Yevhenii
Domaratskyi
Kherson
State Agrarian University, Ukraine
E-mail: jdomar1981@gmail.com
Anastasia
Kaplina
Kherson
State Agrarian University, Ukraine
E-mail: kaplina.anastasia.ivanovna@gmail.com
Olga
Kozlova
Kherson
State Agrarian University, Ukraine
E-mail: kozlova_olga_zikova@gmail.com
Nonna
Koval
State
Agrarian and Engineering University in Podilya, Ukraine
E-mail: nonnakoval69@gmail.com
Andrii
Dobrovolskyi
State
Institution "Mykolayiv State Agricultural Research Station Institute of
Irrigated Agriculture National Academy of Agrarian Sciences of Ukraine", Ukraine
E-mail: dobrovolskiy.andrey.v@gmail.com
Submission: 8/10/2020
Revision: 8/17/2020
Accept: 8/26/2020
ABSTRACT
The study presents economic substantiation of applying environmentally friendly plant growth stimulators in combination with biological fungicides in sunflower production under conditions of the South of Ukraine. The field research was conducted at Kherson State Agricultural University (Ukraine) in 2017 – 2019 under conditions of dark chestnut alkaline soils with the humus content of 2.5% in the plough layer. The results of the three-year field research prove that the net profit reached the absolute maximum in the variant of the hybrid LG 5580 under conditions of applying the bio-fungicide Fitotsyd-r with the stimulator Ahrostymulin at the stage of budding and amounted to $1081/ha. In this case the cost price was the least – $141.6/ha, and the profitability level was the highest – 196%. In the areas sown with the hybrid Tunca the variant with the combination of Fitotsyd-r and the growth stimulator Ahrostymulin also provided a positive result, but it yielded a little to the combination of the preparations Fitosporyn / Ahrostymulin: the net profit was $579.7/ha, the price cost made $203.4/ha and the profitability was 106 %.On the whole this analysis makes it possible to maintain that additional costs related to purchasing and applying fertlizers are totally compensated owing to the cost of an increase in the yield.
Keywords: Environmentally friendly fertilizers; Sunflower; Production costs; Product cost; Net profit; Profitability
1.
INTRODUCTION
An
important place in increasing yields and improving product quality belongs to
the improvement of technologies for growing agricultural crops. Success in
obtaining high stable yields in the face of rising energy prices can be
achieved with the help of resource-saving technologies, which include a high
level of agricultural technology, optimal fertilization rates and an integrated
system for protecting plants from diseases, weeds and pests, and the
introduction of new varieties and hybrids.
Modern
conditions of agricultural production require measures to ensure the most
realistic level of crop productivity, high quality grain and seeds, while
reducing the cost of growing them. One of the most effective measures for
solving these problems in the cultivation of agricultural crops is the use of
biological growth-regulating preparations for inoculation of seeds and foliar
feeding of plants.
Currently,
the use of biological products is an integral aspect of modern crop production,
they optimize plant nutrition, stimulate their development and increase
productivity. In the context of climate change, taking into account modern
scientific and practical approaches, taking into account the yield potential of
modern varieties and hybrids, an important problem is the search for adaptive
elements of their cultivation technologies, which provide an increase and
stabilization of the productivity of agricultural crops by years of cultivation
using modern multifunctional growth-regulating biological preparations, for
which and research was directed.
2.
LITERATURE REVIEW
The
means of regulation of nutrient content in soils, nutrient intake by plants
with different ratio is a system of nutrition regime. It has a radical impact
on the level of supplying plants with mineral elements. But practice shows that
mineral fertilizers do not solve all the problems related with the optimization
of nutrition regime. During their growing season plants are under stress for
quite a long time, their nutrition under such environmental conditions becomes
less efficient (JASPERS; KANGASJÄRVI, 2010; CHIAPPERO, et al., 2019).
The
task of a farmer is to provide suitable conditions for plants to overcome
stress as fast as possible (RADY, 2012; HANSERUD et al., 2018).
