Hasil untuk "Agricultural industries"

Kashif Abbass, M. Qasim, Huaming Song et al.

Climate change is a long-lasting change in the weather arrays across tropics to polls. It is a global threat that has embarked on to put stress on various sectors. This study is aimed to conceptually engineer how climate variability is deteriorating the sustainability of diverse sectors worldwide. Specifically, the agricultural sector’s vulnerability is a globally concerning scenario, as sufficient production and food supplies are threatened due to irreversible weather fluctuations. In turn, it is challenging the global feeding patterns, particularly in countries with agriculture as an integral part of their economy and total productivity. Climate change has also put the integrity and survival of many species at stake due to shifts in optimum temperature ranges, thereby accelerating biodiversity loss by progressively changing the ecosystem structures. Climate variations increase the likelihood of particular food and waterborne and vector-borne diseases, and a recent example is a coronavirus pandemic. Climate change also accelerates the enigma of antimicrobial resistance, another threat to human health due to the increasing incidence of resistant pathogenic infections. Besides, the global tourism industry is devastated as climate change impacts unfavorable tourism spots. The methodology investigates hypothetical scenarios of climate variability and attempts to describe the quality of evidence to facilitate readers’ careful, critical engagement. Secondary data is used to identify sustainability issues such as environmental, social, and economic viability. To better understand the problem, gathered the information in this report from various media outlets, research agencies, policy papers, newspapers, and other sources. This review is a sectorial assessment of climate change mitigation and adaptation approaches worldwide in the aforementioned sectors and the associated economic costs. According to the findings, government involvement is necessary for the country’s long-term development through strict accountability of resources and regulations implemented in the past to generate cutting-edge climate policy. Therefore, mitigating the impacts of climate change must be of the utmost importance, and hence, this global threat requires global commitment to address its dreadful implications to ensure global sustenance.

J. Briffa, E. Sinagra, R. Blundell

Environmental pollution of heavy metals is increasingly becoming a problem and has become of great concern due to the adverse effects it is causing around the world. These inorganic pollutants are being discarded in our waters, soils and into the atmosphere due to the rapidly growing agriculture and metal industries, improper waste disposal, fertilizers and pesticides. This review shows how pollutants enter the environment together with their fate. Some metals affect biological functions and growth, while other metals accumulate in one or more different organs causing many serious diseases such as cancer. The pharmacokinetics and toxicological processes in humans for each metal is described. In summary, the review shows the physiological and biochemical effects of each heavy metal bioaccumulation in humans and the level of gravity and disquieting factor of the disease.

N. Shahrubudin, T. C. Lee, R. Ramlan

Abstract Digital fabrication technology, also referred to as 3D printing or additive manufacturing, creates physical objects from a geometrical representation by successive addition of materials. 3D printing technology is a fast-emerging technology. Nowadays, 3D Printing is widely used in the world. 3D printing technology increasingly used for the mass customization, production of any types of open source designs in the field of agriculture, in healthcare, automotive industry, locomotive industry and aviation industries. 3D printing technology can print an object layer by layer deposition of material directly from a computer aided design (CAD) model. This paper presents the overview of the types of 3D printing technologies, the application of 3D printing technology and lastly, the materials used for 3D printing technology in manufacturing industry.

S. Zolghadri, A. Bahrami, Mahmud Tareq Hassan Khan et al.

Abstract Tyrosinase is a multi-copper enzyme which is widely distributed in different organisms and plays an important role in the melanogenesis and enzymatic browning. Therefore, its inhibitors can be attractive in cosmetics and medicinal industries as depigmentation agents and also in food and agriculture industries as antibrowning compounds. For this purpose, many natural, semi-synthetic and synthetic inhibitors have been developed by different screening methods to date. This review has focused on the tyrosinase inhibitors discovered from all sources and biochemically characterised in the last four decades.

