Friday 28 June 2013

Market Study: Global Crop Protection (Pesticides) Market Trends Report - 2013 Edition


Crop protection products are widely used across the globe since they are very useful in safeguarding the crops against various insects, diseases and pests. Pesticides are very important as they improve the quality and yield of agricultural produce. Based on applications, crop protection chemicals market can be bifurcated into three types; herbicides, insecticides, and fungicides. Growth in the market is being driven by an increasing demand for agricultural crops resulting from global population growth, increasing standard of living and an increasing demand for biofuels. The growing demand for agricultural crops lead to increasing crop and food prices, acting as a further incentive for farmers to increase their production and protect their harvests.

A key trend observed within the market is the rapidly growing generics segment. On the development front, there has been an increase in the launch of new products by various companies. But there are certain challenges which the industry is facing as of now which includes environment and health effects. The major factors which will contribute in the growth of the industry include growth in GDP, rising world population, declining arable land per person and increasing urbanization.




The report studies the crop protection market on a global scale and its various segments and also provides detailed information regarding the key regional markets. The competition in the global crop protection market is intense with few large players viz. Syngenta AG, Bayer CropScience AG, BASF SE and Dow. In addition, global competitive landscape along with the company profiles of the leading players in the market is discussed in detail.

By combining SPSS Inc.’s data integration and analysis capabilities with our relevant findings, we have predicted the future growth of the industry. We employed various significant variables that have an impact on this industry and created regression models with SPSS Base to determine the future direction of the industry. Before deploying the regression model, the relationship between several independent or predictor variables and the dependent variable was analyzed using standard SPSS output, including charts, tables and tests.



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