The report aims to inform and update all those interested in the technologies and players involved in providing precision products and services, especially for crop protection, encompassing both established and novel precision technologies used in the collection of crop protection data, its use in diagnostics and decision support systems and its application to operations. In particular those related to disease, insect and weed control sectors are fully covered.
The report examines major crop protection company’s activities, leading specialist precision agriculture company profiles and specialist institutes, universities and major collaborative projects.
The report will help your business:
- Find opportunities by examining the latest applications and developments for precision farming and crop protection
- Minimise risk by understanding the technology and players involved in the industry
- Make informed decisions by learning about the use of precision technologies in collecting data, diagnostics, decision support systems and its applications to operations
- Track your competitors activities by viewing company activities and company profiles
1.3 Market drivers and development
1.4 Key concepts in precision farming
184.108.40.206 Remote sensing
220.127.116.11 Proximal sensing
1.4.3 Imaging and mapping
1.4.4 Decision support systems
18.104.22.168 Apps for decision support
1.4.5 Variable rate application
1.4.6 Auto-steering, guidance and controlled traffic
22.214.171.124 Unmanned aerial vehicles (Drones)
1.5 Networking and information
1.5.1 Precision agriculture associations and forums
1.5.2 Journals, websites
126.96.36.199 Scientific journals
188.8.131.52 Web magazines
1.6 References and resources
2. Control of diseases
2.3.1 Powdery mildew
2.4 Other field crops
2.4.2 Oilseed rape
2.4.3 Opium poppy
2.4.7 Sugar beet
2.5 Orchards and plantations
2.5.3 Oil palm
2.6 Soft fruit and vegetables
2.8 References and resources
3. Control of insects and other pests
3.3 Field crops
3.3.4 Sugar beet
3.4 Orchards and plantations
3.5 Stored products
3.6 References and resources
4. Control of weeds
4.3 Weed identification
4.3.1 Weeds in cereals
4.3.2 Weeds in maize
4.3.3 Weeds in vegetables
4.3.4 Weeds in sugar beet
4.3.5 Non-crop weed control
184.108.40.206 Aquatic weeds
4.3.6 Herbicide resistant weeds
4.4 Patch spraying and variable rate application
4.4.1 Commercial systems
4.5 Guided tillage
4.6 References and resources
5. Crop protection majors
5.3.1 Crop protection background
5.3.2 Precision farming activities
5.4 Bayer CropSciences
5.4.1 Crop protection background
5.4.2 Precision farming activities
5.5 Dow AgroSciences
5.5.1 Crop protection background
5.5.2 Precision farming activities
5.6.1 Crop protection background
5.6.2 Precision farming activities
5.7.1 Crop protection background
5.7.2 Precision farming activities
5.8.1 Crop protection background
5.8.2 Precision farming activities
5.9 References and resources
6. Engineering, IT, navigation and other companies
6.3 General precision agriculture companies
6.3.1 Ag Leader Technology
6.3.2 Farmers’ Edge
6.3.4 Raven Industries
6.3.5 Topcon Precision Agriculture
6.3.6 Trimble Navigation
6.4 Information and data management specialists
6.4.4 Ursula Agriculture
6.5 Agricultural machinery companies
6.5.2 Deere and Company
6.5.3 Yamaha Motor Company
6.6 Spray application specialists
6.6.3 TeeJet Technologies
6.7 References and resources
7. Universities and research institutes
7.3.1 University of Bonn’s Institute of Crop Science and Resource Conservation
7.3.2 University of Bonn’s Center for Remote Sensing of Land Surfaces
7.3.3 Leibniz Institute for Agricultural Engineering, Germany
7.3.4 The Institute for Sustainable Agriculture (CISC/IAS)
7.3.5 The UK National Centre for Precision Farming
7.4 United States
7.4.1 Oklahoma State University, Dept. of Biosystems and Agricultural Engineering
7.4.2 University of California Center for Spatial Technologies and Remote Sensing
7.4.3 University of Minnesota Precision Agriculture Center
7.4.4 University of Wisconsin Environmental Remote Sensing Center
7.4.5 USDA’s Southern Plains Agricultural Research Center
7.4.6 Washington State University Center for Precision and Automated Systems
7.5 Rest of World
7.5.1 Beijing Research Centre for Information Technology in Agriculture
7.5.2 Ben-Gurion University of the Negev’s ABC Robotics Initiative
7.5.3 Ben-Gurion University of the Negev’s Remote Sensing Laboratory
7.5.4 New Zealand Centre for Precision Agriculture
7.5.5 University of Sydney’s Precision Agriculture Laboratory
7.5.6 Volcani Centre
Precision agriculture tackles the variability inherent in farming systems to improve productivity and profitability and to reduce risks and environmental impact. It involves the application of information and communications technology software and hardware to farming. Integrated systems cycle through data collection, its use in decision-support models and enterprise management, operations, and analysis and evaluation.
