategies and household ecology intersect with structural inequalities. These findings offer key insights for policies aimed at improving women’s autonomy, access to resources, and reproductive health in rural Timor-Leste. Full article

Is additive manufacturing (AM) a sustainable process? Can the process be optimised to produce sustainable AM parts and production techniques? Additive manufacturing offers the production of parts made of different types of materials in addition to the complex geometry that is difficult or impossible to produce by using the traditional subtractive methods. This study is focused on the optimisation of laser powder bed fusion (L-PBF), one of the most common technologies used in additive manufacturing and 3D printing. This research was carried out by modulating the build layer thickness of the deposited metal powder and the input volumetric energy density. The aim of the proposed strategy is to save the build time by maximizing the applied layer thickness of nitinol powder while retrieving the different AM part properties. The saving in the process time has a direct effect on the total cost of the produced part as a result of several components like electric energy, inert gas consumption, and labour. Nickel-rich nitinol (52.39 Ni at.%) was selected for investigation in this study due to its extremely high superplastic and shape memory properties in addition to the wide application in various industries like aerospace, biomedical, and automotive. The results obtained show that significant energy and material consumption can be found by producing near full dens AM parts with limited or no alteration in chemical and mechanical properties. Full article

We aim to develop new portable desktop tissue analysers (DTAs) to provide fast, low-cost, and precise test results for fast nanomechanical profiling of tumours. This paper will explain the reasoning for choosing indentation-type atomic force microscopy (IT-AFM) to reveal the functional details of cancer. Determining the subtype, cancer stage, and prognosis will be possible, which aids in choosing the best treatment. DTAs are based on fast IT-AFM at the size of a small box that can be made for a low budget compared to other clinical imaging tools. The DTAs can work in remote areas and all parts of the world. There are a number of direct benefits: First, it is no longer needed to wait a week for the pathology report as the test will only take 10 min. Second, it avoids the complicated steps of making histopathology slides and saves costs of labour. Third, computers and robots are more consistent, more reliable, and more economical than human workers which may result in fewer diagnostic errors. Fourth, the IT-AFM analysis is capable of distinguishing between various cancer subtypes. Fifth, the IT-AFM analysis could reveal new insights about why immunotherapy fails. Sixth, IT-AFM may provide new insights into the neoadjuvant treatment response. Seventh, the healthcare system saves money by reducing diagnostic backlogs. Eighth, the results are stored on a central server and can be accessed to develop strategies to prevent cancer. To bring the IT-AFM technology from the bench to the operation theatre, a fast IT-AFM sensor needs to be developed and integrated into the DTAs. Full article

Upscaling sustainable intensification (SI) technologies is crucial to enhancing the resilience of fragile farming systems and vulnerable livelihoods of smallholder farmers. It is also critical to shape the future land-use and land-cover changes in a region. Zero-tillage potato cultivation (ZTPC), introduced as an SI intervention in parts of the Indian Sundarbans, has demonstrated promises of rapid upscaling, and thus, changes in the seasonal land-use pattern in the region. This study aims to understand the socioecological complexity of farming systems to comprehend how the nascent stage of ZTPC thrives at the farm level and what preconditions are necessary to upscale them. The objectives are to analyse the farm resource recycling pattern in ZTPC, and map and simulate its system’s complexity to strategize ZTPC upscaling in the region. The analysis of farm resource recycling data reveals that ZTPC stability hinges on managing trade-offs in resource allocations, specifically involving straw, organic manure, sweet water, and family labour. The decision to manage such trade-offs depends on farm type characterizations by their landholdings, distance from the homestead, pond, and cattle ownership, competing crops, and family composition. Using a semiquantitative systems model developed through fuzzy cognitive mapping, the study underscores the significance of effective training, input support, enterprise diversification by introducing livestock, timely tuber supply, access to critical irrigation, and capacity building of local institutions as the essential preconditions to sustain and upscale ZTPC. This research contributes a systems perspective to predict agricultural land use within technology transfer initiatives, providing insights into how farm- and extra-farm factors influence resource allocations for ZTPC. Public extension offices must understand the trade-offs associated with straw, organic matter, and harvested water and design differentiated supports for different farm types. The most compelling interventions to upscale ZTPC includes farm diversification by introducing livestock through institutional convergence, pragmatic agroforestry initiatives to enhance on-farm biomass and fuel production, building awareness and integrating alternative energy use to save straw and cow dung, building social capital to ensure access to sweet irrigation water, and developing and/or strengthening farmer collectives to ensure the supply of quality tuber and marketing of farm produce. Full article