N. A. Sagar, S. Pareek, Sunil Sharma et al.

Shiza Malik, K. Muhammad, Yasir Waheed

Nanotechnology, contrary to its name, has massively revolutionized industries around the world. This paper predominantly deals with data regarding the applications of nanotechnology in the modernization of several industries. A comprehensive research strategy is adopted to incorporate the latest data driven from major science platforms. Resultantly, a broad-spectrum overview is presented which comprises the diverse applications of nanotechnology in modern industries. This study reveals that nanotechnology is not limited to research labs or small-scale manufacturing units of nanomedicine, but instead has taken a major share in different industries. Companies around the world are now trying to make their innovations more efficient in terms of structuring, working, and designing outlook and productivity by taking advantage of nanotechnology. From small-scale manufacturing and processing units such as those in agriculture, food, and medicine industries to larger-scale production units such as those operating in industries of automobiles, civil engineering, and environmental management, nanotechnology has manifested the modernization of almost every industrial domain on a global scale. With pronounced cooperation among researchers, industrialists, scientists, technologists, environmentalists, and educationists, the more sustainable development of nano-based industries can be predicted in the future.

Jaya Baranwal, Brajesh Barse, G. Gatto et al.

The world of sensors is diverse and is advancing at a rapid pace due to the fact of its high demand and constant technological improvements. Electrochemical sensors provide a low-cost and convenient solution for the detection of variable analytes and are widely utilized in agriculture, food, and oil industries as well as in environmental and biomedical applications. The popularity of electrochemical sensing stems from two main advantages: the variability of the reporting signals, such as the voltage, current, overall power output, or electrochemical impedance, and the low theoretical detection limits that originate from the differences in the Faradaic and nonFaradaic currents. This review article attempts to cover the latest advances and applications of electrochemical sensors in different industries. The role of nanomaterials in electrochemical sensor research and advancements is also examined. We believe the information presented here will encourage further efforts on the understanding and progress of electrochemical sensors.

T. Gomiero, D. Pimentel, M. Paoletti

Y. Dumas, M. Dadomo, G. D. Lucca et al.

Josip Tomo Licardo, Mihael Domjan, T. Orehovački

Intelligent robotics has the potential to revolutionize various industries by amplifying output, streamlining operations, and enriching customer interactions. This systematic literature review aims to analyze emerging technologies and trends in intelligent robotics, addressing key research questions, identifying challenges and opportunities, and proposing the best practices for responsible and beneficial integration into various sectors. Our research uncovers the significant improvements brought by intelligent robotics across industries such as manufacturing, logistics, tourism, agriculture, healthcare, and construction. The main results indicate the importance of focusing on human–robot collaboration, ethical considerations, sustainable practices, and addressing industry-specific challenges to harness the opportunities presented by intelligent robotics fully. The implications and future directions of intelligent robotics involve addressing both challenges and potential risks, maximizing benefits, and ensuring responsible implementation. The continuous improvement and refinement of existing technology will shape human life and industries, driving innovation and advancements in intelligent robotics.

M. Słowiński, A. Halaś, M. A. Niedzielski et al.

<p>This study presents the first national-scale spatial inventory of relict charcoal hearths (RCHs) in Poland, based on high-resolution LiDAR data and digital terrain analysis. Using a combination of manual interpretation, GIS-based feature extraction, and <span class="inline-formula"><i>K</i></span>-prototypes clustering, we identified and classified 634 815 RCHs across forested regions of the country. Each feature was georeferenced and categorized by size, morphological characteristics, slope position, and environmental context, including current and potential vegetation and soil types. Spatial analyses revealed significant regional differences in hearth density, with the highest concentrations found in western and south-central Poland, particularly in the Lower Silesian, Stobrawa, and Świętokrzyskie forests. Cluster analysis distinguished three major types of RCHs, differing in their environmental settings and spatial organization: (1) lowland pine-dominated clusters on gentle terrain, (2) isolated features on steep slopes in mixed forests, and (3) high-density hearth groups in elevated areas. Although large portions of the country appear devoid of RCHs, we argue that this reflects limitations in preservation and detection – due to long-term agricultural activity in lowlands and erosion in mountainous areas – rather than an actual absence of charcoal production. The resulting ReCHAR database offers a unique, open-access tool for interdisciplinary research on<span id="page494"/> forest history, human–environment interactions, and early industrial landscapes. Its modular design supports further expansion, including links to historical settlements and industries reliant on charcoal, such as metallurgy, glassmaking, and tar or potash production. The data set is available at <a href="https://doi.org/10.5281/zenodo.15630690">https://doi.org/10.5281/zenodo.15630690</a> (Słowiński et al., 2025).</p>

