Nitrogen Management for Maize using Image Processing
Abstract: Maize is the third most cultivated cereal crop in India. Nitrogen is the major nutrient required to attain maximum yield for maize. But however excess application of nitrogen may have detrimental effects on the environment and there is a possibility to leach into the underground water. Managing nitrogen to match the crop requirement is very important. Six panel Leaf Colour Chart (LCC) is a tool that provides an assessment of maizes demand for nitrogen. The use of LCC is highly dependent on the persons relative colour perception. To address this limitation of the LCC, an efficient image processing application is developed in this paper. Experiments are conducted on images of different samples of leaves and the results are presented. Testing for accuracy was based on the correlation of results based on the LCC and the image processing application. After a series of sampling, it was found out that the LCC results and the applications results shows minimal discrepancy based on the Z-test one proportion.
Keywords: Leaf Color Chart, Image Processing, Color Histogram, Z-test one proportion
How to Cite?: K.Vasantha Kumar, V. Valli Kumari, "Nitrogen Management for Maize using Image Processing", Volume 4 Issue 10, October 2015, International Journal of Science and Research (IJSR), Pages: 433-436, https://www.ijsr.net/getabstract.php?paperid=SUB158630, DOI: https://dx.doi.org/10.21275/SUB158630