Hasil untuk "Agricultural industries"

M. Kah, N. Tufenkji, J. White

D. Cordell, J. Drangert, S. White

R. C. Kuhad, Rishi Gupta, A. Singh

Microbial cellulases have shown their potential application in various industries including pulp and paper, textile, laundry, biofuel production, food and feed industry, brewing, and agriculture. Due to the complexity of enzyme system and immense industrial potential, cellulases have been a potential candidate for research by both the academic and industrial research groups. Nowadays, significant attentions have been devoted to the current knowledge of cellulase production and the challenges in cellulase research especially in the direction of improving the process economics of various industries. Scientific and technological developments and the future prospects for application of cellulases in different industries are discussed in this paper.

N. Misra, Ahmad Al-Mallahi, A. Martynenko et al.

Internet of Things (IoT) results in a massive amount of streaming data, often referred to as “big data,” which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review, we present an overview of IoT, big data, and artificial intelligence (AI), and their disruptive role in shaping the future of agri-food systems. Following an introduction to the fields of IoT, big data, and AI, we discuss the role of IoT and big data analysis in agriculture (including greenhouse monitoring, intelligent farm machines, and drone-based crop imaging), supply chain modernization, social media (for open innovation and sentiment analysis) in food industry, food quality assessment (using spectral methods and sensor fusion), and finally, food safety (using gene sequencing and blockchain-based digital traceability). A special emphasis is laid on the commercial status of applications and translational research outcomes.

P. Busby, C. Soman, Maggie R. Wagner et al.

Feeding a growing world population amidst climate change requires optimizing the reliability, resource use, and environmental impacts of food production. One way to assist in achieving these goals is to integrate beneficial plant microbiomes—i.e., those enhancing plant growth, nutrient use efficiency, abiotic stress tolerance, and disease resistance—into agricultural production. This integration will require a large-scale effort among academic researchers, industry researchers, and farmers to understand and manage plant-microbiome interactions in the context of modern agricultural systems. Here, we identify priorities for research in this area: (1) develop model host–microbiome systems for crop plants and non-crop plants with associated microbial culture collections and reference genomes, (2) define core microbiomes and metagenomes in these model systems, (3) elucidate the rules of synthetic, functionally programmable microbiome assembly, (4) determine functional mechanisms of plant-microbiome interactions, and (5) characterize and refine plant genotype-by-environment-by-microbiome-by-management interactions. Meeting these goals should accelerate our ability to design and implement effective agricultural microbiome manipulations and management strategies, which, in turn, will pay dividends for both the consumers and producers of the world food supply.

H. Murray

T. Benton, J. Vickery, Jeremy D. Wilson

G. Battese, T. Coelli

Chaoqun Lu, H. Tian

Abstract. In addition to enhancing agricultural productivity, synthetic nitrogen (N) and phosphorous (P) fertilizer application in croplands dramatically alters global nutrient budget, water quality, greenhouse gas balance, and their feedback to the climate system. However, due to the lack of geospatial fertilizer input data, current Earth system and land surface modeling studies have to ignore or use oversimplified data (e.g., static, spatially uniform fertilizer use) to characterize agricultural N and P input over decadal or century-long periods. In this study, we therefore develop global time series gridded data of annual synthetic N and P fertilizer use rate in agricultural lands, matched with HYDE 3.2 historical land use maps, at a resolution of 0.5°  ×  0.5° latitude–longitude during 1961–2013. Our data indicate N and P fertilizer use rates on per unit cropland area increased by approximately 8 times and 3 times, respectively, since the year 1961 when IFA (International Fertilizer Industry Association) and FAO (Food and Agricultural Organization) surveys of country-level fertilizer input became available. Considering cropland expansion, the increase in total fertilizer consumption is even larger. Hotspots of agricultural N fertilizer application shifted from the US and western Europe in the 1960s to eastern Asia in the early 21st century. P fertilizer input shows a similar pattern with an additional current hotspot in Brazil. We found a global increase in fertilizer N ∕ P ratio by 0.8 g N g−1 P per decade (p  doi:10.1594/PANGAEA.863323 .

Yaowen Liu, Saeed Ahmed, Dur E. Sameen et al.