There
is a number of factors causing stress-reactions of plant organisms during the
growing season. By the nature of impact they are divided into chemical (salts,
gases, xenobiotics); biological (negative impact of pests, pathogenic agents,
competition with other plants) and physical (excess or deficiency of moisture,
temperature regime, light and radioactivity) (WHIPPS,
1997; GOSWAMI; DEKA, 2020).
Under
these conditions it is necessary to apply complex multi-functional fertilizers,
containing mixtures of organic, humic and fulvic acids, a number of micro-elements in a chelated form
in their formulation causing their fungicide action and activating
microorganisms. It ultimately leads to stimulation of growth processes and
contributes to the overcoming stress phenomena of plant organisms (KUMAR et al., 2015; DOMARATSKIY, et al., 2018; DOMARATSKIY, et al. 2019).
Two
trials were conducted on sunflower (Helianthus annuus
L., ‘Dwarf Sunsation’) to compare the influence and
interaction of arbuscular mycorrhizal fungi (AMF) inoculation with organic and
conventional synthetic fertilisers on plant growth and development.
Commercially produced AMF was applied as a spore application with liquid
organic fertiliser (Quadshot®) applied at 0 and
20 L ha-1 in Trial 1; and 0, 20 L ha-1 and
40 L ha-1 in Trial 2, or liquid synthetic (inorganic) fertiliser
(SF) applied at 0 or 100% concentration (Hoagland's solution regular strength
with low P).
Results
showed limited interaction between AMF and fertiliser type. Sunflower plants
inoculated with AMF and synthetic fertiliser had greater plant height and stem
diameter in Trial 1 and leaf chlorophyll content at various assessment times in
both trials. The presence of mycorrhizal hyphae and arbuscules
increased in sunflower plants grown with AMF inoculation and organic
fertiliser. There was a strong treatment influence of AMF inoculation on plant
height in Trial 2, and number of nodes, flower head diameter, AMF colonisation
and AMF structures in both trials. In addition, SF increased the leaf
chlorophyll content, number of nodes and flower head diameter in both trials,
and flower number in Trial 2 (ABOBAKER, et al., 2018).
Plants
are exposed to diverse abiotic stresses like drought, heat, salinity, and
high-metal concentrations at different stages of their life cycle. As
protection against stress, plants release signaling
molecules that initiate a cascade of stress-adaptation responses leading either
to programmed cell death or plant acclimation. application of exogenous NO
alleviates the negative stress effects in plants and improves antioxidant
activity in most plant species. In addition, S-nitrosylation
and tyrosine nitration are two NO-mediated posttranslational modification. All
these factors are important in protecting plants from diverse stresses and vary
with the species (NABI, et al., 2019).
The scientific
research conducted in North America establishes that plant growth regulators
applied in low concentrations are able to affect the division and growth of
cells, their structure and functioning (SMALL; DEGENHARDT, 2018). Direct application of such natural
hormones and their synthetic analogs to plant stems,
leaves and flowers increases their resistance to biotic and abiotic
environmental factors, improves drought-resistance of crops and water-use
efficiency (ROSTAMI; AZHDARPOOR, 2019). The studies show that such fertilizers
are capable of increasing nitrogen use efficiency, contribute to an increase in
root weight and also stimulate the growth and development of lateral roots,
assist in enhancing photosynthesis. Organic biostimulants
also prove to be helpful to affect plant physio-biochemistry and antioxidative defense system (REHMAN, et
al. 2018; GUPTA, et al.
2019).
These
substances are usually applied in agriculture, viticulture and horticulture to
increase yields under conditions of low agricultural background, moisture
deficit and other unfavorable environmental factors (SIDDIQI;
HUSEN, 2017; ADNAN et al., 2019). Beyond the inhibitory action
against the gibberellin biosynthesis, some plant growth retardants (PGRs) can
play an important role in regulating plant responses to abiotic stress through
the induction of different tolerance mechanisms (KARIMI, et al. 2019).
Brassinosteroids
(BRs) are considered as the 6th group of plant growth regulators with
significant growth promoting activity. BRs were initially extensively studied
for their profound growth promoting physiological responses viz., growth,
yield, seed germination, photosynthesis, senescence, photomorphogenesis,
flowering etc.