A clear understanding of the number of pigs plays a crucial role in breeding management. Computer vision technology possesses several advantages, as it is harmless and labour-saving compared to traditional counting methods. Nevertheless, the existing methods still face some challenges, such as: (1) the lack of a substantial high-precision pig-counting dataset; (2) creating a dataset for instance segmentation can be time-consuming and labor-intensive; (3) interactive occlusion and overlapping always lead to incorrect recognition of pigs; (4) existing methods for counting such as object detection have limited accuracy. To address the issues of dataset scarcity and labor-intensive manual labeling, we make a semi-auto instance labeling tool (SAI) to help us to produce a high-precision pig counting dataset named Count1200 including 1220 images and 25,762 instances. The speed at which we make labels far exceeds the speed of manual annotation. A concise and efficient instance segmentation model built upon several novel modules, referred to as the Instances Counting Network (ICNet), is proposed in this paper for pig counting. ICNet is a dual-branch model ingeniously formed of a combination of several layers, which is named the Parallel Deformable Convolutions Layer (PDCL), which is trained from scratch and primarily composed of a couple of parallel deformable convolution blocks (PDCBs). We effectively leverage the characteristic of modeling long-range sequences to build our basic block and compute layer. Along with the benefits of a large effective receptive field, PDCL achieves a better performance for multi-scale objects. In the trade-off between computational resources and performance, ICNet demonstrates excellent performance and surpasses other models in Count1200, $AP$ of 71.4% and $A{P}^{50}$ of 95.7% are obtained in our experiments. This work provides inspiration for the rapid creation of high-precision datasets and proposes an accurate approach to pig counting. Full article

Smart building technologies and building automation and control systems (BACS) can offer a range of additional benefits beyond energy savings, in particular by improving building responsiveness to user needs. Although in recent years these technologies have gained popularity as a means of reducing energy consumption and improving building performance, a clear picture of the role of BACS in providing a wider range of benefits is still missing. This review identifies and collects BACS impacts in office buildings with a special emphasis on improving indoor environmental quality by adapting building operation to changing conditions and guaranteeing feedback and real-time interaction with occupants. The resulting benefits, such as increased employee productivity, fewer occurrences of sick leave, and lower rates of absenteeism are highlighted. Offices represent an interesting field of application, as small improvements in the built environment can have a significant impact on labour costs which are the predominant share of the total operating costs. Furthermore, quantitative relationships between physical factors of the indoor environment and benefits have been displayed where available. This literature review aims at establishing an approach that comprehensively evaluates BACS across their entire spectrum, leading to the promotion of novel business cases. Full article

Environmentally friendly fertilisers (EFFs) can improve the quality of cultivated land, purify the soil environment, and promote reduction in the amounts of fertiliser applied by improving efficiency. However, few studies have analysed the spillover effects of EFF applications on agricultural labour inputs. Hence, this study discusses the impact of EFFs on agricultural labour input, using the propensity score matching method based on the micro-survey data of peanut growers in the main producing areas in China. The results showed that EFFs have a labour-saving advantage, with a significant average reduction in the number of labourers’ input and labour days in agriculture production of 0.127 persons/mu and 0.601 days/mu at the 1% to 10% significance level. Additionally, EFFs improve yield and revenue but significantly raise production costs, ultimately increasing net revenue for farmers. The mechanism of the labour-saving effect is the capability of EFFs to reduce the amount and frequency of fertilisers applications, the amounts of pesticides applied, and irrigation water consumption by their technical characteristics and farmland’s ecological environment enhancement. Accordingly, the time effect strengthens the ecological regulation function and the application reduction effect of EFFs, further decreasing agricultural labour inputs. At the same time, the application of EFFs contributes to the adoption of mechanical deep tillage and fertilisation technology (MDTFT), thereby reducing fertiliser application and ultimately improving the labour-saving effect of EFFs. Heterogeneity analysis revealed that the labour-saving effect of EFFs is more obvious for farmers operating with a larger planting scale. To improve the labour-saving effect of EFFs, the findings imply that the application years of EFFs should be appropriately extended and the MDTFT should be promoted according to local conditions. Full article

