VIII International Scientific Agriculture Symposium
Jahorina, October 05 - 08, 2017
VIII International Scientific Agriculture Symposium „AGROSYM 2017“
Book of Abstracts Published by
University of East Sarajevo, Faculty of Agriculture, Republic of Srpska, Bosnia
University of Belgrade, Faculty of Agriculture, Serbia
Mediterranean Agronomic Institute of Bari (CIHEAM - IAMB) Italy
International Society of Environment and Rural Development, Japan
Regional Rural Development Standing Working Group (SWG) in Southeastern Europe, Macedonia
Balkan Environmental Association (B.EN.A), Greece
University of Applied Sciences Osnabrück, Germany
Perm State Agricultural Academy, Russia
Voronezh State Agricultural University named after Peter The Great, Russia
Centre for Development Research, University of Natural Resources and Life Sciences (BOKU), Austria
Selçuk University, Turkey
University of Agronomic Sciences and Veterinary Medicine of Bucharest, Romania
University of Valencia, Spain
Faculty of Agriculture, Cairo University, Egypt
Tarbiat Modares University, Iran
Higher Institute of Agronomy, Chott Mariem-Sousse, Tunisia
Faculty of Economics Brcko, University of East Sarajevo, Bosnia and Herzegovina
Biotechnical Faculty, University of Montenegro, Montenegro
Institute of Field and Vegetable Crops, Serbia
Institute of Lowland Forestry and Environment, Serbia
Institute for Science Application in Agriculture, Serbia
Agricultural Institute of Republic of Srpska - Banja Luka, Bosnia and Herzegovina
Maize Research Institute “Zemun Polje”, Serbia
Faculty of Agriculture, University of Novi Sad, Serbia
Institute for Animal Science, Ss. Cyril and Methodius University in Skopje, Macedonia
Academy of Engineering Sciences of Serbia, Serbia
Balkan Scientific Association of Agricultural Economics, Serbia
Institute of Agricultural Economics, Serbia
Editor in Chief
CIP - Каталогизација у публикацији
Народна и универзитетска библиотека
Републике Српске, Бања Лука
INTERNATIONAL Scientific Agricultural Symposium "Agrosym
2017" (8 ; Jahorina)
Book of Proceedings [Elektronski izvor] / VIII International
Scientific Agriculture Symposium "Agrosym 2017", Jahorina,
October 05 - 08, 2017 ; [editor in chief Dušan Kovačević]. - East
Sarajevo =Istočno Sarajevo : Faculty of Agriculture =Poljoprivredni
Način pristupa (URL):
BOOK_OF_PROCEEDINGS_2017_FINAL.pdf. - Bibliografija uz
radove. - Registar.
ECONOMIC PARAMETERS OF SOUR CHERRY PRODUCTION IN
POMORAVLJE REGION, SERBIA
Jasmina FILIPOVIC1, Sladjan STANKOVIC2*, Dragan RAHOVIC2, Ivana BAKIC2, Robert
RADISIC2, Vedran TOMIC2
1Agricultural Advisory Service of Jagodina, Jagodina, Serbia
2Institute for Science Application in Agriculture, Belgrade, Serbia
*Corresponding author: email@example.com
Sour cherry, after plums and apples, holds third place in Serbia in terms of volume and area
of production. Serbia, within the CEFTA countries, is the largest exporter of sour cherries
(approx. 4.4% of total exports of fruit in Serbia). Farmers need to be introduced to the economic
effect of a sour cherry production and gross margin (GM). GM is a quick and efficient indicator for
comparing production lines in different conditions and it was used as an indicator of economic
effects of production. Data for GM calculations were collected through a questionnaire from
sour cherry production farm in Pomoravlje region in the period 2011-2014. For calculating the
basic elements of gross margin, the following data were used: data on yield and price, by-product
price, quantity and value of fertilizers, pesticides, and fuel, and costs for contracted services. GM
represents the total value of a production line subtracted by the direct costs for the production line
in question (purchased inputs). Price of sour cherry shows considerable variability during the
observation period (Cv= 54.95 %). The average price of sour cherries in the reporting period was
approx. EUR 530/t, while the maximum price recorded was almost twice higher (1,016 EUR/t).
