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Current and future agricultural practices and technologies which affect fuel efficiency

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IEE/09/764/SI2.558250
D 3.1.
Current and future agricultural
practices and technologies which
affect fuel efficiency
Version: 1
L. Biggs and D. Giles
Author’s Email: dgiles@harper-adams.ac.uk
Authors Phone: +44 (0) 1952 815244
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Abstract
The report investigated how fuel efficiency could be improved in agriculture, providing signposts for future research and
development, with the objective of informing agricultural equipment manufacturers, dealers and agricultural support
organisations. The farming practices of precision agriculture, controlled traffic farming (CTF), direct drilling and minimum
tillage, energy independent farms (EIF), hydroponics and vertical farming were established as priority topics for research and
development. As were the technologies of hydrogen fuel cells, electric vehicles, automatic boom and variable rate application.
Fuel efficiency improvement in the priority topics was high, ranging from a 20% fuel efficiency improvement in automatic
boom technology and variable rate application, to an improvement in fuel efficiency of over 100% in hydroponics and vertical
farming when compared to current arable farming. The priority topics ranged from being commercially normal practices from
the present with direct drilling and min-till, to fifteen years or more in the case of hydrogen fuel cells, CTF and EIF.
Certain topics outside the top eight should be investigated further, due to their ability to provide a fuel efficiency
improvement of over 20%. These topics were alternative methods of woodchip drying in the forestry sector, hybrid and contour
mapping. The first could provide fuel efficiency improvements of up to 100%. Contour mapping could be straightforwardly
integrated into the agriculture sector. These topics are recommended for further research and development.
1. Introduction
Background
The European Union (EU) has set a 20% energy reduction
target for countries to comply with by 2020. The
agriculture sector is a large consumer of energy and is
being encouraged to assist in meeting this target. This
target, in combination with rising fossil fuel prices, has
resulted in many different developments in agricultural
practices to reduce energy consumption. Efficient 20, a
European project aimed at encouraging the agriculture
sector to assist in reaching this target, commissioned this
report to highlight the different practices and technologies
that could result in improved fuel efficiency.
Confusion can arise when using different energy related
terms, such as energy efficiency, fuel efficiency, life cycle
assessment and fuel consumption. Further confusion can
arise when the two agricultural variables of yield and
chemical use are brought into the situation. To avoid such
confusion, the terms, and their definition in respect to the
report, are stated as:
Energy Efficiency The percentage of energy outputs of a
process in comparison to the total energy inputs. Yield is
classed as an output, and chemical use an input, due to the
energy use to create fertilisers, herbicides and pesticides.
Thus, an increase in energy efficiency can be achieved
through an increase in yield or decrease in chemical use.
Fuel Efficiency - The percentage of energy outputs of a
process in comparison to the total fossil fuel energy input.
Due to the use of fossil fuels to create chemicals, a decrease
in chemical use will increase fuel efficiency. Likewise, as
yield is normally the result of using fossil fuels used as
inputs, an improvement in yield will increase fuel
efficiency. Furthermore, replacing the fossils fuels used
with alternative sustainable fuels will be classified as
improving fuel efficiency.
Life Cycle Assessment An assessment of energy used by
a product from ‘cradle to grave’, i.e. from design and
manufacturing, through its life and its final disposal.
Fuel Consumption The total fossil fuel used by a product
or process over a given period of time or distance.
Distinguishing the difference between energy and fuel
efficiency was important when looking at alternative fuels
and the technologies which use them. Establishing the
effect of yield improvements and chemical use reductions
was also important. Some of the technologies will have
reductions in chemical use as the main benefit.
Manufacturing the chemicals is energy intensive and uses
fossil fuels, thus it is important to convert the reduction in
chemical usage to an improvement in fuel efficiency.
Objectives
The objectives set for the report are stated. However, the
report structure will not be based around these objectives as
it would result in an unstructured report due to the quantity
of technologies and practices investigated.
i. Establish how farming practice is changing to
improve efficiency, identifying the latest research and
emerging technologies which are likely to reach the
market in 3, 5 or 10 years’ time.
ii. Determine how the machine manufacturers are
adapting to, or driving these changing practices.
iii. Investigate what the companies producing diesel
engines for agricultural vehicles are doing to improve
efficiency.
iv. Explore what farmers are doing to improve efficiency.
This should identify new techniques and methods that
farmers are starting to adopt.
v. Signpost future research and developments.
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Constraints
There were constraints set when the report was
commissioned, and further constraints became apparent as
the report was undertaken. The constraints are stated.
i. Agriculture is to be defined as both farming and
forestry sectors.
ii. The report is to be aimed at informing agricultural
equipment manufacturers, dealers and agricultural
support organisations.
iii. A maximum of ten researchers to be approached.
iv. Any farming technologies and practices should only
be targeted towards arable and fresh produce
production. Thus, the research excludes livestock
production.
Acronyms
AMS Agricultural Management System
CDA Controlled Droplet Application
CNH Case New Holland
CPPS Closed Plant Production System
CR Common Rail
CTF Controlled Traffic Farming
EGR Exhaust Gas Recirculation
EIF Energy Independent Farm
EPM Engine Power Management
EU European Union
EV Electric Vehicle
GIS Geographic Information System
GPS Global Positioning System
ICE Internal Combustion Engine
ICEV Internal Combustion Engine Vehicle
JD John Deere
LCA Life Cycle Assessment
LED Light-emitting Diode
NDVI Normalised Difference Vegetation Index
NH New Holland
PA Precision Agriculture
SCR Selective Catalyst Reduction
SRC Short Rotation Coppice
SSNM Site Specific Nutrient Mapping
UGV Unmanned Ground Vehicle
VRA Variable Rate Application
2. Material and Methods
A literature review was conducted investigating the
practices and technologies effecting agriculture. This
involved the use of journals, books, online and magazine
articles, manufacturer pamphlets and opinions from
unbiased people within the sector. This literature review
specifically targeted fuel efficiency, and the changing
practices and technologies that were not affecting this were
removed from the process. The literature review formed the
basis for the assessment of agricultural practices and
technologies listed through Section 3 to 8. For each
practice or technology reviewed, the effect on fuel
efficiency was discussed and if possible quantified.
Following this process, a research priority table was
produced, with each technology or practice rated in terms
of improvement in fuel efficiency according to a set scale.
They were also rated by what other benefits they could give
to agriculture according to a set scale. These two numbers
were added together, and the eight highest scoring became
the priority topics for improving fuel efficiency in
agriculture. This table is available in Appendix A.
The eight priority topics became the basis for a survey
process. A prominent researcher for each of the topics was
approached and surveys were tailor made for each of the
topics, ensuring that relevant information was gathered.
The important information was extracted and summarised
in Section 10, the full survey results are listed as
appendices.
The results of the literature review and survey process
were discussed. Following this conclusions were made,
giving strong signposts for future research and
development.
3. Diesel Engines
Diesel engines have traditionally been the main focus in
improving fuel efficiency in agriculture. Billions of pounds
of investment have been made by the automotive sector
into improving the diesel engine.
A major consideration when objectively looking at diesel
engines is that the thermal efficiency of an internal
combustion engine (ICE) is poor, with the most advanced
diesel engines in the world only being about 50% efficient
[48]. Currently most production steel diesel engines have a
limit of 37% thermal efficiency and an overall energy
efficiency of about 20% [50], thus the efficiency of the
diesel engine is not anticipated to vastly improve and fuel
efficiency enhancements will be limited. Therefore is it
time to prioritise alternative methods for improving fuel
efficiency in agriculture?
Diesel engine manufacturers argue that further
improvements can be made to improve fuel efficiency.
Some of the technologies that could or are currently
achieving a fuel efficiency improvement in agriculture are
detailed.
3.1 Emission Control
John Deere and New Holland and the other main machine
manufacturers have adopted emission control products to
meet European emissions regulations for their diesel
engines. John Deere has opted to develop exhaust gas
recirculation (EGR), whilst New Holland have decided
against this for tractors over 100bhp and have instead
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opted for selective catalytic reduction (SCR) also known as
AdBlue.
EGR circulates the waste exhaust gases back into the
engine cylinders, lowering the combustion temperature,
which reduces the amount nitrogen oxide, a harmful
emission produced by the engine [27]. However, in
reducing the combustion temperature, the power, toque and
fuel economy of the engine are reduced as the engine is
less efficient. Thus EGR is reducing fuel efficiency, but
does reduce emissions.
SCR uses a catalyst, AdBlue, to treat the nitrogen oxide
in the exhaust gases, converting it into water and Nitrogen
[40]. This is a post combustion process and has no effect
on the engine performance. New Holland’s promotional
material suggests otherwise, claiming the new engine
‘breathes clean fresh air’, but this is due to other design
modifications. Furthermore, in the promotional material
the effect of SCR is being combined with Engine Power
Management (EPM) technology, which improves fuel
economy, torque and power. Therefore, SCR does not
improve fuel efficiency, but does reduce emissions.
3.2 Engine Power Management
New Holland use engine power management (EPM)
alongside SCR in their EcoBlue engines. EPM tailors the
engine power delivery to the operation that is being
completed by the tractor [40]. Thus, a boost in power is
automaticallymade available to the operator when the
machine requires it. For example a 125hp rated tractor
such as the New Holland T6050, runs at 125hp but has a
reserve power increase available of around 36hp, raising
the machine to 161hp for high power applications.
Therefore because the engine is not running at full capacity
all of the time, fuel consumption is reduced, improving fuel
efficiency. New Holland states their EcoBlue engines
improve fuel consumption by up to 10% and that power
and torque are increased by 7% and 13% respectively [40].
3.3 Stop Start Technology
Stop-start technology has been introduced into the
automotive industry, with the main companies such as
BMW, Volkswagen, PSA Peugeot Citroen, Mazda and
recently Ford all adopting the technology for their ICEs.
The technology automatically shuts down the ICE as the
vehicle stops; reducing the time the engine is spent idling.
In the automotive industry stop-start technology typically
reduces fuel consumption by 5-10% [53]. This technology
could be transferred to agricultural machines, where
depending on the operation being completed, machines can
be idling for periods of time.
3.4 Piezoelectric Injectors & Common Rail
The third generation common rail (CR) diesel engine with
piezoelectric injectors was launched in 2003 and was first
used by Audi in automotive vehicles. The injectors consist
of several hundred piezoelectric wafers, which expand
rapidly when an electric current is run through them [45].
Using this method of injection increases injection speed,
accuracy and fuel atomization.
It has been stated [47] that using a third generation CR
with piezoelectric injectors in a turbo boosted diesel engine
reduces fuel consumption and emissions. Robert Bosch
GmbH [45] quantifies these reductions as 3% and 20%
respectively. DENSO [16] have further developed the third
generation CR diesel engine so that it now operates at a
pressure of over 200MPa compared to 160MPa when it was
first introduced, improving power and efficiency. This
advancement has further increased fuel efficiency.
3.5 Petroleum Diesel Catalyst
Research has been conducted [56] establishing the effect of
a ferrous picrate based homogeneous combustion catalyst
on the combustion and fuel consumption characteristics of
a diesel engine. The results indicated that the fuel
consumption decreased and the thermal efficiency
increased when using the catalyst. Fuel consumption was
reduced by 2.0-4.2% depending on the load applied to the
engine. Pending further testing it is something that can be
introduced as an additive to diesel to improve fuel
efficiency.
4. Alternative Fuels
4.1 Biodiesel
Biodiesel is a fuel that has been increasing in popularity
due to it being cheaper than equivalent fuels. Research [49]
states that there is little difference in fuel efficiency
between a production diesel engine using the biodiesel and
standard petroleum diesel. It was also stated that the
efficiency of the engine depends on whether it has been set
up for each type of fuel, with the right setup producing
similar results between diesel and biodiesel. However, it
has been stated [12] that there are good results in reducing
most emissions using biodiesel with up to 50% reduction in
carbon emissions using a 100% biodiesel fuel.
Furthermore, because it is from a sustainable resource and
is an alternative to fossil fuels, it can be stated that
machines using 100% biodiesel fuel improve their fuel
efficiency by 100%. However, most diesel engines will only
run a 20% biodiesel to 80% petroleum diesel mix without
any modifications, thus the fuel efficiency improvement is
currently 20%.
4.2 Fuel from Pyrolysis
Another form of biofuel, currently at an experimental
stage, is pyrolysis oil and synthesis gas (syngas) obtained
from the pyrolysis of organic materials. A pyroformer
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converts organic material into charcoal, oil and gas
through heating the material. The ratio of each product is
dependent on the running temperature, heating rate,
heating duration, operating pressure and the type of
organic material utilised [52]. Pyrolysis oil can be
converted to syngas which can be used to create biodiesel.
Research [52] yielded impressive results when establishing
whether unconverted pyrolysis oil obtained between the
400-480 degrees range with added catalysts, could be used
as a petroleum diesel substitute. The research used fish as
the organic matter for the pyrolysis. Pyrolysis oil and
petroleum diesel have similar efficiency and combustion
characteristics. However, pyrolysis oil gives a significant
reduction in most emissions. Establishing the fuel
efficiency improvement pyrolysis fuel can give is difficult
due to it being at an experimental stage.
Pyrolysis is a future technology that could be used in the
form of a pyroformer on farms to convert waste organic
matter into a fuel that can be used by machines. Sufficient
charcoal is produced from the pyroformer to continuously
heat the process to gain useful oil and gas. The technology
lends itself to the ideal of an energy self-sufficient farm.
4.3 Hybrid Vehicles
Hybrid vehicles have become more popular and widespread
within the automotive sector. Hybrid vehicles are split into
two driveline configurations; series and parallel [26]. A
series configuration has one energy converter providing
power, and a separate energy source or sources providing
the energy. An example of a series configuration would be
a diesel engine generator charging batteries, powering an
electric motor providing the vehicle drive.
