Trends In Production Research Articles

Analysis of Growth Trends, Regional Variations and Productivity Metrics of Apple Cultivation in Himachal Pradesh, India

India has seen a spatial escalation on apple growth and it fostered the country’s economy and employment opportunities of the apple growing states. States of Jammu & Kashmir, Himachal Pradesh, Uttarakhand and Arunachal Pradesh are primarily known for apple production. Therefore, we worked on the secondary data on apple growth trends, its production from the different sources and analyzed it through growth rate, decomposition analysis and instability index techniques to quantify the production metrics and trend shift. Our findings reported that between1973–1974 to 2021–2022, there was an increase found in the global area, productivity and production of apples in Asia and India. The output of apples worldwide has found to be escalated at a compound annual growth rate of 2.51%, whereas, India has experienced a notable rise of 3.40 percent annually. The majority of the apple's area, output and productivity came from the Asian region, with growth rates of 3.38, 5.97, and 2.59 %, respectively. Furthermore, Worldwide scenario on apple cultivation reported that Poland had the highest relative instability in apple productivity (21.44%), followed by India (15.96%), China (12.53%), Turkey (11.18%) and USA (8.61%). Area yield effect was used to explain the rise in apple output in Asia, however, area expansion was found as the primary cause of increase in area under apple production. In Himachal Pradesh, Zone III has the greatest average yearly productivity (4.78%), followed by Zone II (3.35 %) and Zone IV (0.57%). In zones III and IV, the expansion of area (96.93%) and yields (85.13%) was the reason for the increase in apple production, however, in zone II, the yield effect (102.05%) was the only cause found for the increase in apple’s production.

Emerging trends in the selective production of value-added aromatics

Emerging trends in the selective production of value-added aromatics

Mapping the Evolution of Digital Health Research: Bibliometric Overview of Research Hotspots, Trends, and Collaboration of Publications in JMIR (1999-2024).

While bibliometric studies of individual journals have been conducted, to the best of our knowledge, bibliometric mapping has not yet been utilized to analyze the literature published by the Journal of Medical Internet Research (JMIR). In celebration of the journal's 25th anniversary, this study aimed to review the entire collection of JMIR publications from 1999 to 2024 and provide a comprehensive overview of the main publication characteristics. This study included papers published in JMIR during the 25-year period from 1999 to 2024. The data were analyzed using CiteSpace, VOSviewer, and the "Bibliometrix" package in R. Through descriptive bibliometrics, we examined the dynamics and trend patterns of JMIR literature production and identified the most prolific authors, papers, institutions, and countries. Bibliometric maps were used to visualize the content of published articles and to identify the most prominent research terms and topics, along with their evolution. A bibliometric network map was constructed to determine the hot research topics over the past 25 years. This study revealed positive trends in literature production, with both the total number of publications and the average number of citations increasing over the years. And the global COVID-19 pandemic induced an explosive rise in the number of publications in JMIR. The most productive institutions were predominantly from the United States, which ranked highest in successful publications within the journal. The editor-in-chief of JMIR was identified as a pioneer in this field. The thematic analysis indicated that the most prolific topics aligned with the primary aims and scope of the journal. Currently and in the foreseeable future, the main themes of JMIR include "artificial intelligence," "patient empowerment," and "victimization." This bibliometric study highlighted significant contributions to digital health by identifying key research trends, themes, influential authors, and collaborations. The findings underscore the necessity to enhance publications from developing countries, improve gender diversity among authors, and expand the range of research topics explored in the journal.

