| dc.contributor.author | Pathak, Rohit | |
| dc.description.abstract | Remote sensing techniques using near infrared band and experimental field data has been already applied on experimental field conditions. However, actual field conditions can be different than experimental plots. This study aimed to test different regression model for precise mid-season corn yield prediction potential using digital imagery from Rapid Eye and actual field data and also to compare effective corn yield prediction potential of red and red edge band. In the research the concept of different management zones and effect of yield prediction potential was achieved through soil series data. Exponential and quadratic model was considerably better as compared to linear model in defining the relationship between dry yield and Normalized Difference Vegetative Index (NDVI) at V11-V14 and V20-R1 growth stages. Prominent changes in yield prediction potential for certain soil series validated the need of different management zones. V11-V12 growth stage yield prediction potential was superior to VE-V2 growth stages. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Use of Digital Imagery to Evaluate the Relationship Between NDVI and Crop Production Field Data at Stutsman County, North Dakota | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2018-04-23T18:09:43Z | |
| dc.date.available | 2018-04-23T18:09:43Z | |
| dc.date.issued | 2016 | en_US |
| dc.identifier.uri | https://hdl.handle.net/10365/28003 | |
| dc.description.sponsorship | Dr. Anne Denton | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Graduate and Interdisciplinary Studies | |
| ndsu.department | Agricultural and Biosystems Engineering | en_US |
| ndsu.program | Agricultural and Biosystems Engineering | en_US |
| ndsu.advisor | Bora, Ganesh C. | |
