MONITORING AND MANAGEMENT OF MAIZE RUST DISEASE (Puccinia sorghi) BY

A DRONE PROTOTYPE IN SOUTHERN HIGHLANDS, TANZANIA

PALILO, AGAPE

AGR/D/11/T/0046

BSC. AGRONOMY

FIELD PRACTICAL TRAINING TECHNICAL REPORT

SOKOINE UNIVERSITY OF AGRICULTURE

MOROGORO, TANZANIA

2014

ABSTRACT

The increase of world population, along with the poor agricultural practices have made it

necessary to use new technologies like RS in the agricultural sector. The use of RS is important

because precision agriculture is data intensive.

Agricultural management issues have a critical geographic dimension. RS technology enhances

the storage and management of geographic information in order to analyze patterns, relationships,

and trends for better decisions. Observing the colors of leaves or the overall appearances of plants

can determine the plant’s condition. Remotely sensed images taken from drones and aircrafts

provide a means to assess field conditions without physically touching them.

This enables more precision and accuracy thus opening the way to precision agriculture. This

paper will discuss highly effective farming strategy which allows a farmer to tend maize rust

disease in the southern highlands of Tanzania. This will help small holder farmers to increase

productivity while lowering costs and minimising environmental impact.

CHAPTER 1

1.0 NTRODUCTION, JUSTIFICATIONS AND OBJECTIVES

1.1 Introduction on Maize rust disease

Maize rust is fungal disease recognized by the appearance of circular to elongate pustules scattered

over both surfaces of the leaf at early stages of infections. The Pustules which are powdery and

brown in colour contain masses of spores (uredospores) tends to appear on any above-ground part

of the plant, however they cause much infections on the leaves. As the time progresses the pustules

tends to split exposing the spores, which are spread and disseminated by the wind to initiate and

thus causing new infections. The disease is caused by a fungi known as Puccinia sorghi.

When maize approaches maturity the colour of spores in pustules change from reddish to black

due to formation of teliospores (resting spores). The disease infections are initiated from the leaf

margins and leaf apex then extend inwards to the leaf petiole. The disease is spread by air through

the wind (Carrier) and deposited to new areas thus causing infections in other maize crops.

The fungal infection causes black colorations on the leaves thus reducing the plant photosynthetic

areas which in turn decrease food synthesis in the plant affecting its physiology and consequently

reducing the yields.

1.1.1 Management actions of common rust in the maize fields

(a) Use of resistant maize varieties or hybrids

Biological control through breeding for disease resistance or tolerance is the only feasible

economic control. The diseases cannot be controlled economically by chemical means.

(b) Deep plough crop residue

This will help to minimize disease spread by limiting disease dissemination and blocking the

pathogen life cycle so preventing their success to next.

(c) Destroy the weed Oxalis sp. (an alternate host).

Although weeds need to be controlled to reduce their impact on crop yield and quality, in the case

of maize rust the weeds must be destroyed to get rid of the pathogen shelters.

1.2 Remote sensing technology and the drone prototype

Remote sensing is a process of observing things without physically touching them. The process is

aided through sensors designated depending on a specific task intended to be carried. Remote

sensors can be either passive or active. Passive sensors respond to external stimuli such that they

record radiation that is reflected from Earth’s surface, usually from the sun. Because of this,

passive sensors can only be used to collect data during daylight hours.

In contrast, active sensors use internal stimuli to collect data about Earth. For example, a laser-

beam remote sensing system projects a laser onto the surface of Earth and measures the time that

it takes for the laser to reflect back to its sensor.

Among the two types of remote sensing systems the most common used in agriculture is a passive

system which senses the electromagnetic energy reflected from plants through electromagnetic

sensors. The sensors can be installed on satellites, manned or unmanned aircraft, or right on farm

equipment. The choice of a remote sensing system for a particular application is guided by several

factors. These includes spatial resolution, spectral resolution, radiometric resolution, and temporal

resolution.