Spatiotemporal dynamics of vegetation net primary productivity and its response to climate variability

Despite its significance, net primary productivity is rarely used as an indicator of climate change. The purpose of this study was to assess the spatiotemporal dynamics of vegetation net primary productivity and its response to climate variability in the Welmel watershed, southeastern Ethiopia. The investigation utilized data from the Moderate Resolution Imaging Spectroradiometer, and the Climate Hazards Group Infrared Precipitation with Stations accessed through the Google Earth Engine cloud computing platform. To evaluate the trend and response of net primary productivity to climatic factors, the Mann-Kendall and Theil Sen’s tests, the Pearson correlation coefficient, and stability analysis through the coefficient of variation of net primary productivity were utilized. The analysis of the temporal trend of net primary productivity revealed that the entire watershed, forest, wood, and cultivated land areas exhibited decreasing trends with net primary productivity values of -0.681, -4.361, -1.41, and − 3.25 g C m− 2/year, respectively. On the other hand, shrubs and grazing land displayed increasing trends of 1.15 and 2.04 g C m− 2/year, respectively. The wood and shrubland trends were statistically significant (p < 0.05). In the spatial analysis, an area of 64.6% showed a decreasing trend, whereas 33.78% displayed an increasing trend in net primary productivity values. The areas with stable and unstable variations in net primary productivity accounted for 26.47% and 8.02%, respectively. The net primary productivity of the land cover types and entire watershed were positively correlated with rainfall, however, only forests and woodlands were statistically significantly correlated (p < 0.05). The net primary productivity and land surface temperature were negatively correlated, except for forests and cultivated land, which were positively correlated. The results of this study provide essential information for managing ecosystems, supporting agricultural practices, and enhancing community resilience in a changing climate.

Synthesis of Ag/Cu decorated 3D self-assembled nanowire TiO2 photocatalyst for hydrogen production: a promising pathway towards sustainable energy generation.

Here, synthesis and characterization of TiO2 with different morphologies along with the cost-effective bimetallic decoration on optimized 3D self-assembled nanowire TiO2 (NWT) photocatalyst (Ag/Cu-NWT) with overwhelming hydrogen production rate is reported. All the photocatalysts were well characterized by different characterization techniques. Initially, the effect of morphology change obtained by changing the NaOH concentration has been studied for TiO2. Morphology obtained at 10M NaOH solution, i.e., NWT (678μmol/g), showed better hydrogen production than morphology obtained at 5M (410μmol/g), 15M (210μmol/g), and 20M (160μmol/g) NaOH solutions. Further, with the aim to achieve comparable or better activity low-cost photocatalyst as compared to Pt-TiO2 system, NWT was decorated with various Cu percentages and then with a minimal percentage of Ag on an optimized Cu-NWT photocatalyst. The observed trend for photocatalytic hydrogen production has been found to be P25 TiO2 < NWT < 1.0Cu-NWT < 0.5Pt-NWT ≤ 0.1Ag/1.0Cu-NWT. The marked increase by a factor of 103 in hydrogen production for the optimized bimetallic 0.1Ag/1.0Cu-NWT (10,184μmol/g) photocatalyst compared to P25 TiO2 (99μmol/g), nearly threefold increment in hydrogen production than an optimized 1.0 Cu-NWT (3907μmol/g) photocatalyst and comparable hydrogen production as compared to 0.5Pt-NWT (10,050μmol/g) may be attributed to the successful synthesis of a highly porous NWT morphology, which offers large surface area, increased light absorption combined with the synergistic effects of surface plasmon resonance (SPR), and the Schottky barrier for H+ reduction to H2 gas. The optimization of TiO2 morphology and an inexpensive bimetallic decoration strategy opens up promising opportunities for the development of cost-effective photocatalysts in the realm of energy and environment.

