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PROJECT TOPIC: APPLICATION OF DATA MINING TECHNIQUES IN THE PREDICTION OF CLIMATE EFFECT ON AGRICULTURE

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CHAPTER ONE

INTRODUCTION

1.1       BACKGROUND TO THE STUDY

Prediction of climate effect plays an essential role for agriculture and other industrial sector. A vast proportion of agricultural activities are convincingly affected by climate conditions. From the short-term perspective, the temperature and precipitation are essential condition for crop growth and yield in agriculture. In agricultural practices, every crop has its own minimum, optimal, maximum temperature for growing. The crop stops growing when the temperature goes below the minimum temperature. The crop growth increased as the temperature goes up from the minimum to the maximum temperature. However the crop growth decreases as the temperature goes beyond its optimal temperature to the maximum temperature. The crop growth stops again when the temperature reaches its maximum temperature. Warmer temperature may favor some crops to grow more quickly and increase their yields, but it could also reduce growth and yields for other kinds of crops. So accurate prediction of future climate effect and weather condition could help farmers select the proper crops in order to increase growth and yield as well as economic incomes. The fast growth of crops such as grains may reduce the amount of time that seeds need to grow and mature (Semenov and Porter, 2005). The crop growth not only depends on the temperature, but also on soil water and nutrient elements such as nitrogen, phosphorus and potassium which are all connected to the climatic conditions. The soil nutrients are absorbed by crops with soil water adsorption. The proper soil moisture is strongly related to the precipitation.


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