Estimating sugarcane yield potential using an in-season determination of normalized difference vegetative index

Sensors (Basel). 2012;12(6):7529-47. doi: 10.3390/s120607529. Epub 2012 Jun 4.

Abstract

Estimating crop yield using remote sensing techniques has proven to be successful. However, sugarcane possesses unique characteristics; such as, a multi-year cropping cycle and plant height-limiting for midseason fertilizer application timing. Our study objective was to determine if sugarcane yield potential could be estimated using an in-season estimation of normalized difference vegetative index (NDVI). Sensor readings were taken using the GreenSeeker® handheld sensor from 2008 to 2011 in St. Gabriel and Jeanerette, LA, USA. In-season estimates of yield (INSEY) values were calculated by dividing NDVI by thermal variables. Optimum timing for estimating sugarcane yield was between 601-750 GDD. In-season estimated yield values improved the yield potential (YP) model compared to using NDVI. Generally, INSEY value showed a positive exponential relationship with yield (r(2) values 0.48 and 0.42 for cane tonnage and sugar yield, respectively). When models were separated based on canopy structure there was an increase the strength of the relationship for the erectophile varieties (r(2) 0.53 and 0.47 for cane tonnage and sugar yield, respectively); however, the model for planophile varieties weakened slightly. Results of this study indicate using an INSEY value for predicting sugarcane yield shows potential of being a valuable management tool for sugarcane producers in Louisiana.

Keywords: NDVI; nitrogen; precision agriculture; sugarcane.

MeSH terms

  • Agriculture
  • Biosensing Techniques / methods*
  • Fertilizers
  • Light*
  • Louisiana
  • Models, Biological
  • Plant Leaves / physiology
  • Rain
  • Saccharum / growth & development*
  • Seasons*
  • Temperature
  • Time Factors

Substances

  • Fertilizers