Complementary and competitive dynamics of CO2 and N2 in CH4 – Flue gas replacement within natural gas hydrates

To mitigate global warming, the paramount imperative lies in curbing the emission of CO2. The guest replacement method is a prominent carbon-neutral technological advancement that involves injecting CO2 into natural gas hydrate layers to accomplish the dual objectives of energy production and carbon storage. In this study, the guest dynamics in the CH4 – flue gas replacement process were examined, and the impacts of the N2 concentration of the injected gas were systematically analyzed. A powder X-ray diffraction analysis of the cage-specific guest distributions after CH4 − CO2 (20 %) + N2 (80 %) replacement revealed that CH4 production increased in both the large and small cages compared to the CH4 – CO2 replacement. This enhancement was attributed to the N2 molecules participating in both cages. However, this simultaneously led to a decrease in CO2 storage potential, indicating a ‘complementary’ relationship for CH4 production and a ‘competitive’ one for CO2 storage with respect to CO2 and N2. In situ Raman spectroscopy revealed that the introduction of N2 resulted in a deceleration of CO2 storage kinetics. Guest composition measurements after replacement showed an upward trend in CH4 production and a simultaneous decline in CO2 storage as the N2 composition increased. Notably, an intriguing correlation was established between the CO2/N2 ratios for the injected gas and the replaced hydrates, exhibiting a strong alignment with a simple first-order equation. The findings not only contribute to a deeper understanding of the CH4 − CO2 + N2 replacement technique but provide practical insights for its application in real-world scenarios.

Intercomparison of gross primary productivity in spatio-temporal distribution over a typical tropical region based on different datasets.

Gross Primary Productivity (GPP) plays a vital role in the carbon cycle of terrestrial ecosystems. For the purpose of assessing the performance of various GPP products in a typical tropical area, this study conducted an intercomparison of seven different GPP products over Hainan Island, China, and analyzed spatiotemporal characteristics of GPP in different elevation regions and vegetation types over study area. The results showed that although the GPP spatial distribution pattern over Hainan Island, as presented by different GPP products, is similar- showing that GPP values in the southwest are higher than those in the northeast- there are significant differences in the spatial distributions and magnitudes of each GPP product. The multi-annual mean GPP values from the seven GPP products exhibited similar temporal variation trends, with GOSIF being obviously higher than other GPP products. The GPP products indicated significant differences in different elevation and vegetation type groups. The GPP gap between GLASS AVHRR and BESS V2 decreases slightly with the increase in elevation. Most GPP products show a consistent change trend over time. There were also significant differences in the results of significance tests for the change trends of GPP products. Though GOSIF is significantly higher than other GPP products, it demonstrated a relatively high correlation with all GPP products, while AGPP exhibited relatively low correlations with all GPP products. The quantitatively comparative analysis of seven different GPP products in this study is valuable for improving GPP retrieval models and can also serve as a scientific reference for the application of GPP products in tropical region vegetation studies.

Forecasting Emerging Product Trends in Smart Supply Chains

Forecasting Emerging Product Trends in Smart Supply Chains

Enhanced relationship between seasonal soil moisture droughts and vegetation under climate change over China

Climate change could intensify seasonal soil moisture droughts and subsequently degrade vegetation, but it can also facilitate vegetation growth with the rising temperature and CO2 concentrations. Therefore, the change of the vegetation-drought relationship under climate change remains elusive. Here, we investigate the effects of vegetation greening (i.e., increasing leaf area index (LAI)) on seasonal soil moisture drought trends by performing a set of land surface model simulations with the Conjunctive Surface-Subsurface Process model version 2 (CSSPv2), as well as the impact of seasonal soil moisture drought change on vegetation productivity via a statistical fitting model. Our results indicate that both the impact of increasing LAI on exacerbating seasonal droughts and the impact of increasing seasonal droughts on reducing vegetation productivity have been enhanced over China during 1961–2018. Specifically, increased LAI accounts for 48 % of the rising drought frequency through escalated evapotranspiration losses, with more pronounced effects in northern semiarid regions. The decrease in vegetation stomatal conductance caused by rising CO2 concentrations limits transpiration and alleviates 11 % of the increase in drought frequency, but it cannot fully offset the drought aggravation induced by increased vegetation water consumption under climate warming. Meanwhile, increased drought frequency and intensity have reduced the upward trend in vegetation productivity by 5 % over China, and by 8 % in water-limited northern regions. Our study shows the relationship between seasonal soil moisture droughts and vegetation over China has strengthened, indicating that vegetation greening will lead to increased water shortages and further impact vegetation growth and carbon sequestration. This challenges water resources management and environmental sustainability, especially in semiarid regions.