Firlej Krzysztof, Sebastian Kubala

The main objective of the study was to empirically verify the existence of statistically significant differences in profitability levels between food sector companies listed on the Warsaw Stock Exchange (WSE) and those not listed on the public market. The analysis focused on three profitability indicators: return on equity (ROE), return on assets (ROA), and return on sales (ROS). To compare the mean values of individual profitability indicators between the groups, analysis of variance (ANOVA) was applied. Additionally, to assess differences across all three indicators simultaneously, multivariate analysis of variance (MANOVA) was employed. The experimental group (A) comprised companies included in the WIG-Food index as of December 31, 2024, while the control group (B) consisted of 15 food sector enterprises not listed on the WSE. Financial data were obtained from the companies’ financial statements for the years 2020-2024. Empirical analyses were conducted using R-Studio software. The results indicate that stock market status is not a decisive factor for the financial performance of food enterprises in Poland. However, it was observed that companies listed in the WIG-Food index demonstrate slightly but consistently higher average profitability indicators, with distributions that are more dispersed and contain a greater number of outliers compared to companies not listed on the WSE. The findings may provide useful insights for entrepreneurs and managers in the studied groups and contribute to a new perspective on the business performance of these entities in both practical and academic contexts.

Omid Zamani, Craig Chibanda, Mavis Boimah et al.

Abstract This paper examines policy coherence in Ghana's poultry sector by assessing potential interactions between policy objectives. Using panel simultaneous equation models and the data-driven synthetic control method, we analyze the effects of policy interventions on domestic poultry production during 1999–2019. Our findings underscore the impact of policies enacted during this period on the growth of domestic poultry production. However, growth in production remains notably lower than the escalating imports of frozen poultry meat. Our coherence analysis identifies lowering production costs and enhancing productivity as crucial policy objectives that could positively affect food security and rural development. Nonetheless, we caution against prioritizing one objective over others, as this may adversely affect overall policy coherence and outcomes. Specifically, our study emphasizes the importance of striking a balance between fostering domestic production and ensuring food security.