A parallel configuration has multiple energy converters
coupled together to provide a combined drive. An example
of a parallel configuration would be the Toyota Prius
driveline; electric motors and an ICE combine through a
planetary gearbox, resulting in one combined drive.
Typical series systems are generally less fuel efficient than
parallel systems, due to the combined efficiency of
requiring three propulsion systems; ICE, generator and
electric motor [26]. However, the Caterpillar D7E hybrid
tracked bulldozer shows that it can be an efficient
configuration. The D7E has a 25% gain in overall
efficiency and a 20% reduction in fuel consumption over
the standard D7R model [9]. This technology could be
transferred to the agriculture sector.
Research investigating the life cycle assessment (LCA)
of a solar assist plug-in hybrid electric tractor [39] showed
that during the complete product lifecycle the hybrid’s
energy emissions were approximately 17% of a
comparative diesel engine tractor. Energy consumption in
this example was generated from renewable sources,
exaggerating the emission savings as this change from
fossil fuels was also used as part of the calculation.
4.4 Electric Vehicles
Electric vehicles (EVs) can be more fuel efficient than
those powered by an ICE. The primary reason for this is
due to the high efficiency of the electric motor, which can
be over 80% efficient [26] indicating a gain of 60% over an
ICE. However, Table 4.1 shows that when taking into
account the electricity generation method from crude oil
and other system inefficiencies, difference in energy
efficiency and therefore fuel efficiency is minimal. Should
the electricity come directly from renewable energy
sources, for example an on-site wind turbine, then the
inefficiency of using a generator is removed. If this was the
case, an EV system would be approximately 55% efficient.
This would represent a 35% improvement in energy
efficiency and a 100% improvement in fuel efficiency as no
fossil fuels would be required.
Unfortunately EV development has been hindered due to
an insufficient international copper supply to mass
manufacture electric motors. This will change as the
aluminium electric motor is developed as an alternative. It
is estimated aluminium electric motors are approximately 5
years away from commercial introduction.
Another issue with the electric motor specific to
agriculture is that although it has a large quantity of torque
available at low speeds, large EVs struggle with starting to
move in high resistance situations; for example on hill
starts. As a result there is a lot of work being conducted by
electric motor companies such as ZF [55] looking at new
transmissions to get around this situation. These
transmissions should allow high torque from zero mph
through the low speeds.
4.5 Hydrogen Fuel Cells
The hydrogen fuel cell is similar to a battery; the difference
is that as long as fuel in the form of hydrogen and oxygen
is supplied to the fuel cell it will keep producing energy,
whereas batteries produce electricity from stored chemical
energy and need recharging [26]. The only emission from a
hydrogen fuel cell in operation is water, although energy is
required to produce the hydrogen required. New Holland
Table 4.1 - EV and ICEV Efficiencies (Source: Husain, 2003)
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[41] have produced two prototype hydrogen fuel cell
tractors, the newest being the NH2. They have been
promoting the NH2 alongside energy independent farms
such as La Bellotta in Italy where they are conducting
trials.
The fuel efficiency of a hydrogen fuel cell is dependent
on where the energy comes from for the fuel production.
Should this be from renewable resources, the only energy
expenditure is from manufacturing and decommissioning
the vehicle. Sorensen (2004) compares the LCA of a fuel
cell car to that of a car using the most efficient common
rail diesel engine. Utilising fuel produced from renewable
resources sees an LCA fuel efficiency improvement of
36%, whilst utilising fuel produced from fossil fuels sees a
smaller improvement of 20%. Differences will occur due to
operating factors when investigating the effect on
agricultural vehicles.
One major issue that is slowing down the commercial
availability of fuel cells, other than it being relatively new
technology, is the same copper supply issue with EVs; they
use electric motors for propulsion. Another well publicised
issue is that a new infrastructure providing the hydrogen
would need to be setup in Europe. This issue can be
negated in agriculture when producing all the required
hydrogen on-site at energy independent farms. In reality
should this become a commercially normal technology then
it is likely several small farms will combine and have one
hydrogen station servicing them all. Should the hydrogen
be produced in this way from renewable energy sources
such as crop residues, then this will represent a 100%
improvement in fuel efficiency as no fossil fuels will be
required.
5. Changing Farming Practices
5.1 Direct Drilling& Minimum Tillage
Direct drilling and minimum tillage (min-till) are farming
practices that have increased in popularity over the last
twenty years. Both systems replace the plough as methods
of establishing a crop. Direct drilling is pretty self-
explanatory and drills the seed into uncultivated land,
reducing the energy input considerably, but also reducing
yield. The min-till technique uses tines and discs to
cultivate, which both use substantially less energy than a
plough, and has been shown to increase yields. It works on
the concept that by turning over the stubble from the
previous crop, this will decompose and produce the
nutrients required for the following crop.
It has been stated [23] that direct drilling decreased yield
by approximately 7% on average compared to ploughing
over a three year period, and that min-till increased yield
by approximately 2.5% on average. These figures vary
depending on the quantity of passes. Amazone [3] states
that the fuel consumption saving between min-till and
ploughing is 41-46% during cultivation and tillage
operations dependant on soil type. Bayhan et al. [4] states
the fuel consumption saving during tillage operations is
slightly higher at 49%, and estimates the fuel consumption
saving between direct drilling and ploughing during tillage
operations is approximately 89%.
These are impressive statistics, but must be taken with
caution. Many farmers have stated that certain soils are not
suitable for direct drilling, as they become hard without
cultivation and lead to poor yields. This has resulted in the
halfway stage of min-till becoming more popular, as it does
not suffer from this issue as much.
5.2 Field & Tractor Course Design
Field design can have a strong bearing on the fuel
efficiency of agricultural operations. Shape, contours and
obstacles can all cause fuel inefficiencies due to increased
manoeuvring or through reduced yield via nutrient loss. It
has been stated [1] that efficiency of farm machinery
operation can be affected by three factors: the travel speed,
the effective swath width, and the field traffic pattern.
Field design can impact all three, thus is an important
consideration when trying to improve fuel efficiency. Long
thin fields are often used abroad to improve fuel efficiency
due to reduced machine turning. However, research in
Spain [46] showed that machine efficiency improved very
little above a threshold of one to two hectares. In large
parts of Europe, increasing field size is unlikely due to the
public’s value of biodiversity and smaller aesthetic fields.
The coordinates of tractors during spraying operations
were recorded [42] using precise GPS coordinates, to
establish the effect of tractor course on the consumption of
fuel, time and chemicals. Using a predetermined optimum
tractor course for each field resulted in up to a 16%
reduction in distance travelled and a reduction of 10% on
inputs due to reduced overlap and misses. Thus 16% of
tractor fuel would be saved and reduction of chemicals
would save fossil fuels in production. It can be estimated
that in this case fuel efficiency could be improved by up to
20% with the use of a predetermined course in fields that
are extremely irregularly shaped; this would drop
significantly for regularly shaped fields. This is something
that could be done now to improve fuel efficiency.
5.3 Precision Agriculture
“Precision agriculture offers the possibility of growing
better quality crops, while optimising the use of inputs and
minimising environmental impacts. It is a revolution in
agriculture brought about by the application of information
technology.” [13]. Thus any form of agriculture that uses
some form of new technology is labelled precision
agriculture. Precision agriculture is a change in farming
practice to using technology to improve accuracy, yields
and efficiency. As technology drives change through
improvement, most changes to farming practice and new
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agricultural technologies are linked to precision
agriculture.
When looking collectively at the new and current
precision agriculture technologies such as global
positioning systems (GPS), aerial and satellite imagery,
geographic information system (GIS) mapping, yield
monitoring, site specific nutrient mapping (SSNM),
contour mapping, normalised difference vegetation index
(NDVI) mapping, the N-Sensor, automatic steering
(autosteer) and automatic boom (auto-boom) systems, the
technologies can provide an accumulative fuel efficiency
improvement of approximately 80%. These technologies
and the benefits associated with them are detailed in
Section 6, dedicated specifically to precision agriculture.
5.4 Controlled Traffic Farming
Controlled traffic farming (CTF) is the practice of using
one set of permanent tracks for all the machinery
operations on the field. This reduces soil compaction
across the rest of the field, which improves yield, reduces
fuel consumption of machines with implements, and allows
wider use of minimum tillage and direct drilling.
The use of CTF in Australia was estimated in 2005 as
over one million ha [10]. One consideration to take into
account is that in Australia the standard track width for the
majority of agricultural vehicles is now three metres [10],
ideally sized as the Australians have wider roads to
transfer machinery about; this is not the case in the large
parts of Europe. Furthermore, it was stated [10] that the
main barriers of entry to European farmers are;
incompatibility of existing machinery, cost of conversion,
poor attitude from farmers to CTF and change in general,
and contractors are unlikely to have compatibly sized
equipment.
Due to the soil compaction benefits of CTF [15],
uncompacted soils result in energy savings for operations
such as tillage. Trials implementing complete CTF showed
that “Energy demands for seedbed preparation fell by up to
87%, while power requirements for primary and secondary
tillage were reduced by 45% and 47% respectively.” [10];
this represents an improvement in fuel efficiency of at least
45%.
Soil compaction also impacts yield through the loss of
nutrients. “There is a considerable body of evidence to
suggest that wheel loads in excess of 5000kg will cause a
permanent 2.5% reduction in yield due to subsoil damage”
[10], although the same source also states there was no
clear relationship between soil type, yield and compaction.
Furthermore, avoiding soil compaction can increase
nutrient recovery by up to 20%.
5.5 Hydroponics & Vertical Farming
It was asserted [5] that plant growth in a rooting media,
including soil, is technically hydroponic, as soils are water
based solutions. However, hydroponics is often associated
with suspending plants roots into a container based
nutrient solution, replacing the need for soil. It can also be
achieved by using an inert medium such as sand, gravel or
perlite with a nutrient solution flowing between. The
advantages of hydroponics are: complete nutrient
management, increased yields and easier harvesting [44].
The main disadvantages are: no soil barrier to hinder the
rapid spread of diseases and the high initial capital cost.
It has been stated [44] that hydroponics can increase
yields per acre of cereals and fresh produce, from 38% in
cabbage, to 3000% in tomato production as shown in Table
5.1. Where the produce is grown in artificial conditions
and the yields are increased, it is presumed that the method
uses more fuel per acre compared to traditional soil
production. However, due to substantially increased yields,
hydroponics could significantly increase fuel efficiency; in
many cases by over 100%. A life cycle analysis of using
hydroponics for each crop needs to be conducted to
accurately establish changes in energy consumption.
Table 5.1 Soiled and Hydroponic Yields (Source: Resh, 1998)
Yield Per Acre
Vertical farming is the current and future research of
hydroponics in urban high rise buildings, with hydroponic
tanks on each floor resulting in a building for food
produce. With the continuing exponential growth in world
population, more efficient use of land will have to be
implemented to satisfy the demand for food; vertical
farming fits well into this ideal.
A similar technology in principal to hydroponics and
vertical farming is the closed plant production system
(CPPS). CPPS is like an artificial greenhouse, with on
average ten layers of plants being grown indoors using
artificial light. However, unlike hydroponics, the plants are
grown in soil. Compared to a similarly sized standard
commercial greenhouse, CPPS with ten layers can increase
productivity by fifty to sixty times [32]. This is due to the
use of artificial lighting, as it allows for more harvests,
increased quality of plants, closer spacing of plants and
multiple layers.
Currently, CPPS is at a fully commercial state, utilising
autonomous irrigators [32]. The main benefit is for
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greenhouse grown fresh produce, such as lettuce and for
plants that are initially grown in greenhouses and then
replanted in the field. In theory, artificial lighting could be
used for growing any crop, but with larger crops,
depending on the height of the building, layers would
decrease, and harvesting becomes an issue.
5.6 Energy Independent Farms
The idea of farms that are completely self-sufficient in
energy use and production is an attractive proposition.
Research was conducted by the Swedish University of
Agricultural Sciences looking at this idea [31]. The
research investigated using ley or straw; a residue left over
from arable production. The residue was put through an
anaerobic digester to produce biogas; this was either
refined to make biofuel or used in a gas turbine generator
to satisfy the electricity requirements of the farm. The
report states that all the energy requirements of the farm
could be met from the straw and ley residues of 24% and
13% of the farm area respectively.
The same concept could be used with other renewable
energy technologies such as solar panels, wind turbines,
hydrogen fuel cells, biomass boilers, heat sink pumps and
pyroformers. These could all be used to produce electricity
or forms of biofuel, which could be used to fulfil the energy
requirements of the farm. A realistic commercial model
could involve several farms in a local area joining together
for energy production, sharing the high initial capital
investment in one or more of the technologies.
New Holland are trialling their new hydrogen 135hp
fuel cell tractor at an energy independent farm near Turin,
Italy [17]. The farm, La Bellotta, takes the idea of
producing all the energy required on site and puts it into
practice. The site has its own 1MW anaerobic digester
(AD) on site and an 180kW photovoltaic panel plant
installed to the roofs of the farm buildings [33]. This
covers the energy requirements of the farm, and produces
an additional income of excess energy sold to the local
community. The mainstay of the farm is egg production,
although it does have organic crops and forestry, most of
which are used for biomass.
Both the examples show that energy independent farms
are a realistic proposition, providing the technology chosen
is correct for the resources and local environment. In a
truly energy independent farm, fuel efficiency is improved
by 100% due to the complete replacement of fossil fuels.
