Probit analysis is a type of regression used to analyze binomial response variables. The statistical theory and techniques using probit analysis for analyzing data from dose‐quantal response experiments were developed by D.J. Finney (1971) and details are discussed in Finney (1978) and Robertson et al (2007). Data obtained from the bioassays are generally in percent response (mortality or affected) at the corresponding doses (or concentrations). The response is always binomial (e.g. death/no death) and the relationship between the response and the various concentrations is always sigmoid. Probit analysis acts as a transformation from sigmoid to linear and then runs a regression on the relationship. Once a regression is run, the researcher can use the output of the probit analysis to compare the amount of chemical required to create the same response in each of the various chemicals. There are many endpoints used to compare the differences of doses response, but LD50 are the most widely used outcomes of the modern dose‐response experiments. LD50 represent dose at which 50 % of the population responds. The critical LD50 values may be estimated from probits and log doses in several ways. The simplest is by graphical methods. Another is by using standard computation using a calculator (Finney 1971, Heong 1998). Step by step calculations are also available in Busvine (1971). The faster and more accurate way is using computer program or software. Several statistical packages like SAS, SPSS, R, Statistica etc. have probit analyses options. Aim of this study, to introduce the application of software SPSS 14.01 in calculation of LD50. The parameter estimates, probit analysis and graphs in probit transformed responses were output automatically. As a result, the calculation of LD 50 using Probit Analysis with SPSS is simple, rapid, visual and convenient.

This study aimed to investigate changes in the prices of animal products (meat, milk, eggs), and feed before and during the pandemic period on a sectoral basis in Turkey. The material for the study consisted of the prices of animal products (beef, lamb and, poultry meat, eggs, and milk) and feed collected from official institutions and producer associations in the period before (December 2019-February 2020) and during (March-May 2020) the pandemic. Considering the prices of investigated animal products, there were increases at different rates in all products during the pandemic (1.82-11.57%). While the differences between producer prices of beef and broiler meat before and during the pandemic were found to be statistically significant (P<0.05), the changes in lamb meat and egg prices were not statistically significant. On the other hand, feed prices were found to be increased by 9.71-12.57%. It was determined that the feed, which is the most critical input of producers, showed a significant increase (P<0.05) during the pandemic, especially in the poultry sector. During the pandemic, the highest reduction in livestock product/feed parity was experienced in the egg sector, with -10.28%. In conclusion, examined animal product prices increased during the pandemic period, but input prices increased more than products. In addition, it was determined that the producers had to produce with lower profitability according to the product-feed parity values, especially in the egg poultry sector during the pandemic period.

Many species of parasitic mites have been identified in honey bees (Apoidea), five of which are reproductive in the western honey bee (Apis mellifera). Among these species, Varroa destructor and Tr...