Spatial resolution denotes the minimum size of an object that can be noticed in an image. A pixel

the basic unit in an image. One-meter spatial resolution implies each pixel image stand for an area

of one square meter. As the area represented by one pixel decreases, the resolution of the image

increases.

Spectral resolution refers to the number and the wavelength width of each band (a narrow portion

of the electromagnetic spectrum). Higher spectral resolution images are more preferable for

distinction of shorter wavelength widths.

The images from Multi-spectral camera can measure several wavelength bands such as visible

green or NIR. Hyperspectral imagery measures energy in narrower and more numerous bands than

multi-spectral imagery. The narrow bands of hyperspectral imagery are more sensitive to

variations in energy wavelengths and therefore have a greater potential to detect crop stress than

multi-spectral imagery. Multi-spectral and hyperspectral imagery are used together to provide a

more complete picture of crop conditions.

Radiometric resolution refers to the sensitivity of a remote sensor to variations in the reflectance

levels. The higher the radiometric resolution of a remote sensor, the more sensitive it is to detecting

small differences in reflectance values. Higher radiometric resolution allows a remote sensor to

provide a more precise picture of a specific portion of the electromagnetic spectrum.

Temporal resolution refers to how often a remote sensing platform can provide coverage of an

area. Geo-stationary satellites can provide continuous sensing while normal orbiting satellites can

only provide data each time they pass over an area.

Remote sensing taken from cameras mounted on airplanes is often used to provide data for

applications requiring more frequent sensing. Cloud cover can interfere with the data from a

scheduled remotely sensed data system. Remote sensors located in fields or attached to agricultural

equipment can provide the most frequent data.

1.3 Statement of problem and justification

For Maize growers in the southern highlands of Tanzania who most are small holder farmers,

Maize rust is one of the biggest problem and unavoidable issue, which can ruin a whole crop if not

managed aggressively. As an agricultural student the writer have been working on a new tool to

combat the Maize rust: A drone.

1.4 OBJECTIVES

1.4.1 General objective

To Monitor and manage maize rust disease (Puccinia sorghi) by a drone prototype in

Southern highlands, Tanzania

1.4.2 Specific objectives

To manage common maize rust (Puccinia sorghi) in southern highlands Tanzania by using

a drone prototype

To incorporate the Remote sensing (R.S) technology in the small holder farming industry

in Southern highlands, Tanzania

CHAPTER 2

2.0 METHODOLOGY

2.1 How remote sensing technology can be used in the farms

Remotely sensed images can be used to identify nutrient deficiencies, diseases, water deficiency

or surplus, weed infestations, insect damage, hail damage, wind damage, herbicide damage, and

plant populations. Survey of crops is feasible using infrared and colour cameras to detect the onset

of disease through Changes in crop colour. Information from remote sensing can be used as base

maps in variable rate applications of fertilizers and pesticides. The Energy bounces off leaves and

is readily identified by human eyes as the green color of plants. A plant looks green because the

chlorophyll in the leaves absorbs much of the energy in the visible wavelengths and the green color

is reflected. Sunlight that is not reflected or absorbed is transmitted through the leaves to the

ground. Interactions between reflected, absorbed, and transmitted energy can be detected by

remote sensing.

2.2 Drone prototype to combat maize rust in maize fields

The use of UAS and the integration of specialised earth observation sensors, such as multispectral

and hyper spectral sensors, thermal cameras, and laser scanners, to map and monitor different

aspects of the environment at ultra-high resolutions is on demand for different farm activities. The

concept focuses on the use of unmanned aircraft systems (UAS) and the integration of small

sensors for farm remote sensing and aerial surveys.

