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Öğe A different factor in the use of plants in landscape architecture: Sound (type, intensity and duration) in the example of Hyacinthus orientalis L.(Univ Agr Sci & Veterinary Med Cluj-Napoca, 2023) Cig, Arzu; Mutlu, Arzu Kocak; Mikail, NazireThe effect of music on people has been known for years and is still being researched from different aspects. The effects of music and sound waves on ornamental plants, whose effects on some vegetables, fruits and grains are examined, are also inquired. Especially the positive change in the development and showiness of the flowers of ornamental plant species with commercial importance will increase the market value of the plant. Again, with the effect of this sound wave, in order for the plants and their flowers to show the expected development, they should benefit from the planting environment and growing conditions at the maximum level. In the measurements taken from hyacinths (Hyacinthus orientalis L.) at the end of the duration that the plants were exposed to different types of sounds in different intensities, it was observed that these factors positively affected these parameters successively; 1 hour of bird sound in 50 dB, the number of leaves; 1 hour of bird sound in 90 dB, leaf width and floret length; 3 hours of bird sound in 70 dB, floret number; 3 hours of bird sound in 90 dB, the plant and flower height; 1 hour of bee sound in 50 dB, the stem thickness; 3 hours of vehicle sound in 50 dB, flower and floret width; 3 hours of vehicle sound in 70 dB, leaf length. At the end of the study, whereas it was determined that the bee sound had the least effect on the growth and flowering of the hyacinth, it was observed that the bird and vehicle sounds, that the plants were expose to in different intensities and durations, had a positive effect.Öğe Analysis of the First Lactation Curve in Holstein Cows with Different Mathematical Models(Kahramanmaras Sutcu Imam Univ Rektorlugu, 2019) Gok, Turgut; Mikail, Nazire; Akkol, SunaThe shape of the lactation curve of cows as well as the total or 305 day milk yield is considered as an important criterion in the livestock farms. Five different. mathematical models. used in defining lactation curves were used in this study to fit first loci at ion curves of Holstein cattle. Total of 4172 weekly average milk yield of the first lactation of 104 cows between 2001-2008 years, was used for this aim. The models used in the study were; Wood; Morgan; tlompertz; Ali and Schaeffer and Dijkstra. The models' fit to t h e lactation curve has been examined and compared. Lactation curves also have been investigated according to the lactation years. The R-2, R-adj(2), AIC, BIC and MAPE values were used in the comparison of the models. The lowest AIC (-3.29), BIC (-3.12) and MAPE (0.55) and highest R-2 (0.99) and R-adj(2) (0.99) values were found for the Ali and Schaeffer model. This model was followed by the Dijkstra model. As a result of the study, it was determined that the most suitable models fir predicting the first lactation milk yield curves and curves features like maximum milk yield and days in milk to peak yield of Holstein cattle were Ali and Schaeffer and Dijkstra models.Öğe Application of Artificial Intelligence Methods to Predict Cotton Production in Turkey(2021) Mikail, Nazire; Baran, Mehmet FıratFarmers are always curious about the factors affecting yield in plant production. Determining thesefactors can give information about the yield in the future. Reliability of information is dependent on a goodprediction model. According to the operating process artificial neural networks imitate the neural network inhumans. The ability to make predictions for the current situation by combining the information people havegained from different experiences is designed in artificial neural networks. Therefore, in complex problems, itgives better results than conventional statistical methods. In this study, artificial neural networks and supportvector machines methods of artificial intelligence were used in order to predict the production of cotton. Froma comprehensive data collection spanning 73 farms in Diyarbakır, Turkey, the mean cotton production wasprevised at 559.19 kg da-1. There is four factors that picked as pivotal input into this model. As a result, theultimate artificial neural network model is able to foreshow cotton production, which is built on elements like:farm states (cotton area and irrigation periodicity), machinery usage and fertilizer consumption. At the end ofthe study, cotton yield was estimated with %84 accuracy.Öğe APPLICATION OF CONJOINT ANALYSIS TO DETERMINE CONSUMERS' RED MEAT PREFERENCES IN SIIRT PROVINCE(Univ Agricultural Sciences & Veterinary Medicine Bucharest, 2018) Kibar, Mustafa; Mikail, NazireThe aim of this paper is defining consumers' preferences for the red meat in Siirt Province. This paper illustrates the conjoint analysis application in determining consumers' preferences for the attributes of red meat according to the amount of consumption. Multiple regression analysis used for determination most valued attributes and their levels. A random sample of 160 red meat consumers was interviewed in Siirt Province. They were asked to provide demographic information and responses to several survey questions, as well as to participate in a conjoint analysis study. For the survey portion of the interview, respondents were asked to assess the importance of the following attributes: meat type, purchasing sources and price. As a result of the study, it was found that relative importance of attributes for the regular consumers were 48.8% price, 30.7% purchasing source, 20.5% meat type, and for non-regular consumers were 37.3% meat type, 34.3% price and 28.4% purchasing source. Determination coefficients of the models for regular and non-regular consumers were found as 99.3% and 99.2%, respectively.