6. Precision Agriculture
6.1 Global Positioning System
The use of global positioning systems (GPS) to give precise
location coordinates is a current technology being
implemented in agriculture. Having knowledge of a
machines position enables other technologies and farming
practices such as CTF, yield monitoring, auto-steering,
auto-boom technology and GIS mapping. GPS doesn’t
improve fuel efficiency, but enables other technologies and
farming practices that do improve fuel efficiency.
The Galileo navigation system is a GPS system being
installed for exclusive European use. Whereas before GPS
relied predominately on US and Russian satellites which
are susceptible to offline periods of time in times of war.
Galileo offers free use up to a precision of one metre, but
has a commercial option for one centimetre accuracy. This
is an important development ensuring the technology can
be reliably used uninterrupted all year round. The full array
of 30 satellites is expected to be completed and launched by
2019 [18].
6.2 Geographic Information System Mapping
Geographic information system (GIS) mapping is an
enabler to other precision agriculture technologies and
forms the basis for which most of them operate. Data from
different sensors and GPS coordinates provide the
information input to be plotted on mapping from satellite
or aerial imagery; this information is often shaded in
different colours according to a pre-set scale. This allows
for mapping of different variables across a field. For
example, if yield was mapped from data taken from a yield
monitor during harvesting, poor yielding areas of a field
could be identified. The definition of a system is dependent
on the image resolution used to create the map and the
GPS and sensor sampling rates; the higher the resolution
and sampling, the more accurate the mapping. GIS
mapping does not improve fuel efficiency, but does enable
other technologies which do improve fuel efficiency.
6.3 Yield Monitoring
Yield monitors are a commercially available product that
records the moisture content and yield levels of grain as it
is harvested, allowing management decisions about future
trading and storage of the grain to be made. Yield GIS
maps can be produced, showing variances in yield across a
field and over harvests in different years. One way it can
improve fuel efficiency is in parts of a field where the yield
is not worth the energy put into growing the product.
These areas can be identified and not planted, thus in
doing so saving fuel and other inputs. This fuel efficiency
saving is estimated at under 5%.
6.4 Site Specific Nutrient Mapping
Site specific nutrient mapping (SSNM) is best described as
a halfway stage between standard spraying and variable
rate application. SSNM uses GIS mapping to assess the
field as a whole and fertilizer quantities are determined
from this data. The amount of fertilizer required by a rice
crop to achieve a profitable yield target is determined by
the calculated crop response to the fertilizer [8]. The
8
timing of applications is decided upon according to critical
growth stages of the crop. Each field therefore has a
different level of fertiliser application. Research [22]
conducted on rice in the Mekong Delta, Vietnam, showed
an increase in yield of between 6-10% with the application
of the SSNM technique. However it has been stated [11]
that the energy use for an SSNM system can be up to a
10% increase in comparison to a standard un-specific
spraying technique. Thus, the improvement in fuel
efficiency is negligible.
6.5 Contour Mapping
The contours of a field can have a significant effect on
energy efficiency, with corn grown on the summit or
shoulder positions of a field being 30-40% less efficient
[43]. This reduction in energy efficiency and therefore fuel
efficiency was predominately due to reduced yields, caused
by nutrient loss from slope run-off. Through GIS mapping
of these contours, areas of the field that require increased
or decreased fertiliser application can be identified to the
farmer, improving yield and subsequently fuel efficiency.
Implementing this into the practice of precision agriculture
is anticipated to be a development in the near future.
6.6 Normalised Difference Vegetation Index
Normalized Difference Vegetation Index (NDVI) is a
measure of plant growth, typically from satellite imaging.
NDVI involves looking at the greenness of plants, mapping
it and using this information for fertilizer application
through auto-boom technology [11]. The greenness of the
plant is matched to that of previous yields recorded for
different crops, identifying whether a plant needs more or
less nutrients to produce optimum yield.
It has been stated [11] that using NDVI mapping in
accordance with variable rate application can reduce
fertilizer use by 40%. Meisterling [37] states that fertilizer
production accounts for approximately 25% of energy use
in producing wheat crops using an LCA approach. Thus,
using NDVI mapping can reduce energy use by 10%,
improving fuel efficiency. NDVI and VRA combined will
also increase yield by a similar amount using auto-boom
technology.
6.7 N-Sensor
Yara, a UK based company has produced a product called
the N-Sensor. The N Sensor measures the light reflectance
of crops and relays this information back to its controller in
real time. The information is instantly processed by the
program and a suitable fertilizer application rate is selected
for that part of the field. This allows for real time variable
rate application of fertilizer without the need for a GPS
system or nitrogen application maps. However, there is the
option to add a GPS system for retrospective nitrogen
mapping of fields for future planning. Currently software
has been developed for winter wheat, winter barley, spring
wheat and spring barley, winter oilseed rape and potatoes
[54]. Software has also been developed for protein
application in cereals. N Sensors are available with their
own light source for operation at night.
N Sensor technology improves crop yields by up to 8%
[54] and reduces fertilizer use; both improve fuel
efficiency. Yield increase was confirmed by a case study on
a 440 ha arable farm in Oxfordshire [25], where yield
increased on average by 3% and the quality of the crop also
increased. The additional power required to run the sensor
has not been discussed in the company literature; using the
sensor will increase fuel consumption due to the power
required to run it. However, when balancing the increased
fuel consumption with the increased yield and fertilizer
use, it is estimated that the maximum fuel efficiency
increase from the system is 10%.
6.8 Automatic Boom & Variable Rate Application
Automatic boom (auto-boom) technology uses GIS
mapping produced from GPS data in the tractor to vary the
rate of fertiliser, pesticide and herbicide application across
independent sprayer nozzles across the sprayer. If the
sprayer has already sprayed an area, it is detected in the
mapping, and the nozzles covering that area are closed,
reducing overlap. In irregularly shaped small fields, auto-
boom technology can reduce fertiliser, herbicide and
pesticide use by 15.2-17.5% [34]. NDVI, nutrient and
contour GIS maps can also be used, with the areas
requiring additional or reduced fertilizer identified, and
spraying changed accordingly. This practice is also known
as variable rate application (VRA). The technology does
not affect fuel consumption, but when combined with
autosteer reduces overlap, resulting in improved fuel
consumption. VRA also improves yield, and therefore
improves fuel efficiency. Furthermore, VRA reduces the
amount of chemicals required, which is a high energy
product.
N-tech Industries, California, is a company that
specialises in auto-boom technology and VRA. They have
two main products; Weedseeker and Greenseeker.
Weedseeker is an automated spot sprayer that uses optical
sensors on the machine to identify weeds and spray them.
The same sensors are used on Greenseeker, but record the
NDVI values and identify the amount of fertiliser required
to achieve optimum yield for any particular spot in the
crop. Weedseeker and Greenseeker make substantial
savings on the use of weed killer and fertiliser respectively,
and the latter actively improves yields. By combining the
benefits of reduced chemical use, improved fuel
consumption through reduced overlap, and an increase in
yield, an estimate in fuel efficiency improvement is given
at approximately 20-25%.
An alternative technique for reducing pesticide usage
during spraying operations is controlled droplet application
(CDA). This technique was first introduced by the spraying
9
company Micron in the 80s. CDA works by providing a
gravity supply of chemicals to the sprayer nozzle, which
creates identically sized spray droplets by spinning the
nozzle through the use of a battery powered motor [38]. By
having the correct sized droplets, substantial savings on
pesticide use can be made. This technology has become
widely used in handheld fertiliser applications, but could
be used more in automotive applications as an alternative
to pressure nozzle spraying. Concerns have been raised
about vortexes being created behind tractors when fine
droplets are used. If CDA and VRA could be combined,
substantial reductions in chemical use could be achieved,
resulting in increased fuel efficiency.
6.9 Automatic Steering Systems
Automatic steering (autosteer) systems use a GPS in the
machine to plot a path for the vehicle to follow. This
enables the operator to concentrate on the implement and
the operation it is conducting, improving accuracy, saving
time, reducing overlap on spraying, and improving
machine efficiency. When combined with turning
algorithms for the ends of the field [6], efficiency is
improved further as the operator only has to manage speed
settings and the implement.
John Deere AMS (Agricultural Management Systems)
offer a full range of auto-steer systems, from minimal auto-
steer to fully automated systems where no driver input is
required for steering [28]. These automated systems reduce
driver error and pass overlap, resulting in improved fuel
efficiency. Other companies such as Trimble, Case New
Holland (CNH) and Ag Leader also offer similar systems.
These systems are currently on the market and ready to
use, but uptake is slow due to cost, reluctance to change,
and the reliability of GPS systems.
Autosteer is also an enabler for future fully autonomous
unmanned ground vehicles (UGVs). These vehicles are
already used in the military sector, an example is the
Israeli Guardium UGV [20], which is set a patrol route to
follow using GPS, but also has additional sensors which
allow it to react to obstacles or unforeseen circumstances.
These sensors are a combination of imaging, laser and
radar. This technology could be transferred to the
agricultural sector to enable an autosteer tractor to avoid
obstacles such as electricity pylons or mid-field ditches.
In a case example from a 1050ha arable farm in Essex,
UK, it was stated that over three cultivation passes and
three drilling passes of the land, a total of 200ha of
overlapping was eliminated [24]. This represents
approximately a 3% improvement in fuel efficiency. This
was a large farm; with smaller or irregularly shaped fields
the amount of overlap will be higher. Combining this with
the potential benefit from turning algorithms and the
increased accuracy in which the driver can conduct
operations, leads to a prediction in fuel efficiency
improvement of between 5-15%.
7. Other
7.1 Varying Machine Size
The current tractor design trend has seen an increase in
tractor size to improve operation efficiency. However,
larger, heavier tractors use proportionally more fuel and
cause unwanted side-effects such as soil compaction. It is
anticipated by agricultural companies and researchers [21,
51] that the future of agriculture will involve smaller, fully
autonomous unmanned tractors. These tractors have the
benefit of reducing soil compaction, and use less fuel.
Scientific principles show that the force required to move a
tractor, is equal to mass multiplied by acceleration, with
implements and rolling resistance acting as proportional
resisting forces against the tractor. With a smaller tractor,
the forces required are reduced due to reduced mass,
rolling resistance, and smaller implements. Furthermore,
smaller more efficient engines could be utilised.
The drawback is that more passes have to be completed
by the tractor to cover the same field area. Research is
required to establish whether smaller tractors with more
passes are proportionally more fuel efficient than larger
tractors with fewer passes. It is anticipated that the future
design of autonomous tractors will be dependent on the
operation, resulting in a variety of different size
autonomous vehicles. Currently it is unable to quantify the
impact size has on fuel efficiency.
7.2 Machine Maintenance
Machine maintenance can have an impact on fuel
efficiency; a well maintained machine will be more
efficient. By carrying out regular maintenance such as
maintaining the correct oil level, changing oil at the
required distances and replacing filters the engine will run
cleaner and will require less fuel to achieve the same
power. It is a benefit that has been importantly advertised
to agriculture for a long time now. This awareness drive
should continue to ensure the importance of maintenance is
recognised. It has been stated that correct machine
maintenance can reduce fuel consumption by 5-15%
compared with a badly maintained machine [2].
7.3 Implement Travel Speed
Selecting the wrong implement travel speed is another
preventable cause for poor fuel efficiency. Each implement
will be designed a different way, therefore will have
different optimum operating speeds. Kichler [30]
researched operating speed for two different tillage
implements. The results showed that operating speed had a
large effect on fuel consumption, in one case a 115%
increase in fuel consumption. The results also showed that
a slower or faster speed did not necessarily result in higher
or lower fuel consumption; but rather it depended on how
the implement was designed. Thus, if looking to reduce
10
fuel consumption and increase fuel efficiency, an optimum
speed should be chosen for the implement according to the
manufacturer’s specifications. However the trade-off
between productivity and fuel consumption must be taken
into account. The improvement in fuel efficiency depends
on the implement and cannot be quantified for the report.
7.4 Lightweight Materials
Lightweight materials, similar to those used in the
automotive sector, are beginning to be introduced to the
agriculture sector. It has been stated [35] that lightweight
aluminium alloys are being used for machine components
where weight reduction is critical. An example given was
the KRONE row independent maize header for the Big X
forage harvester; cast aluminium gear housings are used
for the different header drives. This saved about 120kg,
enabling a larger header, in this case fourteen rows;
without this modification the weight transfer of the rear
axle would be too large.
Another set of lightweight materials that will have a
large impact is the use of composites such as carbon and
glass fibres. The body panels of many agricultural
machines are made using glass fibre [35]. Other materials,
such as metal-ceramic composites, will slowly be
introduced into the agriculture sector as their use increases
in the automotive sector. Lighter machines that are the
same size as existing machines, retaining similar
performance, will improve fuel efficiency. Quantifying the
effect lightweight materials could not be achieved for the
report, as it would involve investigating every machine
component.
8. Forestry Specific
8.1 Shift Towards Energy Production
Due to the increasing cost of fossil fuels, there has been an
increase in demand for wood to be used as biofuel across
Europe. As an example of this increase in demand for
biofuel, it is anticipated that by 2017 the demand for wood
fibre in Britain will be fifty million tonnes [14]. However,
Britain currently only has the capacity to produce twenty-
three million tonnes. This leaves two options to make up
the shortfall in supply; importing wood from other
countries such as Canada, or increasing the supply.
This move towards energy production has benefits for
trying to improve fuel efficiency, but does have a negative
impact on the timber sector. Energy produced from
woodfuel is considered to be almost carbon neutral, as trees
use the carbon in the atmosphere to grow. Thus, replacing
fossil fuels with woodfuel will result in an improvement in
fuel efficiency in sectors outside of forestry. However, the
timber sector still needs a supply of wood for construction,
which is being threatened by this move to energy
production. This improvement in fuel efficiency in the
energy production sector is countered by the argument that
importing wood from abroad is not fuel efficient.
