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

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Tarih

2021

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Science Sa

Erişim Hakkı

info:eu-repo/semantics/closedAccess

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 (R-2 = 0.73; SEP = 1.43 % for water, R-2 = 0.68; SEP = 0.28 % for N). Also, NDVI performed well (R-2 > 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 (R-2 = 0.66; SEP = 0.03 %) and Mg contents (R-2 = 0.47; SEP = 0.01 %). Yet, the prototype sensor did not provide good results for Fe, Cu, Mn and Zn (R-2 < 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. (C) 2021 Elsevier B.V. All rights reserved.

Açıklama

Anahtar Kelimeler

Design, Optical sensor, Turfgrass, Nutrient content, Water content, Prediction

Kaynak

Sensors and Actuators A-Physical

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

323

Sayı

Künye