Proximal NDVI derived phenology improves in-season predictions of wheat quantity and quality

Agricultural and Forest Meteorology

Volumn 217, Issue , 2016, Pages 46-60

  Magney, Troy S ^a   Eitel, Jan U H ^a   Huggins, David R ^b   Vierling, Lee A ^a  

^a UNIVERSITY OF IDAHO   (United States)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

Author keywords

Agronomy; Grain quality; Normalized difference vegetation index; Phenology; Phenotyping; Proximal remote sensing; Spectral reflectance sensors; Yield prediction

Indexed keywords

AGRONOMY; AUTOMATION; CONCENTRATION (COMPOSITION); CROP PERFORMANCE; CROP YIELD; GROWING SEASON; HYPOTHESIS TESTING; NDVI; PHENOLOGY; PHENOTYPE; PHYTOMASS; PROTEIN; REGRESSION ANALYSIS; REMOTE SENSING; RIPENING; SOIL WATER; WHEAT;

TRITICUM AESTIVUM;

EID: 84949035147     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2015.11.009     Document Type: Article

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