The alternative of increasing wood fibre supply has led
to substantial research into the use of energy crops such as
miscanthus, trees with accelerated growth such as
eucalyptus, the use of crop residues and looking again at
short rotation coppice (SRC). Each option has a major
disadvantage; energy crops challenge food security, trees
with accelerated growth are killed by harsh frosts, using
crop residues stops nutrients in the residue going back to
the soil and SRC isn’t financially feasible.
Establishing the effect this change in forestry practice
has on fuel efficiency is difficult, and the time was not
available to calculate this for the report. However, it is
definitely having an effect in the energy production sector.
8.2 Harvesting Methods
Figure 8.1 Midfield & Standard Harvesting (Source: Mederski, 2006)
Varying harvesting methods can have an impact on fuel
efficiency. A study [36] showed that by using a midfield
operation in thinning and using wider spaced skid roads,
productivity could be improved. Figure 8.1 compares the
midfield method and the standard method typically used
for harvesting operations. By felling trees towards the skid
roads, using a harvester for trees within reach of the skid
road and following up with a forwarder to collect the trees,
productivity was improved by 11-27% for the forwarder
11
and 30-33% for the harvester. Thus fuel efficiency
improved by the same amount. The machinery became
more productive with this method as the age of the trees
was increased. Furthermore, by using a chainsaw instead of
a harvester for the felling of about half of the trees, fuel
efficiency was increased further. Using this midfield
method of harvesting could improve fuel efficiency by
approximately 10-40%.
John Deere Forestry has produced a system called
Timberlink for their harvesters and forwarders. The system
measures productivity and fuel economy, showing the
operator how to optimise the two whilst they are harvesting
[29]. The information is recorded for management
purposes, and operators who are efficient and productive
are rewarded, whilst those that aren’t can be retrained
using the techniques of the efficient operators. This is
similar to a yield monitor on farming machines, and
increases yield through management of technique. To
quantify this fuel efficiency improvement is difficult due to
variation between operators and management practices.
8.3 Woodchip Drying
Actively drying woodchips is an area within the forestry
sector that would benefit from structure. From previous
conversations with members of the Technical Development
department of the UK Forestry Commission’s research
arm, it was stated that there is no recommended or proven
optimum method for actively drying woodchips. Currently
it is done as seen fit by woodchip producers, with little
regard or knowledge for fuel efficiency. Woodchips are
dried to improve their calorific value for combustion by
reducing moisture content.
A report commissioned into woodchip drying [19] stated
that a fuel efficient method of woodchip drying had been
introduced to a biomass power station in Sweden. The
plant used the heat lost through thermal inefficiencies in
the biomass generator to actively dry the woodchip supply
for the generator. In this example fuel efficiency would be
improved by 100% as no fossil fuels are used during the
drying process. Furthermore, by drying the wood the
calorific value of the chips was also increased. Similar
improvements in the rest of Europe should be a priority in
this sector.
9. Survey Results
9.1 Priority & Recipient Selection
Each of the topics reviewed in the report were prioritised
by their potential to improve fuel efficiency and the other
benefits they could give to agriculture. This priority table
and when the author anticipates that the topics will be
commercially introduced and become commercially normal
is available as Appendix A. The eight highest priority
topics were identified, and an expert or researcher for each
of the topics was approached. A survey was sent to each of
these recipients, and the results of which are summarised
in this section. Results for the topic of direct drilling and
minimum tillage were not obtained due to the topic having
been extensively covered in agriculture. Results for the
topics of electric vehicles and hydrogen fuel cells were
unavailable due to research conducted in these areas being
commercially sensitive; the majority of research in these
topics is conducted at a commercial level. To compensate
for this loss of survey topics, a general survey on fuel
efficiency in agriculture was sent to an expert in the topic.
The full survey results are available as Appendices C - H.
9.2 Precision Agriculture
Professor Khosla, President of the International Society of
Precision Agriculture was approached for his opinion on a
set of questions regarding the agricultural practice of
precision agriculture (PA). Professor Khosla gave very
detailed responses to the questions asked of him, thus this
is merely a summary of what he said.
When asked about the affect PA can have on fuel
efficiency Prof. Khosla states that fuel efficiency has been
improved by farmers reducing the quantity of operations
they have to conduct in the field through the aid of PA.
However, he states individual technologies and practices
have not been evaluated by the group regarding fuel
efficiency. He also states that the time period for which PA
becomes a normal agricultural practice varies upon the
extent to which it is practiced; in the US approximately
>75% of farmers use some form of GPS during operations,
whereas very few are practicing variable rate application in
comparison. Prof. Khosla believes PA will become more
widespread sooner than most people anticipate due to the
falling cost of technology combined with the rising cost of
produce.
Prof. Khosla states that determining the most important
tool for PA is very difficult due to the variability between
different farms, with no ‘one size fits all’ option available.
However he does state that the ability to predict water and
nutritional needs for different crops is important, but is
currently restricted by available sensing technology. At the
end of the survey he states that this technology and robotic
automation are two of the most important areas requiring
development and research.
When asked what barriers are hindering the introduction
of PA to agriculture, Prof. Khosla detailed the three areas
of education and extension, compatibility and portability,
and expectation and realisation. The first two areas have
been issues in other technologies and practices. A detailed
explanation of each is available in Question 5 of the full
survey, available as Appendix C.
Regarding the period of time it would take for a farmer
to repay the investment in PA from the results achieved,
Prof. Khosla indicates that this is variable on the
technology being utilised. Some technologies, such as
variable rate application, will pay for themselves in the
12
first year, whilst others may take longer. The size and
physical properties of the farm will also affect the impact
of PA practices and technologies.
Regarding the opinion that PA is too complex, Prof.
Khosla completely agrees with this and is sympathetic to
frustrations farmers have regarding new complicated
technology. He states that this is due to PA still being in its
infancy and that this will improve over time.
Finally Prof. Khosla states that the big uptake in PA in
the US has been a result of consolidation of farms. Farm
sizes have grown significantly with the average farm size
in Colorado currently over one thousand acres. These large
farms are well suited to PA and find it easier to swallow up
the initial outlay on PA technology through a scale up of
the benefits. In many parts of Europe, with the exception of
parts of Eastern Europe this is not the case, with smaller
farms still prevalent. This issue can be negated by sharing
equipment between farms, reducing the cost of investment.
The full survey results are available as Appendix C.
9.3 Hydroponics & Vertical Farming
Dr. Dickson Dispommier from Columbia State University,
New York, was approached as a one of the leading
international experts in vertical farming. It was his belief
that vertical farming would become a commercially normal
practice and produce a large proportion of cities food
requirements within ten years. He goes on to state that
there are already commercial vertical farms in existence
and that there are no barriers hindering the introduction of
vertical farms. Taking this information into account, and
the potential yield improvements stated in Section 5.5, it is
the author’s opinion that this practice will become
widespread within the ten years stated. The area which Dr.
Dispommier indicates needs further development to aid the
introduction of vertical farming is in the field of light-
emitting diode (LED) efficiency.
Furthermore, four commercial examples of vertical
farming were stated or mentioned in the survey, with Dr.
Dispommier being involved as a consultant for the latter
three. These were; the Plantagon seventeen story vertical
farm in the Swedish city of Linkoping, a three story
building in the South Korean city of Suwon, the four story
Nuvege building in the Japanese city of Kyoto and the
PlantLab Company in the Netherlands. The Plantagon
seventeen story building in Sweden is set to become the
international flagship building for vertical farming. The
full survey is available as Appendix D.
9.4 Energy Independent Farms
Mr Luca Remmert, owner and farm manager of La
Bellotta, Turin, Italy, was approached due to La Bellotta
being one of very few farms that are completely energy
independent. There were some language issues, but the
information provided by Mr Remmert was very insightful
into how these farms can become a reality. He states that in
Italy, as with many countries in Europe, the farms are not
big enough to merit each producing their own energy. This
problem could be solved by the introduction of a sharing
system between several farms, similar to how farms
currently share machinery.
Mr Remmert also states that the farm has broken even
on the initial investment it made into the energy
production systems it acquired. The photovoltaic panels
were introduced in 2008, and the anaerobic digester in
2010. The next technology planned to be introduced on the
farm is a hydroelectric power generator to make use of the
river flowing through the farm. It is important to note that
the ideal energy generating technology for a farm is
dependent on the local environment and the produce of the
farm. Having detailed research to what technology is best
for the situation is something that Mr Remmert specified
as important.
In a separate email with Mr Remmert, he explained how
the farm maintains its organic status, even though the
faecal waste from the hens on the farm is fed into the
anaerobic digester as opposed to being spread across the
fields. The digestate, the waste product from anaerobic
digestion, has very good fertiliser properties, thus is used
instead. This is a mixture of digested crop residues and
faecal waste from the hens. The full survey is available as
Appendix E.
9.5 Controlled Traffic Farming
Mr Tim Chamen, Director of CTF Europe Ltd. was
approached due to his high level of expertise and
experience in the area of controlled traffic farming. Mr
Chamen stated that a fuel saving of 35-40% can be made
when switching to CTF with a minimum tillage or direct
drilling approach, and that CTF will become common
practice in 15-20 years. Mr Chamen goes on further to
state that the main barriers to the uptake of CTF is an
intransigent mind set by many farmers, incompatibility of
current machinery and the perceived high cost of
conversion. In relation to this he states that a fundamental
change in machine design is currently under development
and is likely to be exhibited at Agrictechnica 2013.
Furthermore, Mr Chamen states that the period for full
repayment in the conversion investment varies between
twelve months and ten years dependent on the level of
investment required in new machinery and the size of the
farm. Regarding the perception that CTF is too complex, it
was stated that this problem can be overcome through the
demonstration of farms that have converted to farmers who
are interested in conversion. Proof of improvement will be
the main driver for increased CTF popularity in Europe.
Finally Mr Chamen states six priorities for future
research for the topic of CTF, these were: management of
the traffic lanes, management of non-trafficked beds and
the possibility of designer soils, the extent of which CTF
reduces nitrous oxide emissions, effective control of slugs
and snails in low input systems, whether converting to
13
CTF simultaneously with direct drilling removes the issues
of direct drilling, and the benefits and extent to which CTF
could reduce tillage in root vegetable production. The full
survey is available as Appendix F.
9.6 Automatic Boom & Variable Rate Application
Mr Tom Bals, Chairman of the Micron Group, a UK
spraying company was approached for his views on
variable rate application (VRA) and additionally for
further information about the company’s controlled droplet
application (CDA) technology. Mr Bals states that VRA is
not as new a technology advance as it would seem, with
Micron developing a VRA system in the middle of the
1990s. Due to the continued innovation in their own CDA
technology, the VRA development was stopped due to
research and development costs. Mr Bals also states that it
is anticipated that VRA will become a standard practice in
some form by 2025 on the majority of large arable farms in
the UK. It is the author’s opinion that a similar estimation
could be given for the rest of Europe.
Mr Bals continues by estimating that VRA can save
between 0-70% in chemical use during spraying
operations. Furthermore, CDA could save between 0-95%
in chemicals in herbicide and pesticide use. Using the table
given in Appendix B, VRA therefore could improve fuel
efficiency by 0-17.5%, and due to fertilisers not being
applied using CDA, the CDA technology could improve
fuel efficiency by approximately 0-16%. Further
improvement in fuel efficiency will be obtained from VRA
technology due to a reduction in the number of passes a
machine has to make. Mr Bals went on to make
reassurances of how Micron is developing shielding to
overcome the issue of vortexes behind sprayers when fine
droplet sizes are used. Finally he stated that to improve the
popularity of VRA, simple and cheap mapping needs to be
researched and developed to make the technology more
accessible. The full survey is available as Appendix G.
9.7 Fuel Efficiency In Agriculture
Mr Andres Annuk from the Department of Energy
Engineering, Estonian University of Life Sciences, was
approached for a general opinion on fuel efficiency in
Agriculture. He is primarily involved in research for the
sustainable energy sector which has strong links to many of
the technologies and practices investigated by the report.
Mr Annuk gave a conservative estimate for fuel efficiency
improvement in agriculture of 2%, 3% and 5% for the next
three, five and ten years respectively. This falls short of the
European target of 20% reduction in energy use by 2020.
Mr Annuk also stated that in his opinion the key to
improving fuel efficiency in agriculture is to improve
ground treatment, by reducing the use of fertilisers and
ensuring nitrogen is not lost from the ground. He also
stated that optimising the distance travelled by machinery
and the logistics system of moving produce is important.
Furthermore Mr Annuk stated that cooperation from local
producers was an issue stopping the improvement of fuel
efficiency. To solve the problems hindering the
improvement of fuel efficiency he stated that more
resources are required to inform producers about energy,
fiscal policies require change and new technologies need to
be developed.
When asked what technologies or practices will be
prominent in the future of agriculture in Europe, Mr
Annuk stated that energy production will be more
decentralized, with energy produced being utilised nearby.
Also he stated that a smaller proportion of energy will be
used with the use of different tillage systems. Furthermore
he anticipated that logistics would be developed, so that the
movement of produce will be designed around the most
energy efficient solutions. Finally, Mr Annuk was asked
what should be the research priorities for improving fuel
efficiency in agriculture. He responded with the following
priorities; development of new technologies and materials,
integration of different technologies together, development
of smart electricity grid systems to cater for local energy
production, energy storage, and new technologies for
obtaining liquid biofuels from local resources. The full
survey is available as Appendix H.