In contrast to the yield, price showed significantly more pronounced tendency to increase - an
average annual rate of 9.72%. The average value of total variable costs was approx. 1406
EUR/ha. A positive feature of variable costs of the sour cherry production is that they show a
tendency to decrease, with an average annual rate of 2.64%. The average value of gross margin in
the observed period amounted to approximately 4013 EUR/ha. The value of rate of change shows
that the gross margin year on year growth records an average of 11.71% annually.
Keywords: gross margin, sour cherry, variable costs, yield, price.
After plum and apples, sour cherry holds the third place in Serbia on the basis of land area
and production. The areas under the sour cherries in Serbia in 2010 amounted to close to
15,000 hectares, from which the area was reduced to about 14 000 hectares, which has been a
constant area under these plants for three years. Total yields in 2014 were 22.4% lower than
in 2013. Average yields vary, regardless of the constant area, and in 2014 they were 33.7%
lower than in 2013. The average cherry yield in the observed period is 7.76 t/ha in Serbia.
The purchase of sour cherries is mainly focused on refrigerating and exports. Sour cherry is
also used in processing as frozen, for juices and other canned products. The least is used for
consuming and selling on the market. In 2014, the purchase of cherries was lower by 25%
than in 2013, and 91.6% was used for processing from the total quantity purchased.
The average producer prices for sour cherries are the lowest in relation to all European
countries (except Bulgaria and Macedonia). Within CEFTA countries, Serbia is the largest
exporter of sour cherries, and even within the EU countries, only Poland, Bulgaria and
Hungary export more than Serbia. Sour cherry participates in about 4.4% of total fruit exports
in Serbia. In 2014 the largest quantities of cherries are exported to Germany, Russia, France,
then to Austria, the Netherlands and Italy.
Significant improvements in the production of sour cherries could be achieved by
intensifying production and selecting the appropriate market, as well as selecting the
appropriate land and applying adequate agro-technology.
The region of Sumadija and Western Serbia, in relation to Serbia, has an area of 17% under
sour cherry. The area in the region has been growing for three years. The total yields vary
from year to year, and the average yield in the observed period is 7.84 t/ha and is slightly
higher than the average yield in Serbia (7.76 t/ha).
Gross margin (GM) was used in this paper as an indicator narrower than an analytic
calculation and it shows the difference between the cost of production and direct costs, which
makes it an important tool from the economic aspect (Barnard and Nix, 1979; Anđelić et al.,
2010; Stanković et al., 2015; Filipović et al., 2015). We used the methodology for calculation
of a standard GM as a scientific tool to support technical and economic orientation of farms,
in order to analyze economic results in fruit production.
Materials and Methods
Data on sour cherry production were collected from a questionnaire survey conducted on a
representative farm in Pomoravlje region during the period 2012–2014. GM calculations, as a
standard descriptive statistic method, were used as an indicator of economic effects of sour
cherry production. Basic elements for gross margin calculation were used: yield and price;
quantity and value of fertilizers, pesticides, and fuel, as well as costs of contracted services.
Original data were collected in Serbian dinars (RSD), but all prices are given in EUR. Prices
were calculated based on Serbian National Bank average exchange rate against major world
currencies for particular year (www.nbs.rs/internet/cirilica/scripts/kl_prosecni.html).
Indicators of the value of production, total variable costs and gross margin were calculated
according to the methodology provided by the website of the Serbian Agriculture Advisory
Service (www.psss.rs). We used Microsoft Excel for data processing and GM calculating; The
program was set to calculate the average value of each element of the calculation. GM is the
difference of total income and total variable costs (TVC), achieved in a line of agricultural
production per unit of production area (in crop production). We also calculated the critical
values (Stanković et al., 2015, Filipović et al., 2016) with the aim of estimating results of
production under conditions of uncertainty. Critical values are those values at which the GM
equates to zero.
