This survey was conducted on all the 85 beekeeping farms collected with census study method in Igdir province of Turkey with the purpose of determining some factors influencing average honey yield (AHY) per beehive in the year 2014. For this purpose, predictive performances of several data mining algorithms (CART, CHAID, Exhaustive CHAID and MARS) and artificial neural network algorithm (Multilayer Perceptron, MLP) were evaluated comparatively. Several factors thought as independent variables in the survey were age of beekeeper (AB), education level (EL), number of full beehives (NFB), bee race (BR), the time spent in plateau (TSP), feed of autumn and spring (FAS), working period in apiculture during year (WPA), frequency of changing queen (FCQ), and controlling beehives in summer (CFB), respectively. Minimum beekeeping farm numbers for parent and child nodes were arranged as 8:4 in CART, CHAID and Exhaustive CHAID for attaining the best predictive performance in AHY. In the Exhaustive CHAID, only 3 independent variables, NFB, WPA and CFB were found statistically. In the CART algorithm, only NFB, WPA and AB independent variables were found significantly. In the MARS algorithm, significant independent variables were determined to be some main and interaction effects of NFB, FAS, WPA, EL, AB, FCQ and TSP. The significant order of the Pearson coefficients between actual and fitted values in AHY was MARS (0.913a) > ANN (0.885ab) > Exhaustive CHAID (0.786b) > CHAID (0.769b) > CART (0.744). It was concluded that the MARS algorithm having the best predictive accuracy among all the algorithms might offer a good solution to beekeepers in describing interactions of significant independent variables.

En tr This study aims to determine demographic characteristics, problems related to sheep breeding and make recommendations for solution of these problems in sheep farms located in Hakkâri province. For this aim, a questionnaire was applied to 113 sheep farms in Hakkâri selected according to simple random sampling method. Data from the questionnaire shows that average age of the farmers is 49 while the average experience in animal breeding is 27 years. Average population of the farms in terms of Male Work Unit (MWU) is 6,51. Grain, barley and vegetables are produced on an average land area of 14 da. per farm. Each farm owns an average of 96 sheep, 86 lambs and 6 rams at the end of the activity season and respective values of these stocks are 416 TL, 309 TL and 958 TL. Average total stock value at the end of season is 74.336 TL.Stockbreeders are not registered with any agricultural organization and 15,9% of breeders have an average of 8.819TL of debt at the end of the season. Debtors are relatives and other real persons. Farms do not sell sheep’s milk, however, milk, butter, yogurt, cheese and ayran are produced in the farms and marketed through middlemen. High input prices, inadequacy of water for both animals and irrigation and and problems in production of feedstuff are the most important factors that have a negative impact on sheepbreeding. In order to improve sheepbreeding in the region, inputs and feedstuff to sheep farms must be subsidized, water problems in villages and pastures must be solved, illegal entry of meat and live animals must be stopped by increasing border security and sheepbreeding policies, tailored for the region, must be formulated. Demographic Characteristics, sheepbreeding, Hakkari, producer problems. Hakkâri ili koyunculuk işletmelerinin demografik özellikleri, koyunculuk faaliyeti ile ilgili problemleri ve çözüm önerilerinin belirlenmesi amacıyla yapılan çalışmada Basit Tesadüfi Örnekleme Yöntemine göre belirlenen 113 işletme ile anket yapılmıştır. Çalışma sonucunda üreticilerin yaş ortalamasının 49 ve koyunculuk tecrübesinin 27 yıl olduğu belirlenmiştir. İşletme başına nüfus ortalaması 10,21 olup bu değer Erkek İş Birimi (EİB) cinsinden ise 6,51 dir. Üreticilerin %9,7’si okuryazar olmayıp %64,7’si ilkokul mezunudur. İşletme başına ortalama 14 da’lık alanda buğday, yonca ve bostan üretimi yapılmaktadır. Faaliyet dönemi sonunda her işletmede ortalama 96 koyun, 86 kuzu ve 6 koç olup bunların her birinin değeri 416 TL, 309 TL ve 958 TL olup toplam değerleri ise 74.336 TL dir. Üreticiler herhangi bir tarımsal örgüte üye olmayıp bunların %15,9’unun ortalama 8.819 TL dönem sonu borcu bulunmaktadır. Borç kaynağı akraba ve diğer şahıslardır. İşletmelerde koyun sütü satışı bulunmamakla birlikte elde edilen süt yağ, yoğurt, peynir ve ayrana dönüştürülerek aracılar vasıtası ile pazarlanmaktadır. Girdi fiyatlarının yüksek olması, sulama sorunu ve yem bitkileri üretiminin yetersiz olması en önemli üretici sorunlardır. Bölge koyunculuk işletmelerinin sorunlarının çözümü için yem bitkileri üretiminin ve girdi desteğinin artırılması, sulama sorunun çözülmesi, sınır güvenliğinin sağlanarak kaçak et ve canlı hayvan girişinin önlenmesi ile bölgeye yönelik küçükbaş hayvancılık politikalarının oluşturulması önerilebilir.