10. Discussion
From the information gained from the literature review, it
is the author’s opinion that a shift in focus should be
implemented away from the majority of research funding
being invested in the development of higher efficiency
diesel engines. Only a small percentage increase in fuel
efficiency can be gained from improving diesel engines,
whereas much more significant improvements can be made
in other aspects of agriculture. However, stop-start
technology and the use of new catalysts in petroleum diesel
are potential quick-win solutions to improve fuel
efficiency.
The research priority table in Appendix A showed that
the greatest gains in fuel efficiency can be achieved
through changing farming practices. These were practices
that are all currently commercially achievable, but are just
waiting for the agriculture sector to start implementing
them in larger quantities. The majority of changes in
farming practice are available for existing arable and fresh
produce farmers, with the exception of vertical farming,
which will take substantial investment that is more likely
to come from new business ventures. The future of
agriculture is anticipated to be a combination of all these
farming practices; how long until this becomes reality in
Europe is dependent on the sector’s ability to embrace
change.
Substantial improvements in machine fuel efficiency can
be achieved from the renewable energy sector, with the
hydrogen fuel cell and electric motors being important to
this success. However, these will not become successful
14
and widespread until alternative electric motors become
available, due to there not being enough copper to mass
manufacture electric motors.
The topic of precision agriculture was looked at in detail
due to the high quantity of technologies being developed
that will have a role to play in improving fuel efficiency.
The leading advance in technology to improve fuel
efficiency was the use of auto-boom technology and VRA.
Different packages are currently commercially available for
VRA from various manufacturers. Future systems will see
the majority of the precision agriculture technologies
combined into one easy to use unit for the operator. The
development of such a unit is being developed by large
precision agriculture companies in the US, and to a slightly
reduced state by Trimble in the UK. It is the author’s
opinion that the majority of precision agriculture
technologies will only be used by farmers if they become
automated, or at least partially automated and easier to use.
Something else that can be done in the present is to
further publish and make farmers aware of the importance
of machine maintenance. This has been made common
knowledge, but can be forgotten when farmers are busy.
This is also important in the forestry sector for any
mechanised machinery.
In the forestry sector, practice change is pushing the
sector towards using wood for woodfuel to produce energy.
As a result, the demand for wood fibre will soon outstrip
supply. Whilst using sustainable energy sources such as
wood to produce energy should be commended, as it
improves fuel efficiency, other sources of supply need to be
established to ensure huge quantities of wood fibre are not
imported into the country. Another important improvement
in the forestry sector is to establish the best practice for
actively drying woodchip.
11. Conclusions
In conclusion, the farming practices of precision
agriculture, controlled traffic farming (CTF), direct
drilling and minimum tillage, energy independent farms
(EIF), hydroponics and vertical farming were established
as priority topics for research and development. As were
the technologies of hydrogen fuel cells, electric vehicles,
automatic boom and variable rate application. Fuel
efficiency improvement in the priority topics was high,
ranging from a 20% fuel efficiency improvement in
automatic boom technology and variable rate application,
to an improvement in fuel efficiency of over 100% in
hydroponics and vertical farming when compared to
current arable farming. The priority topics ranged from
being commercially normal practices from the present with
direct drilling and min-till, to fifteen years or more in the
case of hydrogen fuel cells, CTF and EIF.
Certain topics outside the top eight should be
investigated further, due to their ability to provide a fuel
efficiency improvement of over 20%. These topics were
alternative methods of woodchip drying in the forestry
sector, hybrid vehicles and contour mapping. The first
could provide fuel efficiency improvements of up to 100%.
Contour mapping could be straightforwardly integrated
into the agriculture sector. These topics are recommended
for further research and development.
15
Appendices
Appendix A Technology & Practice Evaluation Tables
Each of the practices and technologies were scored in Table A.3, according to the fuel efficiency improvement they could offer
and the other improvements they could provide to agriculture, as scored in Table A.1 and Table A.2 respectively. The fuel
efficiency improvement was taken from the literature reviewed when possible or calculated by the author, in some cases a
combination of the two was used and as such all scoring of fuel efficiency improvements are estimations and should not be used
as precise figures. If it was not possible to establish the fuel efficiency improvement, a score of N/A was entered in the table.
The other improvements to agriculture in Table A.2 led to a scoring of one point for each improvement a technology or practice
could offer, these scores were based upon the author’s opinion. Table A.4 shows the technologies and practices sorted by order
of priority according to the score they received, along with an estimation of when the topic would be commercially introduced
and when it would become commercially normal.
Table A.1 Fuel Efficiency Improvement Scoring System
Fuel Efficiency
Improvement (%)
Relating
Score
0 0
0-5 1
5-10 2
10-15 3
15-20 4
20-30 5
30-40 6
40-50 7
50-75 8
75-100 9
100+ 10
Table A.2 Other Improvements to Agriculture Scoring System
Other Improvements to Agriculture
Emmissions Reductions
Improved Power
Improved Torque
Improved Yield
Reduced Soil Compaction
Labour Reduction
Improved Accuracy
Enabling Technologies/Practices
Renewable Energy
Time Saving
Reduces Cost (Exc. Fuel)
Improved Food Security
Improved Energy Security
16
Area Technology / Agricultural Practice
Fuel Efficiency
Improvement
Other
Improvements
Score
(Max 23)
Priority
Emission Control 0 1 1 31
Piezo Injectors in Common Rail
Diesel Engines
1 2 3 24
Stop Start Technology 2 1 3 23
Engine Power Management 2 2 4 19
Catalyst in Petroleum Diesel 1 0 1 30
Biodiesel 4 4 8 15
Fuel From Pyrolysis N/A 3 3 28
Hydrogen Fuel Cells 10 414 4
Hybrid Vehicles 5 3 8 14
Electric Vehicles 10 313 6
Precision Agriculture 9 7 16 1
Controlled Traffic Farming (CTF) 7 5 12 7
Direct Drilling & Minimum Tillage 9 5 14 5
Hydroponics & Vertical Farming 10 515 2
Field & Tractor Course Design 4 4 8 13
Energy Independent Farms 10 414 3
GIS Mapping 0 3 3 25
Yield Monitoring 1 2 3 26
N-Sensor 2 4 6 17
GPS 0 2 2 29
Autosteer Systems 3 6 9 12
Site Specific Nutrient Mapping 1 3 4 20
Auto-boom Technology &
Variable Rate Application
5 6 11 8
NDVI 2 4 6 18
Contour Mapping 5 4 9 11
Varying Machine Size N/A 4 4 21
Machine Maintenance 3 4 7 16
Implement Speed N/A 1 1 32
Lightweight Materials N/A 3 3 27
Change to Energy Production N/A 3 3 22
Harvesting Methods 6 4 10 10
Active Woodchip Drying 9 1 10 9
Forestry
Other
Diesel Engines
Alternative Fuels
Precision
Agriculture
Changing Farming
Practices
Table A.3 Practice and Technology Scoring
17
Technology / Agricultural Practice
Score
(Max 23)
Priority
Commercial
Introduction (Years)
Commercial
Norm (Years)
Precision Agriculture 16 1 0 3
Hydroponics & Vertical Farming 15 2 0 10
Energy Independent Farms 14 3 0 15
Hydrogen Fuel Cells 14 4 5 15
Direct Drilling & Minimum Tillage 14 5 0 0
Electric Vehicles 13 6 5 10
Controlled Traffic Farming (CTF) 12 7 0 15
Auto-boom Technology &
Variable Rate Application
11 8 0 10
Active Woodchip Drying 10 9 0 10
Harvesting Methods 10 10 0 5
Contour Mapping 9 11 3 5
Autosteer Systems 9 12 0 3
Field & Tractor Course Design 8 13 0 3
Hybrid Vehicles 8 14 3 5
Biodiesel 8 15 010
Machine Maintenance 7 16 0 0
N-Sensor 6 17 0 3
NDVI 6 18 0 5
Engine Power Management 4 19 0 3
Site Specific Nutrient Mapping 4 20 0 5
Varying Machine Size 4 21 10 15
Change to Energy Production 3 22 0 0
Stop Start Technology 3 23 3 5
Piezo Injectors in Common Rail
Diesel Engines
324 0 5
GIS Mapping 3 25 0 5
Yield Monitoring 3 26 0 3
Lightweight Materials 3 27 0 0
Fuel From Pyrolysis 3 28 10 15
GPS 2 29 0 3
Catalyst in Petroleum Diesel 1 30 3 5
Emission Control 1 31 0 0
Implement Speed 1 32 0 0
Table A.4 Practices and Technologies Priority Sorted with Estimated Commercial Introduction and Norm
18
Appendix B Chemical Use Energy Calculations
Determining the fuel efficiency improvement from reduced use of chemicals required the use of an LCA of a typical
agricultural production cycle. A report investigating the lifecycle of wheat by Meisterling et al. [37] was used as the example.
Using conventional growing techniques including chemical application, it was stated that chemical production accounts for
approximately 25% of all energy used in an agriculture production cycle. Table B.1 shows what a percentage reduction in
chemical use translates to as an improvement in fuel efficiency.
Table B.1 Fuel Efficiency Improvement for Chemical Saving
Chemical
Saving (%)
Fuel Efficiency
Improvement (%)
10 2.5
20 5.0
30 7.5
40 10.0
50 12.5
60 15.0
70 17.5
80 20.0
90 22.5
100 25.0
19
Appendix C Precision Agriculture Survey
The survey results from Professor Khosla, President of the International Society of Precision Agriculture.
1. What research are you conducting or have conducted in the area of precision agriculture?
The main focus of my Precision Agricultural Laboratory at Colorado State University has been on quantifying spatial variability
in soils for the purpose of precision nutrient management. However, in more recent years (~ past 7yrs), in addition to soils, we
have been involved with crop sensing for in-season precision nutrient management and more recently, Precision Water
Management as well.
2. What improvements in fuel efficiency (percentage) would you expect different precision agriculture techniques to give to an
average arable farm?
Well that depends on the operation. For operations today, farmers have been able to couple several operations into one and
hence have cut down on their frequent trips to farm fields. Quite logically in those situations fuel efficiency has gone up. I am
not so sure about other methodically evaluated changes in fuel efficiency due to precision agricultural practices, something our
group has not looked at.
3. In your opinion, how long will it take before precision agriculture becomes a normal farming practice? i.e. when a large
proportion of arable farms are using this practice.
It is happening today as we speak. However, different people perceive precision agriculture differently. A great majority
(approximately > 75%) of farmers in the United States are using some form of GPS equipped guidance systems on their farm
tractors. Is that Precision Agriculture? Absolutely!! But are they all practicing variable rate seeding, nutrient, water and
pesticide management, of course not. Are they all doing grid sampling, or management zones, or remote-sensing, or crop
sensing, no they are not and we are not there yet. It will take additional time for us to be there. Price of technology is coming
down and price of farm produce is heading up, with this combination we will get their sooner than what we think.
4. There are quite a few different techniques and technologies attributed to precision agriculture, which in your opinion is
most important to the agriculture sector?
That is a tough question, because we do not have a technique or technology in place that is “one size fits all”. There is a r eason
why Precision Agriculture is also referred to as “Site-Specific Farm Management” what works in one farm, in one field doesn’t
necessarily mean is good for all other farms and fields. The type of operation, scale of operation, scale of variability, resources
available and many other factors govern what is the most important input/technique or technology that would be most
important for each farm. Having said that, ability to accurately predict crop water and nutritional needs to maximize yield and
minimize losses would be the one we need to continue to work on till we get there. This will require next generation of crop
canopy sensors that can differentiate crop stresses (pest and diseases infestation, versus nutrient deficiency, versus water stress,
etc.) Even within nutrients our ability with current sensors is really limited. We do not have technology to differentiate nitrogen
stress from iron stress or potassium stress and so forth. We need next generation of sensors that would help us achieve that
level of accuracy.
5. What barriers are there stopping the further use of precision agriculture in the agriculture sector?
There are many things we need to overcome for accomplishing further adoption of precision agriculture. I will share a few:
(i) Education and Extension: If you look back, you may realize that too much space-age technology was handed over to
agriculture sector in a short span of time. Agricultural institutions, Colleges and Universities were caught off-guard and
were not prepared to offer education and training on new agricultural technologies. This has changed over the years,
however, more needs to be done to further strengthen University faculty and resources who would impart precision
agricultural education to meet the growing need. This will require investment in the agricultural education. Likewise we
need to extend this knowledge to “agents of change - technology transfers”, i.e., extension agents, crop advisors, crop
consultants, and others. Some of this is happening right now, but it is a colossal task to bring everybody up to speed.
20
(ii) Compatibility and portability: Often times we hear the frustration from farmers that one piece of technology on their
equipment would fail to communicate with other, which limits their ability and choices to expand and be creative with the
available resources. That needs to change. Agriculture industry needs to become more transparent and allow compatibility
across brand names and platforms.
(iii) Expectation and realization: We must realize that PA has been around only about 20 years that may seem like a long
time, when really it is not. In many cases “technology is ahead of science. For example, we now have precision irrigation
Pivot sprinkler system that can vary the rate of water application at every nozzle level. What we do not have is the science
to make a decision on how much, when and where in field water needs to be applied such that it synchronizes with the
spatial and temporal crop water use. We need time to research, develop algorithms, and evaluate current technologies to
take out the guess work and frustration associated with working with new technologies.
6. What technology needs to be developed or changes need to happen to get past these issues?
I think, I have addressed those in my response to your previous question.
7. In your opinion, how many years would it take for a farmer to be repaid by the benefits of an investment in precision
agriculture systems for their farm?
