Turkey has high agriculture produce and produced agricultural products export potential due to Turkey’s climate and geographical location. At the beginning of these products are cereals and dried fruits. Most produced agricultural products must pass a storage phase before they are sold to the domestic market and exported. The main cause of product losses at this stage is the stored product pests. If there is no control of the pests, a huge loss may happen. Various control measurs are applied to prevent the losses. In our country, mostly physical methods such as ventilation are used, but these applications are insufficient. Fumigation is also applied with various chemiclas. In addition to all these applications, there is now a trend towards permanent (residual) pesticide applications. A review about residual pesticide applications is presented in this article.

Berry fruits are among the most important fruit cultivated in Turkey. Due to their wide area of usage, the production of these fruits has been increasing. The present study was conducted to determine the projection of some berry fruits produced in Turkey according to TUIK database. Projection coefficient has been calculated as 6.8 % for strawberry, 12.07 % for raspberry and mulberry 3,77 %. The positive projection coefficient predicts that production will be increasing in the following decade.

Evapotranspiration (ET) is one of the basic components of the hydrologic cycle. Daily evapotranspiration data of plants is needed for irrigation scheduling of the plants. In this study, it was aimed to estimate daily reference evapotranspiration (ET°) by using Artificial Neural Networks Method (ANN). The data used to determine reference evapotranspiration (ET°) (daily minimum and maximum relative humidity, minimum and maximum temperatures, wind speed, sunshine intensity and sunshine duration) were obtained from the Turkish State Meteorological Service for the years 2010-2017. Daily meteorological data between 2010-2015 were used as training data and 2016-2017 as test data. Based on the climate data, 11 different ANN models were formed. The best result was obtained from the model including wind, minimum and maximum relative humidity, minimum and maximum temperature, sunshine intensity, sunshine duration and daily time index parameters with correlation coefficient (R²) of 0.998. The second best performance was obtained from the model including sunshine intensity, vapor pressure deficit, average temperature, wind and daily time index with a correlation coefficient (R²) of 0.997. In the study, correlation coefficient was determined as 0.950 for the model with the least parameters (relative sunshine duration, vapor pressure deficit and daily time index). As a result of the study, it was seen that ANN models yielded successful results in daily ET0 estimations for Kayseri province and even ANN models with less data combinations yielded reliable results for ET0 values as compared to the valuesobtained by FAO 56 Penman-Monteith method.

The aim of the current experiment was to determine the effect of maturity stage (preflowering, flowering and seeding maturity) on the potential nutritive value, gas and methane production, metabolisable energy and organic matter digestibility of Erciyes sainfoin plant. Onobrychis argaea plants were manually harvested from three plots that were established over the natural pastures of in Erciyes Mountain, Kayseri in completely randomized block design in the experimental field in 2017. Maturity stage had a significant (P=0.01) effect on chemical composition, gas and methane production, organic matter digestibility and metabolisable energy.Acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents increased, crude protein, crude oil, condens tannin and crude ash contents decreased with advancing maturity whereas. The 24 hour gas and methane production, organic matter digestibility and metabolisable energy decreased with increasing maturity. Therefore it was concluded that Onobrychis argaea plants should be harvested or grazed before flowering stages and flowering stages because of high crude protein content and metabolisable energy of these stage.

Ruminants are clearly separated from other farm animals by a series of digestive processes that occur in the rumen. The resulting digestion in the rumen, which occurs with the ingestion of nutrients and microorganism activity is obtained as yield from animals. However, as a result of these activities, some metabolites are formed and these metabolites cause loss of nutrients and environmental problems. In the current studies, it is aimed to reduce the end products such as methane, hydrogen and carbon dioxide which are formed in the rumen in order to increase the efficiency of the animals. Therefore, it is thought that microorganisms responsible for this condition need to be modified or manipulated. In recent years, feed additives, plant secondary metabolites, as well as faunation and genetic manipulation methods have been used for this purpose. In this study, some methods used to manipulate rumen microorganisms were collected.