The system of Precision farming guarantees a detail monitoring of data and information necessary for a successful decision in a crop production. The system is designed for a data collection from several sources. The data are collected by a service company and also directly by farmers. The paper also analyses the economical efficiency on the base of Medlov Farm. Next development is currently running under projects Prezem and AgriSensor.GPS, GIS, precision farming, economical analysis, monitoring, Farm Management, Research and Development/Tech Change/Emerging Technologies,

Cepicky, Jachym

Charvat, Karel

Gnip, Pavel

Kafka, Stepan

English

Research Papers in Economics

 
[37] 
 
Agris on-line Papers in Economics and Informatics 
Volume I  Number 2, 2009 
Prefarm Systems and economical analysis of practical experiences 
P. Gnip, S. Kafka, J. Čepický, K. Charvát 
WIrelessInfo, Help Service Remote Sensing, Litovel, Czech Republic 
Abstract 
The  system  of  Precision  farming  guarantees  a  detail  monitoring  of  data  and  information  necessary  for  a 
successful decision in a crop production. The system is designed for a data collection from several sources. The 
data are collected by a service company and also directly by farmers. The paper also analyses the economical 
efficiency  on  the  base  of  Medlov  Farm.  Next  development  is  currently  running  under  projects  Prezem  and 
AgriSensor. 
Key words 
GPS, GIS, precision farming, economical analysis, monitoring. 
Anotace 
Systém  hospodaření  Prefarm  zaručuje  detail  monitorování  dat  a  informací,  které  jsou  nezbytné  pro  úspěšné 
rozhodování v rostlinné výrobě. Systém je  určen pro sběr dat  z různých zdrojů. Údaje jsou shromažďovány 
servisní organizací, ale i přímo zemědělci. Článek shrnuje praktické zkušenosti na podniku Medlov. Systém je v 
současné době dále rozvíjen v projektech  Prezem a AgriSensor. 
Klíčová slova 
GPS, GIS, precizní zemědělství, ekonomická analýza, monitoring. 
Material and Methods  
A  technology  of  Precision  farming  guarantees  a 
success of this system on the market. Difficulties of 
technologies, currently and continually involved in 
this  system,  argue  against  its  practical  use  by 
farmers. In  this case, a service company wants to 
offer  a  suitable  environment  not  only  for  data 
collection,  data  processing,  but  also  for  the  high 
quality  of  other  information  related  with  a  farm 
management  and  a  crop  production.  The  practical 
distribution  of  results  to  customers  helps  them  to 
ensure a variable application of results on the field. 
The most important part of services is a technology 
of  data  collection,  a  system  of  data  processing. 
Remote  sensing,  crop  scanning  and  soil  sampling 
for  management  zones  classification  mean  for 
farmers  or  other  users  a  simplification  of  the 
difficult operations and recommendations including 
economic calculations.  
A  professional  service  in  the  market  in  this  area 
uses a follow tools: 
-  navigation  system  GPS  with  or  without 
Differential GPS,  
-  environment  of  Geographic  information 
system (GIS), 
-  internet  as  a  tool  for  data  transport,  data 
presentation, 
-  map  server  technology,  web  mapping 
services (wms / raster). 
The  complex  advisory  and  service  system  on  the 
market is based on results of field trials in different 
crops and locations. The data for WEB processing 
are prepared and stored by service organization and 
farmers. A central database store data is following: 
-  soil measuring (EM 38 data, soil type data), 
-  soil  sampling  (lab  analysis  for  Phosphor, 
Potash, Magnesium, Calcium, soil pH….), 
-  crop  scanning  (NDVI  data  created  from 
satellite or airborne pictures), 
-  yield data from yield monitor created during 
harvest,  
-  other  remote  sensing  data  (N-sensor 
scanning), Prefarm Systems and economical analysis of practical experiences 
[38] 
 