The aim of this investigation was to determine risk factors affecting production of beekeeping farms in Igdir province of Turkey and to develop strategies in coping with these risks. Research was based on data collected through a questionnaire applied to 85 beekeeping farms registered to Igdir Beekeepers’ Union according to exact counting method. Factor analysis was applied to collected data to identify risk factors and risk management strategies. Factor analysis was conducted under principle component extraction method and VARIMAX rotation. A stepwise regression analysis was used to reveal the relationship between each of four strategy factors and eight risk factors. As risks in procuring labor occur, farmers are more likely to adopt modern agricultural techniques and risk management strategies, such as registering to a cooperative, product insurance, contract farming, and cooperating with public bodies. Unfavorable security conditions and lack of proper bookkeeping in farms are more likely to lead to adoption of careful production and investment planning. As enterprise conditions get better or external conditions get worse, protecting the investment through disease-prevention and better marketing through getting more market information becomes important. Thus, thirteen applicable strategies are determined in the study. As a result, the approach developed in this research could be suggested for beekeepers in selecting necessary strategies against possible risk factors defined here for sustainable honey production and more income.

This study was conducted to compare predictive performances of different data-mining algorithms for determining factors influencing the average daily milk yield at dairy cattle enterprises of Ardahan province, located in the Eastern Anatolia region of Turkey. The algorithms employed in the present study were Classification and Regression Tree (CART), Chi-Square Automatic Interaction Detector (CHAID), Exhaustive Chi-Square Automatic Interaction Detector (Exhaustive CHAID), Multivariate Adaptive Regression Splines (MARS), and Multilayer Perceptron (MLP). The MARS algorithm outperformed the other algorithms in the study. Visual results of CART revealed that the culture-breed cows with a lactation length greater than 237.500 days had the highest milk yield (10.64 kg/day). Culture-breed cows calving earlier than the 4th month gave the highest yield of approximately 10 kg/day in the regression tree of CHAID. The Exhaustive CHAID results were almost the same as the structure of the CHAID. The use of MARS may provide an opportunity to detect factors affecting milk production (breed, feed supply, type of milking, mastitis control, cow year group, and lactation length) and their interactions. Moreover, the MARS algorithm may be useful in making an accurate decision about increasing milk yield per cow.

Organik tarım ve gıda ürünleri insan sağlığı başta olmak üzere gıda güvenliği, hayvan refahı ve doğayı koruduğu için tercih edilmekte ve bu konu hakkında yapılan çalışmalar gün geçtikçe artmaktadır. Bu çalışmanın amacı, Iğdır İli kentsel alanda yaşayan tüketicilerin organik tarım ve gıda ürünleri tutum ve satın alma davranışlarını ortaya koymaktır. Çalışma kapsamında, 168 tüketici ile yüz yüze anket yöntemi kullanılarak veriler toplanmış ve istatiksel analizi veri madenciliği yöntemlerinden karar ağacı algoritması kullanılarak belirlenmiştir. Organik gıda ürünleri satın almayı etkileyen en belirleyici değişkenin Hanedeki Birey Sayısı olduğu görülmüştür. Hanedeki Birey Sayısı 6 ve daha altında olan (n=125, %86.2) kişiden Hanedeki Birey Sayısı 7 ve daha üstünde olanlara (n=14,%8.3) oranla daha fazla organik ürün tükettiği gözlenmiştir. Diğer önemli belirleyici faktörler ise “Aylık Hane Halkı Geliri” ve “Eğitim Durumu” olmuştur.

Amaç: Organik gıda ürün reklamından Iğdır ilindeki tüketicilerin etkilenme faktörlerini belirlemektir. Materyal ve Yöntem: Çalışmada Veri Madenciliği Karar Ağacı yönteminden Ki-kare otomatik etkileşim detektörü (CHAID) algoritması kullanılmıştır. Çalışmanın örneklemini Iğdır ilinde bulunan bireylerden örnekleme metoduyla seçilen 165 tüketici oluşturmaktadır. Çalışmanın verileri anket yöntemi ile toplanmıştır. Araştırma Bulguları: Çalışmanın sonucunda organik gıda ürün reklamından etkilenme faktörleri; Medeni durum, aylık hane halkı geliri, eğitim durumu, iş durumu ve yaş olduğu görülmüştür. Sonuç: Tüketicilerin farklı demografik özellikleri ürün reklamından etkilenme faktörlerini farklılaştırdığı görülmüştür.