Estimation of occupational risk in herbicide application

The aim of this study was to estimate the occupational risk for operators and workers in herbicide application in Sanliurfa, Turkey. In this study, 2,4-D, clodinafop-propar- gyl, dicamba, diclofop-methyl, fenoxaprop-p-ethyl, foramsulfuron, icdosulfuron-methyl-sodium, nicosulfuron, pinoxaden, tribenuron-methyl, and tritosulfuron were used for determining the occupational risk. In this study, it was obtained that the highest risk was assessed in diclofop-methyl as 1.913 Exceedence Factor (EF) value. The lowest risk was found in nicosulfuron due to its 0.230 EF value. In the result of this study, it was determined that herbicide has risk for occupational health. These risks can be minimized by using equipment such as personnel protective equipment, increasing awareness of pesticide side effects on operator and worker and advanced proper application technique and equipment, etc

Ustalenie kształtu owoców laurowiśni wschodniej (Prunus laurocerasus) przy użyciu analizy eliptycznej Fouriera

Cherry laurel (Prunus laurocerasus) is an important wild edible fruits naturally grown in black sea region in Turkey. Shape attributes of twenty-one cherry laurel accessions were determined both descriptively and based on elliptic Fourier analysis first time in the literature. In the semantic evaluation, shape of most of the accessions was near to sphere. But, the results of the descriptive data showed that the accessions had different size, shape and gravimetric attributes. The accessions such as 30023, 30024 and 30027 had the highest means as to the gravimetric and size attributes, while the means of the 20043, 30028 and 30030 accessions were found to be the lowest. The sphericity data of 30019, 30028, 30030 and 30033 accessions had the highest means ranged between 96.2 and 97.8%. The cluster test divided the accessions to five subclasses. The genotypes in the 5th cluster had the highest gravimetric and size attributes than the other accessions. While the accessions in the 1st cluster were the highest sphericity mean, they had the lowest gravimetric and size attributes.Laurowiśnia wschodnia (Prunus laurocerasus) jest ważną dziką rośliną o jadalnych owocach rosnącą w rejonie Morza Czarnego w Turcji. Określono cechy kształtu dwudziestu dwóch jej odmian, zarówno w sposób opisowy, jak i – po raz pierwszy w literaturze – w oparciu o eliptyczna analizę Fouriera. W ocenie semantycznej kształt większości był zbliżony do kuli, jednak wyniki danych opisowych wykazały różnicę w rozmiarze, kształcie i cechach grawimetrycznych. Odmiany takie jak 30023, 30024 i 30027 miały najwieksze średnie wartości odnoszące się do cech rozmiaru i cech grawimetrycznych, natomiast średnie odmian 20043, 30028 i 30030 były najmiejsze. Dane dotyczące kulistości odmian 30019, 30028, 30030 i 30033 wskazywały na największe średnie mieszczące się w przedziale między 96,2 a 97,8%. Test skupisk podzielił odmiany na pięć podklas. Genotypy w piątym skupisku miały większe wartości cech grawimetrycznych i cech dotyczących kształtu niż pozostałe. Odmiany w pierwszym skupisku miały największą średnią sferyczności, ale najmiejsze wartości cech grawimetrycznych i cech dotyczących kształtu

Design des neuronalen Netzes als Prädiktor für die physikalischen Eigenschaften von Mandeln

In this study, an adaptive neuro fuzzy interface system (ANFIS) based predictor was designed to predict the physical properties of four almond types. Measurements of the dimensions, length, width and thickness were carried out for one hundred randomly selected samples of each type. With using these three major perpendicular dimensions, some physical parameters such as projected area, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, shape index and aspect ratio were estimated. In in a various Artificial Neural Network (ANN) structures, ANFIS structure which has given the best results was selected. The parameters analytically estimated and those predicted were given in the form of figures. The root mean-squared error (RMSE) was found to be 0.0001 which is quite low. ANFIS approach has given a superior outcome in the prediction of the Physical Properties of Almond Nuts