Detecting abiotic stress in soybean with a proximal canopy sensor

J. H. Grove, M. M. Navarro, E. M. Pena-Yewtukhiw

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

On farms under a corn-soybean rotation, the value of any proximal canopy sensor increases significantly if that sensor can be used on both crop species. These sensors have been most often used to diagnose nitrogen stress in cereal and forage grasses. The relationship of soybean yield losses due to reduced plant population or nutrition stress due to phosphorus (P) or potassium (K) deficiencies with sensor normalized difference vegetation index (NDVI) values at growth stage R1 was studied. The NDVI data from a GreenSeekerTM unit were obtained for five seeding rates and two nutrition studies, and related to the observed yield losses. Those yield losses were generally well related to decreased NDVI values due either to low plant numbers in the seeding rate studies or reduced plant biomass in the nutrition studies. The results indicated that proximal active sensor technology will be useful in soybean production systems.

Original languageEnglish
Title of host publicationPrecision Agriculture 2011 - Papers Presented at the 8th European Conference on Precision Agriculture 2011, ECPA 2011
EditorsJohn V. Stafford
Pages523-532
Number of pages10
ISBN (Electronic)9788090483057
StatePublished - 2011
Event8th European Conference on Precision Agriculture 2011, ECPA 2011 - Prague, Czech Republic
Duration: Jul 11 2011Jul 14 2011

Publication series

NamePrecision Agriculture 2011 - Papers Presented at the 8th European Conference on Precision Agriculture 2011, ECPA 2011

Conference

Conference8th European Conference on Precision Agriculture 2011, ECPA 2011
Country/TerritoryCzech Republic
CityPrague
Period7/11/117/14/11

Keywords

  • K nutrition
  • NDVI
  • P nutrition
  • Reflectance sensor
  • Seeding rate
  • Soybean

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Computer Science Applications

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