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ARS Home » Research » Publications at this Location » Publication #127912


item Diker, Kenan
item Bausch, Walter

Submitted to: Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/14/2003
Publication Date: 6/20/2003
Citation: Diker, K., Bausch, W.C. 2003. Potential use of nitrogen reflectance index (nri) to estimate plant variables and yield of corn. Biosystems Engineering.

Interpretive Summary: In season plant stress conditions can cause severs yield reduction. So, producers need a timely determination of any plant stress conditions occurring during the growing season. Once the plant stres is determined in any particular area in the field,then producers can apply the necessary management operations in that particular area to correct the problem and they can produce the optimal yield. This study was conducted to evaluatethe Nitrogen Reflectance Index (NRI) for its performance in predicting plant variables Leaaf Area Index (LAI) and dry matter as plant stress indicators, as well as yield of corn with two difference canopy structures in comparision with commonly used Normalized Difference Vegetation Index (NDVI)and Modified Soil Adjusted Vegetation Index (MSAVI). It was determined that the NRI was related well with the plant variables at all the growth stages of corn, except at early stage. Data showed also that the NRI was superior to NDVI and MSAVI for predicting the final crop yield. Mapping spatial distribution of the plant variables estimated by the optimal ld be a reliabale way to determine the stress areas and make necessary amendments to those areas for being able to achieve the optimal ieldequently, besides estimating the nitrogen status, the NRI could be used to estimate plant variables and yield of corn.

Technical Abstract: Estimating the spatial variability of plant variables such as, leaf area index (LAI), dry matter and yield during the growing season can assist in timely correction of potential stress conditions within a field. Remote sensing offers the opportunity to determine stress conditions and predict yield variation at harvest. The research described herein illustrates that the N Reflectance Index (NRI), developed to estimate plant N status, can successfully be used to estimate plant variables and the yield potential during the growing season. This would enable producers to timely react to correct any stress conditions at any specific location within the field. A study was conducted on two experimental corn sites. The first site consisted of six non-replicated fertilizer plots. Data from these plots were used to develop the relationships between reflectance data and the plant variables. The second site contained four plots with various N and water treatments on which the developed relationships were verified. Leaf area, biomass, and plant reflectance data were collected weekly from both sites during the 1996-growing season. Spatial variability of the measured and estimated yield, LAI and dry matter was mapped in ArcVIEW GIS. Regression analysis showed that the NRI was a better estimator of potential yield than the Normalized ormalized Difference Vegetation Index (NDVI) and Modified Soil Adjusted Vegetation Index (MSAVI). However, ail vegetation indices produced regression coefficients that were very close to each other. The etential and plant variables.