BRs have been further explored for
stress-protective properties in plants against a number of abiotic stresses
like heat, chilling, freezing, drought, flooding, oxidative, salt, allelochemicals, radiation, light, wind, heavy metals
stresses etc. It can be aptly stated that BRs induce plant tolerance to a wide
spectrum of stresses. The ever-changing environmental conditions are causing
serious damages to the plants as the present stressful environmental conditions
are posing unrepairable morphological and anatomical changes wherein the growth
and yield of plants is being greatly hampered (VARDHINI, 2017).
Ukraine
is one of the leaders in the world export of the products of sunflower
processing. The world market expects to receive 5.1 million tons of Ukrainian
sunflower oil this season that is by 16% more than the rate of the previous
year. An increase in
sunflower concentration in the structure of sown areas to 35% will have a
negative impact on productivity that will decrease in all biological and
economic groups. The gross yield of grains will fall from 27.0 to 20.9 million
tons, and there will be an increase in that of sunflower seeds – from 4.5 to
5.8 million tons. Under such conditions the total cost of gross
production of grain and oil crops will fall by $0.25 billion (from $3.04 to
$2.79 billion).
At
first sight the scheme of maximum use of sunflower in crop rotation is not
threatening, but this approach is certainly insecure in terms of increasing
effect of droughts and spread of specific diseases and pests (MOKLYACHUK et al,
2019).
Crop
yield stability in agricultural production aimed at meeting demands of a
continuously increasing population of the planet is possible only under
conditions of applying fertilizers containing basic nutrients for plants.
However, the use of such chemical substances has a negative impact on the environment
and human health. Therefore, application of micro-fertilizers of biological
origin is considered to be the best substitute for chemical fertilizers as an
environmentally friendly method of growing crops and increasing soil fertility.
These
preparations intensify growth processes of plant organisms by means of
different direct and indirect mechanisms of plant growth stimulation such as
biological nitrogen fixation, production of various plant growth hormones,
different hydrolytic ferments etc. Application of biological preparations
increases the potential of vital nutrients supply in appropriate amounts to
boost crop yields without damaging the environment (DIVJOT et al 2020).
The
purpose of the study is to substantiate an economic component
of using environmentally friendly preparations in technological schemes of
sunflower production.
3.
MATERIALS AND METHODS
The
field research was conducted in the research field of Kherson State
Agricultural University (GPS-coordinates: 46.699024, 32.451419) in 2017 – 2019.
The soil on the research plots is dark chestnut alkaline. The humus content is
2.5% in the plough layer of the soil, the content of slightly hydrolyzed nitrogen is 35, the content of movable
phosphorus – 32 and that of metabolic potassium – 430 mg/kg of the soil.The density of one-meter layer of the soil is 1.35,
and its solid phases are 2.66 g/cm3, the general porosity – 49–50%. The
reaction of the soil solution in the topsoil is close to neutral (рН 7.0). It is alkaline closer to the profile –
(рН 7.4 – 7.9).
The
hydrolytic acidity is 0.36–1.9 mg-eq per 100 g of the
soil. The soil permeability for the first hour of absorption is 1.3-2.2 mm/min.
Groundwater is deeper than 5 m and does not affect soil-formation processes. The
climate is moderate and arid. Sowing of sunflower was carried out at the
beginning of the optimal time in the last decade of April. The plants grew
without irrigation.
The
average annual air temperature is 10.30 С, and accumulation of active air
temperatures starts in the 3rd decade of March and finishes in the 2nd decade
of November.The experimental research was carried out
by means of a tree-factor field experiment: Factor А – preparations: – control (clean water), Fitosporyn, Fitosporyn \ Hart
Super, Fitosporyn / Ahrostymulin,
FitoHelp, FitoHelp \ Hart
Super, FitoHelp \ Ahrostymulin,
Fitotsyd- r, Fitotsyd –r \
Hart Super, Fitotsyd-r \ Ahrostymulin;
Factor В – sunflower hybrids of
the company “Limagrein” (Tunca,
LG 5580); Factor С – the period of applying preparations (seed treatment,
the stage of budding).