Mapping the scientific landscape and evolution of the international journal of surgery: A scientometric analysis (2004-2024)

Aim: The purpose of this study was to analyze the publication characteristics and development of the International Journal of Surgery over its 20-year history. Methods: This study included articles published in IJS during the 20 years from 2004 to 2024. The data were analyzed using the Citespace, VOS viewer, and the ‘Bibliometrix’ package in R software. We studied the dynamics and trend patterns of IJS literature production through descriptive bibliometrics and identified the most prolific authors, publications, institutions, and countries. Bibliometric maps were utilized to visualize published articles’ content and identify the most prolific research terms and topics in IJS, as well as their evolution over time. Results: A total of 5964 publications in the IJS from 2004 to 2023 and 356 publications in 2024 were included in the analysis. The study revealed a positive trend in literature production, although the number of articles published in IJS has slightly decreased recently. The most productive country was China (n=1,211), the most productive institution was Sichuan University (n=151), and the most prolific author was Wang Yang (n=87). The top 15 most cited articles focus primarily on research reporting standard guidelines for surgical studies. Research published in IJS mainly targeted middle-aged and older adults, emphasizing postoperative complications and treatment outcomes. The future research focus in IJS might center on integrating artificial intelligence and deep learning technologies to revolutionize surgical research and practice. Conclusions: The International Journal of Surgery significantly contributes to advances in surgical research. IJS prioritized enhancing patient outcomes and advancing surgical techniques, focusing on middle-aged and older adults, postoperative complications, and treatment outcomes. The journal emphasized robust evidence through retrospective, controlled, and cohort surgical studies. Integrating artificial intelligence and deep learning represented a significant frontier poised to revolutionize surgical care, shaping the future landscape of research and practice.

Trends and Future Directions in Analysing Attractiveness of Geoparks Using an Automated Merging Method of Multiple Databases—R-Based Bibliometric Analysis

Since their creation, geoparks have been among the fastest growing natural environments. Their attractiveness is one of the most important factors for the success of this natural destination. Despite their importance, a bibliometric analysis on geopark attractiveness is missing from the studied databases. The aim of this paper is to synthesise a heterogeneous body of knowledge of geoparks in terms of attractiveness, highlighting the evolution and breadth of the research field. To achieve this, the following objectives were set: (a) to adopt a method based on functions provided by the bibliometrix package to automatically combine databases, namely WoS, Scopus, PubMed and Dimensions, detailing the method used and (b) to analyse the bibliometric indicators in order to identify the trends in the literature and the possible directions for future research. The applied methodology was based on bibliometric analysis using R for non-coders. From the 707 documents retrieved, the validation process resulted in 349 eligible documents published between 2002 and 2024, on which the analysis was carried out. The current study elaborated a method and examined the key information on the topic trends, which were given by production performance, productivity trends, spatial analysis and abstract approach analysis. Additionally, strategic mapping of the conceptual context was performed. Thus, the result provides a description of the automatic method with practical applications. As discerned from the three-dimensional analysis (spatial, temporal and size), the emerging research directions within scientific creativity encompassed (1) forms of tourism practiced in geoparks, especially focused on ecotourism and volcanic tourism; (2) geomorphological features, mineral springs and mud volcanoes; (3) aesthetic aspects, scenic sites and mining heritage; and (4) methodology, data analysis and modelling methods across different regions and countries.