somayeh Shirzadi Laskookalayeh

Extended Abstract Background: The inadequacy of the supply of agricultural inputs with the demand for various products of this sector reveals the need for the optimal use of resources and increasing productivity. In this regard, addressing the issue of productivity in rice production is very important due to its essential role in feeding different sections of society, providing food security, reducing dependence on imports and foreign exchange, strengthening trade interactions with other countries, generating income, creating employment, creating balance in the business and capital market, and many other issues. In 2022, Mazandaran Province produced 1.6 million tons of paddy as a strategic product, responsible for 44.47% of Iran's paddy production, and in this sense, it has been ranked first in the country. This province has long been known as the hub of rice production, and this user product, having about 76% of Mazandaran's irrigated crop area, has always made an important contribution to the province's employment. For this purpose, the present study aimed to identify factors affecting the prosperity of the rice production business in Mazandaran Province, focusing on measuring the inefficiency of various production inputs, especially the labor force. Methods: Three institutional, managerial, and policy-market criteria effective in the prosperity of rice production business were extracted in this study. The input criterion includes all production factors affecting the productivity of this product, which includes eight subcriteria as water, labor, land, fertilizer, poison, machinery, capital, and seed. The management criterion is all management actions by relevant organizations and bodies (Jahad Keshavarzi, Regional Water, Room of Commerce), which includes six regulatory, executive, organizational, service, and innovation options. The political-market criterion also covered the macro-government policies that can affect the productivity of rice, and there are six financial, economic, structural, commercial, marketing, and strategic development options. Thus, 19 effective options in the productivity of rice production were considered in this study. In this study, factors affecting the productivity of this product were exracted and prioritized using the Analytical Hierarchy Process (AHP) method, measuring the production efficiency of important cultivars of this product (high-quality rice and high-yielding rice) using the data envelopment analysis method (DEA), and then examining productivity changes over time using the Malmquist Index (MI). The data needed for identifying and prioritizing factors in this research were collected by designing a questionnaire, which was completed based on the opinions of 18 experts, including those from the Agricultural Jihad Organization of Mazandaran Province and Sari City, as well as the academic community. The statistics and information of the Agricultural Jahad Organization of the province were used to complete the data in measuring the productivity of production and efficiency of inputs. Results: The results indicate that among the eight production factors, water, mechanization, and land are the most important input factors in rice production with weights of 0.36, 0.2, and 0.14, respectively. Among the five management factors, benefiting from the opinions of agricultural experts, implementing the optimal cultivation pattern of crops according to the climatic conditions and the status of water resources in the province, and using new technologies in agricultural operations with weights of 0.40, 0.25, and 0.14, respectively, were known as three important and superior factors for the management of rice production business. In addition, the financial, economic options, and improvement of the structure of the rice product marketing system were determined with the weights of 0.30, 0.22, and 0.19, respectively, as three policy-market subcriteria affecting the rice productivity of this province. Based on the findings in the agricultural year of 2017-2018 in the east of this province, Qaemshahr City, the land, machinary, poison, and fertilizer inputs were inefficient at 52.68%, 48.26%, 34.37%, and 33.16%, respectively. In 2018, the inefficiency rates in the use of land, labor, and poison inputs were 71.36%, 15.09%, and 4.46%, respectively. In the production of high-yielding rice in the east of the province, there has been inefficiency in the use of land, machinary, seed, water, and fertilizer inputs. Accordingly, Behshahr City acted inefficiently in consuming the mentioned inputs by 68.29, 52.60, 16.65, 12.63, and 7.55%, respectively. In 1998, the cities of Behshahr and Neka acted inefficiently in the consumption of all the investigated inputs, except for machinery. The percentages of inefficiency in the labor input are 16.14 and 42.07%, respectively. In addition, the productivity growth index values of Malmquist in the production of high-quality rice and high-yielding rice are 1.155 and 1.094, respectively. Hence, it can be concluded that the production productivity of this product has increased in this province. Conclusion: The results indicate that the productivity of different rice varieties has increased during the studied period. In the case of high-yielding rice, however, the technical efficiency of producers in newer technology is lower than in older technology. Therefore, it is necessary for trustee organizations and knowledge-based companies to invest in the research, innovation, and promotion of new technology in training to use this technology. In this study, "water" has been determined as the most important input affecting the productivity of this product; therefore, it is recommended to take necessary measures to promote water storage and reduce its consumption. It is also suggested to provide financial support to rice farmers and the development of knowledge-based companies to provide new irrigation systems. Referring to the results of this study, the use of "machinery" is considered the second most effective factor in increasing productivity. In addition to reducing the cost of manpower and saving time, the uniformity and accuracy of the work are increased with mechanized cultivation, and seedlings are exposed to less damage. However, this issue does not mean to ignore the role and importance of the workforce in the production and elimination of job opportunities. Rather, it is recommended to train skilled and specialized human resources to benefit from mechanization for the long-term stability of the rice production business and stable rural employment.

Kai Wu, Zilin Zhang, Xiuhan He et al.