2.3 How a drone performs its operation to combat maize rust in the maize fields

Drones can be used just like you would a plane or a satellite, it is a mini satellite which can carry

the sensors that are needed to study the farm conditions. The same idea can be used to combat

maize rust in the fields. The main goal is to fly over the farms and map no matter how lush and

dense the crops are. The drone is operated by an unmanned aerial vehicle (UAV) pilot where the

drone can take off and land by itself. It can flies to a given height between 50-100 metres above

the ground and then the autopilot takes over and it flies to GPS waypoints, it can fly between 5-10

minutes and in that time it can cover around two hectares. The main goal is to help farmers and

farm managers to better understand their maize crop health conditions giving a bird's- eye view

(an acute eye vision).

CHAPTER 4

4.0 RESULTS AND DISCUSSIONS

4.1 RESULTS

4.1.1 Monitoring health of maize vegetation through thermal, multi-spectral camera

The drone is used to examine the health of vegetation through thermal, multi-spectral and still-

image cameras attached to its undercarriage. It is deployed in the maize fields with an aid of an

auto pilot where it flies to a given height between 50-100 metres above the ground and then the

autopilot takes over and it flies to GPS waypoints. When reaching the coordinates, drone starts

taking pictures at a farmer-specified setting.

The differences in leaf colors, textures, shapes or even how the leaves are attached to plants,

determine how much energy will be reflected, absorbed or transmitted. The relationship between

reflected, absorbed and transmitted energy is used to determine spectral signatures of individual

plants. Spectral signatures are unique to plant species. The images obtained will identify stressed

areas in fields by first establishing the spectral signatures of healthy plants. The spectral altered

from those of healthy plants.

For Example, The comparison of spectral signatures of healthy and stressed sugar beets. Stressed

sugar beets have a higher reflectance value in the visible region of the spectrum from 400-700 nm.

This pattern is reversed for stressed sugar beets in the nonvisible range from about 750-1200 nm.

The visible pattern is repeated in the higher reflectance range from about 1300-2400 nm.

Interpreting the reflectance values at various wavelengths of energy can be used to assess crop

health. The comparison of the reflectance values at different wavelengths, called a vegetative

index, is commonly used to determine plant vigor. The most common vegetative index is the

normalized difference vegetative index (NDVI). NDVI compares the reflectance values of the red

and NIR regions of the electromagnetic spectrum. The NDVI value of each area on an image helps

identify areas of varying levels of plant vigor within fields.

4.1.2 Monitoring of weeds emergence in the maize fields through thermal, multi-spectral

camera

The differences in leaf colors, textures, shapes or even how the leaves are attached to plants,

determine how much energy will be reflected, absorbed or transmitted. The relationship between

reflected, absorbed and transmitted energy is used to determine spectral signatures of individual

plants. Spectral signatures are unique to plant species. The images obtained will identify weeds

presence in the fields. Spectral signatures of the crop plants will appear different from those of the

weeds.

The weeds Oxalis species are the alternate host to the fungi causing common maize rust in the

maize fields on the images obtained by the drone its Spectral signatures will appear different from

those of the crop plants.

During drone operations the use of unmanned aircraft systems (UAS) and the integration of small

sensors for environmental remote sensing and aerial surveys are put into action where by the drone

works together with other components as a system. The UAS and the integration of specialised

earth observation sensors, such as multispectral and hyper spectral sensors, thermal cameras, and

laser scanners are used to map and monitor different aspects of the farm at ultra-high resolutions.

A drone flies a multispectral sensor that can detect infrared light, which gives an indication of the

health vigor and density of the maize crop. The drone can fly between 5-10 minutes and in that

time it can cover an area of around two hectares of the maize fields substituting the work which

could be done by three people. Farm managers can use these maps to make decisions about where

the rusts has developed and subsequent solutions.

For large scale farmers in Europe they used to hire airplanes which is attached with cameras and

other sensors to detect the field conditions. The method is quite expensive for small holder farmers

in Africa with an average acreage area of about two acres.

However nowadays it’s all about a portable UAV system which does not cost more than 3500

US$. The farmers in Europe and across North America are in the progress of adopting such

technology but it has never been that easy because there is much researches to be done in order to

intergrate this technology into the farms. As it was initially for military reasons.

