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Genetics and Breeding
Tsanko Yablanski (Bulgaria)Atanas Atanasov (Bulgaria)Svetlana Georgieva (Bulgaria)Nikolay Tsenov (Bulgaria)Max Rothschild (USA)Ihsan Soysal (Turkey)Horia Grosu (Romania)Stoicho Metodiev (Bulgaria)Bojin Bojinov (Bulgaria)
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2017
ISSN 1313 - 8820 (print)ISSN 1314 - 412X (online)
Volume 9, Number 2June 2017
Agriculture and Environment
Modeling and simulation of fuzzy logic controller for optimization of the greenhouse microclimate management
1 1 2 3Didi Faouzi* , N. Bibi-Triki , B. Draoui , A. Abene
1Materials and Renewable Energy Research Unit M.R.E.R.U, University of Abou-bakr Belkaïd, B.P. 119Tlemcen, Algeria2Energy Laboratory in Drylands, University of Bechar, Bechar Algeria3Euro-Mediterranean Institute of Environment and Renewable Energies, University of Valenciennes, France
(Manuscript received 21 November 2016; accepted for publication 8 June 2017)
Abstract. Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia. The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost. Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying. The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and the factors are light, temperature and relative humidity. This state of thermal evolution is the level sealing of the cover of its physical characteristics to be transparent to solar, absorbent and reflective of infrared radiation emitted by the enclosure where the solar radiation trapping effect otherwise called "greenhouse effect" and its technical and technological means of air that accompany. The socio-economic analysis of populations in the world leaves appear especially the last two decades of rapid and profound transformations These changes are accompanied by changes in eating habits, mainly characterized by rising consumption spread along the year. To effectively meet this demand, greenhouse-systems have evolved, particularly towards greater control of production conditions (climate, irrigation, ventilation techniques, CO supply, etc.). Technological 2
progress has allowed the development of greenhouses so that they become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc.) New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence such as neural networks and / or fuzzy logic, etc. As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year, The application of artificial intelligence in the industry known for considerable growth, which is not the case in the field of agricultural greenhouses, where enforcement remains timid. It is from this fact, we undertake research work in this area and conduct a simulation based on meteorological data through MATLAB Simulink to finally analyze the thermal behavior - greenhouse microclimate energy.
Keywords: agriculture greenhouse, microclimate, modeling, fuzzy logic controller, optimization, solar energy, climate model
AGRICULTURAL SCIENCE AND TECHNOLOGY, VOL. 9, No 2, pp , 2017DOI: 10.15547/ast.2017.02.024
132 - 139
Introduction control of the conditions of production (Bibi-Trikiet al., 2011). For fully exploit the increased opportunities for crops, it is essential to adjust the state of the system in an automatic manner. Better management In recent years, the cultivation of horticultural plants under of climatic parameters under glass today constitutes a major greenhouses has increasing application in Algeria. The reason for challenge at the global level (El Aoud and Maher, 2014). This is this development is the standard of living of the population, on the particularly true in the field of agriculture. one hand, and the increased demand for fresh produce throughout
Greenhouse systems must be modernization and move more the year. The use of greenhouses is an important technique in the towards the use of new cropping techniques and the appropriate development of agriculture; however, a decrease in production is automatic devices. To improve profitability, there is a need to noticed during the coldest, due to a significant loss of energy through increase cultures in optimal environments. It is therefore important to the walls of the greenhouses. This inadequate maintenance of an control the temperature air, moisture, and CO content (Didi Faouzi 2adequate climate in the greenhouse has production of cultivated et al., 2016). All these factors must be considered in the energy products, consequently a change in its sale would be justified balance, because each of them can influence others. During the last (Gurbaoui and al., 2013). Greenhouse cultivation has been years, greenhouse equipment manufacturers have met the undergoing significant development for several years to face an expectations of new technologies and new products that level of increasingly competitive market and conditioned by quality efficiency in greenhouse production (Hasni et al., 2009). Advances standards severe(Bendimerad et al., 2014). Production greenhouse in computing, including increased capabilities of computers, have systems are becoming considerably sophisticated and therefore considerably contributed to the automatic control of processes disproportionately expensive. For this reason, locksmiths who want climate change (Geethanjali et al., 2007). Computer-assisted to remain competitive must optimize their investment by a greater
* e-mail: [email protected]
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management has become an indispensable tool in the study of the The effectiveness of the typical tablet is about 85%. The heat climate in greenhouses. It contributes to improving the climatic loss rate depends on the fan speed.conditions cultivation under glass. But above all, it is the only rational way to predict climate change under glass. (2)
The improvement of article work on the structure of the greenhouse, on the choice of coverage, on the choice of the site and (3)the bioclimatic stage. The growth of the sheltered plant depends on the temperature of the indoor air of the greenhouse kept in the (4)shelter. Among the means of climate control during the summer period (Yih-Lon Lin et al., 2007), the greenhouses plays a key role in where: η is pad efficiency T , T are the difference between the pad out wb
reducing the temperature (Bouaama et al., 2008; Dhamakale and outside temperature and wet bulb (K); C is specific heat (J/kg.k ); p3Patil, 2011). The heating of greenhouses in winter is also important p is density (kg /m ); V is fan speed (m/s).