Abstract Nondestructive, rapid, and accurate detection of nutritional compositions in sorghum is crucial for agricultural and food industries. In our study, the crude protein, tannin, and crude fat contents of sorghum variety samples were taken as the research object. The visible near-infrared (VIS-NIR) hyperspectral of sorghum were measured by the indoor mobile scanning platform. The nutritional components were determined using chemical methods to analyze the differences in nutritional composition among different varieties. After preprocessing the original spectral, the competitive adaptive reweighted sampling (CARS) and bootstrapping soft shrinkage (BOSS) algorithms were used to coarsely extract the key variables. Subsequently, the iteratively retains informative variables (IRIV) was employed to assess the importance of these key variables, resulting in explanatory wavelength sets for crude protein, tannin, and crude fat. Finally, the partial least squares (PLS), back propagation (BP) and extreme learning machine (ELM) were utilized to establish detection models. The results indicated that the optimal wavelength variable sets for crude protein, tannin, and crude fat contained 41, 38, and 22 wavelength variables, respectively. The CARS-IRIV-PLS, BOSS-IRIV-PLS and BOSS-IRIV-ELM were suitable for detecting crude protein, tannin and crude fat, respectively. Meanwhile, the Rp 2, RMSEp and RPDp values of the model were 0.69, 0.80% and 1.80, 0.88, 0.22% and 2.84, 0.61, 0.32% and 1.61, respectively. These detection models can be used for the effective estimation of the nutritional compositions in sorghum with VIS-NIR spectral data, and can provide an important basis for the application of food nutrition assessment.

Massimiliano Varani, Giovanni Molari, Gianvito Annesi et al.

The increasing complexity of modern agriculture and the growing demand for sustainability have accelerated the adoption of advanced decision-support systems in farm management. Accurate cost estimation of machinery operations is particularly critical in large-scale farming, where machinery represents a substantial portion of operational expenses. Traditional costing methods often rely on assumptions, leading to inefficiencies. Activity-Based Costing (ABC) offers a more accurate alternative by linking costs to specific operations, but its data-intensive nature has limited practical application. This study presents an improved methodology that combines ABC with automated data collection from CANBUS systems integrated into agricultural tractors. CANBUS technology enables the continuous acquisition of detailed operational data, such as engine load, speed, fuel consumption, and positioning, without manual input. These data are processed to classify tasks and allocate resource use precisely. The methodology was applied to a fleet of nine tractors - ranging from utility to high-power models - on a cooperative farm in Italy over a one-year period. The CANBUS data were integrated with economic parameters like depreciation, maintenance, fuel, and labour costs to estimate job-specific and per-hectare costs. While results showed variations in cost structure and usage patterns across tractor types, the primary contribution of this work lies in demonstrating a scalable, automated ABC framework. This approach reduces reliance on manual reporting, enhances cost transparency, and supports more informed machinery management decisions. It offers a strong foundation for future digital tools aimed at improving the efficiency and sustainability of farm operations, especially in data-rich and mechanized agricultural systems.

Yulin Xu, Lian Li, Yuanzhong Wang et al.

Various Dendrobium species used as traditional Chinese medicine have similar appearances but different bioactive component, with significant differences in medicinal and economic values. Many commercially available herbal medicines, including Dendrobium are usually powdered, and commercial fraud by adulterating cheap species in the supply chain often occurs. Therefore, it is necessary to develop accurate and feasible authentication methods for herbal medicines. Currently, non-destructive testing and analysis are gradually becoming a hot issue in various industries. This study attempts to use machine learning techniques for non-destructive combination authentication of different Dendrobium species based on plant photographs (SONY) and Fourier transform near-infrared spectroscopy (FT-NIR). Simultaneously validated the ability of the residual neural network (ResNet) and support vector machine (SVM) models to extract and recognize features from different preprocessed datasets. The results showed that Dendrobium officinale had the highest absorbance followed by Dendrobium thyrsiflorum and Dendrobium crepidatum had the lowest. When the weight decay coefficient λ of the deep learning model based on ResNet is 0.0001 and the learning rate is 0.01, it can identify up to 100 % of Dendrobium species. ResNet recognizes feature information of plant images with an accuracy of up to 88.2 %. Using flower parts with more recognised features or controlling the consistency of the background may improve recognition accuracy. The dataset of synchronized two-dimensional correlation spectroscopy (2DCOS) does not require preprocessing, and the ResNet model can accurately and quickly extract recognition features. Deep learning models based on ResNet have absolute advantages over traditional SVM models in terms of accuracy and recognition speed. The analytical method proposed in this study may provide new ideas for non-destructive identification of similar species, genuine and fake products, pest and disease characteristics in the field of agriculture.