The global market for precision farming technologies is forecast to reach a value of nearly $4 billion by 2018 at an estimated CAGR of over 13%.
To date, commercial applications of precision agriculture have been strongly biased towards crop nutrition, based on mapping of soil types, crop yield and variable rate fertilizer application. However, precision farming technologies for crop protection are being taken-up on farms and are the focus of this report.
The development and implementation of precision farming has been made possible by GPS (and other satellite systems) and geographic information systems (GIS). These technologies enable data collected in real-time to be linked with accurate position information.
Remote sensing is the detection and/or identification of an object(s) or landscape without direct contact. Operations may be conducted at various altitudes, e.g. by satellites, aircraft or drones. Common forms include colour and infrared aerial photography, satellite imaging and radar sensing. UAVs or drones offer the potential for rapid assessment and high-resolution imagery. Remote sensing can be used to create images and maps.
Proximal sensors mounted on vehicles traversing a field have obvious advantages of immediacy, better resolution and connectivity to application equipment over remote sensing systems.
The Internet has allowed farmers easy access to agronomic decisions aids. Smartphones and tablets have meant that information and decision aids can now be readily accessed in the field. A variety of apps are available and examples are described.
Variable rate technology is well established for increasing the precision of seeding and fertilizer spreading and is becoming used in crop protection, albeit that the challenges are considerably greater. Sensor systems are now commercially available allowing site-specific weed management.
Auto-steering, machinery guidance offer the potential to reduce over- and under-spraying and controlled traffic systems can reduce soil compaction by coordinating restricted passage of machinery.
Information concerning associations and forums devoted to precision agriculture, scientific journals, and online magazines and other websites is presented.
Chapter 2: Control of diseases
Advances made in the field of disease control using precision farming technologies reported over the past five years are described.
Early remote detection of disease infection, ideally before symptoms become visible, has been the major target for research. Mapping fields to designate areas of soil-borne infection is another important topic.
Various spectral imaging techniques have given encouraging results in experiments aiming to remotely detect the early signs of powdery mildew infection in wheat.
There has been some success in distinguishing rust infections in wheat from leaf chlorosis caused by nitrogen deficiency. Complications in identifying infections are caused by light reflected from top or undersides of leaves. Chlorophyll fluorescence imaging has shown promise as a tool for early screening for rust resistance in breeding programmes. Easier detection of mycotoxins is another target.
Recent research on other field crops has included: remote monitoring of patchy infected areas of cotton and oilseed rape to map soil-borne disease; early diagnosis of oilseed rape leaf diseases by hyperspectral imaging and multivariate techniques; remote diagnosis of bacterial wilt of potatoes; monitoring rice and soybean fields for Rhizoctonia solani carried over through the rotation; and the identification of leaf diseases of sugar beet by spectral analysis.
Recent research in orchards and plantations has included: early detection of scab infection on apple leaves by spectral reflectance and fluorescence imaging; sensing and quantifying apple scab using digital infrared thermography; using hyperspectral imaging to detect citrus greening disease; using high-resolution QuickBird satellite imagery to detect oil palms in Indonesia infected by basal stem rot; looking for indicators of infection of olives by verticillium wilt using high-resolution thermal and hyperspectral imagery.
Other research has included investigating the use of infrared thermography for pre-symptomatic detection of disease in ornamentals.
Chapter 3: Control of insects and other pests
Advances made in the field of pest control, covering insects and nematodes, using precision farming technologies reported over the past five years are described.
Site-specific control of root-knot nematodes in cotton may be facilitated in future by the use of prescription soil maps as infestations tend to be related to soil type.
Satellite multispectral imagery has been used to map damage caused by armyworm to maize and has been successfully employed in China.
SPAD meters, usually used to indicate plant nitrogen status, have been used in combination with canopy reflectance readings to indicate the level of brown planthopper in rice.
Symptoms of root rot caused by nematodes induced changes in sugar beet foliage have been detected by hyperspectral image analysis.
An alternative method to monitoring moth populations in tomatoes is to record the sound made by moths in traps.
Spectral indices commonly used to monitor crop stresses have been successfully employed to estimate aphid population density in wheat.
Recent research on orchards has included studying the spatial and temporal dynamics of fruit flies in aiming to define a methodology to optimise monitoring for IPM programmes.
Imaging techniques to identify insect species and geographical strains infesting grain stores have been investigated.
Chapter 4: Control of weeds
Advances made in the field of weed control using precision farming technologies reported over the past five years are described: progress made in the identification of weeds and how precision farming is enabling the application of herbicides to patches at variable rates, or using guided tillage.
Site-specific weed management using remote sensing for accurately mapping the extent of weed invasion and the position of patches offers several advantages in efficiency and effectiveness over ground-based methods. It also offers the opportunity to locate map and control small infestations before they reach significant levels.