The
seeds were treated according to the research scheme – a day before seeding, the
plant treatment – at the stage of budding (9–10 pairs of true leaves). Harvesting
and accounting of the crop was carried out mechanically using a combine
harvester with a device for mowing sunflower. The plots were placed by the
block-splitting method. The exchange rate of the NBU was 1$ – 24.32 UAH.
4.
RESULTS AND DISCUSSION
Application
of bio-preparations is related to the necessity of increasing production costs anf. bio-fertilizers are substances with a low selling
price. The calculation of the cost of fertilizers for treating sunflower seeds
and plants is given in Table 1.
It
is necessary to add the cost of the crop treatment to the obtained results.
Spraying the crops with 200 l/ha of the treatment solution costs $11.5/ha.
Therefore, the total costs of applying Fitosporyn
will be $14.1/ha; Fito Help –$19.4/ha; Fitotsyd-R – $15.4/ha.
Table 1: Calculation of the cost of fertilizers
(prices on January, 1st 2019)
Fertilizers |
Market price, US
dollar/L |
The dose of the fertilizer |
The cost per 1 ha,
US dollar |
||
Per 1 t of seeds, l |
Per 1ha of crops, l |
Seed treatment |
Plant treatment |
||
Fitosporyn |
6.6 |
0.15 |
0.4 |
0.1 |
2.6 |
Fito Help |
15.8 |
0.8 |
0.5 |
1.2 |
7.9 |
Fitotsyd-R |
13.2 |
0.15 |
0.3 |
0.2 |
3.9 |
Hart Super |
33.7 |
0.02 |
0.8 |
0.1 |
26.9 |
Ahrostymulin |
79 |
0.02 |
0.2 |
0.2 |
15.8 |
Source:
Prepared by the authors (2019)
The stimulators were applied with
bio-fungicides, therefore there were not additional costs.
The main aim of economic evaluation
is to compare the product cost and production costs (Table 2).
Table 2: Sunflower product cost depending on
bio-fertilizers (average for 2017–2019)
Fertilizers |
The period of applying |
Tunca |
LG 5580 |
||||
Productivity, t/ha |
The cost of 1 t of seeds, US dollar |
The product cost, US dollar/ha |
Productivity, t/ha |
The cost of 1 t of seeds, US dollar |
The product cost, US dollar/ha |
||
Control (clean water) |
2.26 |
419.7 |
948.6 |
2.8 |
419.7 |
1179 |
|
Fitosporyn |
seeds |
2.4 |
419.7 |
1007 |
2.9 |
419.7 |
1200 |
budding |
2.5 |
419.7 |
1070 |
3.3 |
419.7 |
1406 |
|
Fito Help |
seeds |
2.4 |
419.7 |
1020 |
2.9 |
419.7 |
1196 |
budding |
2.5 |
419.7 |
1057 |
3.4 |
419.7 |
1423 |
|
Fitotsyd-R |
seeds |
2.3 |
419.7 |
982 |
2.9 |
419.7 |
1221 |
budding |
2.4 |
419.7 |
1003 |
3.4 |
419.7 |
1422 |
|
Fitosporyn / Ahrostymulin |
seeds |
2.5 |
419.7 |
1049 |
3.3 |
419.7 |
1376 |
budding |
3.0 |
419.7 |
1267 |
3.6 |
419.7 |
1532 |
|
Fitotsyd-R / Ahrostymulin |
seeds |
2.5 |
419.7 |
1049 |
3.4 |
419.7 |
1439 |
budding |
2.7 |
419.7 |
1125 |
4.0 |
419.7 |
1632 |
Source:
Prepared by the authors
The calculation of the product cost
with the determination of quality indexes was done for the sunflower with the
fat content of 48%. This result was provided by the laboratory of the LLC “Nibulon”. If oil fat is lower by 1%, the price will be
lower by 1/48*100 = 2.08%, and vice versa, the higher oil fat content is, the
higher the price will be. But currently there is not such a system, therefore
we used one price for all cases – $419.7.