because it allows increasing the temperature inside the greenhouse (Abdelhafid Hasni et al., 2008). The thermal performance of the 2.2. Model of fogging systemsgreenhouse must also be taken into account, especially with regard to their insulation, thermal storage and heating equipment (Draoui
The flow of steam and heat are determined through Ohm's and al., 2013).Law and is as following:The present study is part of a contribution to the development of
greenhouse farming and aims to develop intelligent controllers (5)(Chau and al.,2006) to optimize the management of parameters
under greenhouse conditions (Liao and al., 2007). For this reason (6)we have done the modeling of a fuzzy controller by the application of
fuzzy logic using Mamdani method.Where: q is the heat transfer between the nebulizer and the air of
2agricultural greenhouse (W/m ); K is global coefficient of heat 2transmission (W/m .k); P is saturation pressure (Pascal); is satMaterial and methods
2Ambient air pressure (Pascal); λ is thermal conductivity (W/m .k).
1. Modeling the greenhouse2.3. Evaluation Model of the wall temperature (T )PThis article deals with the modeling and simulation of our The T wall temperature evaluation model (Bibi-Triki et al., greenhouse model which is based on the method of GUESS P
2011), closest to reality is determined based on the average (Jamisson, 2006). GUESS is a model set in parameter block, temperatures T and T :meaning that spatial heterogeneity is ignored and it is assumed that Pi Pe
the inner content and the flow through the system boundary are evenly distributed. The conservation equations are used to model (7)the rate of system status change.
џ For a warm greenhouse these state variables would be the The indoor and outdoor temperatures T and T are:Pi pe
indoor temperature, relative humidity, air pressure and CO 2
concentration. (8)џ For the plant state variables are the water content, the body
temperature, dry weight or biomass, and internally sheet CO .2
The temperature evaluation model of T wall will be expressed:A complete equation for the transport of some scalar quantity p
through a control volume is as following:
(1)
3 3Where: C is the heat capacity (J/m .k), V is system volume (m ); Φ is 2 Where:a quantity describing the state of the system (W / m );dx is material
2thickness (m); A is the flow boundary surface (control surface) (m ); 2 T ,T , is dry air temperature inside/outside (K); F , F areinternal and external flux (W/m ). air, I air eint out
h and h is coefficient of superficial exchanges at the inter wall, Pi Pe2of the outer wall (W/m .k);2. Modeling the climate of the greenhouse systems
C is quotient de Bibi.B
2.1. Cooling pads ModelIn a greenhouse, evaporative cooling devices are used to This report dimensionless C is used in evaluating the T wall B p
reduce the temperature when the fan cannot reach appropriate temperature, it is now called the quotient of Bibi, it is the ratio of the levels for optimal plant growth. In equipped greenhouses, cooling difference of surface thermal exchange by conduction, convection evaporation is the second part of the unrealized gain. Most and radiation occurring at the level of the greenhouse coverage.evaporative cooling methods can be modeled as adiabatic cooling process; the minimum temperature and the achievable maximum 2.4. Heating systemsvapor pressure is equal to the wet bulb (Jamisson, 2006). The heat produced per unit of fuel is modeled as (Jamisson,
P air
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2006): is the temperature of the exhaust gas (k); r is the return ratio.
