Assessment of Agri-Resource Potential of West Georgia and Landscape Zoning for Dissemination Actinidia

Full text

Earth Science
s
2015; 4(5-1): 104-107
Published online July 27, 2015 (http://www.sciencepublishinggroup.com/j/earth)
doi: 10.11648/j.earth.s.2015040501.29
ISSN: 2328-5974 (Print); ISSN: 2328-5982 (Online)
Assessment of Agri-Resource Potential of West Georgia
and Landscape Zoning for Dissemination Actinidia
Seperteladze Zurab
1
, Davitaia Eter
1
, Memarne Guram
2
, Khalvashi Neli
3
, Gaprindashvili George
4
1
Faculty of Exact and Natural Sciences, Tbilisi State University, Tbilisi, Georgia
2
Batumi Shota Rustaveli State University, Institute of Phytopathology and Biodiversity, Batumi, Georgia
3
Batumi Shota Rustaveli State University, Institute of Phytopathology and Biodiversity, Division of Biodiversity Monitoring and Conservation,
Batumi, Georgia
4
Faculty of Exact and Natural Sciences, Tbilisi State University, Institute of Geography, Tbilisi, Georgia
Email address:
zura_sep@mail.ru (S. Zurab), eteri.davitaia@yandex.ru (D. Eter), plantimmunity@yahoo.com (M. Guram), nelikoo@mail.ru (K. Neli),
gaprindashvili.george@gmail.com (G. George)
To cite this article:
Seperteladze Zurab, Davitaia Eter, Memarne Guram, Khalvashi Neli, Gaprindashvili George. Assessment of Agri-Resource Potential of West
Georgia and Landscape Zoning for Dissemination Actinidia. Earth Sciences. Special Issue: Modern Problems of Geography and Anthropology.
Vol. 4, No. 5-1, 2015, pp. 104-107. doi: 10.11648/j.earth.s.2015040501.29
Abstract:
The methodology has been developed and established in West Georgia for agro-resource potential spatial
distribution regularities for ACTINIDIA (according to hypsometric levels and types of landscapes of Georgia). On the basis of a
large amount of data processing and systematization, also different data scattered in various scientific-research organizations
agri-resource potential of West Georgia were determined. For Multiple database creation and processing, based on GIS
technology. Conducted large-scale landscape zoning.
Keywords:
Agro-climatic Zones, Standard-model, Landscape, Multifactor Analysis, Vegetation Period
1. Introduction
Estimation of the agro-resource potential of an area is much
important to rationally grow some or other culture and identify
the potential prospects to improve its productivity (harvest).
The latter depends on many factors, with natural
physical-geographical factor as one of the most important of
them. This factor is multi-factorial and multi-dimensional.
Application of a mathematical method allowing improving the
geographical approach and providing a more objective and
complex estimation of the area in this respect was considered
by us as the most optimal way to solve this complex problem.
This method also facilitates selecting and estimating the areas
with their numerical values varying within a great range and
with different dimensions.
By using the above-mentioned method by the authors [4,5],
the present work accents the kiwi culture commonly spread in
west Georgia in recent period. The experimental plantations of
kiwi (Actinidia chinensis) are grown only in the low- and
middle-mountainous landscape zones of Adjara-Guria
segment, in west Georgia (even at 1200 m asl); however, the
questions of optimal landscapes and zoning of the habitats of
the given culture are not developed yet. With this thought in
mind, we, a group of authors, in cooperation with agricultural
technicians, who are practitioners [2], have developed and
estimated the agro-climatic properties of kiwi culture, selected
and identified the optimal natural conditions (without
agricultural measures) (by designing a virtual standard model)
and provided the landscape zoning of West Georgia by using
GIS-analysis.
The major scientific novelty of the project is selecting and
ranging the areas with the conditions optimal to grow kiwi by
using a mathematical method, in particular, estimating
(selecting and processing) the agro-climatic properties,
designing a virtual standard model and providing the
landscape zoning of the territory based on the proximity to the
virtual standard model what will allow differentiating the
territory for the given culture by considering its potential
validity.
2. Object of Research
West Georgia, with its major part occupied by the
landscapes of humid subtropical Kolkheti lowland has been