An important element of economic
analysis is the calculation of direct production costs. At first, according to
the regulations, we calculated the total costs for growing, harvesting and
transporting sunflower products and additional costs related to purchasing and
applying fertilizers, and also, to harvesting and transporting additional
products. The seed cost of the hybrids Tunca – $131.6
per the sowing unit and LG 5580 – $135.8 per the sowing unit are also referred
to the difference in the costs.
The production costs of the variants
in the experiment were equal to $508.9/ha. In our further calculations we added
the cost of additional expenses, mentioned earlier, to this sum. Thus, the
level of the costs for each variant of the experiment is the following (Table
3).
Table 3: Level of the direct production costs
for sunflower depending on the hybrids and fertilizers (average for 2017–2019),
US dollar/ha
Fertilizers |
Periods of application |
Tunca |
LG 5580 |
||||||
Total costs |
Purchasing and applying fertilizers |
Additional harvesting |
In total |
Total costs |
Purchasing and applying fertilizers |
Additional harvesting |
In total |
||
Control (clean water) |
508.9 |
- |
- |
508,9 |
510.6 |
- |
- |
510.6 |
|
Fitosporyn |
1* |
508.9 |
0.1 |
6.0 |
515,0 |
510.6 |
0.1 |
10 |
520.7 |
2* |
508.9 |
14.1 |
12.3 |
535,3 |
510.6 |
14.1 |
14.6 |
539.3 |
|
Fito Help |
1 |
508.9 |
1.2 |
5.1 |
515,2 |
510.6 |
1.2 |
8.3 |
520.1 |
2 |
508.9 |
19.4 |
13.0 |
541,3 |
510.6 |
19.4 |
16.5 |
546.5 |
|
Fititsyd-R |
1 |
508.9 |
0.2 |
5.3 |
514,4 |
510.6 |
0.2 |
7.7 |
518.5 |
2 |
508.9 |
15.4 |
13.9 |
538,2 |
510.6 |
15.4 |
17.3 |
543.3 |
|
Fitosporyn / Ahrostymulin |
1 |
508.9 |
0.28 |
15.9 |
525,08 |
510,6 |
0.28 |
16.7 |
527.6 |
2 |
508.9 |
29.9 |
18.1 |
556,9 |
510.6 |
29.9 |
21.1 |
561.6 |
|
Fititsyd-R / Ahrostymulin |
1 |
508.9 |
0.37 |
15.1 |
524,37 |
510.6 |
0.37 |
19.7 |
530.7 |
2 |
508.9 |
19.4 |
16.7 |
545 |
510.6 |
19.4 |
20.8 |
550.8 |
: 1* – seed treatment; 2* –
plant treatment at the stage of budding
Source:
Prepared by the authors
The difference in the direct
production costs between the control and the research variants reaches the
maximum of $459.6 per hectare in the hybrid Tunca,
and $5.1 per hectare in the hybrid LG 5580. It is worth noting that we
calculated only direct production costs without considering the overheads:
salaries for managers, tax payments, advertising, sales etc. (Table 4).
The investigation of the degree of
impact of these factors on economic efficiency is a complicated but a very
important stage in the development of every enterprise in particular and
Ukraine AIC on the whole.
Examining the experience of
agricultural activity and the level of profitability of agricultural production
we maintain that it is necessary to create a correlation and regression model
of profitability of sunflower production with application of bio-preparations.
