Food security has been one of the most pressing issues since time immemorial. Food production and provisioning have always been demanding task, especially in times of war. An armed conflict often leads to disruption of the prevailing social order and it transforms social and economic patterns of everyday life. Moreover, wars also generally result in shortages of food, water and medical supplies, which further generates undernourishment as well as chronic hunger and famine. This article discusses the role of food in armed
conflicts with an increased focus on situations when starvation is intentionally imposed on targeted populations. As Collinson and Macbeth (2014) emphasise, such intentional restriction of food by either of the sides of a conflict is a "weapon of war". These complex
processes are going to be illustrated primarily on the example of the 1990s war in Bosnia and Herzegovina. Nevertheless, selected events and circumstances are going to be additionally compared with historical use and social significance of salt with an emphasis on warfare. The main research focus is aimed at the former UN "Safe" Area Srebrenica and theoverall scarcity of salt in the besieged enclave during the 1990s war. Not only that during the Bosnian War, salt was purchased for precious metal items but also for those on the verge of life and death, the small amount of salt sometimes became worth more than gold.
The effects of water stress and salt levels on hypericum's leaves were examined on greenhouse-grown plants of Hypericum perforatum L. by spectral reflectance. Salt levels and irrigation levels were applied 0, 1, 2.5 and 4 deci Siemens per meter (dS/m), 80%, 100% and 120% respectively. Adaptive Network based Fuzzy Inference System (ANFIS) was performed to estimate the effects of water stress and salt levels on spectral reflectance. As a result of ANFIS, it was found that there was close relationship between actual and predicted reflectance values in Hypericum perforatum L. leaves. Performance of ANFIS was examined under different numbers of epoch and rules. On the other hand, RMSE, correlation and analysis time values were found as outputs. Correlation was 99%. The estimation of optimal ANFIS model was determined in 3*3*3 number of rules with 400 epochs.