3. Energy balance of the greenhouse
The analytical energy balance equation of the greenhouse:Stored energy change = (Gain from internal sources+ Gain from Where: h is sensible heat load of a condensing water combution sensible the sun)–(Losses due to conduction through the cover + Losses due
heater (J); LHV is lower heating value (KJ/kg); Φ is the fuel air; 36/16 to long wave radiation + Unrealized losses /evaporation/+ Losses
is the weight ratio of the produced steam to supply the burner; T exhaust due to the exchange of air).
(9)
(10)
Where esat indicates the report saturated with the relative air); ζ is the number of moles of carbon per mole of fuel; V is inf 3humidity in the sub-model of combustion (Kg steam / kg air); ventilation rate (m air/s); F is the amount of heat supplied by photosyntesis
is the heat provided by the heating system (W); r r photosynthesis (W). conv, in conv, out
are heat transfer coefficients - inside and outside by convection 2(W/m .k). 5. Photosynthesis
4. The mass transfer in the greenhouse Photosynthesis is a complex process. CO fixation and 2
The mass balance for moisture in the greenhouse can be subsequent conversion into carbohydrates are not a single reaction, written as following (eq. 11): but a series of steps, the Calvin cycle (Figure 1).
(11)
where: V is the speed of air infiltration (m/s); V is the total greenhouse inf3volume of agricultural greenhouse (m ); H , H is the indoor and in out
3outdoor humidity (KJ/kg); V is ventilation rate (m air/s).vent
And for the humidity balance:Rates of change in absolute humidity = Infiltration + Ventilation *
(humidity difference with the outside) + Misting + Cooling + AND - Condensation
The status of humidity function is (eq. 12):
The reaction at the apex (CO fixation and RuBP) is catalyzed 2
by the enzyme Rubisco. This reaction ordered carbon assimilation rates, and that is modeled by Farquhar and al. (2006) equations. Source: Cellupedia, “Calvin cycle” (2002).
where: CO is mass balance in molar units (ppm or μmol CO per mol 2 2 According to Farquhar model, the CO compensation model is:2
Figure 1. Schematic Calvin cycle
135
(14) variable to defuzzification. It is possible, and in some cases much more efficient to use a single peak as output membership function, rather than a distributed fuzzy set. This is sometimes known as Farquhar model with Γ, CO compensation point; C Internal CO 2 i 2
singleton output membership function, and we can think like a fuzzy concentration (ppm).set of pre defuzzification. It improves the efficiency of defuzzification because it greatly simplifies the calculation required by the more 6 Plant state of water balancegeneral method Mamdani which has the center of gravity of a two-The equation of thermal balance of water is as follows:dimensional function.
To calculate the output of the SIF in view of inputs, six steps (15)should be followed:
џ The determination of a set of fuzzy rules.where Ψ is the potential of water; C is the capacity of the plant plant 2 2 џ Fuzzification inputs using the input membership functions.(mole*m ); E is evapotranspiration; A is the root surface (m ); Rroot root
џ By combining Fuzzificaion entries according to the fuzzy is the growth rate.
rules to establish a resistance to the rule.џ Find the consequence of rule by combining the resistance to
In the model of GUESS, we assume that the soil is well watered, the rule and the output membership function.
so that the physiological effects of the state of water should be џ By combining the consequences to get a distribution outlet.
minimal, except in stomata.џ Defuzzification the output distribution.
7. Stomatal conductance and balance CO2 10. Fuzzy sets
The rate of photosynthesis in the Farquhar model depends on The input variables in a fuzzy control system are generally the internal concentration of CO .2 mapped by sets of membership functions similar to it, called "fuzzy
To determine the concentration of CO , a mass balance is set". The process of converting a crisp input value to a fuzzy value is 2
performed on the sheet. called "fuzzy logic". A control system may also have different types of switch, or "ON-OFF", inputs and analog inputs and during switching
(16) inputs will always be a truth value of 1 or 0, but the system can handle as simplified fuzzy functions happen to be one value or another.
According to GUESS the plant stomatal equation of is: Given "mappings" of input variables membership functions (A) (Figure 2) and truth values, the microcontroller then makes decisions for action on the basis of a set of "rules” (B).
