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

ŞEKERLİ Y. E., KESKİN M., SOYSAL Y.

Sensors and Actuators, A: Physical, cilt.323, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 323
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.sna.2021.112615
  • Dergi Adı: Sensors and Actuators, A: Physical
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Biotechnology Research Abstracts, Chemical Abstracts Core, Communication Abstracts, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Design, Nutrient content, Optical sensor, Prediction, Turfgrass, Water content
  • Hatay Mustafa Kemal Üniversitesi Adresli: Evet

Özet

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 nm). 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 = 0.73; SEP = 1.43 % for water, R2 = 0.68; SEP = 0.28 % for N). Also, NDVI performed well (R2 > 0.60) with reasonable SEP values for P (SEP = 0.04 %) and K contents (SEP = 0.23 %). GRVI and DVI (G–R) yielded the best result for Ca (R2 = 0.66; SEP = 0.03 %) and Mg contents (R2 = 0.47; SEP = 0.01 %). Yet, the prototype sensor did not provide good results for Fe, Cu, Mn and Zn (R2 < 0.40). The performance of the prototype sensor was also evaluated based on classifying the sample into three groups (low, medium and high). The highest classification success ratio (SR = 80.4 %) was obtained for K while its success for the other nutrients (N, P, Ca, Mg) and water content was lower (50–70 %). A simple and low-cost optical sensor developed in this study offers promising results as it is capable of giving prior knowledge about a number of macro and micro nutrients and water content of turfgrass clippings.