The technology allows small holder farmers in Africa to increase their yields because it allows

early assessment of the field crop conditions and providing answers instantaneously with low

costs.

4.2 DISCUSSIONS

4.2.1 Un Manned Aircraft Vehicles (UAVs) and privacy

There has been a lot of negative news about the use drones being dangerous and that they invade

privacy. The uses of UAV technologies raise a broad range of issues that relate to collection,

retention, use, disclosure, and eventual safe destruction of personal information. The potential for

institutional or other abuse, arising as a result of the inappropriate use of these technologies,

suggests a need for safeguards tailored to prevent intrusions into privacy and liberty. Whether

sensor enhanced UAVs are used by government agencies, commercial entities, or small personal

entities or whether model aircraft are used by private individuals for recreational purposes privacy

issues must be addressed. UAVs present unique privacy challenges, due to the manner in which

they may collect information. While some of the sensor equipment on board UAVs may be

commonplace in the consumer electronics marketplace, the ability to gather information

dynamically from unique vantage points would appear to distinguish UAV use from other video

surveillance cameras, and from data collected using cell phone technology. Rather than taking a

privacy compliance approach to system design, organizations should take a proactive approach to

developing and operating a UAV program which respects privacy. This will ensure that the

proposed design and operation of the UAV system limits privacy intrusion, if any, to that which is

absolutely necessary to achieve required, lawful goals.

4.2.2 Un Manned Aircraft Vehicles (UAVs) future

To ensure drone privacy policy and future, it is worthwhile to consider recent developments,

beginning with U.S. and Japan context which appear that the regulatory authorities of the two

countries are more helpful than in those of some other countries.

The R MAX system is regulated by the Japan Agriculture Aviation Association (JAAA), who

regard the system as agricultural equipment, and it is certified as such for reliability in operation.

The Association require that the distance between the unmanned helicopter and its operator should

not exceed 150 m.

The current rule in the UK, however, asserts that the UAV must stay within the sight of the

operator. To do so totally removes the economic advantage of the UAV operation and so prevents

the use of that operation as a ‘building block’ for future UAS applications.

Public concern with the prospect of unmanned aircraft flying around the skies and possibly

crashing onto people and property or colliding with other aircraft is perfectly understandable. It is

necessary that regulations are in place to prevent cavalier and ill-considered use of non-airworthy

and unreliable systems causing loss of life and damage to property. This is in the interest of

responsible manufacturers and users of UAS who would wish to see public confidence building in

the responsible deployment of well-conceived systems to the economic and environmental

advantage of all.

CHAPTER 5

5.0 CONCLUSSIONS AND RECOMMENDATIONS

5.1 CONCLUSSIONS

The main goal is to help farmers and especially smallholder farmers in Africa to be competitive

on the market in the sense of required products, quality and amount. This will enable them to

counteract changes in the market, changes in subsidies systems, environment destruction, soil

fertility depletion and climate changes.

5.2 RECOMMENDATIONS

One of the major constraints from farm yields increase in Africa is soil fertility depletion resulted

from continuous agricultural activities over the years done without supplementing the absorbed

nutrients.

When synchronized together with other activities like formation of farmer associations, groups

and cooperatives so sharing equipments and tools like machines, workers especially trained experts

like extensionists, Agronomists, engineers etc. The technology can help to ensure the world’s food

security by developing small holder farmers from hand to mouth yields into developed farmer with

surplus productions.

As main stake holders of the farming industry small holder farmers must have the perspective

which respects changing conditions and demands. This will enable them to be flexible to other

new technologies like Genetic Modified Organisms (GMOs), Integrated Pest Management (IPM)

and Organic farming.

Different stakeholders must be involved to ensure successful precision agriculture technology in

the farming industry. These will include from the Government through the Ministry of Agriculture

food security and cooperatives to provide subsidies, education and experts, individual farmers who

must possess a sense of development and agrarian revolution for the global future. There must be

a complete and continuous chain from national level to the individual farmer level to achieve the

goals of the successful farming industry.

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