B. Rules of decisions(17) џ If (Ti is TVCOLD) then (FOG1FAN1 is OFF)(FOG2FAN2 is
OFF)(FOG3FAN3 is OFF)(NV is OFF)(Heater1 is ON)(Heater2 is Ball-Berry modified model used in GUESS, where: g is ON)(Heater3 is ON) (1) stomatal
-1 -2.џ If (Ti is TCOLD) then (FOG1FAN1 is OFF)(FOG2FAN2 is stomatal conductance in units of (mole.s .m ).
OFF)(FOG3FAN3 is OFF)(NV is OFF)(Heater1 is ON)(Heater2 is Plant energy balances. Equation for the temperature of a Leaf is ON)(Heater3 is OFF) (1) as follow:
џ If (Ti is TCOOL) then (FOG1FAN1 is OFF)(FOG2FAN2 is OFF)(FOG3FAN3 is OFF)(NV is OFF)(Heater1 is ON)(Heater2 is OFF)(Heater3 is OFF) (1)
џ If (Ti is TSH) then (FOG1FAN1 is OFF)(FOG2FAN2 is (18)OFF)(FOG3FAN3 is OFF)(NV is ON)(Heater1 is OFF)(Heater2 is OFF)(Heater3 is OFF) (1)
џ If (Ti is TH) then (FOG1FAN1 is ON)(FOG2FAN2 is 8. Fuzzy logic controller modelingOFF)(FOG3FAN3 is OFF)(NV is OFF)(Heater1 is OFF)(Heater2 is OFF)(Heater3 is OFF) (1) Fuzzy logic is widely used in the machine control. The term
џ If (Ti is TVH) then (FOG1FAN1 is ON)(FOG2FAN2 is "fuzzy" refers to the fact that the logic can deal with concepts that ON)(FOG3FAN3 is OFF)(NV is OFF)(Heater1 is OFF)(Heater2 is cannot be expressed as the "true" or "false" but rather as "partially OFF)(Heater3 is OFF) (1) true"[9]. While alternative approaches such as genetic algorithms
џ If (Ti is TEH) then (FOG1FAN1 is ON)(FOG2FAN2 is and neural networks can perform just as well as fuzzy logic in many ON)(FOG3FAN3 is ON)(NV is OFF)(Heater1 is OFF)(Heater2 is cases, fuzzy logic has the advantage that the solution can be cast in OFF)(Heater3 is OFF) (1)terms that human operators can understand, so that their
experience can be used in the design of the control device. This 11. Simulation and model validationmakes it easier to mechanize the tasks have already been
performed successfully by man.Our model is based on the greenhouse GUESS model that is
set for a multi greenhouse chapel which each module is 8.5 m wide, 9. Fuzzy inference method Mamdani34 m deep and ridge height of 4.5 m. Infiltration rate is 1.1 air
2Fuzzy inference Mamdani type, as defined for Toolbox fuzzy changes per hour, and a U value of 5.76 W/m .K was used. The logic, expects the output membership functions to be fuzzy sets. model of the plant was set for Douglas seedling plants were started After the aggregation process, there is a fuzzy set for each output at 0.57 g dry weight, and harvested 1.67 g dry weight; a new growing
.
136
season was recorded at harvest. A set of hourly data for 2015 (1 Simulink. The simulation was performed on a Toshiba laptop. The January to 31 December) weather station of Dar El Beida, Algeria laptop is equipped with a hard drive 700 GB and 5 GB of RAM. was used to validate our model as a CSV file that consists of four Simulink model of the parties were made in "Accelerator" mode that columns (global solar radiation, temperature, humidity and wind has first generated a compact representation of Code C of the speed). diagram, then compiled and executed.
The model of the greenhouse was coded using the full version Greenhouse global Model and Fuzzy logic controller simulation of Windows MATLAB R2012b (8.0.0.783), 64bit (win64) with model of the greenhouse are shown in Figures 3 and 4.
Figure 2. Representation rules of membership
Figure 3. Simulink representation of the global greenhouse climate model
137
Results and discussion
The simulation results clearly visualize the actual thermo-energy behavior of agricultural greenhouse, applying the model of artificial intelligence, namely the application of fuzzy logic (Figure 5). We added to our model of the greenhouse an intelligent regulator using the fuzzy logic and we chose the Mamdani method with a single input, we started by first defining the input data and the outputs, and by the following has been attempted to link the membership functions in a logical manner in order to respond to the following steps: Then the range of variations (the fuzzy sets) and the membership functions for the input and the output were defined and each part of the membership function was called by a significant name (Figure 2). After defining the membership functions, the inference rules have been implemented in such a way as to achieve optimum control as desired, for example if the climate inside the greenhouse becomes lime the regulator will automatically Lower the temperature by closing a heating system or opening a cooling system or by any other means and all this, in order to keep the required instruction which will be translated by the command (Rules of decisions).