Abstract: Background Food packaging is a globally relevant and widely used technique for food preservation. Natural, biodegradable, and bioavailable polymers are gaining popularity in the field of food packaging. Cellulose and its derivatives are amongst the most abundant and widely used polymers in the packaging industry. There are many natural sources for cellulose, and they can also be obtained from bio-wastes and agricultural wastes. Thus, it is available in large quality and is cost effective. Scope and approach In this review, we discussed the importance, functioning, properties, and characteristics of cellulose and its derivatives for food packaging. The application of cellulose in food packaging from the discovery of cellulose in 1839–2020 was introduced in this article. Which includes its use for the preservation of fruits and vegetables is discussed in detail, and its application as carrier of various natural antibacterial and antioxidant compounds was introduced. Various types of composite films prepared using cellulose and its derivatives are also discussed in this review. Furthermore, numerous functional properties of cellulose have been mentioned. Key findings and conclusion Cellulose is one of the most important polymers in the food industry. This study explores its properties and its encapsulations and stabilization of compounds without altering their properties. Through extensive study of existing literature on the subject, this review compiles the information relevant to the use of cellulose in food preservation. In addition, various future considerations are further presented.

Ritu Gothwal, T. Shashidhar

V. K. Quy, Nguyen Van Hau, Dang Van Anh et al.

The growth of the global population coupled with a decline in natural resources, farmland, and the increase in unpredictable environmental conditions leads to food security is becoming a major concern for all nations worldwide. These problems are motivators that are driving the agricultural industry to transition to smart agriculture with the application of the Internet of Things (IoT) and big data solutions to improve operational efficiency and productivity. The IoT integrates a series of existing state-of-the-art solutions and technologies, such as wireless sensor networks, cognitive radio ad hoc networks, cloud computing, big data, and end-user applications. This study presents a survey of IoT solutions and demonstrates how IoT can be integrated into the smart agriculture sector. To achieve this objective, we discuss the vision of IoT-enabled smart agriculture ecosystems by evaluating their architecture (IoT devices, communication technologies, big data storage, and processing), their applications, and research timeline. In addition, we discuss trends and opportunities of IoT applications for smart agriculture and also indicate the open issues and challenges of IoT application in smart agriculture. We hope that the findings of this study will constitute important guidelines in research and promotion of IoT solutions aiming to improve the productivity and quality of the agriculture sector as well as facilitating the transition towards a future sustainable environment with an agroecological approach.

Sreedevi Aswathy, U. Narendrakumar, I. Manjubala

Hydrogels are polymeric networks having the ability to absorb a large volume of water. Flexibility, versatility, stimuli-responsive, soft structure are the advantages of hydrogels. It is classified based on its source, preparation, ionic charge, response, crosslinking and physical properties. Hydrogels are used in various fields like agriculture, food industry, biosensor, biomedical, etc. Even though hydrogels are used in various industries, more researches are going in the field of biomedical applications because of its resembles to living tissue, biocompatibility, and biodegradability. Here, we are mainly focused on the commercially available hydrogels used for biomedical applications like wound dressings, contact lenses, cosmetic applications, tissue engineering, and drug delivery.

S. Sarkodie, V. Strezov

Abstract This study examines Environmental Kuznets and Environmental Sustainability curve hypotheses for Australia, China, Ghana and the USA from 1971 to 2013 in order to examine the factors contributing to adverse greenhouse gas emission and economic impacts relative to their development. The study revealed that the decline of carbon dioxide emissions in developed countries can be attributed to a paradigm shift and structural change from high-energy intensive and carbon-intensive industries to services and information-intensive industries. The increasing levels of carbon dioxide emissions in developing and least developing countries can be attributed to the economy driven by agriculture, transport and services. Environmental policies and regulations in developing and least developing countries are weaker compared to developed countries, as such, they become a haven for high-energy and carbon-intensive industries. The high awareness of environmental sustainability, technological advancement, stringent environmental regulations and policies in developed countries result in a decline in energy intensity and a decline in carbon dioxide emissions. The Environmental Sustainability Curve hypothesis shows that the affecting factors include economic growth, energy consumption patterns and carbon dioxide emissions. The study reveals electric power consumption as the main contributor of energy intensity in the selected countries. Decoupling economic growth from electric power consumption and improving energy efficiency in China, Ghana, Australia, and the USA will enhance energy security and decline the economic related dynamics and activities on the environment.

