The Implications of Digital Agriculture and Big Data for Australian Agriculture
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Digital Agribusiness Models”
Int.J.Curr.Microbiol.App.Sci (2020) 9(8): 3030-3038 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 8 (2020) Journal homepage: http://www.ijcmas.com Review Article https://doi.org/10.20546/ijcmas.2020.908.342 Innovations in Agriculture – A Case of “Digital Agribusiness Models” C. Muralidharan* Department of Social Sciences, Agricultural College and Research Insititute, Killikulam, Vallanad, Tuticorin District, India *Corresponding author ABSTRACT World population will increase at geometric rate of progression and an estimated 9.6 billion people and will require 70 percent more food than is available today. In order to increase the production efficiency, expertise in the domain of agriculture opined and K e yw or ds developed different agribusiness models to address the above aspects. In order to conduct this research, case study method was adopted to collect the necessary data and information Digital agriculture, from the entrepreneurs performing successful ventures in digital mode of agribusiness by Startups , Artificial adopting purposive sampling method. Secondary data pertaining to different countries Intelligence and were collected from the websites of digital agribusiness of their respective country. Digital Internet of Things agripreneurs enrolled in the Agribusiness incubation society were contacted personally to (IoT) collect the required data. M/s Kisangates Agro Informatics is an innovative startup with a motive to revolutionize business processes in agricultural ecosystem through strategic Article Info models and digital transformations that are synergistic with environment and business needs. Further, M/s Jeypee Biotechs, Virudhunagar developed the digital and ICT enabled Accepted: field advisory system model and executes networking among farmers on a common 24 July 2020 platform for dry chillies cultivation for export purposes. -
Agriculture 4.0 and Smart Sensors. the Scientific Evolution of Digital Agriculture: Challenges and Opportunities
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 31 May 2021 doi:10.20944/preprints202105.0758.v1 Article Agriculture 4.0 and Smart Sensors. The Scientific Evolution of Digital Agriculture: Challenges and Opportunities Michele Kremer Sott 1,*, Leandro da Silva Nascimento 2, Cristian Rogério Foguesatto 1, Leonardo B. Furstenau 2, Kadígia Faccin 1, Paulo Antônio Zawislak 2, Bruce Mellado 3, Jude Dzevela Kong 4 and Nicola Luigi Bragazzi 4,* 1 Unisinos University; [email protected] (M.K.S.), [email protected] (C.R.F.), [email protected] (K.F.) 2 Federal University of Rio Grande do Sul; [email protected] (L.B.F.), [email protected] (L.S.N.), [email protected] (P.A.Z.) 3 School of Physics and Institute for Collider Particle Physics, University of the Witwatersrand, Johannes- 7 burg, Wits 2050, South Africa; [email protected] 4 Department of Mathematics and Statistics, York University; [email protected] *Correspondence: [email protected] (M.K.S.); [email protected] (N.L.B.) Abstract: The agriculture sector is one of the backbones of many countries’ economies and its processes have been changing in order to enable technological adoption to increase productivity, quality, and sustainable development. In this research, we present a theoretical reflection through a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, the so-called Precision Agriculture (PA) and Agriculture 4.0 (A4.0). To do this, we used 4,694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis (BPNA) of the literature with the support of the PICOC protocol and the SciMAT software. -
Assessing Crop Performance in Maize Field Trials Using a Vegetation Index
Open Agriculture. 2018; 3: 250–263 Research Article Carl-Philipp Federolf, Matthias Westerschulte, Hans-Werner Olfs, Gabriele Broll*, Dieter Trautz Assessing crop performance in maize field trials using a vegetation index https://doi.org/10.1515/opag-2018-0027 received February 17, 2018; accepted June 20, 2018 1 Introduction Abstract: New agronomic systems need scientific Nitrogen (N) is a crucial nutrient for crop growth and below proof before being adapted by farmers. To increase the optimal plant N concentration can lead to significant yield informative value of field trials, expensive samplings losses (Mollier and Pellerin 1999, Plénet and Lemaire 2000). throughout the cropping season are required. In a series Excess N fertilization however, can have a negative impact of trials where different application techniques and on ecosystems (Sutton et al. 2011). To acquire reliable rates of liquid manure in maize were tested, a handheld information on balanced N fertilization, researchers sensor metering the red edge inflection point (REIP) usually use multi-location and/or multi-annual field trials was compared to conventional biomass sampling at to acquire fundamental information (Gomez and Gomez different growth stages and in different environments. 1984). Regarding maize (Zea mays L.) fertilization trials in In a repeatedly measured trial during the 2014, 2015, and areas with higher contents of soil organic matter, major 2016 growing seasons, the coefficients of determination differences in early-growth might become insignificant at between REIP and biomass / nitrogen uptake (Nupt) harvest due to a high N mineralization potential (Federolf ascended from 4 leaves stage to 8 leaves stage, followed by et al. -