-  agronomy,  field  management  data  (crop 
rotation,  variety,  data  of  applications, 
weather conditions…..).  
The main point of system is to collect different data 
in the easiest way on a field and on a farm, and then 
to use the collected data for data processing via web 
tools.  
Open source solution Mapserver. Inside of services 
it was developed a mobile interface for  this Open 
Source  solution  and  also  there  were implemented 
OGC  standards  (WMS)  for  utilization  of  data  in 
distributed system. A connection with another open 
source  systems  (GRASS,  etc),  was  established. 
Current  solutions  are  Internet  Mobile  Systems, 
including analytical tools.  The most successful and 
currently used application from the service system 
is  „GIS  server  for  precision  farming  application 
with  mobile  access“.  It  is  focused  on  increase  of 
agricultural profitability and reduction of  fertilizer 
and  chemical  bad  influence  on  a  surrounding 
environment.  
The system provides analysis as follow: 
1. Field area calculation – number of  hectares for 
crop rotation, field cutting (Fig. 1, 2)  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 1. 
 
1999              2002 
 
 
 
 
 
 
 
 
 
 
  2004              2006 
             
 
 
 
 
 
 
 
 
 
Figure 2.Prefarm Systems and economical analysis of practical experiences 
[39] 
 
2.  1999  -2006,  Phosphor  content  in  topsoil,  %  of 
categories (Graph 1) 
4.  Variable  rate  (VRA)  and  multivariable  rate 
(MVRA)  recommendations  for  basic  fertilizer 
application(P,  K,  Mg,  Ca  and  Nitrogen).  (Fig.  3, 
Graph 2, 3) 
5. History – Traceability (Fig. 4) 
Management zones are a result of map analysis to 
get  an  optimal  amount  of  each  input  in  crop 
production  founded  on  variability  of  soil 
characteristic and other factors conditioning a crop 
yield. In this case, the analysis can be done in one 
time for one field, a group of fields, or a whole farm 
with  the  same  or  similar  conditions  for  the  crop 
planning. In the system a location can be set with a 
very  high  resemblance  of  soil  conditions  or  other 
elements and  monitored characteristic. The GIS in 
farm  management  allows  us  to  analyze  data  and 
yearly results from the crop production on the farm. 
 
Graph 1. 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 3. 
 
 
 
 
 
 
 
 
 
 
 
 
15.85
42.94
28.24
10.66
2.31
4.53
33.71
37.39
20.68
3.68
2.51
42.55
38.10
14.89
1.93
6.11
38.26
38.26
14.20
3.16
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1999 2002 2004 2006
very high
high
good
acceptable
low
0
10
20
30
40
50
60
70
80
90
1999 2000 2001 2002 2003 2004 2005 2006 2007
year
% P fert
K fert
Ca ferPrefarm Systems and economical analysis of practical experiences 
[40] 
 
Graph 2. 
 
Graph 3. 
 
 
Figure 4. 
 
How to start? 
A  system  of  adoption  and  running,  described 
below,  was  built  on  the  farm  by  an  Advisor 
Company  including  a  data  collection  and  a  field 
application,  so  the  farmer  does  not  have  to  be 
trained on different technique and equipment or a 
special  knowledge.  Every  step  and  result  is 
translated  to  agronomic  or  farm  management 
language.  The  system  was  adopted  in  the  first  3 
years  periods,  than  modified  in  the  next  3  years, 
periodically repeated so far. 
 First year 
1.1.  Calculation of system adoption 
-  Field boundary  mapping by  GPS. First of 
all, we have to make a field geographical 
description  in  Geographic  information 
system  (GIS).  We  map  by  GPS  a  field 
boundary on the farm and clarify field area 
in  GIS.  Foundation  of  field  database  in 
GIS. 
-  Management  zone  definition,  by  analysis 
of satellite imagery. This is the  first data 
processing  and  calculation  to  describe 
variability of each field. 
-  Soil  sample  grid  setting  -  calculating  of 
soil sample control point for soil sampling. 
-  Agronomic yield data description 
-  Price calculation of system adoption 
1.2.  Data collection 
-  Soil sampling and analysis of samples for 
phosphorus,  potash,  magnesium,  calcium, 
soil pH and soil granularity. 
-  Map analysis of heterogeneity of each 
monitored element and soil characteristic  
-  Editing agronomical data to GIS 
-  Recommendation for variable rate 
application of lime, phosphor, potash or 
0
1
2
3
4
5
6
7
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
year
E
U
R save EUR per ha / brutto
spend EUR per ha
save EUR per ha/ nettoPrefarm Systems and economical analysis of practical experiences 
[41] 
 
