Proper nitrogen (N) management is essential to optimize crop production. This study was conducted to evaluate different N fertilizer management strategies to improve N use efficiency and yield in sugarcane production in Louisiana. This research was initiated in 2013 at the Sugar Research Station in St. Gabriel, LA and was arranged in a randomized complete block design with four replications consisting of different N rates (0, 45, 90, and 135 kg N ha-1) and sources (urea-46% N, ammonium nitrate [AN]-34% N, and urea-ammonium-nitrate solution [UAN]-32% N dribbled and knifed-in) as treatments. Sensor readings were taken from different N response trials to validate the sugarcane yield potential prediction and N response index (RI) models based on normalized difference vegetation index (NDVI). Soil nitrate (NO3-) and ammonium (NH4+) at 0-15 and 15-30 cm depths were also measured at different dates after N fertilization. At the grand growth stage, plots which were knifed-in with UAN showed a more even distribution of NO3- and NH4+ compared to urea- and AN-treated plots for both depths. Among the treatments, the highest sugarcane yield was achieved from plots treated with 90 kg N ha-1 as UAN knife-in and 135 kg N ha-1 as AN. Yield potential prediction models established in 2012 and 2015 could be used to estimate sugar and cane yield using NDVI readings collected at 21 (r2=0.30 and r2=0.51) and 60 (r2=0.41 and r2=0.52) days after N fertilization (DANF), respectively. Both RI and modified RI models demonstrated a better level of precision when RI was predicted at 60 DANF (r2=0.30) for both cane and sugar yield compared to 21 DANF (r2=0.15). The outcomes of this study demonstrated the effectivity of UAN knife-in as N source and the current N recommendation, but there were indications that application of higher N rate may further maximize yield. This study also revealed some limitations of the models used for predicting the components of remote sensor-based N recommendations for Louisiana sugarcane production. Apart from strengthening the yield and sensor readings database, areas of focus for future research include the use of different vegetation indices and reflectance readings from different wavebands.
| Identifer | oai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-07072017-191947 |
| Date | 17 July 2017 |
| Creators | Forestieri, Daniel Ernesto |
| Contributors | Kimbeng, Collins, Tubana, Brenda, Fultz, Lisa |
| Publisher | LSU |
| Source Sets | Louisiana State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lsu.edu/docs/available/etd-07072017-191947/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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