We save the file (.fis) to load it into the workspace and retrieve it in the Simulink Fuzzy block under the same name of the saved file. The simulation of our system was done by MATLAB / SIMULINK. The results of the MATLAB / SIMULINK software indicate the high capacity of the proposed technique to control the internal temperature of the greenhouse even in the event of a rapid change in atmospheric conditions. The modeling of the system is defined in the form of this block diagram introduced in our Simulink shown in (Figure 5). Its goal is to achieve the set temperature of 20°C required by the internal environment of our greenhouse. Indeed, by varying the ranges of inferences, the efficiency of the regulator has been increased around this set point. It would also be possible to modify the inference rules or the forms of the membership functions used.
It is found that most internal temperature values are between (15°C and 25°C) in Figure 6 for the winter period and between (20°C and 28°C) for the spring summer period. Temperature variation during the autumn and winter period is due to heat loss overnight and
Figure 4. Simulink representation of the fuzzy logic controller model
Figure 5. The evolution of humidity and temperature (interior / exterior)
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the noise appearing in the room temperature signal is caused by the temperature in the desired range. But this solution is insufficient and cyclic activation and deactivation of the heating systems And really costly, for this purpose we should improve the characteristics ventilation. However, the compensation of the heating is insufficient of the cover of the agricultural greenhouse, double wall thermal and expensive, for this reason an improved thermal insulation for the insulation that demonstrates improved heating and cooling wall of the cover is necessary. efficiency, etc.
The improved thermal insulation of the lid can be practically The relative humidity in Figure 7 is generally close to the achieved by the addition of a layer of plastic air bubble mounted on optimum for the entire year except summer when humidity falls the inner wall face. During the spring summer period the below the threshold due to the significant vaporization used for temperature is almost in the desired range in both regions except for temperature compensation. This problem of adding a screen on the the half of the summer where the temperature is a little increase. The roof of the greenhouse for the region of Dar El Beida.use of cooling and spraying systems is necessary to lower the
Figure 7. Plant growth characteristics(Figure 7-1. Plant height, cm; Figure 7-2. Plantrod diameter, mm; Figure 7-3. Plant total biomass (dry weight); Figure 7-4. Crops harvested)
The speed of growth of the mass of the plant is normal for most difficulties for the optimal climate management inside our model of of the year except in the end of autumn and beginning of winter the greenhouse and exactly in the winter period (end of December because of the temperature drops at night and we discussed this and beginning of January) and this indicates that our system is problem and its correction previously. unstable in this period. And that makes us think of its development
The figure 7 represents the characteristics of the plant and how and improve it in the future to get better results.often the product is harvested for one year in each season, also the speed of the harvest in each period, such that it can be seen that by application of our blurred controller we can harvest four times In a Conclusionyear but at the end of the year to December and beginning of the year to January it is observed that the operation of the harvest or the However, our objective is achieved to the extent that it has been growth of the plant is a little heavy and take little more time than the shown through modeling and control by the use of fuzzy logic, this other seasons. area is very difficult because it is a multi-control variable which the
This negative growth is caused by insufficient integral light greenhouse is a biophysical system where parameters are highly during the winter and which means a break in our model and a correlated as shown by the results. This technique of fuzzy logic that lowering in light and photoperiod. And this indicates that despite the has been adapted to the greenhouse to a promising future for the results obtained in the desired interval, our blurred controller found climate control and management of the greenhouse for greenhouse
139
growers, it is a preferred approach for structuring and knowledge Journal of Emerging Technology and Advanced Engineering, 2, 17-aggregation and as a means of identification of gaps in the 19.understanding of mechanisms and interactions that occur in the Didi Faouzi, Bibi-Triki N and Chermitti A, 2016. Optimizing the system - greenhouse. Fuzzy logic is a branch of artificial intelligence, greenhouse micro-climate management by the introduction of which must point out its advantages and disadvantages. Its use has artificial intelligence using fuzzy logic. International Journal of led to quite satisfactory results of the control and regulation Computer Engineering and Technology, 7, 78-92.perspective. Didi Faouzi, Bibi-Triki N, Draoui B and Abène A, 2016,
We remain optimistic in the near future, as to the operation of Comparison of modeling and simulation results management micro artificial intelligence, including the use of fuzzy logic which indicates: climate of the greenhouse by fuzzy logic between a wetland and arid
џ For the control and regulation of the greenhouse region. International Journal of Multidisciplinary Research and microclimate. Modern Education (IJMRME) ISSN (Online): 2454 - 6119 II, II.