Table 4: The basic economic indicators of
sunflower production with application of bio-preparations (the average for
2017-2019)
Fertilizers |
Periods of aplyication |
Tunca |
LG 5580 |
||||||||
Production costs, US dollar/ha |
Product cost, US dollar/ha |
Net profit, US dollar/ha |
Product cost price, US dollar/ha |
Relative level of profitability,% |
Production costs, US dollar/ha |
Product cost, US dollar/ha |
Net profit, US dollar/ha |
Product cost price, US dollar/ha |
Relative level of profitability,% |
||
Control (clean water) |
508.9 |
948.6 |
438.4 |
225.2 |
86 |
510.6 |
1179 |
668 |
181.7 |
131 |
|
Fitosporyn |
seeds |
515.1 |
1007 |
492.3 |
214.6 |
96 |
520.7 |
1200 |
679.7 |
182.1 |
131 |
budding |
535.5 |
1070 |
534.8 |
210.1 |
100 |
539.4 |
1406 |
866.7 |
161.0 |
161 |
|
Fito Help |
seeds |
515.3 |
1020 |
504.6 |
212.1 |
98 |
520.1 |
1196 |
676.1 |
182.5 |
130 |
budding |
514.4 |
1057 |
516.3 |
214.8 |
95 |
546.5 |
1423 |
876.4 |
161.2 |
160 |
|
Fitotsyd-R |
seeds |
514.5 |
982.2 |
467.6 |
219.9 |
91 |
518.5 |
1221 |
702.9 |
178.1 |
136 |
budding |
538.4 |
1003 |
464.7 |
225.2 |
86 |
543.4 |
1422 |
879.5 |
158.9 |
162 |
|
Fitosporyn / Ahrostymulin |
seeds |
525.2 |
1049 |
524.1 |
210.0 |
100 |
527.6 |
1376 |
849 |
160.8 |
161 |
budding |
557.0 |
1267 |
710.5 |
184.4 |
127 |
561.5 |
1532 |
970.4 |
153.8 |
173 |
|
Fitotsyd-R / Ahrostymulin |
seeds |
524.5 |
1049 |
524.8 |
209.7 |
100 |
530.7 |
1439 |
908.9 |
154.7 |
171 |
budding |
545.1 |
1124 |
579.7 |
203.4 |
106 |
550.8 |
1633 |
1081 |
141.6 |
196 |
Source:
Prepared by the authors (2019)
The data of the field research for
2017-2019 was used to conduct this research and create the model.
The developing multiple regression
taking into consideration the profitability of sunflower production Dependent variable
was used to determine the profitability of sunflower. This index was chosen
because it reflects efficiency and appropriateness of agricultural activity. In
order to create a multi-factor correlation and regression model we suggested
using three independent variables:
Х1 – productivity, c/ha (an indirect index of soil fertility),
Х2 – production costs (US dollar per hectare), Х3 – the price of
the products sold (US dollar for 1 centre) (an indirect index of product
quality).
The multiple regression was
performed on the basis of the data of the field research conducted in the
research field of Kherson State Agricultural University in 2017 – 2019.
The model of the multifactor linear
regression was created by means of the statistical method for measuring
correlations (correlation and regression analysis).
To calculate the correlation
coefficient, the following formula is used (by the example of calculating the
correlation х2у):
|
(1) |
The calculations of the correlation
coefficients (the matrix of the pair correlation) are given in Table 5. The
proximity of the correlation coefficients to 1 between some factors indicates
to a strong connection between them or its multiplicative character.
Table 5: Matrix of the pair correlation
Tunca |
у |
х1 |
х2 |
х3 |
у |
1 |
0.962 |
0.837 |
0.671 |
х1 |
0.962 |
1 |
0.833 |
0.847 |
х2 |
0.837 |
0.833 |
1 |
0.602 |
х3 |
0.671 |
0.847 |
0.602 |
1 |
LG 5580 |
у |
х1 |
х2 |
х3 |
у |
1 |
0.988 |
0.270 |
0.821 |
х1 |
0.988 |
1 |
0.367 |
0.899 |
х2 |
0.270 |
0.367 |
1 |
0.584 |
х3 |
0.821 |
0.899 |
0.584 |
1 |
Source:
Prepared by the authors (2019)
Considering the values of the matrix
of the correlation coefficients can draw a conclusion that the most significant
factors affecting profitability are the following: productivity, the price of
the products sold and production costs.
The initial factors were the ones
having the coefficient of the pair correlation within the range of 0.4 to 0.9.
The profitability of sunflower was chosen as a dependent variable, productivity
per hectare, production costs and the price for 1 t were chosen as independent
variables. First of all, assumed that correlation of the dependent variable
with other variables is linear, i.e.
