127-28 Sensing Soybean Canopy Development Responses to P and K Nutritional Stress.

Poster Number 451

See more from this Division: S04 Soil Fertility & Plant Nutrition
See more from this Session: S4-S8 Graduate Student Poster Competition
Monday, October 17, 2011
Henry Gonzalez Convention Center, Hall C
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Martin Navarro, John H. Grove and Chad D. Lee, Plant and Soil Sciences, University of Kentucky, Lexington, KY
Normalized difference vegetative index (NDVI) has been correlated with physiological plant parameters and used to evaluate plant growth. Recently, active canopy reflectance sensors have been used to determine the nitrogen nutritional needs of corn, wheat and forage grasses. There is little information about use of this technique to detect soybean nutrient deficiencies. The objective of this work was to determine the ability of the NDVI sensor to detect phosphorus (P) and potassium (K) deficiencies, and grain yield reduction, in soybean. The NDVI measurements were made on a soybean field trial site known to exhibit yield responses to both P and K nutrition. Four replicates of 8 levels each of P and K nutrition were evaluated. The NDVI measurements were made with an active proximal sensor every seven days after growth stage V2, and until R2. Leaf tissue samples taken at R1 were analyzed for their P and K concentrations. Grain yield was determined by combine harvest. Phosphorus deficiency was detected with the first NDVI measurement, though visible differences were not discernable. Potassium deficiency was first detected just after V4, again before visual detection was possible. Differences in NDVI values due to P or K nutrition increased with continued crop development. There were significant R1 leaf composition and grain yield responses to improved P or K nutrition. The active proximal sensor was able to detect soybean growth differences due to P or K deficiencies in soybean before these could be seen by the human eye.
See more from this Division: S04 Soil Fertility & Plant Nutrition
See more from this Session: S4-S8 Graduate Student Poster Competition