Declining water availability is pressing rice growers to adopt water-saving irrigation practices such as aerobic rice to maintain profitability per megalitre (ML) of water input. Irrigators require well-defined irrigation thresholds to initiate irrigation to maximise water productivity. Such thresholds do not exist for temperate rice regions. Adopting a strategy that has been reported to succeed in non-temperate environments may fail in temperate climates, and therefore, needs investigation. This study aimed to investigate, in a temperate Australian environment, the effect of increasing soil moisture deficit during the rice vegetative period on crop physiological development, grain yield and water productivity. The study was conducted in a commercial farm using a randomised complete block design in the 2020/21 and 2021/22 growing seasons. Automated gravity surface irrigation technologies were adopted to enable high-frequency irrigation. Extending soil moisture deficit beyond 15 kPa was found to significantly delay panicle initiation by at least 13–14 days, exposing rice to cold temperatures in Year 1 during the cold-sensitive early pollen microspore period. This reduced yield by up to 55% (4.5 t/ha) compared to the 15 kPa treatment that was not impacted by cold sterility. In the absence of cold sterility, irrigated water productivity and total water productivity ranged between 1.02 and 1.61 t/ML, and 0.84 and 0.93 t/ML, respectively. The highest yields (8.1 and 7.5 t/ha) were achieved irrigating at a soil tension of 15 kPa in growing seasons 2020/21 and 2021/22. This research demonstrates that sound water productivity can be achieved with aerobic rice cultivation in temperate climates, providing cold temperatures during early pollen microspore are avoided. The quantification of the delay in crop development caused by increasing soil moisture deficit provides rice farmers greater confidence in determining the irrigation strategy and timing of pre-emergent irrigation in regions at risk of cold sterility. However, due to the high labour demand associated with aerobic rice, the adoption of aerobic rice at a commercial scale in this Australian environment is unlikely without adopting automated irrigation technology. Full article

This study examines sustainability and gender dynamics of coffee value-chain development intervention in Ethiopia. The data were collected from male and female farmers and other stakeholders using key informant interviews, focus group discussions, and a questionnaire survey. The study found that some of the introduced technologies/practices were adopted and sustained whereas others were dropped or adapted depending on technical, institutional, and socio-economic factors. The value-chain intervention was generic and not gender-sensitive. Although the intervention generated positive changes and benefits for all household members (by improving coffee quality, market access, and their income), it had mixed outcomes for women. Although women were not primarily targeted by the intervention, their increased involvement in coffee harvesting and processing fostered women’s skills, confidence, and decision-making power. However, some of the new technologies/practices required additional labour, while others were labour saving and eased their work. As a result of increasing the wholesale trading of coffee, the role for marketing largely shifted to men. This study underscores the need for a proper gender analysis and embedding gender-sensitive approaches in designing development interventions to ensure women’s fair representation, and thus equitable and sustainable benefits. Such efforts should entail a paradigm shift from production to promoting women’s role and integration into the entire value chain, as well as improving their access to productive resources and services. Moreover, value-chain development interventions should consider technical, institutional, social, and economic factors that could influence their effectiveness and sustainability. Full article

Background: The number of publications in supply chain management (SCM) and artificial intelligence (AI) has risen significantly in the last two decades, and their quality and outcomes vary widely. This study attempts to synthesise the existing literature in this research area and summarise the findings regarding barriers, drivers, and social implications of using AI in SCM. Methods: The methodology used for this meta-study is based on Kitchenham and Charters guidelines, resulting in a selection of 44 literature reviews published between 2000 and 2021. Results: As a summary of the results, the main areas of AI in SCM were algorithms, followed by the Internet of Things (IoT). The main barriers to AI adoption in SCM are change management, existing technical limitations, and the acceptance of humans for these techniques. The main drivers of AI in SCM are saving costs and increasing efficiency in combination with reducing time and resources. The main social factor is human–robot collaboration. As a result, there will be a decreased amount of labour needed in the future, impacting many existing jobs, especially in low-income areas. Conclusions: Therefore, it is essential for organisations that implement new technology to start as early as possible to inform the organisation about the changes and help them successfully implement them. It is also important to mention that constant learning and improvement of the employees are critical for adopting and successfully using new AI tools. Before investing in new technology, a solid Return on Investment calculation (ROI) and monitoring costs and value are critical to transforming the business successfully. Full article

Robotic Process Automation (RPA) is a source of growing applications in a number of industries both as an individual technology and as a complement to other technologies (such as Internet of Things (IoT)). RPA allows the automation of human activities on a computer, especially when these activities are repetitive and high in volume. RPA saves man-hours and increases the productive capacity of the processes. The application of RPA in civil engineering is still in its early stages, and there has been little work on the subject in the literature. This paper presents RPA technology, for the first time in the literature, as a long-term management, control, and auto fault correction process for a low-cost accelerometer that can be used in SHM applications. However, this process requires a significant number of man-hours to stay operational, given the architecture of its applications. With the application of an RPA implementation workflow formulated based on the Design Science Research Method (DSRM), the management and control of the data acquisition process of a low-cost accelerometer located on a structural column are automated and put into operation in this study. RPA also made it possible to automatically detect and notify users of errors in the process, restart the process, and bring the process back online every time errors occurred. In this way, an automated process was obtained that operated continually and freed up human labour. Full article

