Yazar "Bozkurt, Fatma" seçeneğine göre listele

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    Evaluating Climate Change Knowledge, Attitudes, and Behaviors (KAB) in Agricultural Sciences and Technologies Education
    (2024) Kızıldeniz, Tefide; Bozkurt, Fatma
    The aim of this study is to determine the levels of knowledge, attitudes, and behaviors (KAB) regarding climate change among undergraduate and postgraduate students enrolled into the Agricultural Sciences and Technologies in Niğde province. The research involved 200 students at both undergraduate and postgraduate levels, encompassing Turkish and English speakers. Research data were obtained through a personal information form designed to assess students' knowledge levels, behaviors, and attitudes toward climate change. The survey consists of four sections measuring students' demographic characteristics, behavioral traits related to climate change, attitudes toward climate change, and knowledge about the subject. Descriptive statistics, including percentages for categorical variables and mean ± standard deviation for continuous variables, were used in data analysis to transparently illustrate the distribution of background variables such as age, gender, and education. Focusing on knowledge about climate change, 66% of students indicated that they attribute climate change to human activities. It was observed that students' awareness of environmental issues, specifically recycling, is at a rate of 22.5%. In conclusion, when examining the knowledge, attitudes, and behaviors of students are studied Agricultural Sciences and Technologies regarding climate change, the study highlights the need for more effective education and awareness programs on environmental issues.
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    Examining limitations and future directions in climate change simulation models
    (EDP Sciences, 2024) Bozkurt, Fatma; Kızıldeniz, Tefide
    Climate change refers to significant alterations in long-term climate conditions. If greenhouse gas emissions continue to rise, there is a high probability of exceeding the 1.5°C and 2° thresholds of global warming throughout the 21st century. This situation poses a serious threat to the agriculture sector and can lead to a decline in agricultural production and a reduction in product quality. Additionally, intensive farming practices can decrease the resilience of agriculture. This study aims to examine the effects of climate change on the agriculture sector, explain the concept of modeling and the parameters that can be measured, provide guidance on how modeling studies on alfalfa, and similar crops can be improved by identifying their shortcomings. The modeling method is used in many different fields by creating abstract representations of real-world objects or events via a mathematical equation, writing algorithm, or simulation. Parameters used in alfalfa modeling include yield, growth, carbon, water, nitrogen balance, climate effects, and other factors. However, these models have shortcomings such as the need for more comprehensive data collection and testing, the requirement for more parameter adjustments, the inability to address various crops and different growth cycles, the lack of simulation of crown and root roles in growth, sensitivity in measuring soil and input factors, limited testing and research, inaccuracies in automatic classification, the absence of growth and yield simulation models, and the lack of deep learning techniques. Addressing these shortcomings is crucial for achieving more reliable and effective results in the agricultural sector. Strengthening models and addressing these deficiencies have the potential to lead to more robust and sustainable solutions in agriculture. © The Authors, published by EDP Sciences.