TY - JOUR
T1 - Visible and near infrared spectroscopy for predicting soil nitrogen mineralization rate
T2 - Effect of incubation period and ancillary soil properties
AU - Ruma, Farida Yasmin
AU - Munnaf, Muhammad Abdul
AU - De Neve, Stefaan
AU - Mouazen, Abdul Mounem
PY - 2024/2
Y1 - 2024/2
N2 - Soil nitrogen mineralization rate (SNMR) influences crop N uptake and nitrate leaching leading to environmental pollution. This study aims at (i) examining whether visible and near-infrared reflectance spectroscopy (vis-NIRS) can predict SNMR and (ii) investigating if incubation periods and ancillary soil attributes can improve the prediction accuracy. Total 133 soil samples collected from seven fields were incubated under aerobic conditions for 60 days with seven batches of sub-samples. Mineral N was measured at regular time intervals and soil samples were scanned using a vis-NIRS sensor (Tec5 Technology, Germany) parallelly. SNMR was determined by fitting a zero-order kinetic to the net mineralized N as a function of the incubation time. Soil total nitrogen (TN), total carbon (TC) and electrical conductivity (EC) were determined once. Partial least squares regression (PLSR) models were calibrated individually for each field both for vis-NIR spectra and its combinations with TN, TC and EC. Six out of seven batches of sub-samples were used for calibrating PLSR when remaining one batch was used for model validation, and it rotated across all seven batches. Vis-NIRS alone predicted SNMR with moderate accuracy in five of seven fields (coefficient of determination, 0.53 ≤ R2 ≥ 0.66, ratio of prediction to deviation, 1.51 ≤ RPD ≥ 1.76), while models were poor in two fields (R2 = 0.23–0.26, RPD = 1.18 – 1.20). Inclusion of soil TC, TN and/or EC was expected to improve accuracy, but improvements varied across fields (R2 = 0.23–0.79, RPD = 1.18 – 2.26). Similarly, the incubation period increased vis-NIRS prediction accuracy, but frequently occurred among 2nd to 6th batches (R2 = 0.35–0.82, RPD = 1.28 – 2.44). Even incorporating secondary properties and increasing incubation duration hardly improved predictions, improvement can be compromised since it is not significant mostly and often underperformed or remained unchanged. Considering the time and effort required to incubate and analyze soil properties, this study suggests using a vis-NIRS sensor to estimate SNMR in fresh soil conditions i.e., without incubation and incorporation of secondary properties.
AB - Soil nitrogen mineralization rate (SNMR) influences crop N uptake and nitrate leaching leading to environmental pollution. This study aims at (i) examining whether visible and near-infrared reflectance spectroscopy (vis-NIRS) can predict SNMR and (ii) investigating if incubation periods and ancillary soil attributes can improve the prediction accuracy. Total 133 soil samples collected from seven fields were incubated under aerobic conditions for 60 days with seven batches of sub-samples. Mineral N was measured at regular time intervals and soil samples were scanned using a vis-NIRS sensor (Tec5 Technology, Germany) parallelly. SNMR was determined by fitting a zero-order kinetic to the net mineralized N as a function of the incubation time. Soil total nitrogen (TN), total carbon (TC) and electrical conductivity (EC) were determined once. Partial least squares regression (PLSR) models were calibrated individually for each field both for vis-NIR spectra and its combinations with TN, TC and EC. Six out of seven batches of sub-samples were used for calibrating PLSR when remaining one batch was used for model validation, and it rotated across all seven batches. Vis-NIRS alone predicted SNMR with moderate accuracy in five of seven fields (coefficient of determination, 0.53 ≤ R2 ≥ 0.66, ratio of prediction to deviation, 1.51 ≤ RPD ≥ 1.76), while models were poor in two fields (R2 = 0.23–0.26, RPD = 1.18 – 1.20). Inclusion of soil TC, TN and/or EC was expected to improve accuracy, but improvements varied across fields (R2 = 0.23–0.79, RPD = 1.18 – 2.26). Similarly, the incubation period increased vis-NIRS prediction accuracy, but frequently occurred among 2nd to 6th batches (R2 = 0.35–0.82, RPD = 1.28 – 2.44). Even incorporating secondary properties and increasing incubation duration hardly improved predictions, improvement can be compromised since it is not significant mostly and often underperformed or remained unchanged. Considering the time and effort required to incubate and analyze soil properties, this study suggests using a vis-NIRS sensor to estimate SNMR in fresh soil conditions i.e., without incubation and incorporation of secondary properties.
KW - Multivariate calibration
KW - Precision fertilization
KW - Proximal soil sensing
KW - Soil N dynamics
KW - Soil-water environment
U2 - 10.1016/j.catena.2023.107649
DO - 10.1016/j.catena.2023.107649
M3 - Article
AN - SCOPUS:85175874732
SN - 0341-8162
VL - 235
JO - Catena
JF - Catena
M1 - 107649
ER -