Innovations through crop switching happen on the diverse margins of US agriculture

Crop switching, in which farmers grow a crop that is novel to a given field, can help agricultural systems adapt to changing environmental, cultural, and market forces. Yet while regional crop production trends receive significant attention, relatively little is known about the local-scale crop switching that underlies these macrotrends. We characterized local crop-switching patterns across the United States using the US Department of Agriculture (USDA) Cropland Data Layer, an annual time series of high resolution (30 m pixel size) remote-sensed cropland data from 2008 to 2022. We found that at multiple spatial scales, crop switching was most common in sparsely cultivated landscapes and in landscapes with high crop diversity, whereas it was low in homogeneous, highly agricultural areas such as the Midwestern corn belt, suggesting a number of potential social and economic mechanisms influencing farmers' crop choices. Crop-switching rates were high overall, occurring on more than 6% of all US cropland in the average year. Applying a framework that classified crop switches based on their temporal novelty (crop introduction versus discontinuation), spatial novelty (locally divergent versus convergent switching), and categorical novelty (transformative versus incremental switching), we found distinct spatial patterns for these three novelty dimensions, indicating a dynamic and multifaceted set of cropping changes across US farms. Collectively, these results suggest that innovation through crop switching is playing out very differently in various parts of the country, with potentially significant implications for the resilience of agricultural systems to changes in climate and other systemic trends.

Connection of innovation activity effectiveness and technological novelty of innovation output

The paper studies the relationship between the innovation performance of Russian industrial enterprises and the degree of technological novelty of their innovative products. For this purpose, the innovation function is introduced. That function reflects the dependence of the “output” of the innovation process on its factors measured by the costs of process and product innovations. Hypotheses about the properties of this function are discussed. The relationship between the two types of innovation costs is considered. As an indicator of technological efficiency the ratio of the value of innovative products to the innovative resource costs is used. The dependence of the performance indicator on innovation costs is investigated. The points of local maxima (local technological optimum) of the performance indicator for the size classes of Russian industrial enterprises are found. It is shown that there is a relationship between the effectiveness of innovative activity and the degree of technological novelty of innovative products. As an indicator of the degree of technological novelty the share of the innovative products new to the market in all innovative products is used. It was established that there is a change in the trend of innovative production from the production of radical to incremental innovative products when approaching the technological optimum.

Changing relationships between armaments production and exports and state defense expenditures

The present study is relevant, because in different countries of the world in recent years there have been ambiguous dynamics among armaments and military equipment production and exports and changes in state defense expenditures. Modern geopolitical conflicts distort the existing picture of interrelations between the above parameters, and the article assesses their changes. In particular, as the study result, the underlying hypotheses on the relationships between supply and demand in the global market of armaments and military equipment have been formulated. The key countries analysis showed that the dynamics of indicators in them is determined by different reasons, but the author came to the conclusion that the main factors of changes in the trends of armaments production and exports and defense expenditures are the following: the expansion of illegal circulation of armaments and military equipment in some countries, increased vulnerability of some countries and their direct involvement in military-political conflicts, as well as differentiation of countries’ approaches to national security, which causes different attention to defense capabilities and the defense industry development. At the same time, there are almost always sharp changes and volatility of the indicators under consideration during the periods when a country is in the stage of industrialization or transition to a new technological mode.

The innovated national noise monitoring network in The Netherlands

Over ten years ago, the National Institute for Public Health and the Environment started monitoring noise emissions from major roads and railways in The Netherlands. Today, this monitoring program is still going strong. The measured data is used to validate the yearly reported noise production levels calculated by the Dutch road and railway authorities, to monitor trends in noise production, and to check the validity of the Dutch noise calculation method. Measurements in the entire network are performed at an altitude of four meters close to fifty meters from the major road or railway in free field as these are the requirements for the reported calculated levels. The network therefore, has to operate stand-alone, resulting in challenges in terms of power supply, datastorage and communication. Ten years ago, we started with a battery-powered network of simple and cost-effective dataloggers. Recently, we made innovations by transitioning to a solar-powered network of modern sound level meters with remote data communication. In this presentation I will give a brief history of this monitoring network, how it developed, and show you the possibilities of the present-day innovated network.

European pollen reanalysis, 1980–2022, for alder, birch, and olive

The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980–2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications.

Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis

This study explores the evolution and impact of research on the challenges and opportunities in the implementation of artificial intelligence (AI) in manufacturing between 2019 and August 2024. By addressing the growing integration of AI technologies in the manufacturing sector, the research seeks to provide a comprehensive view of how AI applications are transforming production processes, improving efficiency, and opening new business opportunities. A bibliometric analysis was conducted, examining global scientific production, influential authors, key sources, and thematic trends. Data were collected from Scopus, and a detailed review of key publications was carried out to identify knowledge gaps and unresolved research questions. The results reveal a steady increase in research related to AI in manufacturing, with a strong focus on automation, predictive maintenance, and supply chain optimization. The study also highlights the dominance of certain institutions and key authors driving this field of research. Despite the progress, significant challenges remain, particularly regarding the scalability of AI solutions and ethical considerations. The findings suggest that while AI holds considerable potential for the manufacturing industry, more interdisciplinary research is needed to address existing gaps and maximize its benefits.

Research Output, Key Topics, and Trends in Productivity, Visibility, and Collaboration in Social Sciences Research on COVID-19: A Scientometric Analysis and Visualization

COVID-19 has caused a surge in scientific publications, with increased collaboration. This study aims to elucidate scientific output, focal topics, emerging themes, and trends and patterns of productivity, visibility, and collaboration within social sciences research (SSR) on COVID-19. A scientometric analysis was conducted utilizing Biblioshiny and VOSviewer software. About 65,742 records published on WOS between 2020 and 2022 were analyzed. Topics such as “telehealth,”“well-being,” and “inequalities,” were among the key topics while “interventions” and “mental well-being” were among emerging key topics. Collaboration patterns were regional. Harvard Medical School, the University of Toronto, and the University of Oxford emerge as leaders in collaboration, productivity, and influence. The USA, Italy, India, Spain, and Brazil serve as regional hubs for facilitating collaboration. The USA, England, and China exhibit leadership and influence, playing pivotal roles In shaping the global research. These findings are important for policymakers, funding agencies, and researchers in cultivating future research topics and collaborative efforts. The findings can inform strategic decision-making, resource allocation, and policy development to address present and future health crises. Additionally, these efforts contribute to advancing global sustainability initiatives and promoting human well-being. Encouraging international collaboration is essential, particularly for tackling the regional challenges encountered by countries with limited domestic research capabilities. Future research can improve the methodology used by di-versifying data sources beyond WOS.

Estimating Fishing Exploitation Rates to Simulate Global Catches and Biomass Changes of Pelagic and Demersal Fish

AbstractRobust projections of future trends in global fish biomass, production and catches are needed for informed fisheries policy in a changing climate. Trust in future projections, however, relies on establishing that models can accurately simulate past relationships between exploitation rates and ecosystem states. In addition, historical simulations are important to describe how the oceans have changed due to fishing. Here we use fisheries catch, catch‐only assessment models and effort data to estimate regional fishing exploitation levels, defined as the fishing mortality relative to fishing mortality at maximum sustainable yield (F/FMSY). These estimates are given for large pelagic, forage and demersal fish types across all large marine ecosystems and the high seas between 1961 and 2004; and with a ‘ramp‐up’ between 1841 and 1960. We find that global exploitation rates for large pelagic and demersal fish consistently exceed those for forage fish and peak in the late 1980s. We use the rates to globally simulate historical fishing patterns in a mechanistic fish community model. The modeled catch aligns with the reconstructed catch, both for total catch and catch distribution by functional type. Simulations show a clear deviation from an unfished model state, with a 25% reduction in biomass in large pelagic and demersal fish in shelf regions in recent years and a 50% increase in forage fish, primarily due to reduced predation. The simulations can set a baseline for assessing the effect of climate change relative to fishing. The results highlight the influential role of fishing as a primary driver of global fish community dynamics.

Economic feasibility and trends in fish production: A case study of composite fish culture in Karnataka

Economic feasibility and trends in fish production: A case study of composite fish culture in Karnataka