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Unmanned Aerial Remote Sensing and Field Studies to Assess Agronomic Performance of Corn (Zea mays L.) Under Split Nitrogen Applications
Abstract
Several studies have found higher N demand and uptake in maize (Zea Mays) at grain-filling (reproductive stage). This indicates that delaying split N application until R1 (silking) could benefit overall maize agronomic performance and reduce the N loss to the environment. Studies were conducted in 2021 and 2022 to evaluate the agronomic performance and nitrogen use efficiencies (NUEs) of different ratios of split N applied at planting + V6/R1. Total N(urea) fertilizer applied was 240 kg ha^-1. In 2021, seven split-N treatments and one full N application at planting were introduced; T1(0%), T2 (20% at planting+ 80% at V6) (conventional practice), T3 (100% at planting) (conventional practice), T4 (90% at planting +10% at R1), T5 (80% at planting + 20% at R1), T6 (70% at planting + 30% at R1), T7 (60% at planting + 40% at R1), and T8 (50% at planting + 50% at R1). In 2022, two additional reduced treatments, T9 (50% of total N at planting only), and T10 (25% of total N at planting) were introduced. 2021 was a wet year whereas 2022 was an extreme drought year for maize production. A randomized complete block design was used for the experiment. Data collection and analysis included plant height, chlorophyll (SPAD) reading, leaf area index (LAI), total above-ground biomass (AGB), grain yield, harvest index (HI), plant nitrogen uptake (PNU), nitrogen uptake efficiency (NUpE), nitrogen utilization efficiency (NUtE), and agronomic efficiency (AE). For both years, no significant difference (p > 0.05) in biomass was observed in the split N-fertilized treatments,
even with the reduced N treatments in 2022. However, in the reproductive stage, LAI, SPAD, and PNU were significantly lower (p<0.05) for T7 and T8 in 2021, and T8 and T10 in 2022. The split-N application did not affect grain yield, NUpE, NUtE, AE, and HI in 2021. In 2022, T10 had significantly higher NUpE and AE but significantly lower NUtE. Interestingly, in 2022, grain yield in the reduced N (T9) yield was insignificant with other full N treatments. Compared to 2021, all the growth parameters in 2022 were significantly lower. The result of the study shows that split N application in maize affects the growth parameter, N uptake, and yield uniquely in different weather conditions. It also showed that, under favorable weather conditions, late split N application had no significant effect on growth parameters, N uptake, and yield compared to conventional practices.
The relationship between plant N uptake and yield with vegetation indices (VIs) - Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red-edge Index (NDRE) were also studied to develop maize’s N uptake and yield prediction model. Multispectral images were acquired with unmanned aerial systems (UAS) for both study years. The NDRE showed a better correlation of plant height and SPAD with PNU for 2021 and 2022 across all growth stages. However, both VIs showed a similar correlation with LAI. NDRE produced a robust model in predicting the PNU for 2021 (R^2= 0.72), 2022 (R^2= 0.78), and for the combined data for 2021 and 2022 (R^2= 0.78). The accuracy of the prediction model for PNU was also found higher for NDRE. Yield prediction models were explored for different developmental growth stages. The best model was obtained in the reproductive growth stage (R2) for both years. Due to the significant drought effect in 2022, the R^2 for almost all the measured parameters of interest was lower compared to 2021. The study suggests that UAS-based VIs can effectively monitor plant growth and in-season N uptake in plants. However, extensive research and exploration of different VIs and data collection in various growth stages are highly suggested for developing a robust model and improving the accuracy of the model for precision agriculture. Further research is required to validate the trend observed in non-drought conditions (2021).
Subject
Unmanned Aerial SystemsGeospatial Science
Image Analysis
Crop Health Monitoring
Nitrogen Management
Citation
Bhattarai, Kisman (2023). Unmanned Aerial Remote Sensing and Field Studies to Assess Agronomic Performance of Corn (Zea mays L.) Under Split Nitrogen Applications. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /199189.