N. Renuka, Abhishek Guldhe, R. Prasanna et al.

Algae are a group of ubiquitous photosynthetic organisms comprising eukaryotic green algae and Gram-negative prokaryotic cyanobacteria, which have immense potential as a bioresource for various industries related to biofuels, pharmaceuticals, nutraceuticals and feed. This fascinating group of organisms also has applications in modern agriculture through facilitating increased nutrient availability, maintaining the organic carbon and fertility of soil, and enhancing plant growth and crop yields, as a result of stimulation of soil microbial activity. Several cyanobacteria provide nitrogen fertilization through biological nitrogen fixation and through enzymatic activities related to interconversions and mobilization of different forms of nitrogen. Both green algae and cyanobacteria are involved in the production of metabolites such as growth hormones, polysaccharides, antimicrobial compounds, etc., which play an important role in the colonization of plants and proliferation of microbial and eukaryotic communities in soil. Currently, the development of consortia of cyanobacteria with bacteria or fungi or microalgae or their biofilms has widened their scope of utilization. Development of integrated wastewater treatment and biomass production systems is an emerging technology, which exploits the nutrient sequestering potential of microalgae and its valorisation. This review focuses on prospects and challenges of application of microalgae in various areas of agriculture, including crop production, protection and natural resource management. An overview of the recent advances, novel technologies developed, their commercialization status and future directions are also included.

J. Poveda

Chao Cheng, Jun Fu, Hang Su et al.

In the development of digital agriculture, agricultural robots play a unique role and confer numerous advantages in farming production. From the invention of the first industrial robots in the 1950s, robots have begun to capture the attention of both research and industry. Thanks to the recent advancements in computer science, sensing, and control approaches, agricultural robots have experienced a rapid evolution, relying on various cutting-edge technologies for different application scenarios. Indeed, significant refinements have been achieved by integrating perception, decision-making, control, and execution techniques. However, most agricultural robots continue to require intelligence solutions, limiting them to small-scale applications without quantity production because of their lack of integration with artificial intelligence. Therefore, to help researchers and engineers grasp the prevalent research status of agricultural robots, in this review we refer to more than 100 pieces of literature according to the category of agricultural robots under discussion. In this context, we bring together diverse agricultural robot research statuses and applications and discuss the benefits and challenges involved in further applications. Finally, directional indications are put forward with respect to the research trends relating to agricultural robots.

C. Thirtle, Lin Lin, J. Piesse

Le Wang, Boyuan Zhang

Forecasting agricultural markets remains challenging due to nonlinear dynamics, structural breaks, and sparse data. A long-standing belief holds that simple time-series methods outperform more advanced alternatives. This paper provides the first systematic evidence that this belief no longer holds with modern time-series foundation models (TSFMs). Using USDA ERS monthly commodity price data from 1997-2025, we evaluate 17 forecasting approaches across four model classes, including traditional time-series, machine learning, deep learning, and five state-of-the-art TSFMs (Chronos, Chronos-2, TimesFM 2.5, Time-MoE, Moirai-2), and construct annual marketing year price predictions to compare with USDA's futures-based season-average price (SAP) forecasts. We show that zero-shot foundation models consistently outperform traditional time-series methods, machine learning, and deep learning architectures trained from scratch in both monthly and annual forecasting. Furthermore, foundation models remarkably outperform USDA's futures-based forecasts on three of four major commodities despite USDA's information advantage from forward-looking futures markets. Time-MoE delivers the largest accuracy gains, achieving 54.9% improvement on wheat and 18.5% improvement on corn relative to USDA ERS benchmarks on recent data (2017-2024 excluding COVID). These results point to a paradigm shift in agricultural forecasting.

Arif Ahmed, Parikshit Maini

Accurate reconstruction of leaf surfaces from 3D point cloud is essential for agricultural applications such as phenotyping. However, real-world plant data (i.e., irregular 3D point cloud) are often complex to reconstruct plant parts accurately. A wide range of surface reconstruction methods has been proposed, including parametric, triangulation-based, implicit, and learning based approaches, yet their relative performance for leaf surface reconstruction remains insufficiently understood. In this work, we present a comparative study of nine representative surface reconstruction methods for leaf surfaces. We evaluate these methods on three publicly available datasets: LAST-STRAW, Pheno4D, and Crops3D - spanning diverse species, sensors, and sensing environments, ranging from clean high-resolution indoor scans to noisy low-resolution field settings. The analysis highlights the trade-offs between surface area estimation accuracy, smoothness, robustness to noise and missing data, and computational cost across different methods. These factors affect the cost and constraints of robotic hardware used in agricultural applications. Our results show that each method exhibits distinct advantages depending on application and resource constraints. The findings provide practical guidance for selecting surface reconstruction techniques for resource constrained robotic platforms.