Analysis of VNIR reflectance for prediction of macro and micro nutrient and chlorophyll contents in apple trees (Malus communis)


Basayigit L., Albayrak S., Senol H.

Asian Journal of Chemistry, vol.21, no.2, pp.1302-1308, 2009 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 2
  • Publication Date: 2009
  • Journal Name: Asian Journal of Chemistry
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1302-1308
  • Keywords: Apple tree, Near-infrared, Reflectance, Spectroradiometer
  • Ondokuz Mayıs University Affiliated: No

Abstract

Studies have demonostrated the value of spectral vegetation reflectance's based on visible near infrared spectra in agriculture. The aim of this study was to determine the relationships between nitrogen, phosphorus, potassium, magnesium, calcium, iron, copper, manganese, zinc and chlorophyll content of leaves of three apple trees and spectral reflectance. Blue, green, red and near-infrared bands were used to predict the nitrogen, phosphorus, potassium, magnesium, calcium, iron, copper, manganese, zinc and chlorophyll content of apple trees (Granny smith, Starkrimson delicious and Golden delicious). In Granny smith, it was determined that the highest r2 values were N, Mg, Fe, Zn and chlorophyll contents in degree of 10 angle (0.99, 0.68, 0.94, 0.92 and 0.98, respectively). In contrary, P, K, Ca, Cu and Mn had higher r 2 values in plant probe (0.97, 0.99, 0.71, 0.92 and 0.99, respectively). While the highest r2 values were determined from Ca, Cu, Mn and chlorophyll (0.50, 0.87, 0.99 and 0.93, respectively) in degree of 10 angle, N, P, K, Mg, Fe and Zn had highest r2 values in plant probe in Starkrimson delicious. In golden delicious, the highest r2 values was achieved from P, K, Mg, Fe and chlorophyll (0.83, 0.99, 0.99, 0.94 and 0.99, respectively) in degree of 10 angle, N, Ca, Cu, Mn and Zn had highest r 2 values in plant probe (0.89, 0.99, 0.99, 0.97 and 0.99, respectively). Present results suggest that spectral reflectance can be used for non-destructive prediction of macro and micro nutrient contents in leaves of apple trees.