џ By the conservation of energy. Draoui B, Bounaama F, Boulard T and Bibi-Triki N, 2013. In-situ џ For the efficiency of energy use in the greenhouses modelisation of a greenhouse climate including sensible heat, water
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Agriculture and Environment
Alternatives for optimisation of rumen fermentation in ruminants T. Slavov
Characterization of a new winter malting barley cultivar AhilB. Dyulgerova, D. Vulchev, T. Popova
Evaluation of high yielding mutants of Hordeum vulgare cultivar IzgrevB. Dyulgerova, N. Dyulgerov
In vitro gas production of different feeds and feed ingredients at ruminantsE. Videv, J. Krastanov, S. Laleva, Т. Angelova, M. Oblakova, N. Oblakov, D. Yordanova, V. Karabashev
Evaluation of chemical composition of raw and processed tropical sickle pod (Senna obtusifolia) seed mealAugustine C., Kwari I.D., Igwebuike J.U., Adamu S.B.
Effect of urea-fortified all concentrate corncob diets on serum biochemical and hematological indices of West African dwarf goatsU. M. Kolo, A. A. Adeloye, M. B. Yousuf
Analysis of the technological dairy cows traffic "to and from" herringbone milking parlorsK. Peychev, D. Georgiev, V. Dimova, V. Georgieva
Effect of pre-sowing soil tillage for wheat on the crop structure and the yield components under the conditions of slightly leached chernozem soil in Dobrudzha regionP. Yankov, M. Drumeva
Study on the process of unloading grain harvesters at the end of the fieldG. Tihanov
Modeling and simulation of fuzzy logic controller for optimization of the greenhouse microclimate managementDidi Faouzi, N. Bibi-Triki, B. Draoui, A. Abene
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Floristic diversity of 'Chinarite' protected area – Rodopi municipality, BulgariaL. Dospatliev, M. Lacheva
Heavy metal pools in urban soils from city parks of Sofia, Bulgaria V. G. Kachova, I. D. Atanassova
Ecological characteristics of reclaimed areas in Pernik mines region, BulgariaI. Kirilov, M. Banov
Reclamation of soil excavated from construction and mine searching areas in TurkeyF. Apaydin
Concentration of sulfur-containing amino acids at turkey broilers during and after muscle dystrophy, fed with deficient feed supplemented with oxidised fatK. Stoyanchev
Exopolysaccharide influence's on acid gel formationK. Yoanidu, P. Boyanova, P. Panayotov
Carcass characteristics and technological properties of Musculus Longissimus Lumborum at lambs from the Bulgarian dairy synthetic population and its F1 crosses with meat breedsN. Ivanov, T. Angelova, S. Laleva S. Ribarski, D. Miteva, D. Yordanova, V. Karabashev, I. Penchev
Product Quality and Safety
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Instruction for authors
Preparation of papersPapers shall be submitted at the editorial office typed on standard typing pages (A4, 30 lines per page, 62 characters per line). The editors recommend up to 15 pages for full research paper ( including abstract references, tables, figures and other appendices)The manuscript should be structured as follows: Title, Names of authors and affiliation address, Abstract, List of keywords, Introduction, Material and methods,Results, Discussion, Conclusion, Acknowledgements (if any), References, Tables, Figures.The title needs to be as concise and informative about the nature of research. It should be written with small letter /bold, 14/ without any abbreviations. Names and affiliation of authorsThe names of the authors should be presented from the initials of first names followed by the family names. The complete address and name of the institution should be stated next. The affiliation of authors are designated by different signs. For the author who is going to be corresponding by the editorial board and readers, an E-mail address and telephone number should be presented as footnote on the first page. Corresponding author is indicated with *.Abstract should be not more than 350 words. It should be clearly stated what new findings have been made in the course of research. Abbreviations and references to authors are inadmissible in the summary. It should be understandable without having read the paper and should be in one paragraph. Keywords: Up to maximum of 5 keywords should be selected not repeating the title but giving the essence of study. The introduction must answer the following questions: What is known and what is new on the studied issue? What necessitated the research problem, described in the paper? What is your hypothesis and goal ?Material and methods: The objects of research, organization of experiments, chemical analyses, statistical and other methods and conditions applied for the experiments should be described in detail. A criterion of sufficient information is to be possible for others to repeat the experi-ment in order to verify results.Results are presented in understandable