Digital Agriculture and the Agridigit Project, Italy: Case Study Contribution to the OECD TIP Digital and Open Innovation Project
2 │ Digital Agriculture and the AgriDigit project, Italy: Case study contribution to the OECD TIP Digital and Open Innovation project Authors: Marcello Donatellia, Michele Pisantea,b a CREA, Council for Agricultural Research and Economics b University of Teramo Digital Agriculture and the Agridigit project, Italy – Contribution to the OECD TIP Digital and Open Innovation project │ 3 Table of contents Introduction ........................................................................................................................................... 4 1. Digital transformation of the agri-food sector ................................................................................ 6 2. The effects of digital transformation on innovation practices in the agri-food sector ................ 8 3. The AgriDigit project ...................................................................................................................... 10 References ............................................................................................................................................ 16 Digital Agriculture and the Agridigit project, Italy – Contribution to the OECD TIP Digital and Open Innovation project 4 │ Introduction The rapid development of innovation in the field of digital agriculture and agri-food chain, albeit in a chaotic frame of individual proposals, has highlighted an opportunity for a change of paradigm in establishing productivity in farms and of production areas. This has created a link between the production phase and product -
How South Australian Broadacre Farms Increased Productivity From
THIRTY YEARS OF CHANGE IN SOUTH AUSTRALIAN BROADACRE AGRICULTURE: TREND, YIELD AND PRODUCTIVITY ANALYSES OF INDUSTRY STATISTICS FROM 1977 TO 2006 Ian Black and Chris Dyson January 2009 SARDI Publication Number F2009/000182-1 SARDI Research Report Series Number 340 ISBN: 978-1-921563-09-6 South Australian Research and Development Institute Plant Research Centre Gate 2b Hartley Grove URRBRAE SA 5064 Telephone: (08) 8303 9400 Facsimile: (08) 8303 9403 http://www.sardi.sa.gov.au This Publication may be cited as: Black, I.D. and Dyson, C.B. Thirty Years of Change in South Australian Broadacre Agriculture: Trend, Yield and Productivity Analyses of Industry Statistics from 1977 to 2006. South Australian Research and Development Institute, Adelaide, 79pp. SARDI Publication Number F2009/000182-1. South Australian Research and Development Institute Plant Research Centre Gate 2b Hartley Grove URRBRAE SA 5064 Telephone: (08) 8303 9400 Facsimile: (08) 8303 9403 http://www.sardi.sa.gov.au DISCLAIMER The authors warrant that they have taken all reasonable care in producing this report. The report has been through the SARDI internal review process, and has been formally approved for release by the Deputy Executive Director. Although all reasonable efforts have been made to ensure quality, SARDI does not warrant that the information in this report is free from errors or omissions. SARDI does not accept any liability for the contents of this report or for any consequences arising from its use or any reliance placed upon it. © 2009 SARDI This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission from the authors. -
ITU-FAO Stocktaking Report: Digital Excellence in Agriculture in Europe and Central Asia
Digital Excellence in Agriculture in Europe and Central Asia Good practices in the field of digital agriculture Stocktaking Report @ITU and @FAO | July 2021 -Living document- Please note that the content of this document was provided by the submitter and ITU and FAO are not accountable for the information displayed. 2 ACKNOWLEDGMENTS This report was developed by the ITU Office for Europe within the framework of the ITU Regional Initiative for Europe on information and communication technology-centric innovation ecosystems. It was elaborated by Mr Laszlo Papocsi and Mr Mihaly Csoto, with the support of Ms Daniela DiGianantonio and Mr Eugen Harabara. ITU and FAO would also like to acknowledge the contribution of Mr Rinor Ahmeti (FAO), Ms Sarah Delporte (ITU), Mr Victor Lagutov (FAO), Mr Thembani Malapela (FAO), Mr Valentin Nagy (FAO), Mr Farid Nakhli (ITU), Mr Joshua Oiro (ITU), and Ms Antonia Vanzini (ITU). The work has been undertaken under the supervision and direction of Mr Jaroslaw Ponder, Head of ITU Office for Europe, and Ms Sophie Treinen, Information and Knowledge Management Officer and Digital Agriculture Team Leader of FAO Regional Office for Europe and Central Asia. FAO and ITU would also like to express sincere gratitude to all the participants of the Regional Contest “Digital Excellence in Agriculture in Europe and Central Asia” for their valuable submissions. Please note that the content of this document was provided by the submitter and ITU and FAO are not accountable for the information displayed. 3 DISCLAIMER ITU and FAO. 2021. Digital Excellence in Agriculture in Europe and Central Asia - Call for good practices in the field of digital agriculture - Stocktaking Report. -