Earth Sciences 2015; 4(5-1): 104-107 105
known as a fertile and rich region since the ancient times. In
addition to Kolkheti plain valley, it incorporates the
landscapes of the Kavkasioni in the north, Meskheti ridge in
the south and piedmonts of Imereti plateau and adjacent low-
and average-mountain landscapes in the east. With its peculiar
geographical location and owing to the Great Caucasus
("Kavkasioni") acting as a barrier, diversified relief forms,
hypsometric extension, influence of the Black Sea and, most
importantly, the resultant much favorable soil and climatic
conditions [1,12], the region has rich and diversified nature.
All these factors facilitate to develop subtropical gardening
(citrus-growing and fruit-growing) successfully in the region
[1].
Table 1. Different provisions of the hydrothermal coefficient in the vegetation
period.
Average Value Column2
90 75 50 25 5
1.5 1.0 1.3 1.5 1.9 3.0
2.0 1.5 1.8 2.0 2.6 4.7
2.5 1.9 2.3 2.5 2.9 5.0
3.0 2.2 2.6 3.0 3.4 5.5
3.5 2.5 3.0 3.5 4.0 5.9
Soils of West Georgia mainly set out in the humid
subtropical climate. Precipitation prevalence and the terrain
was caused mainly in the coastal area, wetland soils spread,
On the hills and the foothills of the subtropical organic red and
yellow soils, mountainous part of the clobbered gray, where in
which grow kiwi plantations, in addition to the swamp and
organic soils, due to their heavy loamy soil properties.
The physical and geographical conditions allow us to
determine whether the favorable natural conditions of a
particular agricultural region, particularly in the deployment
and management of high-quality Chinese ACTINIDIA
harvest.
3. Research Methods and Initial Data
The agro-resources of some or other area can be estimated
by using the multifactorial analysis. Therefore, it is important
to use the method allowing most optimal selection of the right
conditions [4]. In this respect, it is important to identify the
leading factors and order them, by considering their functional
priority. Consequently, in estimating the spreading area of
kiwi culture, we think it relevant to fix the weighted distance
from different points to the standard model by considering the
priority of different factors (properties) and to group the
objects depending on their proximity to the standard model.
The research was organized in several stages:
1. Creating the database of the agro-resource potential.
2. By using software MATLAB, calculating the “weighted”
distances from each object to the standard model with
the coefficients of priority, ranging the calculated values
and grouping them by using Sterges formula.
3. Zoning the landscape units with the agro-resource
potential favorable for kiwi to grow [9,10,11] designing
a large-scale landscape map), depending on the
proximity to the standard model, based on GIS-analysis
(Fig. 1).
Figure 1. Landscape and Regions of West Georgia with maximum closeness
to the etalon-object.
The research was based on six major parameters
characterizing the agro-climatic potential of the area in the
warm period of the year: absolute altitude of the location, sum
of active temperature (>10°C), amount of atmospheric
precipitations, hydrothermal coefficient and soil PH value and
prognosis yield per ha.
Data processing was carried out with the mathematical
models in several stages:
- Formation of Matrix
( ) ,
ij n m
a
×
Α =
where
( ); 1, ; 1,
ij j i
a K O i n j m
= = =
(1)
1 2
, ,...,
n
O O O
and
1 2
, ,...,
m
K K K
appropriately determine
objects (territorial units) and selected quantitative
characteristics in accordance with the aim of redistricting
process.
- Data normalizing, because of range of numerical values
variations corresponding to marks and features may differ
from each other by several row.
*
( )
( ) , 1, , 1, ,
j i
j i
j
K O
k O i n j m
K
= = =
(2)
where
*
1 2
max{ ( ), ( ),..., ( )}, 1,
j j j j n
K K O K O K O j m
= =
- Composition of normalizing data matrix
( ) , ( ), 1, , 1,
ij m n ij j i
B b b k O i n j m
×
= = = =
(3)
- Determination of priority coefficient for
i-characteristic
, 1,
j
c j m
=
, where
(4)
1
1,
m
j
j
c
=
=
∑

