A total of 56 sweet cherry samples belonging to four cultivars (Ferrovia, Canada Giant, Lapins, and Germersdorfer) grown in northern Greece were characterized and differentiated according to botanical origin. For the above purpose, the following parameters were determined: conventional quality parameters (titratable acidity (TA), pH, total soluble solids (TSS), total phenolic content (TPC), mechanical properties and sensory evaluation, sugars by High Performance Liquid Chromatography (HPLC), volatile compounds by GC/MS, and minerals by ICP-OES. Statistical treatment of the data was carried out using Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA). The results showed that the combination of volatile compounds and conventional quality parameters provided a correct classification rate of 84.1%, the combination of minerals and conventional quality parameters 86.4%, and the combination of minerals, conventional quality parameters and sugars provided the highest correct classification rate of 88.6%. When the above four cherry cultivars were combined with previously studied Kordia, Regina, Skeena and Mpakirtzeika cultivars, collected from the same regions during the same seasons, the respective values for the differentiation of all eight cultivars were: 85.5% for the combination of conventional quality parameters, volatiles and minerals; and 91.3% for the combination of conventional quality parameters, volatiles, minerals, and sugars.

This study analyses the relationship between food consumption and income, taking the consumption (per capita) of different food categories and GDP (per capita) as indicators. It presents the time series trends and compares the food consumption patterns for two countries-Serbia and Greece-an upper-middle income country outside of the EU and a high-income EU member country, respectively. The analysis showed that consumption of all food groups in Serbia (except milk) over two decades (1994-2016) is significantly affected by the changes in the GDP; while in Greece, only consumption of meat, fruits, grains, and sweetened products was positive or negative influenced by GDP. Trend analysis of the consumption of the different food categories showed huge differences between the two countries.

According to the national and European Community legislation and the quality control regulations for wine, a series of analyses are carried out by government agencies on locally produced wines in Greece. The present study examines the analyses of dry white wines produced in the regions of Ioannina in the Epirus region and the Ionian Islands, correlating them with the climatic conditions of each region. The purpose of this correlation is to evaluate the effect of the local climate on the wines’ individual characteristics, as identified by the analyses. Another crucial objective of this study is the evaluation of the effects caused by the continual changes in climate on these characteristics, as determined by the analyses. Results indicate that the prevailing climatic conditions, in conjunction with climate change, can affect all the parameters evaluated in the analyses for the wines produced in the two regions under this study.

In the past few decades, tourism has clearly become one of the most prominent economic trends for many countries. For many destinations, this trend will continue to rise, and tourism will become the most dynamic and fastest growing sector of the economy. Thus, the reliable and accurate forecasting of tourism demand is necessary in making decisions for effective and efficient planning of tourism policy. The objective of this paper is the modeling and forecasting the international tourist arrivals to four prefectures of Crete in the year 2012, based on the actual tourist arrivals data over the period 1993 – 2011, using one-step-ahead forecast. In particular, this paper presented a comparative study of time series forecasts of international travel demand for the four prefectures of Crete using a variety of statistical quantitative forecasting models along with neural networks and fuzzy models.