The Faba Bean: a Historic Perspective (J.I
Downloaded from orbit.dtu.dk on: Oct 06, 2021 Faba bean in cropping systems Hauggaard-Nielsen, Henrik; Peoples, Mark B.; Jensen, Erik S. Published in: Grain legumes Publication date: 2011 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Hauggaard-Nielsen, H., Peoples, M. B., & Jensen, E. S. (2011). Faba bean in cropping systems. Grain legumes, (56), 32-33. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. ISSUE No. 56 April 2011 Towards the world’s earliest maturing faba beans Molecular breeding approaches in faba bean Diseases infecting faba bean Resistance to freezing in winter faba beans Faba bean in cropping systems ‘Why should I grow faba beans?’ There is hope for faba bean cultivation EVENTS 2011 Model Legume Congress Sainte Maxime, France, 15-19 May 2011 http://inpact.inp-toulouse.fr/ModelLegume2011/index.html -
Urban Bites and Agrarian Bytes: Digital Agriculture and Extended Urbanization
Berkeley Planning Journal 31 100 Urban Bites and Agrarian Bytes: Digital Agriculture and Extended Urbanization TIMOTHY RAVIS AND BENJAMIN NOTKIN Abstract Capitalist agriculture faces a crisis. Plateauing yields and profts are driving up food prices, and the ability to continue the traditional practice of expanding into new, un-commodifed territories appears to be waning. This crisis is due in large part to the accelerating biophysical contradictions of industrial agriculture, which systematically undermine the ecological conditions for its own success in pursuit of proft. We investigate how digital technologies are deployed as a potential data fx that does not solve the crisis but merely staves it of. We situate these technologies within the material context of capitalist urbanization, along the way arguing for bringing information back into the neo-Lefebvrian framework of “extended” or “planetary” urbanization. Digital agriculture technologies continue the centralization of economic knowledge and power as they facilitate the transformation of vast territories into “operational landscapes” that provide the material, energy, and labor for a rapidly expanding urban system. Keywords: Digital Agriculture, Precision Agriculture, Extended Urbanization, Planetary Urbanization, Globalization, Agrarian Studies, Depeasantization, Globalization, Computation “Eventually, precision agriculture could take humans out of the loop entirely. Once that happens, the world won’t just see huge gains in productivity. It will see a fundamental shif in the history of agriculture: farming without farmers.” —Foreign Afairs Magazine (Lowenberg-DeBoer 2015) “99% of all technological disruption is there to merely ensure that nothing of substance gets disrupted at all.” —Evgeny Morozov (2019) Introduction: Feeding “the Next Two Billion” Hundreds of reports and articles begin with a variation on the same apocalyptic exhor- tation: The combination of population growth, food price volatility, and climate change demands a new agricultural revolution to expand and secure the global food supply. -
Value Creation in the Digital Agribusiness Network Transform and Grow to Sustainably Feed the World
Value Creation in the Digital Agribusiness Network Transform and Grow to sustainably feed the world - 1 - SAP Digital Agribusiness Whitepaper (03/16) © 2016 SAP SE. All rights reserved ANJA’S POINT OF VIEW Dear Customers, The world population is growing to upwards of 10 billion people by the middle of the century.1 This growth combined with urbanization and the rise of the middle class will increase the demand for healthy, fairly produced, and sustainable food and will require agricultural production to double.2 To succeed, we need smart solutions from farm to fork. We expect the digitization of agribusiness to play a key role in solving this challenge. New processes and technologies optimize seed selection, irrigation, fertilization, and crop protection; automate farming work with autonomous equipment; optimize asset utilization; and streamline the food supply chain to avoid waste. But even in a high-tech economy, agriculture is still exposed to the weather, crop and animal diseases, and substantial fluctuations on commodity markets. Predictive analytics and simulations enable optimized risk mitigation strategies. Digital technology is turning the farm into a digital enterprise and the farmer into a digital entrepreneur. Farmers stand in the center of a complex ecosystem of farming equipment manufacturers, food "Digital technology and processors, and agrichemical specialists. At the same time, consumer behavior is changing collaboration are key radically. Consumers are the focus point of the food industry. They want to know the origin of their food and how it was produced and processed, driving the need for transparency along the enablers to provide end-to-end agribusiness supply chain. -
Previous Supply Elasticity Estimates for Australian Broadacre Agriculture
