Identifying an In-Season Response Index and the Potential to Increase Wheat Yield with Nitrogen

By R. Mullen, K. Freeman, W. Raun, G. V. Johnson, Marvin L. Stone, J. Solie. 2003

182 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Plant Science

View Paper: https://www.semanticscholar.org/paper/18fc1778aabb3dbaed3751d73334f19d19559124

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In Agronomy and Crop Science

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Citations in the corpus

Potato Crop Nitrogen Status Assessment to Improve N Fertilization Management and Efficiency: Past–Present–Future (2008, methodology): “directly linked to an actual fertilizer N rate (Mullen et al. 2003).”
Adjusting Midseason Nitrogen Rate Using a Sensor-Based Optimization Algorithm to Increase Use Efficiency in Corn (2008, background): “Mullen et al. (2003) explained that after sensing, enhancing or limiting factors affecting crop yield potential may occur that lead to underestimation or overestimation of RIHARVEST by RINDVI.”
Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat (2011, background): “It allowed computation of response (to fertilizer N) indices RINDVI and RIHarvest (Mullen et al. 2003; Johnson and Raun 2003) as: RINDVI ¼ NDVI of the highest yield treatmentð Þ = NDVI of the test plotð Þ ð2Þ RIHarvest ¼ maximum yieldð Þ = yield of the test plotð Þ ð3Þ 2.3 Experiments for evaluating”
In-Season Prediction of Corn Grain Yield Potential Using Normalized Difference Vegetation Index (2006, methodology): “This response index is calculated by dividing NDVI from a nonlimiting-N strip by NDVI from a parallel strip that represents N availability across the field (Mullen et al., 2003).”
Active Sensor Reflectance Measurements of Corn Nitrogen Status and Yield Potential (2008, methodology): “Alternatively, Raun et al. (2002) and Mullen et al. (2003) demonstrated that canopy assessments using the GreenSeeker (NTech Industries, Ukiah, CA) active sensor, which generates its own source of modulated light in the red (~650 nm) and NIR (~770 nm) bands to calculate NDVI, could be used to…”
Generalized Algorithm for Variable‐Rate Nitrogen Application in Cereal Grains (2012, methodology): “With time, this was modified to address the temporal variability in N response (Mullen et al., 2003) and that led to a procedure to calculate N fertilizer application rates using optical sensor measurements of plant reflectance (Raun et al.”
Optical Sensor‐Based Algorithm for Crop Nitrogen Fertilization (2005, background): “was expanded from initial work by Johnson and Raun (2003) to predict crop response to additional N fertilizer using in-season sensor measurements (Mullen et al., 2003).”
Sensor‐Based Nitrogen Applications Out‐Performed Producer‐Chosen Rates for Corn in On‐Farm Demonstrations (2011, methodology): “Th ese advantages have led to the development of methods to translate sensor data into N rate decisions (Mullen et al., 2003; Dellinger et al., 2008; Scharf and Lory, 2009; Barker and Sawyer, 2010; Kitchen et al., 2010).”
Independence of yield potential and crop nitrogen response (2011, methodology): “Mullen et al. (2003) showed that the RI (yield in the high N plot, divided by the control or farmer practice) could be predicted using mid-season optical sensor based NDVI measurements recorded from the same plots (NDVI in the high N plot divided by the control or farmer practice).”
Threshold value for chlorophyll meter as decision tool for nitrogen management of potato (2006, methodology): “Using the sufficiency concept, N fertilizer is applied in an attempt to match the tissue N concentration of plants in a well-fertilized control strip (assumed to be 100% sufficient) without recognizing yield potential ( Mullen et al., 2003 ).”