tables and figures, accompanied by the statistical parameters needed for the evaluation. Data from tables and figures should not be repeated in the text.Tables should be as simple and as few as possible. Each table should have its own explanatory title and to be typed on a separate page. They should be outside the main body of the text and an indication should be given where it should be inserted.Figures should be sharp with good contrast and rendition. Graphic materials should be preferred. Photographs to be appropriate for printing. Illustrations are supplied in colour as an exception after special agreement with the editorial board and possible payment of extra costs. The figures are to be each in a single file and their location should be given within the text. Discussion: The objective of this section is to indicate the scientific significance of the study. By comparing the results and conclusions of other scientists the contribution of the study for expanding or modifying existing knowledge is pointed out clearly and convincingly to the reader.Conclusion: The most important conse- quences for the science and practice resulting from the conducted research should be summarized in a few sentences. The conclusions shouldn't be numbered and no new paragraphs be used. Contributions are the core of conclusions. References:In the text, references should be cited as follows: single author: Sandberg (2002); two authors: Andersson and Georges (2004); more than two authors: Andersson et al.(2003). When several references are cited simultaneously, they should be ranked by chronological order e.g.: (Sandberg, 2002; Andersson et al., 2003; Andersson and Georges, 2004).References are arranged alphabetically by the name of the first author. If an author is cited more than once, first his individual publications are given ranked by year, then come publications with one co-author, two co-authors, etc. The names of authors, article and journal titles in the Cyrillic or alphabet different from Latin, should be transliterated into Latin and article titles should be translated into English. The original language of articles and books translated into English is indicated in parenthesis after the bibliographic reference (Bulgarian = Bg, Russian = Ru, Serbian = Sr, if in the Cyrillic, Mongolian =
Мо, Greek = Gr, Georgian = Geor., Japanese = Jа, Chinese = Ch, Arabic = Аr, etc.)The following order in the reference list is recommended:Journal articles: Author(s) surname and initials, year. Title. Full title of the journal, volume, pages. Example:Simm G, Lewis RM, Grundy B and Dingwall WS, 2002. Responses to selection for lean growth in sheep. Animal Science, 74, 39-50Books: Author(s) surname and initials, year. Title. Edition, name of publisher, place of publication. Example: Oldenbroek JK, 1999. Genebanks and the conservation of farm animal genetic resources, Second edition. DLO Institute for Animal Science and Heal th, Netherlands.Book chapter or conference proceedings: Author(s) surname and initials, year. Title. In: Title of the book or of the proceedings followed by the editor(s), volume, pages. Name of publisher, place of publication. Example: Mauff G, Pulverer G, Operkuch W, Hummel K and Hidden C, 1995. C3-variants and diverse phenotypes of unconverted and converted C3. In: Provides of the Biological Fluids (ed. H. Peters), vol. 22, 143-165, Pergamon Press. Oxford, UK.Todorov N and Mitev J, 1995. Effect of level of feeding during dry period, and body condition score on reproductive perfor-
thmance in dairy cows,IX International Conference on Production Diseases in Farm Animals, September 11–14, Berlin, Germany.Thesis:Hristova D, 2013. Investigation on genetic diversity in local sheep breeds using DNA markers. Thesis for PhD, Trakia University, Stara Zagora, Bulgaria, (Bg).
The Editorial Board of the Journal is not responsible for incorrect quotes of reference sources and the relevant violations of copyrights.
Animal welfareStudies performed on experimental animals should be carried out according to internationally recognized guidelines for animal welfare. That should be clearly described in the respective section “Material and methods”.
Volume 9, Number 2June 2017
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