Weeds must be distinguished from crops. Various technologies including multispectral imaging at various wavelengths and chlorophyll fluorescence have been used, sometimes in combination with others to identify particular weed species.
Unmanned aerial vehicles (UAVs or drones) can take high spatial resolution images that have much better potential than using satellites or conventional aircraft. However, it is necessary to capture a large number of overlapped images that must be mosaicked together for mapping.
Laser line-scan technology has been developed to measure crop plant locations in maize. Once logged, these positions can then be avoided when using tillage to control weeds. Similarly, the difference in height between crop and weeds can be used as a distinguishing factor.
The potential for sensing technologies to identify herbicide resistant weeds has been demonstrated with glyphosate-resistant Palmer amaranth. Differences in reflectance between susceptible and resistant plants may be due to changes in metabolism resulting in the accumulation of more photodynamic compounds in resistant plants.
Once the location of weeds has been registered, decision support systems can be used to determine whether the infestations are economically significant and herbicides or physical methods can be employed to remove weeds.
Trimble’s WeedSeeker is an automatic spot spray system that allows for targeted herbicide application by detecting the presence of living plants. It can be used where weed patches can usefully be specifically targeted, e.g. in perennial crops such as orchards and vineyards; and for non-agricultural situations such as controlling weeds growing through tarmac or in paths.
Guided tillage systems for weed control are being researched and some are available commercially for use in regularly spaced (transplanted crops).
Chapter 5: Crop protection majors
BASF provides a number of services to farmers for agronomic decision-making. The company has signed- up to agreements with others including Iteris and John Deere and is involved in various research projects.
Bayer CropScience emphasises ‘digital farming’ as a key element in its precision agriculture activities. The company is collaborating with John Deere and offers a number of agronomy apps and online tools and services.
Dow AgroSciences has an agreement with John Deere to develop approaches and technology for site- specific applications. The company has a collaborative project in Brazil to use precision technologies to improve the sustainability of agricultural practices.
Dupont has announced collaborations with John Deere and AGCO, working with the company’s plant breeding and seeds business, Dupont Pioneer. Encirca is a new whole-farm decision-making service designed to help growers improve productivity and profitability.
Monsanto’s FieldScripts integrates seed science, agronomy, data analysis, precision agriculture equipment and services to provide farmers with particular maize hybrids and a prescription for variable rate planting across a field to improve yield. The company has made recent acquisitions of The Climate Corporation and Precision Planting to complement its Integrated Farming Systems platform.
Syngenta offers farmers online agronomy tools, and whole farm management information and services. Collaborative projects have included monitoring citrus orchards for disease and cereals for grass weed infestations.
Chapter 6: Engineering, IT, navigation and other companies
This chapter includes profiles of companies primarily involved in technologies used in precision farming. The larger companies and a selection of smaller and start-up companies are covered to provide an overview of the types of the many companies comprising the industry, focusing on those involved in selling products and services aimed at crop protection.
General precision agriculture technology companies included are: Ag Leader Technology, Farmers’ Edge, OmniSTAR, Raven Industries, Topcon Precision Agriculture and Trimble Navigation
Information and data management specialists included are: efarmer, Gamaya, Iteris and Ursula Agriculture Agricultural machinery companies included are: AGCO, Deere and Company, and Yamaha Motor Company Spray application specialists included are: DICKEY-John, Micron and TeeJet Technologies
Chapter 7: Universities and research institutes
The leading universities and research institutes involved in precision farming technologies and their application are listed and profiled.
Institutes in Europe included are: Institute for Sustainable Agriculture (CISC/IAS), Spain; Leibniz Institute for Agricultural Engineering, Germany; University of Bonn’s Institute of Crop Science and Resource Conservation (INRES), Germany; University of Bonn’s Center for Remote Sensing of Land Surfaces, Germany; UK National Centre for Precision Farming.
Institutes in the US included are: Oklahoma State University Department of Biosystems and Agricultural Engineering; University of California Center for Spatial Technologies and Remote Sensing; University of Minnesota Precision Agriculture Center; USDA’s Southern Plains Agricultural Research Center; Washington State University Center for Precision and Automated Systems.
Institutes in the rest of the world included are: Beijing Research Centre for Information Technology in Agriculture; Ben-Gurion University of the Negev’s ABC Robotics Initiative: Agricultural, Biological & Cognitive, Israel; Ben-Gurion University of the Negev’s Remote Sensing Laboratory, Israel; New Zealand Centre for Precision Agriculture, University of Sydney’s Precision Agriculture Laboratory, Australia; Volcani Centre, Israel.
- Bayer cropsciences
- Dow agrosciences
- Farmers’ Edge
- Raven Industries
- TeeJet Technologies
- Topcon Precision Agriculture
- Trimble Navigation
- Ursula Agriculture