A low-cost prototype optical sensor to evaluate water, macro and micro elements of turfgrass clippings

Abstract

Abstract A low-cost prototype optical sensor system was developed to determine water and nutrient concentrations of turfgrass clippings. The indoor sensor included three photodiodes and interference filters (550, 650, and 800\u2009nm). Clipping samples of turfgrass (Lolium perenne L.) were obtained from 12 plots having four different levels of nitrogen (N). Ten different vegetation indices (VIs) were calculated and evaluated. Prediction models were developed by using PLS (Partial Least Square) regression. Normalized Difference Vegetation Index (NDVI) gave the best result for the prediction of water and N concentrations (R2\u2009=\u20090.73; SEP\u2009=\u20091.43% for water, R2\u2009=\u20090.68; SEP\u2009=\u20090.28% for N). Also, NDVI performed well (R2 > 0.60) with reasonable SEP values for P (SEP\u2009=\u20090.04%) and K contents (SEP\u2009=\u20090.23%). GRVI and DVI (G-R) yielded the best result for Ca (R2\u2009=\u20090.66; SEP\u2009=\u20090.03%) and Mg contents (R2\u2009=\u20090.47; SEP\u2009=\u20090.01%). Yet, the prototype sensor did not provide good results for Fe, Cu, Mn and Zn (R2