Application of fourier transform infrared photoacoustic spectroscopy for quantification of nutrient contents and their plant availability in manure and digestate
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Application of fourier transform infrared photoacoustic spectroscopy for quantification of nutrient contents and their plant availability in manure and digestate. / Wali, Khan; Khan, Haris Ahmad; Sica, Pietro; Van Henten, Eldert J.; Meers, Erik; Brunn, Sander.
I: Heliyon, Bind 10, Nr. 7, e28487, 2024.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Application of fourier transform infrared photoacoustic spectroscopy for quantification of nutrient contents and their plant availability in manure and digestate
AU - Wali, Khan
AU - Khan, Haris Ahmad
AU - Sica, Pietro
AU - Van Henten, Eldert J.
AU - Meers, Erik
AU - Brunn, Sander
N1 - Publisher Copyright: © 2024 The Authors
PY - 2024
Y1 - 2024
N2 - In this study, we assess the feasibility of using Fourier Transform Infrared Photoacoustic Spectroscopy (FTIR-PAS) to predict macro- and micro-nutrients in a diverse set of manures and digestates. Furthermore, the prediction capabilities of FTIR-PAS were assessed using a novel error tolerance-based interval method in view of the accuracy required for application in agricultural practices. Partial Least-Squares Regression (PLSR) was used to correlate the FTIR-PAS spectra with nutrient contents. The prediction results were then assessed with conventional assessment methods (root mean square error (RMSE), coefficient of determination R2, and the ratio of prediction to deviation (RPD)). The results show the potential of FTIR-PAS to be used as a rapid analysis technique, with promising prediction results (R2 > 0.91 and RPD >2.5) for all elements except for bicarbonate-extractable P, K, and NH4+-N (0.8 < R2 < 0.9 and 2 < RPD <2.5). The results for nitrogen and phosphorus were further evaluated using the proposed error tolerance-based interval method. The probability of prediction for nitrogen within the allowed limit is calculated to be 94.6 % and for phosphorus 83.8 %. The proposed error tolerance-based interval method provides a better measure to decide if the FTIR-PAS in its current state could be used to meet the required accuracy in agriculture for the quantification of nutrient content in manure and digestate.
AB - In this study, we assess the feasibility of using Fourier Transform Infrared Photoacoustic Spectroscopy (FTIR-PAS) to predict macro- and micro-nutrients in a diverse set of manures and digestates. Furthermore, the prediction capabilities of FTIR-PAS were assessed using a novel error tolerance-based interval method in view of the accuracy required for application in agricultural practices. Partial Least-Squares Regression (PLSR) was used to correlate the FTIR-PAS spectra with nutrient contents. The prediction results were then assessed with conventional assessment methods (root mean square error (RMSE), coefficient of determination R2, and the ratio of prediction to deviation (RPD)). The results show the potential of FTIR-PAS to be used as a rapid analysis technique, with promising prediction results (R2 > 0.91 and RPD >2.5) for all elements except for bicarbonate-extractable P, K, and NH4+-N (0.8 < R2 < 0.9 and 2 < RPD <2.5). The results for nitrogen and phosphorus were further evaluated using the proposed error tolerance-based interval method. The probability of prediction for nitrogen within the allowed limit is calculated to be 94.6 % and for phosphorus 83.8 %. The proposed error tolerance-based interval method provides a better measure to decide if the FTIR-PAS in its current state could be used to meet the required accuracy in agriculture for the quantification of nutrient content in manure and digestate.
KW - Assessment criteria
KW - Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS)
KW - Manure as a bio-based fertilizer
KW - Partial least squares regression (PLSR
KW - Assessment criteria
KW - Fourier transform mid-infrared photoacoustic spectroscopy (FTIR-PAS)
KW - Manure as a bio-based fertilizer
KW - Partial least squares regression (PLSR
U2 - 10.1016/j.heliyon.2024.e28487
DO - 10.1016/j.heliyon.2024.e28487
M3 - Journal article
C2 - 38596044
AN - SCOPUS:85189549756
VL - 10
JO - Heliyon
JF - Heliyon
SN - 2405-8440
IS - 7
M1 - e28487
ER -
ID: 388954796