Estimation of yield, nitrogen and canopy surface area using GreenSeeker sensor

<p><strong><span>Estimation of yield, nitrogen and canopy surface area using GreenSeeker sensor</span></strong></p>\n<p><strong><span>Abstract</span></strong></p>\n<p><span>The use of optical sensors in the assessment of crop health, plant fertilizer demand and yield prediction is the new method in agricultural sector. Grennseeker optical sensor is one of the new tools that has got a lot of attention of worldwide farmers and researchers recently. Detailed examination of the above mentioned variables and measuring of canopy coverage can improve production management and minimize input consumption</span><span>.</span><strong><span> </span></strong><span>Therefore, the purposes of this study are to investigate the ability of the GS sensor to assess nutritional status and surface area of canopy and predict the performance of garlic. </span><span>In this research, five N-fertilizer treatments of N0, N50, N100, N150 and N200 were applied to </span><span>garlic</span><span> in the form of r</span><span>andomized complete block design</span><span> with three replications.</span><span> </span><span>The</span><span> i</span><span>mage processing results showed that the best separation function for elimination of background from canopy can be achieved with the separation function of G-R. </span><span>The results revealed that the best correlation coefficient between NDVI and LAI was 0.69</span><span> but there is no significant relationship was found between N and NDVI.</span><span> </span><span>Finally, it can be concluded that the GS could not estimate the N level of garlic, However, it could satisfactory perform well in the estimating of tuber yield and canopy performance.</span></p>\n<p><strong><span>Keywords</span></strong><span>: </span><span>Greenness Index, Garlic, Modeling, GreenSeeker, NDVI</span></p>