That is a great question. It depends on what component of precision techniques and technologies they are planning to acquire
and use on their farm. The answer would vary. For example, agricultural retailers that are offering “precision nutrient
management” practices to the farmers (i.e., grid soil sampling, management zone delineation, in -season crop sensing, variable
rate nutrient application, etc) claim that most farmers not only could repay for these services they would benefit significantly
(with savings in fertilizers and increase in yields) in the same year. Likewise, I have heard farmers telling me (depending upon
the size of operation) that their investment in auto-pilot system was paid off in first year itself, because of the reduction in stress
and fatigue, number of acres they were able to cover in shorter time span, reduction is skips and overlaps, etc.
8. There is a general, possibly misguided opinion from farmers that precision agriculture systems are too complex, how would
you suggest is the best way to encourage farmers to change to this practice?
I would respectfully disagree with you. I believe in what farmers are saying, precision ag is indeed complex. As indicated in my
previous answers to your questions, I think farmer’s frustration is well founded. It is them who are using a slate of new
technologies and they find it difficult to get easy answers. I also believe that Precision Agriculture is young and there are
growing pains associated with precision agriculture. It will take patience, education and extension to overcome this hurdle.
9. Precision agriculture has seen a large uptake from countries such as Australia and the United States, what do you think has
driven this change?
There are a number of reasons for that. I can speak from the US perspective. We have seen a significant consolidation of our
farms in the last 60 years. Our farm sizes have grown up significantly, for example average farm size in Colorado is currently
1000 acres (~400 ha). Labor costs have gone up and hence mechanization of farms with larger machinery were logically seen
as feasible solutions to continue to farm and stay profitable. Precision techniques and technologies injected additional
capabilities for the farmers and enabled them to farm even larger acreages in the same time frame. In addition, there are
various other advantages of imbibing precision agriculture such as higher input use efficiency, increase in productivity,
profitability and overall sustainability.
10. What do you believe should be the main priority for future research in precision agriculture?
It is hard to peg on one particular aspect. We would need to work in synchrony on multiple on numerous new technologies in
area of remote sensing, water management, automation / robotics, machine vision and more. Precision agriculture is young and
is the wave of the current time. We need to nurture it so that it grows into mainstream agriculture not only for large scale
farming systems but also small scale crop production systems for less developed environments and countries. In my opinion
Precision agriculture can and will play a pivotal role in achieving global food security working closely together with soil
scientists, agronomists, agricultural engineers, ecologists and geneticist. Together we can bridge the gap in potential yield
versus attainable yields in various environments around the world.
21
Appendix D Hydroponics & Vertical Farming Survey
The survey results from Dr Dickson Despommier, Columbia State University, New York, expert in vertical farming.
11. What is your current specific research area within the topic of vertical farming?
Spokesperson
12. What impact can vertical farming have on the quantity of fossil fuels agriculture consumes and the harmful emissions
fossil fuels create?
In the USA,. We use some 20% of all fossil fuels just to farm (plow, plant, harvest, store, ship)
13. In your opinion what is the timescale for vertical farming to become a normal practice in cities across the world? i.e.
when a large proportion of a city’s food requirements are being met through vertical farming.
10 years
14. What barriers are slowing down the uptake of this technology?
Nothing. The idea has just been out since 2006 on the internet. I wrote the book in 2010 and in 2011 there were three Vfs up! I
know of several more in the planning stages or are being built. The one going up in Sweden, 17 stories tall, will become the
flagship VF of the near future.
15. Are there any particular technologies in development that are crucial to overcoming these barriers?
LED lights could become more efficient.
16. Are there any commercial projects you have been involved with or have advised that could be used as an example of what
vertical farming can achieve?
Sure. The one in Korea (Suwon), the one in Japan (Nuvege), the one in Holland (PLantLab).
17. What research topics would you suggest are most important to enable this technology to become normal practice?
Make LEDs more practical, no question!
22
Appendix E Energy Independent Farms
The survey results from Luca Remmert, owner of La Bellotta energy independent farm, Turin, Italy. Unfortunately the language
barrier caused some issues with the questionnaire. It is important to understand that Luca has made these technology
implementations under advice from experts in the sustainable energy sector and is not an expert himself. However, Luca was
very helpful and knowledgeable about his farm, and any further questions can be asked through his website contact form.
1. In your opinion how many years will it take for energy self-sustaining farms, similar to La Bellotta, to become normal across
Europe? i.e. when a large amount of farms are completely self-sufficient in terms of energy.
The European situation is very different from state to state. Not familiar with all the other reality. in Italy the problem is that
the farms are very small. It may not be a problem if the state would promote
2. Has the money invested in renewable energy technology on your farm (anaerobic digester, photovoltaic panels etc.) been
repaid in energy sales and in fuel savings? Please exclude any external funding from this answer.
Even as I expected from the business plan
3. If not, how many years do you anticipate it will take for this money to be repaid?
N/A
4. Do you think there are any major problems which are stopping energy self-sufficient farms being introduced across Europe?
I don’t understand the question
5. Is there any technology you feel needs to be developed to solve these problems?
N/A
6. You are trialling the New Holland NH2 hydrogen fuel cell tractor, how does the farm create the hydrogen required for the
tractor?
Not Yet
7. Do you have a biofuel electricity generator or boiler on site? This was not detailed on your website.
No I don’t have
8. There is a large quantity of hens at La Bellotta as your main agricultural product, have you used or considered using the
waste from the hens for energy production? Or is it used for fertiliser on the farm?
The manure is used in all digesters to produce biogas
9. Would you expect other farms to have a similar level of success as La Bellotta should they invest in becoming energy self-
sufficient? Please explain your answer.
Yes I think so, but I believe that the investment should be very well depth
10. Is there any other renewable energy technologies which you plan to add to the farm in the future?
Yes IDROELETTRICO
23
Appendix F Controlled Traffic Farming Survey
The survey results from Tim Chamen, Director of Controlled Traffic Farming (CTF) Europe.
1. What research are you conducting or have conducted on the topic of CTF?
The effects of low and controlled traffic systems on soil physical properties, yields and the profitability of cereal crops on a
range of soil types. PhD thesis, unpublished. W.C.T. Chamen, April 2011.
2. What improvement in fuel efficiency (percentage) would you expect CTF to give to an average UK arable farm? Please
estimate.
35-50% fuel saving assuming a simultaneous move towards minimal or no till
3. In your opinion, how long will it take before CTF becomes a normal UK farming practice? i.e. when a large proportion of
UK arable farms are using this practice.
15-20 years
4. What barriers are there stopping the introduction of CTF in the UK?
An intransigent mindset together with a lack of understanding by practitioners of the level of change that can be achieved
through CTF. In addition, the incompatibility and inappropriate design of present machinery for delivering efficient CTF
systems and a perceived high cost of conversion when the latter is often not the case.
5. What technology needs to be developed or changes need to happen to get past these issues?
Intransigence and perceptions will only change when farmers and growers start to realise the benefits and share their
experiences with others. Machines will also need to become more compatible and there is some evidence that manufacturers are
responding to this need. My personal opinion is that machines need to change more fundamentally, not only to deliver more
efficiently to the CTF concept, but to bring about lower production costs through a higher level of precision and flexibility.
Such a design based on the wide-span vehicle concept is currently under development and likely to be exhibited at Agritechnica
2013.
6. In your opinion, how many years would it take for a farmer to be repaid by the benefits of a full investment in a complete
advanced CTF system for their farm? Again please estimate.
The answer to this is probably as variable as are farms! Some may realise a full return on investment in 12 months, for others it
could be ten years. The latter reflects the fact that sustainable and cost-effective changes will depend where the farm finds itself
in relation to machinery replacement. An example is a 200 ha farm that only invested £2000-£3000 in wholly CTF related
changes but adopted an RTK auto-steer system to improve accuracy for potato production and a reduction of overlaps. This
farm would probably have seen a return on investment within the first year. Another farm is in a five year programme timed to
avoid or minimise any additional costs due to its conversion to CTF. A further farm realised a net saving in machinery
investment of £250,000 and from 8-17% increase in profitability when converting over a period of three years.
7. There is a general, possibly misguided opinion from farmers that installing a CTF system is too complex, how would you
suggest is the best way to encourage farmers to change to this practice?
Think and plan and in many cases the transition will actually prove to be simple. Farmers can only be encouraged to realise
this by the example of others and through more compatible equipment becoming available. Seeing is believing, so sharing
knowledge and visiting farms that have converted will be the most effective strategy for dispelling the perception of complexity.
This is not to say that there isn’t complexity involved, it’s just something that farmers have not been used to thinking about.
8. What do you believe should be the main priority for future research in CTF?
i.) Management of the cropped traffic lanes. Researching the optimisation of tillage in relation to costs, crop performance and
24
maintenance of the function of the traffic lanes to support traffic.
ii.) Management of the non-trafficked beds. What tillage if any is needed on different soils and for different crops? Can we have
a “designer” soil condition that does not get compromised by uncontrolled wheel compaction? We have never had non-
trafficked soils before so there is a great deal we need to learn in how to manage them.
iii.) To what extent does CTF reduce nitrous oxide emissions? Much research evidence suggests that soils with greater porosity
and improved drainage will reduce the risk of emissions, so does CTF actually deliver reduced emissions?
iv.) More effective slug and snail control in low input systems. The role of tillage, cover crops and novel highly targeted
precision systems.
v.) Does converting to no-till and CTF simultaneously reduce the risk of yield loss and improve the profitability and
sustainability of no-till systems?
vi.) Assuming the machinery is in place to maintain CTF through the establishment and harvesting of all crops, to what extent
can tillage be reduced in root crop production and what other benefits might be derived from a system of this nature?
25
Appendix G Automatic Boom & Variable Rate Application Survey
The survey results from Tom Bals, Chairman of Micron Group, Herefordshire, UK, manufacturers of spraying equipment.
1. How are Micron researching and developing the area of variable rate application and auto-boom technology? How can this
link in with your CDA sprayer technology?
Micron sold the first variable rate application sprayer in Europe in the mid-1990s, developed in collaboration with Silsoe
Research Institute after Micron purchased the key patents from the British Technology Group (BTG).
Micron chose to make this available with standard hydraulic pressure nozzles (using a twin line system with pneumatically
controlled valves to achieve continuous flow rate options), despite the fact that rotary atomisers are well suited to this
application due to their high turn down ratio, since we felt it was important to focus on the one key area, i.e. variable rate
application, rather than confuse the market with a double innovation. However, due to the high (ongoing and global) R&D
costs and the need for widespread agronomic advice and support (which was simply not available at the time) we didn’t carry
the project forward (although all the components of the system, including our PatchSpray controller, are still available).
2. In your opinion, how long will it take before variable rate application becomes a normal farming practice? i.e. when the
majority of farms are using this technology for spraying applications.
In the mid-1990s we thought it would be standard practice by now. We now think it will be standard practice (in some forms)
by 2025 on most large scale arable farms in the UK (majority of area rather than majority of farms).
3. What percentage of pesticides, herbicides and fertilisers can be saved by using variable rate application and/or CDA
technology?
VRA - 0 70%
CDA - 0 95% (not fertilisers)
4. Concerns have been raised about spray vortexes being created behind a tractor when fine droplets are used, what solutions
do you have or are developing to overcome this issue?
Shielding is an option we are developing e.g. see our Varidome, but we are not principally looking at high speed application to
cereals (where air-assistance/air deflection are possibly better options although large scale shields have been used in Canada
and a bluff plate in Australia). NB hydraulic pressure nozzles always produce smaller/fine spray droplets whereas CDA
atomisers can eliminate their production if required.
5. Mapping of nutrients, yield, contours, obstacles etc. can all be used as an input for variable rate application, is this
something Micron have implemented in their products or are looking at implementing?
We were not, and will not be, directly involved but we implemented maps in our PatchSpray controller that was sold with our
VRA unit.
6. In your opinion, is there any technology that needs to be developed or changed to make variable rate application accessible
and feasible to the majority of farmers?
Cheap and simple mapping/patch identification are the key ie agronomic models.
7. What do you believe should be the main priority for future research in variable rate application and auto-boom technology?
See 7 above the technology/hardware is there (and has been since we developed our VRA sprayer in the mid-1990s) NB cost
of the technology/hardware is under £10K, and the sprayer we sold recouped its costs in less than two years just on fertiliser
savings.
26
Appendix H Fuel Efficiency In Agriculture Surveys
The survey results from Andres Annuk, Department of Energy Engineering, Estonian University of Life Sciences.
1. What research are you conducting or have conducted on the topic of fuel efficiency in agriculture?
My main activities are on the field of distributed energetics. Distributed energetics allows more efficient usage of local energy
resources as wind, solar, geothermal and solid biofuels. One topic is cultivating and usage reed canary grass as energy hay.
2. What improvement in fuel efficiency (percentage) would you expect in the next three, five and ten years? Please estimate.
2%, 3% and 5%. This is enough conservative estimation.
3. What changing agricultural practices or new technologies do you think are most important for improving fuel efficiency?
Reducing energy consumption on soil treatment, for fertilizers especially for nitrogen. More nitrogen to turn back from
agricultural coproduce. Reduce nitrogen evaporation using state of art technologies. From biogas production is possible to get
back fertilizers. Optimizing transport distances.
4. What problems are there stopping the improvement of fuel efficiency in Europe?
One problem is insufficient cooperation of local producers. The legislation is enough supported of improvement energy
efficiency in agriculture.
5. How do you think these problems can be solved?
More turn resources to inform of energy topics. Fiscal policies are need to revise. Develop new technologies.
6. What agricultural practices or technologies do you think will be the future of agriculture in Europe?
Energy production will be more decentralized. Produced energy used in nearby. More fertilizers used through closed cycle.
Smaller proportion of energy capacious tillage on treatment of soils. Development of logistics on movement of materials and
products on the assumption that energy saving.