Previous Supply Elasticity Estimates For Australian Broadacre Agriculture Garry Griffith Meat, Dairy and Intensive Livestock Products Program, NSW Agriculture, Armidale Kym I’Anson Previously with the Industry Economics Sub-program, Cooperative Research Centre for the Cattle and Beef Industry, Armidale Debbie Hill Previously with the Industry Economics Sub-program, Cooperative Research Centre for the Cattle and Beef Industry, Armidale David Vere Pastures and Rangelands Program, NSW Agriculture, Orange Economic Research Report No. 6 August 2001 ii © NSW Agriculture 2001 This publication is copyright. Except as permitted under the Copyright Act 1968, no part of the publication may be reproduced by any process, electronic or otherwise, without the specific written permission of the copyright owner. Neither may information be stored electronically in any way whatever without such permission. ISSN 1442-9764 ISBN 0 7347 1263 4 Senior Author's Contact: Dr Garry Griffith, NSW Agriculture, Beef Industry Centre, University of New England, Armidale, 2351. Telephone: (02) 6770 1826 Facsimile: (02) 6770 1830 Email: [email protected] Citation: Griffith, G.R., I'Anson, K., Hill, D.J. and Vere, D.T. (2001), Previous Supply Elasticity Estimates for Australian Broadacre Agriculture, Economic Research Report No. 6, NSW Agriculture, Orange. iii Previous Supply Elasticity Estimates For Australian Broadacre Agriculture Table of Contents Page List of Tables…………………………………………………………………………………iv Acknowledgements…………………………………………………………………………...v Acronyms and Abbreviations Used in the Report…………………………………………..v Executive Summary………………………………………………………………………….vi 1. Introduction………………………………………………………………………………...1 2. Previous Supply Elasticity Studies……………………………………………………….. 4 2.1 Background………………………………………………………………………..4 2.2 Econometric Studies………………………………………………………………5 2.3 Programming Studies……………………………………………………………..8 3. Comparison and Evaluation of Previous Supply Elasticity Estimates………………….11 4. -
From Smart Farming Towards Agriculture 5.0: a Review on Crop Data Management
agronomy Review From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management Verónica Saiz-Rubio * and Francisco Rovira-Más Agricultural Robotics Laboratory (ARL), Universitat Politècnica de València, Camino de Vera, s/n. 46022 Valencia, Spain; [email protected] * Correspondence: [email protected]; Tel.: +34-963-877-291 Received: 2 December 2019; Accepted: 17 January 2020; Published: 3 February 2020 Abstract: The information that crops offer is turned into profitable decisions only when efficiently managed. Current advances in data management are making Smart Farming grow exponentially as data have become the key element in modern agriculture to help producers with critical decision-making. Valuable advantages appear with objective information acquired through sensors with the aim of maximizing productivity and sustainability. This kind of data-based managed farms rely on data that can increase efficiency by avoiding the misuse of resources and the pollution of the environment. Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future. This paper reviews the current status of advanced farm management systems by revisiting each crucial step, from data acquisition in crop fields to variable rate applications, so that growers can make optimized decisions to save money while protecting the environment and transforming how food will be produced to sustainably match the forthcoming population growth. Keywords: agriculture 4.0; big data; farm management information system (FMIS); robotics; IoT; variable-rate technology (VRT); AI 1. Introduction The agriculture sector is undergoing a transformation driven by new technologies, which seems very promising as it will enable this primary sector to move to the next level of farm productivity and profitability [1]. -
Toolkit: Digital Tools in Agriculture Programming
TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................................................... 2 OVERVIEW ................................................................................................................................................... 2 Why are Digital Tools in Agriculture Important? ........................................................................................ 2 Opportunity: Mobile Connectivity in Feed the Future and Affiliate Countries ............................................ 3 PRINCIPLES FOR DIGITAL DEVELOPMENT ............................................................................................ 3 The Principles ............................................................................................................................................ 3 Market Research ....................................................................................................................................... 5 Responsible Data Practices ...................................................................................................................... 7 Examples of Digital Projects Supported by USAID ................................................................................... 8 DIGITAL TOOLS IN AGRICULTURE ........................................................................................................ 10 Data-Driven Agriculture ..........................................................................................................................