Brhanu Teka Gebrezgabher, Mulu Berhe Desta, Fentahun Abebaw Belete

Abstract Using of agricultural residues for briquette production attracts the attention of many researchers to overcome the problems related to the usage of fossil fuels as an energy source. This study focused on the production of briquettes from sesame stalks as an alternative fuel in Cement industries. The briquettes were produced from carbonized sesame stalks using paper waste, cow dung, and a mixture of cow dung and paper waste binders. The data analysis of the charcoal briquettes was carried out using two-way ANOVA without replication using Microsoft Excel. The binder ratio and binder types have a significant effect on the density and shatter resistance. Briquettes made using carbonized sesame stalks have the highest density of 1.133 g/cm3 at 5% of cow dung binder. The highest shatter resistance having a value of 91.00% was found in carbonized briquette prepared using 25% cow dung binder. Six briquettes were selected for proximate and calorific value analysis. The highest heating value of the produced briquettes was 4794.38 kcal/kg at 5% of cow dung binder, which has moisture, ash, fixed carbon, and volatile matter of 6.54, 14, 30.7, and 48.76% respectively. Carbon, hydrogen, oxygen, nitrogen, and sulfur contents of a briquette, which has the highest heating value, were recorded at 46.34, 2.50, 50.89, 0.27, and 0.00% respectively. Production of a briquette from carbonized sesame stalks using 5% cow dung binder is suitable from economic and environmental points of view.

Novi Hidayat Pusponegoro, Ro'fah Nur Rachmawati, Maria A. Hasiholan Siallagan et al.

Background: Spatial employment modeling investigates employment distribution, patterns, influencing factors, neighboring area impact, and regional policy efficacy. Conventional studies often rely on traditional data sources, which may overlook critical employment-related phenomena. In 2022, Java recorded the lowest labor absorption rate in Indonesia, necessitating a new approach. Aim: This study combines imagery, crowdsourced data, and official statistics to identify factors influencing labor absorption in Java Island. Method: Geographically Weighted Regression (GWR) was employed to account for spatial effects in the data. Results: The model reveals that nighttime light intensity in urban and agricultural areas, along with environmental quality, significantly enhances labor absorption across Java. Internet facilities, universities, and the number of micro and small industries also positively influence most districts/cities. Conclusion: Incorporating new data sources offers valuable insights for understanding employment patterns and can enrich employment research frameworks.

Yuli Wibowo , Bambang Herry Purnomo , Salsabila

The development of information technology, especially in digital marketing, has brought significant changes in how companies interact with consumers and build company brand images, including Perum BULOG Jember Branch. This research aims to increase awareness of the "Beras Kita" brand as BULOG's premium rice product and strengthen the brand's position in the minds of consumers with a brand positioning strategy that includes designing a visual identity, namely designing a new logo and tagline, as well as through a digital marketing strategy for premium rice products. premium at Perum BULOG Jember Branch. This research uses the ME-MCDM (Multi-Expert Multi-Criteria Decision Making) method for selecting logos and taglines and the AHP (Analytical Hierarchy Process) method to determine digital marketing strategy priorities. The recommended digital marketing strategy, which has the highest priority, is using local influencers. Implementing this strategy is expected to improve the unfavorable brand image and strengthen the position of the "Beras Kita" brand in the market.