Öğe Application of neural network and adaptive neuro-fuzzy inference system to predict subclinical mastitis in dairy cattle(Indian Journal of Animal Research, 2015) Mikail, NazireMastitis is an important problem, while I guess AI is a possible solution to detect subclinical mastitis in Holstein cows milked with automatic milking systems. Mastitis alerts were generated via ANN and ANFIS model with the input data of lactation rank (current lactation number), milk yield, electrical conductivity, average milking duration and season. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the sampling period. Cattle were judged healthy or infected based on somatic cell counts. This study undertook a detailed scrutiny of ANN, and ANFIS AI methodology; constructed and examined models for each; and chose optimal methods based on that examination. The two mastitis detection models were evaluated as to sensitivity, specificity and error rate. The ANN model yielded 80% sensitivity, 91% specificity, and 64% error and the ANFIS, 55%, 91% and 35%. These results suggest the ANN model is better predictor of subclinical mastitis than ANN based on Z-test (the hypothesis control for the difference between rates). AI models such as these are useful tools in the development of mastitis detection models. Prediction error rates can be decreased through the use of more informative parameters.Öğe Application of the Support Vector Machine to Predict Subclinical Mastitis in Dairy Cattle(The Scientific Word Journal, 2013) Mikail, Nazire; Keskin, İsmail…Öğe Characterization of phytophthora capsici leonian resistance in some pepper genotypes by principal component analysis(Applied Ecology and Environmental Research, 2018) Karipçin, Zeki; Seyidoğlu, Gülşah; Mikail, NazireIn the study, resistance analyses were performed on pepper lines and genotypes (60 genotypes) of mainly common local genotypes found in the gene pool by classical testing methods. Classical tests were first applied in seedling stage. Second inoculation (the last) was carried out (in the stage of fruit retention) on resistant genotypes determined in the first inoculation. Varieties resistant to phytophthora capsici (CM 334 and partially resistant P1, P2 and P4) were also included in the study. Peroxidase and catalase enzyme contents of plant materials have been determined. Scale of 0-5 was applied to inoculated plants. Five pepper properties were measured and used as original variables. The first two principal components accounted for 74% of total variance. Score plots of the first two principal components were used to map genotypes according to their morphological properties. Some relationships between genotypes and their morphological traits were obtained. The results revealed that genotypes of P1, 13 (Urfa), 25 (UKST), 38 (UI), 48 (UKDT), 57 (ANKSB) were partial resistant genotypes while CM334 was fully resistant. To conclude, principal component analysis was shown to be a useful tool for mapping the pepper genotypes in terms of phytophthora capsici resistance.Öğe Classification of ornamental plant species with artifical intelligence applications(İksad Publishing House, 2020 Aralık) Mikail, Nazire; Çığ, ArzuThe aim of this study is to examine some artificial intelligence methods used in the classification of ornamental plants and to compile the researches on this subject and bring them to the attention of subject experts.Öğe COMPARISON OF THE HEATING ENERGY REQUIREMENTS OF THE GREENHOUSES IN THE TIGRIS BASIN WITH ANTALYA(Univ Agricultural Sciences & Veterinary Medicine Bucharest, 2017) Saltuk, Burak; Mikail, Nazire; Atilgan, Atilgan; Aydin, YusufThe rapid growth of the world population also increases the amount of food needed for the human being's life. Therefore, applications that increase productivity and through which production can be made throughout the year in plant production come to the forefront in the world. In this context, one of the most important activities is greenhouse cultivation through which production can be made throughout the year by keeping climate conditions under control. Greenhouses are climate-controlled plant production structures in which indoor environment conditions can be controlled and can be kept in accordance with growing conditions. Heating must be performed during the winter period in greenhouses if it is desired to make production throughout the year. In Turkey, almost all of greenhouse production is performed in the Mediterranean region, and the production areas are situated in a relatively limited area in the Southeastern Anatolia Region. In this study, 10-year climate data (Maximum, Minimum and Average Temperature, Humidity, Sunshine Duration and Amounts) of 5 provinces (Diyarbakir, Mardin, Siirt, Batman and Sirnak) in the Tigris basin were achieved by considering the climatic conditions and production capacity of Antalya province, which has the most production areas in Turkey. According to the results obtained, the average minimum temperature for each month showed a statistically significant difference according to the provinces (p<0.01). Consequently, while the highest heating load was 1852.836 W/m(2) for a greenhouse of 576 m(2) for Antalya province in January during which heating requirement is the maximum, 3887.13 W/m(2) and 5615 W/m(2) heating load differences were obtained from Mardin and Diyarbakir provinces, respectively.