Hasil untuk "Agriculture"

J. S. Duhan, Ravinder Kumar, Naresh Kumar et al.

Highlights • Precision farming is measuring and responding to inter and intra-field variability in crops to form a decision support system.• About 40–70% of N, 80–90% of P and 50–70% of K of the applied fertilizers is lost to the environment causing pollution.• Nanofertilizers helps in slow and sustained release of agrochemicals resulting in precise dosage to the plants.• Green synthesized Ag, ZnO and TiO2 NPs are extensively used for plant protection and treatment of diseases.• Biosensors helps in detecting pesticides in the vegetable crops and form a decision support system for crop commodities.

V. Seufert, N. Ramankutty, J. Foley

F. Stagnari, A. Maggio, A. Galieni et al.

Food security, lowering the risk of climate change and meeting the increasing demand for energy will increasingly be critical challenges in the years to come. Producing sustainably is therefore becoming central in agriculture and food systems. Legume crops could play an important role in this context by delivering multiple services in line with sustainability principles. In addition to serving as fundamental, worldwide source of high-quality food and feed, legumes contribute to reduce the emission of greenhouse gases, as they release 5–7 times less GHG per unit area compared with other crops; allow the sequestration of carbon in soils with values estimated from 7.21 g kg−1 DM, 23.6 versus 21.8 g C kg−1 year; and induce a saving of fossil energy inputs in the system thanks to N fertilizer reduction, corresponding to 277 kg ha−1 of CO2 per year. Legumes could also be competitive crops and, due to their environmental and socioeconomic benefits, could be introduced in modern cropping systems to increase crop diversity and reduce use of external inputs. They also perform well in conservation systems, intercropping systems, which are very important in developing countries as well as in low-input and low-yield farming systems. Legumes fix the atmospheric nitrogen, release in the soil high-quality organic matter and facilitate soil nutrients’ circulation and water retention. Based on these multiple functions, legume crops have high potential for conservation agriculture, being functional either as growing crop or as crop residue. Graphical abstract . .

D. I. Patrício, Rafael Rieder

Abstract Grain production plays an important role in the global economy. In this sense, the demand for efficient and safe methods of food production is increasing. Information Technology is one of the tools to that end. Among the available tools, we highlight computer vision solutions combined with artificial intelligence algorithms that achieved important results in the detection of patterns in images. In this context, this work presents a systematic review that aims to identify the applicability of computer vision in precision agriculture for the production of the five most produced grains in the world: maize, rice, wheat, soybean, and barley. In this sense, we present 25 papers selected in the last five years with different approaches to treat aspects related to disease detection, grain quality, and phenotyping. From the results of the systematic review, it is possible to identify great opportunities, such as the exploitation of GPU (Graphics Processing Unit) and advanced artificial intelligence techniques, such as DBN (Deep Belief Networks) in the construction of robust methods of computer vision applied to precision agriculture.

M. Burke, K. Emerick

Antonis Tzounis, N. Katsoulas, T. Bartzanas et al.

M. Flörke, C. Schneider, R. McDonald

U. Mogili, B. Deepak

Abstract In the present era, there are too many developments in precision agriculture for increasing the crop productivity. Especially, in the developing countries like India, over 70% of the rural people depends upon the agriculture fields. The agriculture fields faces dramatic losses due to the diseases. These diseases came from the pests and insets, which reduces the productivity of the crops. Pesticides and fertilizers are used to kill the insects and pests in order to enhance the crop quality. The WHO (World Health Organization) estimated as one million cases of ill effected, when spraying the pesticides in the crop filed manually. The Unmanned aerial vehicle (UAV) – aircrafts are used to spray the pesticides to avoid the health problems of humans when they spray manually. UAVs can be used easily, where the equipment and labors difficulty to operate. This paper reviews briefly the implementation of UAVs for crop monitoring and pesticide spraying.

Xiaojia He, Hua Deng, H. Hwang

The rapid development of nanotechnology has been facilitating the transformations of traditional food and agriculture sectors, particularly the invention of smart and active packaging, nanosensors, nanopesticides and nanofertilizers. Numerous novel nanomaterials have been developed for improving food quality and safety, crop growth, and monitoring environmental conditions. In this review the most recent trends in nanotechnology are discussed and the most challenging tasks and promising opportunities in the food and agriculture sectors from selected recent studies are addressed. The toxicological fundamentals and risk assessment of nanomaterials in these new food and agriculture products are also discussed. We highlighted the potential application of biosynthesized and bio-inspired nanomaterial for sustainable development. However, fundamental questions with regard to high performance, low toxic nanomaterials need to be addressed to fuel active development and application of nanotechnology. Regulation and legislation are also paramount to regulating the manufacturing, processing, application, as well as disposal of nanomaterials. Efforts are still needed to strengthen public awareness and acceptance of the novel nano-enabled food and agriculture products. We conclude that nanotechnology offers a plethora of opportunities, by providing a novel and sustainable alternative in the food and agriculture sectors.

D. Knowler, B. Bradshaw

S. Howden, J. Soussana, F. Tubiello et al.

S. Šūmane, Ilona Kunda, K. Knickel et al.

M. Ruel, A. Quisumbing, Mysbah Balagamwala

Abstract A growing number of governments, donor agencies, and development organizations are committed to supporting nutrition-sensitive agriculture (NSA) to achieve their development goals. While consensus exists on pathways through which agriculture may influence nutrition-related outcomes, empirical evidence on agriculture's contribution to nutrition and how it can be enhanced is still weak. This paper reviews recent empirical evidence (since 2014), including findings from impact evaluations of a variety of NSA programs using experimental designs as well as observational studies that document linkages between agriculture, women's empowerment, and nutrition linkages. The paper summarizes existing knowledge regarding impacts, but also pathways, mechanisms, and contextual factors that affect where and how agriculture may improve nutrition outcomes. The paper concludes with reflections on implications for agricultural programs, policies, and investments, and highlights future research priorities.