magnesium fertilizer independently 
according to needs. 
1.3  Variable rate application of fertilizer 
-   Variable rate application of P, K, Mg and 
lime fertilizer 
Second year 
2.1.   Data collection 
-  Crop monitoring for Nitrogen variable rate 
application (winter wheat and barley only) 
-  Yield prediction analysis 
-  Editing agronomical data to GIS – crop 
rotation 
-  Recommendation for variable rate 
application of lime, phosphorus, potash or 
magnesium fertilizer independently 
according to needs. 
2.2.  Variable rate application of Nitrogen 
fertilizer (winter wheat and barley only) 
-  Production and quality variable rate of N 
fertilizer 
-  Variable rate application of P, K, Mg and 
lime fertilizer 
Third year  
3.1  Data collection 
-  Crop monitoring for Nitrogen variable rate 
application (winter wheat and barley only) 
-  Yield prediction analysis 
-  Editing agronomical data to GIS – crop 
rotation 
-  Recommendation for variable rate 
application of lime, phosphorus, potash or 
magnesium fertilizer independently 
according to needs. 
3.2  Variable  rate  application  of  Nitrogen 
fertilizer (winter wheat and barley only) 
-  Production and quality variable rate of N 
fertilizer 
-  Variable rate application of P,  K,  Mg and 
lime fertilizer  
 
1. three years period 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit 
in 
EUR/ha 
P  136  80  240  180  15  27  0,36  13,22       
K  134  120  350  200  15  30  0,24  9,65       
Ca  47  500  2000  1400  35  490  0,032  7,37       
Total                       30,24  14  16,24 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit 
in 
EUR/ha 
N  21  210  250  240  8  19,2  0,12  2,30  4    
N  19  220  250  240  7  16,8  0,13  2,18  4    
N  24  200  240  230  10  23  0,15  3,45  4    
Total                       7,94  12,00  -4,06 
Table 2: Cost investment table for 3 x three period in fertilizer saving. 
 
2. three years period 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit in 
EUR/ha 
P  195  80  240  180  13  23,4  0,37  16,88       
K  204  120  350  200  12  24  0,26  12,73       
Ca  57  500  2000  1350  25  337,5  0,033  6,35       
Total                       35,96  9  26,96 Prefarm Systems and economical analysis of practical experiences 
[42] 
 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit in 
EUR/ha 
N  22  230  260  245  5  12,25  0,12  1,47  4    
N  21  235  260  250  4  10  0,13  1,30  4    
N  19  230  270  250  8  20  0,15  3,00  4    
Total                       5,77  12,00  -6,23 
Table 3: Cost investment table for 3 x three period in fertilizer saving. 
 
3. three years period 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit in 
EUR/ha 
P  187  80  240  180  15  27  0,39  19,69       
K  189  120  350  200  16  32  0,48  29,03       
Ca  61  500  2000  1500  30  450  0,023  6,31       
Total                       55,04  9  46,04 
Fertilizer 
% of 
farm 
area 
min. 
rate in 
kg/ha 
max rate 
in kg/ha 
averidge 
in kg/ha 
save 
in %  
save 
in 
kg/ha 
price 
for 1 
kg of 
fert 
EUR 
save 
per ha 
extra 
cost in 
EUR/ha 
profit in 
EUR/ha 
N  22  250  300  270  6  16,2  0,12  1,94  4    
N  21  250  300  270  7  18,9  0,14  2,65  4    
N  24  250  300  270  7  18,9  0,15  2,84  4    
Total                       7,43  12  -4,58 
Table 4: Cost investment table for 3 x three period in fertilizer saving. 
.
The  distribution  of  N  fertilize  is  focused  on  the 
yield and the quality of  yield, so saving is not on 
the first place, however, farmer saved also the same 
fertilizer in the application. 
What about yield? (Graph 4) 
What next? 
Variability between each field showed up during a 
3 three years period (Graph 5)..  
 
 
*yield of sugar beet is recalculate on 16 % of sugar contain and divided by 10 
Graph 4. 
 
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
1999 2000 2001 2002 2003 2004 2005 2006 2007
peas
barley
poppy seeds
winter wheat
rape seed oil
sugar beet*Prefarm Systems and economical analysis of practical experiences 
[43] 
 
 
Graph 5. 
 