Öğe Determination of the Factors Effecting Lactation Milk Yield of Holstein Friesian Cows by the Path Analysis(Selcuk Journal of Agriculture and Food Sciences, 2016) Aytekin, İbrahim; Mikail, Nazire; Altay, Yasin; Topuz, Derviş; Keskin, İsmail…Öğe Fuzzy logic applications in horticulture and a sample design for juice volume prediction in pomegranate (Punica Granatuml.)(Applied Ecology and Environmental Research, 2019) Pakyürek, Mine; Aydın, Yusuf; Mikail, NazireFuzzy expert systems search for a solution based on the expertise of people who are experts in a particular field. This could be described as a kind of advisory system edited on computer. The use of natural language on the basis of fuzzy logic and easier understanding of system logs provide this technique to resolve many daily and current problems. In this study, a sample expert system to estimate juice volume in pomegranate was designed, using the fuzzy logic method, which closest to the logic of the human mindset. Recording of data was performed on the private farm of the province of Siirt, Turkey. The Fuzzy Logic Interface of MATLAB Program was used in the designing phase of the system. The evaluation of the model was carried out according to coefficient of determination and coefficient of correlation. The model revealed R2 = 80% coefficient of determination, and r = 0.89 coefficient of correlation. With more informative parameters, the error rate can be decreased. Fuzzy logic seems one of the useful tools with prediction purposes in horticulture.Öğe HAYVANCILIKTA BULANIK MANTIK UYGULAMALARI(Selçuk Tarım ve Gıda Bilimleri Dergisi, 2009) Mikail, Nazire; Keskin, İsmail…Öğe Hayvancılıkta Veri Madenciliği Uygulamaları(Türkiye Tarımsal Araştırmalar Dergisi, 2016) Mikail, Nazire; Alev Çetin, Feyza…Öğe İneklerde Bulanık Mantık Modeli ile Hareketlilik Ölçüsünden Yararlanılarak Kızgınlığın Tespiti(Kafkas Üniversitesi Veteriner Fakültesi Dergisi, 2011) Mikail, Nazire; Keskin, İsmail…Öğe Investigation of the factors affecting first flowering time of Tulipa gesneriana by path analysis(2020 Aralık) Çığ, Arzu; Mikail, NazireCorrelation coefficients have shown that first flowering time of Tulip was positively and significantly correlated with flower length and negatively and significantly correlated with leaf number. The path analysis has shown that just flower length had the positive significant direct effect to the first flowering time. These parameters may be useful as predictors of the best first flowering time. Path analysis has an important role in revealing the relationships between variables in multivariate analysis and calculating their direct and indirect relation shares with the predicted variable. In agricultural sciences, the direction and amount of the relationships between the characteristics studied in natural phenomena, as well as the calculation of the impact shares in the total relationship are very important in future predictions or finding the best yield. For this reason, estimation of first flowering time, which is an important feature in ornamental plant cultivation, or determining the factors affecting its shortening, will ensure that this feature is kept under control by the cultivator.Öğe Investigation of the Relationship between Body Length and Live Weight of the Pikeperch (Sander Lucioperca Linnaeus, 1758) in Beyşehir Lake Population(2023) Başer, Eyüp; Mikail, Nazire; Aytekın, İbrahimThe aim of this study is to examine the relationship between the total length and standard lengths with live weight of the freshwater pikeperch growing in the Beyşehir Lake population using four mathematical models. 50 female fish materials of marketable size limit age were used. The data obtained were divided into two groups: estimation (70%) and test (30%). The applied models are exponential decay, exponential and Wood models, and in such research generally preferred power model. R2, R2adj, RMSE, AIC, BIC and MAPE values were used as goodness of fit tests and comparison criteria of the models. According to the study results, the total length gives more accurate estimates than a standard length in the estimating live weight. As a result, it was concluded that other models might provide better results than the power model, and they were suggested to be used in estimating the live weight of pikeperch fish.