R. Waheed, Dongfeng Chang, S. Sarwar et al.

Jeongeun Kim, Seungwon Kim, Chanyoung Ju et al.

For agricultural applications, regularized smart-farming solutions are being considered, including the use of unmanned aerial vehicles (UAVs). The UAVs combine information and communication technologies, robots, artificial intelligence, big data, and the Internet of Things. The agricultural UAVs are highly capable, and their use has expanded across all areas of agriculture, including pesticide and fertilizer spraying, seed sowing, and growth assessment and mapping. Accordingly, the market for agricultural UAVs is expected to continue growing with the related technologies. In this study, we consider the latest trends and applications of leading technologies related to agricultural UAVs, control technologies, equipment, and development. We discuss the use of UAVs in real agricultural environments. Furthermore, the future development of the agricultural UAVs and their challenges are presented.

P. Newton, Nicole Civita, Lee Frankel-Goldwater et al.

Regenerative agriculture is an alternative means of producing food that, its advocates claim, may have lower—or even net positive—environmental and/or social impacts. Regenerative agriculture has recently received significant attention from producers, retailers, researchers, and consumers, as well as politicians and the mainstream media. Despite widespread interest in regenerative agriculture, no legal or regulatory definition of the term “regenerative agriculture” exists nor has a widely accepted definition emerged in common usage. This paper answers the research question: How have different scholars and practitioners defined regenerative agriculture? We reviewed 229 journal articles and 25 practitioner websites to characterize the term “regenerative agriculture.” Our review revealed that there were many definitions and descriptions of regenerative agriculture in usage. These were variously based on processes (e.g., use of cover crops, the integration of livestock, and reducing or eliminating tillage), outcomes (e.g., to improve soil health, to sequester carbon, and to increase biodiversity), or combinations of the two. Process-based definitions may imply that advocates or users of such definitions are open-minded about the possible outcomes of these processes. Similarly, outcome-based definitions may imply that users of such definitions are open-minded about the processes that may lead to those outcomes. We discuss the implications of these different forms of definition for policy, including for certification programs and for payments for carbon sequestration programs. More generally, wide variance in the definitions used may lead to uncertainty about what different actors mean when they talk about regenerative agriculture. We suggest that it may be helpful for individual users of the term “regenerative agriculture” to define it comprehensively for their own purpose and context.

Yu Tang, Sathian Dananjayan, C. Hou et al.

Abstract Over the next decade, the superfast 5G network will play a critical role in farming industries to improve the yields and quality of crops while using minimal labor. Smart and precision farming allows farmers to be more informed and productive. The advent of 5G will considerably change the nature of jobs in farming and agriculture. The internet of things (IoT)-based cloud computing service in the 5G network provides flexible and efficient solutions for smart farming. This will allow the automated operation of various unmanned agricultural machines for the plowing, planting, and management phases of crop farming and will ultimately achieve secure, reliable, environmentally friendly, and energy-efficient operations and enable unmanned farms. This paper provides a complete survey on 5G technology in the agricultural sector and discusses the need for and role of smart and precision farming; benefits of 5G; applications of 5G in precision farming such as real-time monitoring, virtual consultation and predictive maintenance, data analytics and cloud repositories; and future prospects.

S. Bhat, N. Huang

Sustainable agricultural development is a significant solution with fast population development through the use of information and communication (ICT) in precision agriculture, which produced new methods for making cultivation further productive, proficient, well-regulated while preserving the climate. Big data (machine learning, deep learning, etc.) is amongst the vital technologies of ICT employed in precision agriculture for their huge data analytical capabilities to abstract significant information and to assist agricultural practitioners to comprehend well farming practices and take precise decisions. The main goal of this article is to acquire an awareness of the Big Data latest applications in smart agriculture and be acquainted with related social and financial challenges to be concentrated on. This article features data creation methods, accessibility of technology, accessibility of devices, software tools, and data analytic methods, and appropriate applications of big data in precision agriculture. Besides, there are still a few challenges that come across the widespread implementation of big data technology in agriculture.

R. Birner, Thomas Daum, C. Pray

Digital agriculture offers far-reaching opportunities for accelerating agricultural transformation. Based on empirical evidence and guided by economic theory, this study shows that digital agriculture is driven by private firms, including established input firms and global software firms and start-ups that are new to agriculture. Although there are concerns that digital agriculture will enhance the market power of large agribusiness enterprises and increase the digital divide, a combination of new actors and public action can help accelerate the supply of digital agricultural technology, manage threats of market concentration, and harness the opportunities of digital agri-culture for all.

F. Shaikh, Sarang Karim, S. Zeadally et al.

Smart agriculture integrates key information communication technologies with sensing technologies to provide effective and cost-efficient agricultural services. Smart agriculture leverages a wide range of advanced technologies, such as wireless sensor networks, Internet of Things, robotics, agricultural bots, drones, artificial intelligence, and cloud computing. The adoption of these technologies in smart agriculture enables all stakeholders in the agricultural sector to develop better managerial decisions to get more yield. We differentiate between traditional agriculture and smart agriculture based on the deployment architectures along with a focus on the various processing stages in smart agriculture. We present a comprehensive review of various types of sensors that are playing a vital role in enabling smart agriculture. We also review the integration of various sensing technologies with emerging technologies and computing infrastructures to make agriculture smarter. Finally, we discuss open research challenges that must be addressed to improve the adoption and deployment of smart agriculture in the future.