7. What do you believe should be the main priorities for future research in to improve fuel efficiency in agriculture?
Development of new technologies and materials. Integration several technologies together. Development of smart grid systems
as wind, solar, biofuels, geothermal and energy storage, small local solutions. Energy storage. New technologies for obtaining
liquid biofuels from local resources.
27
Acknowledgements
The authors would like to acknowledge all of the people
and companies who kindly completed the surveys in the
Appendices. Furthermore, thanks must be given to all the
reference sources, whose information made the bulk of the
report possible.
Bibliography
[1] Ag Leader. 2011. Products. [On-line]. Ag Leader Technology.
Available from: http://www.agleader.com/products/ [Accessed 17th
April 2012].
[2] Alluvione, F., Moretti, B., Sacco, D. and Grignani, C. 2011. EUE
(energy use efficiency) of cropping systems for a sustainable
agriculture. Energy. 36. pp.4468-4481.
[3] AMAZONE. 2010. Intelligent crop production. Hasbergen-Gaste:
AMAZONEN-Werke.
[4] Bailey, A.P., Basford, W.D., Penlington, N., Park, J.R., Keatinge,
J.D.H., Rehman, T., Tranter, R.B. and Yates, C.M. 2003. A
comparison of energy use in conventional and integrated arable farming
systems in the UK. Agriculture, Ecosystems and Environment. 97.
pp.241-253.
[5] Baquero, G., Esteban, B., Riba, J.R., Rius, A. and Puig, R. 2011. An
evaluation of the life cycle cost of rapeseed oil as a straight vegetable
oil fuel to replace petroleum diesel in agriculture. Biomass and
Bioenergy. 35. pp.3687-3697.
[6] Bochtis, D.D., Sorensen, C.G., Green, O., Moshou, D. and Olesen, J.
2010. Effect of controlled traffic on field efficiency. Biosystems
Engineering. 106. pp.14-25.
[7] Burgess, P.J. and Morris, J. 2009. Agricultural technology and land use
futures: The UK case. Land Use Policy. 26S. pp.222-229.
[8] CLA. 2002. Biomass: Green Energy from Forestry and Agriculture
as an Enterprise. London: Country Land & Business Association.
[9] CONFOR. 2010. Scottish forestry at the crossroads: A virtuous cycle
or a spiral of decline? [On-line] CONFOR . Available from:
http://www.confor.org.uk/NewsAndEvents/Listings.aspx?pid=29&id=8
41 [Accessed 2nd April 2012].
[10] CONFOR. 2012. Forestry fit for the 21st Century. [On-line] CONFOR
. Available from:
http://www.confor.org.uk/Upload/Documents/22_ForestryFitfor21stcen
turyDec2011.pdf [Accessed 2nd April 2012].
[11] Davies, D.B. and Finney, J.B. 2002. Reduced Cultivations for
Cereals: Research, Development and Advisory Needs Under
Changing Economic Circumstances. [On-line] HGCA. Available
from:
http://www.hgca.com/publications/documents/cropresearch/RR48_com
plete_final_report.pdf [Accessed 6th June 2012].
[12] Dewangan, K.N. and Prasanna Kumar, G.V. 2006. Comparative Study
of Lever Operated Knapsack Sprayer and Controlled Droplet
Application Sprayer for Hill Agriculture in the North Eastern India.
Journal of Agricultural Engineering. 40(3). pp.101-104.
[13] Ehsani, M., Gao, Y., and Emadi, A. 2010. Modern Electric, Hybrid
Electric and Fuel Cell Vehicles. 2nd ed. Florida: CRC Press
[14] Environment Agency. 2008. Best Farming Practices. Bristol:
Environment Agency.
[15] ESRI. 2009. GIS for Agriculture. [On-line] ESRI . Available from:
http://www.esri.com/library/bestpractices/gis-for-agriculture.pdf
[Accessed 30th April 2012].
[16] Fathollahzadeh, H., Mobli, H. and Tabatabaie, S.M.H. 2009. Effect of
ploughing depth on average and instantaneous tractor fuel consumption
with three-share disc plough. Agrophysics.23. pp.399-402.
[17] Fendt. 2011. Fendt GuideConnect: Two Tractors One Driver. [On-
line]. Fendt. Available from:
http://www.fendt.co.uk/press_pressreleases_3378.asp [Accessed 16th
April 2012].
[18] Garford. 2011. Robocrop InRow: Inter-row and inter-plant weeder.
[On-line]. Garford Farm Machinery Ltd. Available from:
http://www.garford.com/PDF/robocrop%20inrow%20en.pdf [Accessed
30th May 2012].
[19] Grewal, S.S. and Grewal, P.S. 2012. Can cities become self-reliant in
food? Cities. 29. pp.1-11.
[20] Hassall, J. 2009. Future Trends in Precision Agriculture. [On-line].
Nuffield Scholarships. Available from:
http://www.nuffieldinternational.org/rep_pdf/1271281847James_Hass
all_Report_2009.pdf [Accessed 19th April 2012].
[21] Henten, E.J., Goense, D. and Lockhorst, C. 2009. ed. Precision
agriculture ‘09. Wageningen, the Netherlands: Wageningen Academic
Publishers.
[22] Holmes Culley. 2007. Tapping the Potential of Urban Rooftops:
Rooftop Resources Neighbourhood Assessment. [On-line] Holmes
Culley Consulting Structural Engineers . Available from:
http://www.dceplanning.com/reports/Rooftops.pdf [Accessed 30th
April 2012].
[23] Kirchmann, H. and Thorvaldsson, G. 2000. Challenging targets for
future agriculture. European Journal of Agronomy. 12. pp.145-161.
[24] Kitchen, N.R. 2008. Emerging technologies for real-time and integrated
agriculture decisions. Computers and Electronics in Agriculture. 61.
pp.1-3.
[25] Knight, S., Miller, P. and Orson, J. 2009. An up-to-date cost/benefit
analysis of precision farming techniques to guide growers of cereals and
oilseeds. [On-line]. HGCA. Available from:
http://www.hgca.com/cms_publications.output/2/2/Publications/Final%
20project%20reports/An%20up-to-
date%20cost%e2%80%93benefit%20analysis%20of%20precision%20
farming%20techniques%20to%20guide%20growers%20of%20cereals
%20and%20oilseeds.mspx?fn=show&pubcon=6112 [Accessed 19th
April 2012].
[26] Lee, W.S., Alchanatis, V., Yang, C., Hirafuji, M., Moshou, D. and Li,
C. 2010. Sensing technologies for precision speciality crop production.
Computers and Electronics in Agriculture. 74. pp.2-33.
[27] Mitchell, C.P., Stevens, E.A. and Watters, M.P. 1999. Short-rotation
forestry operations, productivity and costs based on experience gained
in the UK. Forest Ecology and Management. 121. pp.123-136.
[28] Murakami, E., Saraiva, A.M., Riberio Junior, L.C.M., Cugnasca, C.E.,
Hirakawa, A.R. and Correa, P.L.P. 2007. An infrastructure for the
development of distributed service-oriented information systems for
precision agriculture. Computers and Electronics in Agriculture. 58.
pp.37-48.
[29] Norse, D. 2012. Low carbon agriculture: Objectives and policy
pathways. Environmental Development. 1. pp.25-39.
[30] Oliver, M.A. 2010. ed. Geostatistical Applications for Precision
Agriculture. Reading: Springer Science + Business Media.
[31] Palander, T., Bergroth, J. and Karha, K. 2012. Excavator technology
for increasing the efficiency of energy wood and pulp wood harvesting.
Biomass and Bioenergy. 40. pp.120-126.
[32] Pederson, S.M., Fountas, S., Have, H. and Blackmore, B.S. 2006.
Agricultural robots: system analysis and economic feasibility.
Precision Agriculture. 7. pp.295-308.
[33] Roser, D., Sikanen, L., Aiskainen, A., Parikka, H. and Vaatainen, K.
2011. Productivity and cost of mechanized energy wood harvesting in
Northern Scotland. Biomass and Bioenergy. 35. pp.4570-4580.
[34] Ruiz-Garcia, L. and Lunadei, L. 2011. The role of RFID in agriculture:
Applications, limitations and challenges. Computers and Electronics
in Agriculture. 79. pp.42-50.
[35] Schellberg, J., Hill, M.J., Gerhards, R., Rothmund, M. and Braun, M.
2008. Precision agriculture on grassland: Applications, perspectives
and constraints. Europ. J. Agronomy. 29. pp.59-71.
28
[36] Serrano, J.M., Peca, J.O., Marques da Silva, J., Pinheiro, A. and
Carvalho, M. 2007. Tractor energy requirements in disc harrow
systems. Biosystems Engineering. 98. pp.286-296.
[37] Slaughter, D.C., Giles, D.K. and Downey, D. 2008. Autonomous
robotic weed control systems: A review. Computers and Electronics in
Agriculture. 61. pp.63-78.
[38] Sorensen, B. 2004. Total life-cycle assessment of PEM fuel cell car.
[On-line]. Bangkok Pollution Control Department. Available from:
http://ptech.pcd.go.th/p2/userfiles/consult/5/LCA%209.pdf [Accessed
14th May 2012].
[39] Sugiara, R., Noguchi, N. and Ishii, K. 2005. Remote-sensing
Technology for Vegetation Monitoring using an Unmanned Helicopter.
Biosystems Engineering. 90(4). pp.369-379.
[40] Talbot, B. and Suadicani, K. 2005. Analysis of Two Simulated In-field
Chipping and Extraction Systems in Spruce Thinnings. Biosystems
Engineering. 91(3). pp.283-292.
[41] Telmo, C. and Lousada, J. 2011. Heating values of wood pellets from
different species. Biomass and Energy. 35. pp.2634-2639.
[42] Tiernan, D., Zeleke, G., Owende, P.M.O., Kanali, C.L., Lyons, J. and
Ward, S.M. 2004. Effect of Working Conditions on Forwarder
Productivity in Cut-to-length Timber Harvesting on Sensitive Forest
Sites in Ireland. Biosystems Engineering. 87(2). pp.167-177.
[43] Trewavas, A. 2004. A critical assessment of organic farming-and-food
assertions with particular respect to the UK and the potential
environmental benefits of no-till agriculture. Crop Protection. 23.
pp.757-781.
[44] Tuomisto, H.L., Hodge, I.D., Riordan, P. and Macdonald, D.W. 2012.
Comparing energy balances, greenhouse gas balances and biodiversity
impacts of contrasting farming systems with alternative land uses.
Agricultural Systems. 108. pp.42-49.
[45] Whittaker, C., Mortimer, N., Murphy, R. and Matthews, R. 2011.
Energy and greenhouse gas balance of the use of forest residues for
bioenergy production in the UK. Biomass and Bioenergy. 35. pp.4581-
4594.
[46] Yeomans, A. and Hemery, G. 2010. Prospects for the market supply of
wood and other forest products from areas with fragmented forest-
ownership structures: England case study. [On-line] SYLVA
Foundation. Available from:
http://ec.europa.eu/agriculture/analysis/external/supply-
wood/england_en.pdf [Accessed 30th April 2012].
[47] Zamel, N. and Li, X. 2006. Life cycle comparison of fuel cell vehicles
and internal combustion engine vehicles for Canada and the United
States. Journal of Power Sources. 162. pp.1241-1253.
[48] Zhang, N., Wang, M. and Wang, N. 2002. Precision Agriculture a
worldwide overview. Computers and Electronics in Agriculture. 36.
pp.113-132.
References (Need to pp. books)
[1] Adamchuk, V.I., Grisso, R.D. and Kocher, M.F. 2011. Spatial
Variability of Field Machinery Use and Efficiency. In: Clay, D.E. and
Shanahan, J.F. ed. GIS Applications in Agriculture: Nutrient
Management for Energy Efficiency. Volume 2. Florida: CRC Press.
Pp. 135-146.
[2] AEA. 2011. Tractor Maintenance. [On-line]. AEA. Available from:
http://www.aea.uk.com/wp-content/uploads/tractor-management.pdf
[Accessed 17th May 2012].
[3] AMAZONE. 2011. Intelligent Crop Production. [On-line].
AMAZONEN-Werke. Available from:
http://info.amazone.de/DisplayInfo.aspx?id=23296 [Accessed 30th
May 2012].
[4] Bayhan, Y., Kayisoglu, B., Gonulol, E., Yalcin, H. and Sungur, N.
2006. Possibilities of direct drilling and reduce tillage in second crop
silage corn. Soil & Tillage Research. 88. pp.1-7.
[5] Benton Jones, J.Jr. 1997. Hydroponics: A Practical Guide for the
Soilless Grower . Florida: St. Lucie Press.
[6] Bochtis, D.D. and Vougioukas, S.G. 2008. Minimising the non-
working distance travelled by machines operating in a headland field
pattern. Biosystems Engineering. 101. pp.1-12.
[7] Bronson, K.F., Scharf, P.C. and Kitchen, N.R. 2011. Use of GIS-Based
Site-Specific Nitrogen Management for Improving Energy Efficiency.
In: Clay, D.E. and Shanahan, J.F. ed. GIS Applications in Agriculture:
Nutrient Management for Energy Efficiency. Volume 2. Florida: CRC
Press. Pp. 359-384.
[8] Buresh, R. 2009. The SSNM Concept and its Implementation in Rice.
In: IFA Crossroads Asia-Pacific: proceedings of conference held at
Kota Kinabalu, Malaysia 8-10 December 2009. Maidenhead: British
Grassland Society.
[9] Caterpillar. 2012. CAT D7E With Electric Drive. [On-line] Caterpillar.
Available from: http://www.cat.com/D7E [Accessed 28th May 2012].