106 Seperteladze Zurab et al.: Assessment of Agri-Resource Potential of West Georgia and
Landscape Zoning for Dissemination Actinidia
- Formation of normalized values
*
, 1, ,
j
i
j
E
e j m
K
= =
(5)
where
j
E
(
1,
j m
=
) are the components of etalon-object
.
E
- Calculation of ,,weighed’’ distances from object to E
etalon-object in Euclid n dimension space:
2
1
( ) , 1,
m
i j ij j
j
d c b e i n
=
= − =
∑
(6)
- Determination of full range of distance dispersion from
the object to etalon
max min
d d
−
,
Where
max 1 2
max{ , ,..., }
n
d d d d
=
,
min 1 2
min{ , ,..., }.
n
d d d d
=
(7)
By Sturges formula
1 3, 222 log
k n
= +
for n optimal
amount of grouping of objects were determined and
determination of verge of grouping intervals:
max min
,
d d
hk
−
=
(8)
- On the basis of complex characteristics the intervals for
grouping of objects was defined:
min min
( , ), 1, .
rd rd h r k
+ =
(9)
The study was based on agro-climatic potential warm
period defining 6 basic parameters: elevation, the sum of
active temperatures (>100C), atmospheric precipitation,
hydrothermal coefficient, soil PH- indicator and forecast
yield per hectare.
Kiwi (Chinese ACTINIDIA) of the highest, most optimal
agro-climatic, natural conditions and expert analysis on the
recommendation of specialists had developed a virtual
standard-model the following indicators: the absolute height -
400 meters, active temperatures (>100) Subtotal - 35,000,
precipitation (during the warm period) - 1,200 mm,
hydro-thermal coefficient (htc) - 3.0, soil PH- indicator - 6.0,
forecast yield 1 -30 tons per hectare.
Agro-climatic characteristics [6,13] was processed in West
Georgia for 7 regions - Adjara, Guria, Imereti, Samegrelo,
Svaneti, Racha and Abkhazia (Table 2).
Table 2. Hypsometric distribution of agroclimatic properties in the warm period of the year.
Region Objects
Place
Elevation,
m
Sum of Active
Temperatures,
C0
Sum of
Atmospheric
Precipitation,
mm
Hydrother
mal
Coefficient
Soil
PH-indi
cator
Prognosis
Yield, per
ton/ha
Adjara
I Batumi, Kobuleti, Chakvi,
Akhalsheni 30-400 4,000-4,500 1,500 3-3.5 7-8 20–25
II Chakvistavi, Keda 400–700 3,800-4,300 1,400-1,500 2.4-4 5-6.5 10–15
III Khulo, Purtio,
Gomarduli 700-1,200 3,100-3,300 500-650 1.5-2 6-6.5 5–7
Guria
I Ureki, Supsa 5-100 4,100-4,400 1,200-1,400 2.7-3.3 5-7 15–20
II Dablatsikhe, Anaseuli,
Atsana 100-500 4,100-4,200 950-1,150 2.3-2.7 5-5.2 10–15
Imereti
I Samtredia, Vani, Tskaltubo,
Khoni, Sakara, Dimi 30-200 4,500 600-1,000 1.5-2 5-7.5 15–17
II Kharagauli, Sachkhere,
Tkibuli 200-500 3,500-4,000 500-1,000 2-3 5-7 10–12
Samegrelo
I Abasha, Anaklia, Senaki,
Kheta 0-100 4,300-4,600 800-1,100 1.8-2.4 7-7.5 15–20
II Chkhorotsku, Martvili,
Zugdidi 100-700 4,000-4,200 1,000-1,200 2.5-3 5-7 10–15
III Tsalenjikha, Mukhuri,
Lebarde 700–1,500 3,000–3,300 600–700 2–2.5 6–7 5–7
Svaneti I Khaishi, Lentekhi 300-1,000 3,300 760 2.3 7.0 4–5
II Mestia, Becho, Koruldashi 1000-1,700
1,750-2,100 1,700-2,100 2.5-6.5 7-7.5 2–3
Racha-Lechkhumi
I Khvanchkara, Chrebalo,
Tsageri, Lentekhi 500-900 3,000-3,500 650-750 1.8-2.5 6.5-7 10–12
II Kharistvala, Oni, Ghebi,
Shovi, Kherga 900-1,900 1,100-2,200 750-1,300 3.5-7.5 7.5 3–5
Aphkhazeti I
Gagra, Gali, Gudauta,
Gulripshi, Ochamchire,
Sokhumi
30-300 4,000-4,500 850-1,000 1.5-2.5 5-7.5 20–25
II Lata, Kvezani 300-500 3,600-4,000 750-1,450 2.9-3.6 5-7 10–15
As the table shows, closest to the standard model is the
second hypsometric zone of Ajara, Apkhazeti, Guria, Imereti
and Samegrelo (from 100 to 400-500 m); however, the I zone
in Guria region (if ignoring a little too much abundant
moisture in it) is quite close to the II zone with humid
subtropical landscapes (see map zones: 2, 3) of a hilly-Terrace
i
O

Earth Sciences 2015; 4(5-1): 104-107 107
piedmont with Alisols, Cambisols and Raw humus Calcareous
(the later type of soil is particularly widely spread in some
parts of Samegrelo, Imereti and also in part of Apkhazeti). As
for Racha-Lechkhumi and Svaneti, their natural conditions are
less favorable for kiwi to grow and develop, with the I zone
(700-1000 m) with the Kolkheti humid subtropical
mountain-forest landscapes with humid yellow-brown and
Raw humus Calcareous soils being closest to the standard
model (see map zones 4, 5), As for the rest hipsometriul zones
(map # 6, 7, 8, 9, 10) are useless kiwi culture zones (7,8),
therefore are away from Etalon-model (Fig. 2).
Figure 2. Closeness value to the etalon-object according to different altitudes
in terms of agri resource potential4. Conclusion
Several important results were gained as a result of the study:
 The methods to estimate the agro-resource potential of
the territorial units were developed. The methods are
based on the calculation of the weighted distances with a
coefficient of priority of factors to the standard object;
 By using the said method, the regularities in the
territorial distribution of Actinidia Chinensis Planch
culture in West Georgia, hypsometric stages with high
potential, landscape types and regions were identified.
Detected different potential of Hypsometric area,
landscape types and regions;
 Based on the database of the agro-resource potential and
GIS-technologies, a large-scale landscape map of the
territory of West Georgia was designed.
Acknowledgements
This research would not have been possible without the
support of many people and also without using many scientific
researches done by the staff of the Geographical Department
(Faculty of Exact and Natural Sciences) of Ivane Javakhishvili
Tbilisi State University and Institute of Phytopathology and
Biodiversity of Batumi Shota Rustaveli State University. The
authors of the work express their gratitude to all them.
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0 10 20 30 40 50
0
-
30
80-200
500
-
800
1000-1500
>2000
Absolute Height (m)
Clossenes value
to the etalon
object