Results and Discussion
Values of basic statistical indicators of sour cherry production parameters in farms,
monitored by the advisory service in the period 2011-2015 are shown in Table 1. The average
yield of sour cherry was 11.2 t/ha, ranging from minimum 7 to maximum 15 t/ha. For sour
cherry yield, it can be noticed that it shows oscillations during the analyzed period. The rate
of change in value is negligible and amounts to only 0.06% per year.
The price of sour cherry shows significant variability during the observed period (Cv =
54.95%). The average price of sour cherries in the analyzed period was close to 528.82
euro/t, while the maximum price recorded was almost twice as high as 1,013.57 euros/t. The
price, unlike yield, shows a significantly more pronounced tendency of growth, which is an
average annual rate of 9.72%.
The average value of total variable costs in the analyzed period was at about 1402.26
euros/ha. The positive characteristic of variable costs in cherries is that they show a tendency
to decrease, on average annually at the rate of 2.64%.
The average value of the gross margin in the analyzed period amounted to about 4000
euros/ha. The value of the change rate shows that the gross margin grows annually on an
average of 11.71%.
For efficient cost management and decision-making, GM is adequate analytical basis. In
addition for such analysis advisors requires data on what, when and how much of something is
produced, so that one can compare the performance of individual production lines and make
decisions on the future structure of production (Munćan and Živković, 2006; Munćan et al.,
2013). Gross margin can be used as a criterion for determining the structure of financial and
performance analysis. GM is not the most important analytical model, but it is a good starting
point. It also requires relatively simple data and methodology.
The above characteristics of the sour cherry production parameters are given on the basis of
the calculated values of the basic indicators of the descriptive statistics shown in Table 1.
Table. 1. Basic indicators of the production parameters of sour cherry (2011-2015).
of variation -
The rate of
Total Variable Costs
The gross margin is to a certain extent the result of the impact of yield, prices and variable
costs, and accordingly regression analysis quantified the impact of these factors on its value.
The change in the gross margin was 97.8% explained by the impact of the observed factors.
The results of the analysis show that with the increase in the yield of sour cherries by 1 t/ha,
the gross margin is increased by 756.65 euros/ha. Variable costs have a negative impact on
the gross margin of sour cherries. However, the results of the estimated regression model
show that the impact of variable costs is not statistically significant.
The values of standardized regression coefficients (Beta values) show that the greatest
relative impact on the change in gross margin is the price of cherry, and the smallest relative
impact has variable costs and it is not significant.
Due to the insufficient number of observation units, it was not possible to check the
significance of the difference in gross margins in observed years, by t-test, with the value of
the gross margin in 2015. During 2013 and 2014, the number of sour cherries farms was
increased, and it was possible to carry out the test. The results of the test (Table 2) show that
the gross margin achieved in 2014 is statistically significantly different from the gross margin
in the control year.
Тable 2. T-test of gross margin values.
* p < 0.05, significant difference between the calculated values
Price of sour cherry shows considerable variability during the observation period (Cv= 54.95%).
The average price of sour cherries in the reporting period was approx. EUR 530/t, while the
maximum price recorded was almost twice higher (1,016 EUR/t). In contrast to the yield, price
showed significantly more pronounced tendency to increase - an average annual rate of 9.72%.
The average value of total variable costs was approx. 1406 EUR/ha. A positive feature of variable
costs of the sour cherry production is that they show a tendency to decrease, with an average
annual rate of 2.64%. Occasional increases or decreases in the gross margin of the plant
production lines in the years 2011 to 2015 have the highest increase in the price of products
(2012), or the decrease in product prices (2014).
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