X = % of yield index in the time, y= fields 
According to above mentioned figure, variable rate 
application and the fertilizer saving does not cause 
yield homogeneity of each crop, but Theky show up 
very clear which field is more productive and which 
less.  The  farm  management  continues  in  next 
decisions  with  ideas  redistribute  more  a  digger 
amount  of  fertilizer  on  fields  with  a  higher 
productivity and to change the crop rotation system 
according to the produktivity of fields.    
Discusion 
The  farm  management  forms  collect  necessary 
tasks which contain the ownership and the renting 
plan  management  for  soil,  the  monitoring  of 
seedling plan and plant production for each field. In 
the  European  context,  one  of  the  most  important 
results is to explain simply the data of results to a 
final user, and to train  him/her, how to work with 
the system, and what is the benefit from? 
First of all, we have  to pay attention  for  the data 
collection system which is dependent on accuracy, 
density and repetition in time.  An easy work with 
data  in  the  central  database  is  one  of  the  most 
important  characteristic  of  the  system.  The  main 
aim  was  to  prepare  a  solution  accessible  from  an 
office and also from a field. Other advantages of the 
system are following: 
-  transparent results of data analysis (Maps and 
tables), 
-  easy  data  access  (  map  view,  tabs,  statistic, 
new notes), 
-  multifunction  level  of  use  on  a  farm  or 
company  (  chairman,  lawyer,  crop  manager,  
driver), 
-  traceability  –  complete  notes  (crop  plan, 
fertilizer using….), 
-  possibility  of  another  database  connection 
(WMS, cadastral maps…). 
The  Precision  farming  is  a  system  focused  on 
keeping a detail record in farming when each task 
of operation is recorded to the field as the smallest 
element,  but  each  task  is  captured  to  a  specific 
location  (a  part  of  the  field).  The  farmer  can 
achieve a lower cost or to increase a  yield of the 
crop  by  using  this  technology.  The  Precision 
farming  manages  a  very  precise  application  of 
chemicals and fertilizers according to really  needs 
on the field, and by these  methods the farmer can 
decrease also the bad influence of use of chemicals 
in  farming,  which  is  very  important  for  the 
surrounding environment. 
The collaborative environment provides a possible 
area  for  farmers,  EO  data  providers  and  other 
organizations to communicate, share and exchange 
information.  Also,  any  recent  changes  can  be 
notified  to  the  coverage  and  portfolio  of  related 
products and services.  
The implementation of Web based technologies and 
OGC is compliant to WMS and WFS to assist the Prefarm Systems and economical analysis of practical experiences 
[44] 
 
user  in  describing  the  area  of  interest  and  in 
retrieving  appropriate  product  details  from  the 
catalogue. 
Mainly methodologies, which are based on analyses 
of satellite or airborne imagery, offer possibilities to 
start  with  the  precision  farming  without  a  small 
initial  investment  on  the  side  of  farmers. 
Practically,  before  the  service  company  start  to 
present  collected  data  and  results  to  farmers,  the 
data  must  be  taken  and  treated  in  the  central 
database. 
 
Corresponding author:  
Ing Pavel Gnip 
WirelessInfo 
 Cholinská  1048/19, 784 01 Litovel, Czech Republic  
e-mail: gnip@wirelessinfo.cz   
 
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Forestry, Denver, USA 5.-6.11.2001 
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[4]  Charvat at all E-content agriculture applications using wireless communications ITT Baltic April 2002   
[5]  Charvat,  K.  –  Gnip,  P:  GIS  server  for  precision  farming  application  with  mobile  acces,  abstrakt, 
prezentace  IST  –  2000-28177  PREMATHMOD,  workshop  Mobile  Information  System  in 
Agriculture2002, Keszthely, Maďarsko,18.10.2002, CD   
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Charvat at all E-content agriculture applications using wireless communications ITT Baltic

GIS server for precision farming application with mobile acces, abstrakt,

Precision farming trough Internet and mobile communication,

PREFARM – System of precision farming in Czech Republic.

Prefarm Systems and economical analysis of practical experiences

Prefarm Systems and economical analysis of practical experiences

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