The global spread of COVID-19 has complicated the international equilibrium of grain production and trade. China now faces external shocks in the international grain market and deep-seated problems associated with the structure of domestic supply. We used a dynamic, computable general equilibrium (CGE) model to analyse the effects on China’s food security and macroeconomics under the COVID-19 scenario and four technological progress paths in the agricultural sector. We showed that the COVID-19 pandemic is disrupting China’s food security in the short term, and critical quantitative variables such as grain production and grain consumption per capita have declined. Considering food security and macroeconomic development, labour-saving technological progress outperformed neutral technological progress, land-saving technological progress, and capital-saving technological progress in the short run. While land-saving technological progress contributes the most to the arable land area per capita of wheat and other grains in the long run. Full article

The research object is the installation process of modular green roofs with planters placed on the concrete roof’s surface. These roofs effectively reduce rainfall disposal, prolong the lifespan of the roof coating, and enhance urban aesthetic and recreational spaces. Green roofs reduce houses’ gas emissions and increase green spaces in densely built areas. The spatial–technological model was developed for the proposed modular green roof based on network planning, scheduling theory, and graph theory. The sequence and composition of technological processes and operations were established for the installation process. The functional model of installing a modular green roof has been developed. The model makes it possible to optimise the principles of saving labour contribution (working hours) and time. Full article

Finger millet (Eleusine coracana (L.) Gaertn) is a highly nutritious crop, predominantly grown in the semi-arid tropics of the world. Finger millet has a niche market opportunity due to its human health benefits and being rich in calcium, iron and dietary fiber and gluten-free. Ethiopia is the center of the genetic diversity of the crop. However, the productivity of finger millet in the country is low (<2.4 tons ha⁻¹) compared with its potential yield (6 tons ha⁻¹). The yield gap in Ethiopia is due to a range of biotic and abiotic stresses and socio-economic constraints that are yet to be systemically documented and prioritized to guide future production and improved variety development and release. The objective of this study was to document finger millet production opportunities, constraints and farmer-preferred traits in Ethiopia as a guide to variety design in improvement programs. A participatory rural appraisal (PRA) study was undertaken in six selected districts of the Southern Nation Nationalities People Region (SNNPR) and Oromia Region in Ethiopia. Data were collected from 240 and 180 participant farmers through a semi-structured questionnaire and focus group discussion, respectively. Finger millet was the most important crop in the study areas grown mainly for a combination of uses, including for food, feed and cash (reported by 38.8% of respondent farmers), food and feed (14.5%), food and cash (13.7%), food (11.5%) and food, cash, feed and construction material (9.7%). Hand weeding was used by 59.2% of the respondent farmers, followed by hand weeding and chemical herbicides (40.8%). Finger millet was mainly planted as a sole crop (reported by 97.0% respondents), mixed (1.7%) and sole and mixed (1.3%). About 75.6% of respondent farmers only practiced finger millet rotation with other crops. Respondent farmers indicated their source of fresh seed was from the Bureau of Agriculture (49.1%), farmer-to-farmer seed exchange (22.1%), own saved seed (7.5%), local producers (7.5%), research institutions (5.8%), unknown sources (4.1%), local market (3.5%) and cooperatives (0.42%). The total cost of finger millet production per hectare was calculated at 1249 USD with a total income of 2139 USD/ha, making a benefit to cost ratio of 1.71:1.00 and indicating the relatively low yield gains using the currently grown varieties. The main constraints to finger millet production in the study areas were drought stress (reported by 41.3% respondents), lack of improved varieties (12.9%), lack of financial resources (11.3%), small land holdings (10.8%), limited access to seed (10.0%), a shortage of fertilizers (5.4%), poor soil fertility (4.6%), shortage of draught power (1.3%), labour shortages (1.3%) and high labour costs (1.3%). The most important farmer-preferred traits in a finger millet variety were high grain yield, compact head shape, ‘enjera’-making quality, high marketability and early maturity, resolved through principal component analysis. The above-mentioned production constraints and farmer-preferred traits are strategic drivers to enhance finger millet productivity and need to be incorporated into Ethiopia’s finger millet breeding and technology development. Full article