Öğe Investigation of the relationship between morphological features of different hyacinth (Hyacinthus orientalis L.) cultivars by path analysis(2nd International Conference on Food, Agriculture and Animal Sciences (ICOFAAS 2019), Aralık-2019) Mikail, Nazire; Çığ, Arzu; Türkoğlu, NalanPath analysis is included in the group of alternative multivariate statistical methods within a multivariate structure. Path analysis is an extension of the regression model, where we can analyze not just direct effect of the predictors to the response variable, also the indirect effects of whole predictors to the response variable. The purpose of the path analysis is to estimate the importance and amount of hypotheses created for causal relationships between variables. This is well explained by the path diagram. The main objective of the current study investigation of the effect of morphological parameters of the four hyacinth (Hyacinthus orientalis L.) cultivars (“Blue Jacket”, “Carnegie”, “City of Haarlem”, and “Jan Bos”) grown in the field conditions to the first flowering time by means of path analysis. The data set contains of 123 observations. According to the results of the study, the leaf length and stalk thickness had the positive significant direct and indirect effects to the first flowering time. Floret length, flower diameter, flower length and floret diameter had the negative significant direct and indirect effects to the first flowering time.Öğe Most probable producing ability as a within-herd management and culling tool(The Journal of Animal and Plant Sciences, 2019) Mikail, Nazire; Cue, Roger; Bakır, GalipThe objectives of this study were to examine the effects of management and environmental effects on milk yield (factors such as herd, year of calving, parity and age at calving), total and 305-dayand to examine the magnitude of the variability amongst cows. Data were obtained from three state farms. Data set consisted of records from 1004 Holstein-Friesian and 6690Brown Swiss cows. The average total milk yield, days in milk and 305 day milk yield were 5760 kg, 316 days and 5420 kg, respectively. Repeatability of total milk yield, 305 day milk yield and most probable producing ability of each cow were calculated. Repeatability of total and 305 day milk yield was estimated to be 0.31. The results of this study suggest positive trends for lactation milk yield and the significant repeatability shows that it is possible to rank cows, on a within-herd basis, on the basis of their Most Probable Producing Ability, and hence use this as a phenotypic selection and culling criteria for herd management.Öğe PREDICTION OF BODYWEIGHT OF HOLSTEIN AND BROWN-SWISS MALE CATTLE BY USING DIGITAL IMAGES(Univ Agricultural Sciences & Veterinary Medicine Bucharest, 2017) Bozkurt, Yalcin; Mikail, Nazire; Ulusar, Umit Deniz; Aktas, Hakan; Dogan, CihanThis research aimed to develop prediction models for accurate estimation of performance and body measurements of beef cattle grown in feedlot beef system by using Digital Image Analysis (DIA). For this purpose, 40 animals were used in total and composed of 20 animals of the Brown Swiss breed and 20 animals of the Holstein breed with the age of about 4-5 months at the beginning of the experiment. Animals were fed the same dietary rations throughout the experimental period of 12 months. When the animals reached 500-550 kg bodyweights (BW), they were slaughtered. The digital images of each live animal were taken and the same parameters (digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were also determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by DIA. The linear, quadratic and cubic regression models were performed to predict BW for both breeds and since there was no statistically significant differences (P > 0.05) in body measurements between breeds. The data of these breeds were combined and found that DJBL and DJWH would be the best possible traits in predicting BW (R-2 = 93.9% and 90.7% respectively) among the other measurements. The linear terms of all body measurements by DIA were considered for analysis and they were significant and R2 values for other body measurements DJHW, DJBD, DJHH and DJPL were approximately 78.4, 81.4, 87.7 and 67.7% respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds.Öğe PREDICTION OF CARCASS WEIGHT OF HOLSTEIN AND BROWN SWISS CATTLE GROWN IN A 12-MONTHS INTENSIVE BEEF PRODUCTION SYSTEM BY USING REAL-TIME CARCASS MEASUREMENTS(Univ Agricultural Sciences & Veterinary Medicine Bucharest, 2017) Bozkurt, Yalcin; Varban, Stepan; Mikail, Nazire; Dogan, CihanIn this study, it was aimed to evaluate the use of some morphometric carcass measurements to predict carcass weight of Holstein and Brown Swiss cattle grown in a 12-months intensive beef production system. Associations between carcass weights (CW) and some carcass measurements such as carcass heart girth (CHG), carcass length (CL) and carcass depth (CD) were examined for prediction ability, using the data with 134 observations for each traits. The linear, quadratic and cubic regression models were performed to predict CW for both breeds and since there were no statistically significant (P > 0.05) differences in carcass measurements between breeds. The data of these breeds were combined and found that CL and CHG would be the best possible traits in predicting CW (R-2 = 57.9 and 50.7% respectively) among the other measurements. The highest R-2 values were obtained from both the equation contained all carcass traits (R-2 = 65.5%) and the equation that included only CHG and CL (R-2 = 65.4%). All type of regressions showed that addition of quadratic and cubic terms contributed little benefit in predicting CW. Therefore, all linear terms of all carcass measurements were considered for analysis and they were significant (P. 0.05) and the R-2 value for other carcass measurement CD was approximately 20.8%. It can be concluded that in management situations where CW cannot be measured it can be predicted accurately by measuring CL and CHG alone and different models may be needed to predict CW in different feeding and environmental conditions and for other breeds.
