Abstract
This study was carried out to analyze the spectral reflectance response of different nitrogen levels for corn crops. Four different nitrogen treatments of 0%, 80%, 100% and 120% BMP (best management practice) were studied. Principal component analysis-loading (PCA-loading) was used to identify the effective wavelengths. Partial least squares (PLS) and multiple linear regression (MLR) models were built to predict different nitrogen values. Vegetation indices (VIs) were calculated and then used to build more prediction models. Both full and selected wavelengths-based models showed similar prediction trends. The overall PLS model obtained the coefficient of determination (R2) of 0.6535 with a root mean square error (RMSE) of 0.2681 in the prediction set. The selected wavelengths for overall MLR model obtained the R2 of 0.6735 and RMSE of 0.3457 in the prediction set. The results showed that the wavelengths in visible and near infrared region (350- 1000 nm) performed better than the two either spectral regions (1001-1350/1425-1800 nm and 2000-2400 nm). For each data set, the wavelengths around 555 nm and 730 nm were identified to be the most important to predict nitrogen rates. The vogelmann red edge index 2 (VOG 2) performed the best among all VIs. It demonstrated that spectral reflectance has the potential to be used for analyzing nitrogen response in corn. Keywords: spectrum, effective wavelengths, principal component analysis-loading (PCA-loading), prediction, vegetation indices (VIs), corn DOI: 10.25165/j.ijabe.20181104.2960 Citation: Xie C Q, Yang C, Hummel Jr A, Johnson G A, Izuno F T. Spectral reflectance response to nitrogen fertilization in field grown corn. Int J Agric & Biol Eng, 2018; 11(4): 118-126.
Highlights
The United States Department of Agriculture (USDA) reports that approximately 8.1 million acres of corn were planted in Minnesota in 2015
Applying too much nitrogen leads to production inefficiencies while applying too little can result in significant yield loss
Nitrogen deficiencies in corn vary spatially and temporally in agricultural fields, leading to significant yield loss if not treated in time. Detection of these deficiencies while the crop is actively growing can be followed by a variable rate nitrogen fertilizer application to prevent yield loss and avoid adverse environmental effects
Summary
The United States Department of Agriculture (USDA) reports that approximately 8.1 million acres of corn were planted in Minnesota in 2015 These yields resulted in 1.43 billion bushels of corn grain, 9.68 million tons of corn silage, and 4.8 US billion dollars[1]. Nitrogen deficiencies in corn vary spatially and temporally in agricultural fields, leading to significant yield loss if not treated in time. Detection of these deficiencies (mid to late June) while the crop is actively growing can be followed by a variable rate nitrogen fertilizer application to prevent yield loss and avoid adverse environmental effects. Early detection of nitrogen deficiencies (detection of nitrogen rates) is challenging because of the limitations of human labor
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