[10] Chamen, T. 2006. ‘Controlled Traffic’ Farming: Review and Apraisal
of Potential Use in the UK. Bedfordshire: HGCA.
[11] Clay, D.E and Shanahan, J.F. 2011. GIS Applications in Agriculture:
Volume Two Nutrient Management for Energy Efficiency. Florida:
CRC Press.
[12] Clean Cities. 2008. Biodiesel Blends. [On-line]. US Department of
Energy. Available from: http://www.nrel.gov/docs/fy05osti/37136.pdf
[Accessed 6th May 2012].
[13] CPA (Centre for Precision Agriculture). 2012. Precision Agriculture
Laboratory. [On-line]. Sydney University. Available from:
http://sydney.edu.au/agriculture/research/australian_centre_for_precisi
on_agriculture.shtml [Accessed 17th April 2012].
[14] CONFOR. 2010. Wood Fibre Availability and Demand in Britain:
2007-2025. [On-line] CONFOR. Available from:
http://www.confor.org.uk/NewsAndEvents/Listings.aspx?pid=29&id=8
39 [Accessed 30th March 2012].
[15] CTF. 2012. Benefits of CTF. [On-line]. CTF Europe. Available from:
http://www.controlledtrafficfarming.com/content/benefits.aspx
[Accessed 5th May 2012].
[16] DENSO. 2009. Third Generation Common Rail System (CRS). [On-
line]. DENSO Corporation. Available from:
http://www.globaldenso.com/en/technology/product/powertrain/files/co
mmon_rail_3rd_e.pdf [Accessed 30th April 2012].
[17] Discovery. 2012. Future Farmers Will Drive Fuel Cell Tractors. [On-
line]. Discovery News. Available from:
http://news.discovery.com/autos/fuel-cell-tractor-120213.html
[Accessed 2nd May 2012].
[18] EC (European Commission). 2011. Satellite Navigation Galileo:
Satellite Launches. [On-line]. EC. Available from:
http://ec.europa.eu/enterprise/policies/satnav/galileo/satellite-
launches/index_en.htm [Accessed 16th April 2012].
[19] Forestry Commission. 2011. Woodchip Drying. [On-line]. Forestry
Commission. Available from: http://www.forestry.gov.uk/fr/INFD-
7SUE6F [Accessed 4th April 2012].
[20] G-Nius. 2008. Guardium Mk I. [On-line]. G-Nius Ltd. Available from:
http://www.g-nius.co.il/unmanned-ground-systems/guardium-ugv.html
[Accessed 31st May 2012].
[21] Gardner, D. 2010. The Appliance of New Science and Frontier
Technologies to Transform UK Agriculture and UK Agri-Food. [On-
line]. Nuffield Scholarships. Available from:
http://www.nuffieldinternational.org/rep_pdf/12724884662009_David
_Gardner_Final_Arden_Report_Web_version.pdf [Accessed 20th
April 2012].
[22] Hach, C.V. and Tan, P.S. 2007. Study on site-specific nutrient
management (SSNM) for high-yielding rice in the Mekong delta.
Omonrice. 15. pp.144-152.
[23] HGCA. 2003. Reducing Costs of Establishing and Managing Wheat.
[On-line]. HGCA. Available from:
http://www.hgca.com/research/topicsheets/topicsheet65.html [Accessed
13th April 2012].
[24] HGCA. 2009. Precision Farming Solution: Autosteer. [On-line].
HGCA. Available from:
http://www.hgca.com/document.aspx?fn=load&media_id=5356&publi
cationId=4040 [Accessed 6th May 2012].
29
[25] HGCA. 2009. Precision Farming Solution: N-Sensor to Vary
Nitrogen Rate. [On-line]. HGCA. Available from:
http://www.hgca.com/document.aspx?fn=load&media_id=5464&publi
cationId=4040 [Accessed 6th May 2012].
[26] Husain, I. 2003. Electric and Hybrid Vehicles Design Fundamentals.
New York: CRC press.
[27] John Deere. 2012. Emmission Information: The John Deere Solution.
[On-line]. John Deere. Available from:
http://www.deere.co.uk/wps/dcom/en_GB/services_and_support/emissi
ons_information/the_john_deere_solution.page [Accessed 20th April
2012].
[28] John Deere Agricultural Management Systems. 2012. Guidance
Systems. [On-line]. John Deere. Available from:
http://www.deere.com/wps/dcom/en_INT/products/equipment/agricultu
ral_management_solutions/guidance_systems/guidance_systems.page
[Accessed 16th April 2012].
[29] John Deere Forestry. 2012. Timberlink. [On-line]. John Deere.
Available from:
http://www.deere.co.uk/wps/dcom/en_GB/products/equipment/measuri
ng_and_control_systems/timberlink/timberlink.page [Accessed 5th
June 2012].
[30] Kichler, C.M., Fulton, J.P., Raper, R.L., Macdonald, T.P. and Zech,
W.C. 2011. Effects of transmission gear selection on tractor
performance and fuel costs during deep tillage operations. Soil &
Tillage Research. 113. pp.105-111.
[31] Kimming, M., Sundberg, C., Nordberg, A., Baky, A., Bernesson, S.,
Noren, O. and Hansson, P.A. 2010. Life cycle assessment of energy
self-sufficiency systems based on agricultural residues for organic
arable farms. Bioresource Technology. 102 (2). pp.1425-1432. [On-
line] Science Direct. Available From:
http://www.sciencedirect.com/science?_ob=MiamiImageURL&_cid=2
71433&_user=2051519&_pii=S0960852410015816&_check=y&_or
igin=article&_zone=toolbar&_coverDate=31-Jan-
2011&view=c&originContentFamily=serial&wchp=dGLzVlV-
zSkWz&md5=c80043afb3fbc127fc1f65e768188270/1-s2.0-
S0960852410015816-main.pdf [Accessed 1st May 2012].
[32] Kozai, T. 2011. Integrative Environment Control System for a Plant
Factory - with concepts of closed system, resource use efficiency and
rate variables. In: The sixth International Symposium on Intelligent
Information Technology in Agriculture (6th ISIITA): proceedings of
conference held at Beijing, China 28-30 October 2011. Beijing:
NERCITA.
[33] La Bellotta. 2012. Energy Independent Farm. [On-line]. La Bellotta.
Available from: http://www.labellotta.com/#farm [Accessed 15th April
2012].
[34] Luck, J.D., Pitla, S.K., Shearer, S.A., Mueller, T.G., Dillon, C.R.,
Fulton, J.P. and Higgins, S.F. 2010. Potential for pesticide and nutrient
savings via map-based automatic boom section control of spray nozzles.
Computers and Electronics in Agriculture. 70. pp.19-26.
[35] Martensen, K. 2006. Progress in typical materials for agricultural
machinery. [On-line] Club of Bologna . Available from:
http://www.clubofbologna.org/ew/documents/Martensen-paper.pdf
[Accessed 7th May 2012].
[36] Mederski, P.S. 2006. A comparison of harvesting productivity and
costs in thinning operations with and without midfield. Forestry
Ecology and Management. 224. pp.286-296.
[37] Meisterling, K., Samaras, C. and Schweizer, V. 2009. Decisions to
reduce greenhouse gases from agriculture and product transport: LCA
case study of organic and conventional wheat. Journal of Cleaner
Production. 17. pp.222-230.
[38] Micron. 2012. Controlled Droplet Application. [On-line]. Micron
Group. Available from: http://www.micron.co.uk/why_cda [Accessed
15th May 2012].
[39] Mousazadeh, H., Keyhani, A., Javadi, A., Mobli, H., Abrinia, K. and
Sharifi, A. 2011. Life-cycle assessment of a Solar Assist Plug-in Hybrid
electric Tractor (SAPHT) in comparison with a conventional tractor.
Energy Conversion and Management. 52. pp.1700-1710
[40] New Holland. 2012. SCR: High Performance, Efficient Solution for
High Powered Machines. [On-line]. New Holland. Available from:
http://www.thecleanenergyleader.com/en/tier_IV/thetechnology/scr.htm
l [Accessed 20th April 2012].
[41] New Holland. 2012. NH2: Hydrogen Powered Tractor. [On-line].
New Holland. Available from:
http://www.thecleanenergyleader.com/en/nh2_tm_hydrogen.html
[Accessed 10th April 2012].
[42] Palmer, R.J., Wild, D. and Runtz, K. 2003. Improving the Efficiency of
Field Operations. Biosystems Engineering. 84(3). pp.283-288.
[43] Pati, F.M., Clay, D.E. and Carlson, G. 2011. Nutrient Management for
Improved Energy Efficiency. In: Clay, D.E. and Shanahan, J.F. ed. GIS
Applications in Agriculture: Nutrient Management for Energy
Efficiency. Volume 2. Florida: CRC Press. Pp. 19-30.
[44] Resh, H.M. 1998. Hydroponic Food Production: A definitive
guidebook for the advanced home gardner and the commercial
Hydroponic Grower. 5th ed. California: Woodbridge Press Publishing
Company.
[45] Robert Bosch GmbH. 2004. The Common Rail Diesel Injection
System Explained. [On-line]. Robert Bosch GmbH. Available from:
http://www.swedespeed.com/news/publish/Features/printer_272.html
[Accessed 29th April 2012].
[46] Rodriguez, C. and Wiegand, K. 2009. Evaluating the trade-off between
machinery efficiency and loss of biodiversity-friendly habitats in arable
landscapes: The role of field size. Agriculture, Ecosystems and
Environment.129. pp.361-366.
[47] Sarvi, A., Kilinene, P. and Zevenhoven, R.. 2009. Emissions from
large-scale medium-speed diesel engines: 3. Influence of direct water
injection and common rail. Fuel Processing Technology. 90. pp.222-
231.
[48] Takaishi, T., Numata, A., Nakano, R. and Sakaguchi, K. 2008.
Approach to High Efficiency Diesel and Gas Engines. [On-line]
Mitsubishi Heavy Industries Ltd. Available From:
https://www.mhi.co.jp/technology/review/pdf/e451/e451021.pdf
[Accessed 1st May 2012].
[49] Tompkins, B.T., Song, H., Bittle, J.A. and Jacobs, T.J. 2012.
Efficiency considerations for the use of blended biofuel in diesel
engines. Applied Energy. (Unpublished).
[50] University of Washington. 2010. Improving IC Engine Efficiency.
[On-line]. University of Washington. Available from:
http://courses.washington.edu/me341/oct22v2.htm [Accessed 28th May
2012].
[51] Valtra RoboTrac. 2007. Valtra RoboTrac. [On-line]. Core77 Inc.
Available from: http://www.coroflot.com/seebergdesign/Valtra-
RoboTrac [Accessed 16th May 2012].
[52] Varuvel, E.G., Mrad, N., Tazerout, M. and Aloui, F. 2012.
Experimental analysis of biofuel as an alternative fuel for diesel
engines. Applied Energy. 94. pp.224-231.
[53] Which?. 2012. Car Features: Stop-Start Systems. [On-line]. Which?.
Available from: http://www.which.co.uk/cars/choosing-a-car/car-
features/green-car-technologies-explained/stop-start-systems/
[Accessed 6th June 2012].
[54] Yara. 2012. N Sensor: How It Operates. [On-line]. Yara. Available
from:
http://www.yara.co.uk/fertilizer/tools_and_services/n_sensor/how_it_o
perates/index.aspx [Accessed 4th May 2012].
[55] ZF. 2012. ZF Technology for Tractors: Robust and Powerful. [On-
line]. ZF Friedrichshafen AG. Available from:
http://www.zf.com/corporate/de/products/product_range/agricultural_
machinery/tractors/tractors.html [Accessed 12th May 2012].
[56] Zhu, M. and Zhang, D. 2012. Effect of a homogenous combustion
catalyst on the combustion characteristics and fuel efficiency in a diesel
engine. Applied Energy. 91. pp.166-172.
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To our knowledge, geographical information system (GIS)-based site-specic nitrogen management (SSNM) techniques have not been used to assess agricultural energy costs and efciency. This chapter uses SSNM case studies for corn (Zea mays L.) grown in Missouri and cotton (Gossypium hirsutum L.) grown in Texas. In ve case studies, the impact of SSNM will be compared with blanket N fertilizer recommendations. The ve case studies are investigating (1) the impact N on energy produced in cotton production, (2) the impact of variable-rate N for cotton production based on soil nitrate and crop re°ectance, (3) the feasibility of variable-rate N based on corn crop re°ectance, (4) the use of corn management zones and crop re°ectance for improving N recommendations and energy efciency, and (5) the ability of using aerial photographs to improve N recommendations in corn.
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To meet future food, ber, and energy requirements, it is anticipated that agricultural yields will need to be doubled by 2050. Meeting this goal is complicated by increasing cost and availability of fertilizers, anticipated shortages in critical resources (land, Pfertilizer, and liquid fuels), and urbanization that is reducing arable lands. Doubling food production with diminishing resources will require wide-scale investments in production agriculture, the development of new genomics that increase energy and production efciency, and the adoption of precision management techniques that increase productivity as well as resource use efciency. This chapter provides a framework for assessing energy efciency and an example using the readily available life-cycle assessment (LCA) model, biofuel energy simulator (BESS), to calculate energy returns at two landscape positions.
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Analyzing the impact of different nutrient management scenarios on energy efficiency, this reference offers powerful techniques to help farmers produce greater abundance at lower costs. Sections cover manure management; water and nutrient management in relation to energy efficiency and ethanol production; matching crops, landscape positions, and nutrient management; and nitrogen and energy efficiency. The book includes a broad range of GIS techniques useful over a range of spatial and temporal scales. An interactive CD is provided to help readers work through examples and data.