У
= а0+ а1х1+а2х2+а3х3 |
(2) |
Unknown coefficients are determined
by means of the method of least squares the essence of which is to minimize the
sum of the squares of the deviations of the actual data from the theoretical
data, obtained by the regression equation. The minimization criterion looks
like this:
|
(3) |
Considering the function S as the
function of the parameters а0, а1, а2 and making mathematical
transformations (differentiations), we have a system of equations:
|
(4) |
Transforming this system, we have
obtained a system of normal equations for the stage of seeds. Solving it we
find necessary coefficients. On this basis we have obtained the function for Tunca and LG 5580:
У = 48.507 +63.369х1 – 0.0041х2 – 0.005х3
У = 117.977 +77,83х1 – 0.017х2 +6.84х3
The most complicated step is
interpreting the equation, i.e. translating it from the language of statistics
into the language of economics. The regression coefficient – the parameter
а0 is a reference point in the model on the diagram of the correlation field;
the parameters а1-а3 show how the values of the dependent variable
change on the average when the independent variable increases by the unit of
its measurement.
The more the value of the regression
coefficient is, the more considerable impact this factor has on the dependent
variable. The sign before the regression coefficient indicating to the
character of the impact on the dependent variable has special importance. The
coefficient of х1 is equal to 77.83. It means that the dependent variable
will increase by 77.83% when the productivity increases by 1%, the
profitability will increase by 0.017% when the production costs per 1 t
decrease by 1% and the profitability will increase by 6.84% when the selling
price increases by 1 %.
Therefore, it is necessary to check
the adequacy of this model. The following variants are possible:
- This
model is adequate on the whole on the basis of checking it by the F-test of Fisher, and all the
regression coefficients are significant. Such a model can be used for making
decisions and creating forecasts;
- The model
is adequate by the F-test of Fisher, but some regression coefficients are
insignificant. In this case the model is suitable for making some decisions,
but it is not good for creating forecasts;
- The model is adequate by the F-test of
Fisher, but all the regression coefficients are insignificant.
Therefore, the model is considered
as totally inadequate. The coefficient of multiple correlation is 0.97,
indicating that there is correlation of the dependent variable with the
independent variables. But we cannot draw conclusions about the adequacy of the
model on this basis.
The checking the adequacy of the
model with testing the significance of each regression coefficient was done by
means of Student’s t-test:
|
(5) |
The coefficient of the model will be
considered as statistically significant if tр≥
tkp =0.619.
The calculated tpi
are equal to 2.107; 35.589; -0.222; -0.601 respectively, i.e. only а1, а2 meet the requirements
of significance.
By the F-test of Fisher we obtained
F=45.12. Comparing it with the Table value of the Fisher-Snedecor
distribution (F-distribution) F>F Table, where F Table=2.99 with the degree
of probability of 95%. It proves that
the model is adequate by the F-test of Fisher. The average approximation error
ε =1.068%, though it should not exceed 12-15%.
The coefficient of multiple
correlation is rather high, the model is adequate on the whole on the basis of
checking it by the F-test of Fisher, and all the regression coefficients are
significant. The average error does not exceed the established norm. Therefore,
such a model can be used for making decisions and plans or creating forecasts.
5.
CONCLUSIONS
The
main indicator of economic suitability of this or that measure is a net profit.
Neither cost price, nor profitability, but a net profit determines the real
difference between the product cost and the level of production costs. For
three years of the field research this indicator reached the absolute maximum
in the hybrid LG 5580 when the bio-fungicide Fitotsyd-r
and the stimulator Ahrostymulin were applied at the
stage of budding, and it made $1081. In this case the cost price was the least
– $141.6, and the level of profitability was the highest –196%.
The
variant with the combination of Fitotsyd-r / Ahrostymulin also provided a positive result in the hybrid Tunca, but it yielded a bit to the combination of the
preparations Fitosporyn / Ahrostymulin,
and the net profit was $579.7, the cost price – $203.4 and the profitability –
106 %.
On the whole this analysis makes it possible to
receive evidence that additional costs, related to purchasing and applying
fertilizers, are compensated by an increase in the yields.
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