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Online measurement of soil organic carbon as correlated with wheat normalised difference vegetation index in a vertisol field.

Tekin Y, Ulusoy Y, Tümsavaş Z, Mouazen AM - ScientificWorldJournal (2014)

Bottom Line: Calibration model of SOC in full cross-validation resulted in a good accuracy (R (2) = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81).The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R (2) = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R (2) = 0.60, RMSEP = 0.20%, and RPD = 1.41).Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map.

View Article: PubMed Central - PubMed

Affiliation: Vocational School of Technical Science, Uludag University, 16059 Bursa, Turkey.

ABSTRACT
This study explores the potential of visible and near infrared (vis-NIR) spectroscopy for online measurement of soil organic carbon (SOC). It also attempts to explore correlations and similarities between the spatial distribution of SOC and normalized differential vegetation index (NDVI) of a wheat crop. The online measurement was carried out in a clay vertisol field covering 10 ha of area in Karacabey, Bursa, Turkey. Kappa statistics were carried out between different SOC and NDVI data to investigate potential similarities. Calibration model of SOC in full cross-validation resulted in a good accuracy (R (2) = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81). The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R (2) = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R (2) = 0.60, RMSEP = 0.20%, and RPD = 1.41). Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map.

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Related in: MedlinePlus

The online visible and near infrared (vis-NIR) soil sensor attached to the three-point linkage of a tractor, simulating the design of Mouazen et al. [31].
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Related In: Results  -  Collection


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fig1: The online visible and near infrared (vis-NIR) soil sensor attached to the three-point linkage of a tractor, simulating the design of Mouazen et al. [31].

Mentions: The online soil sensor consists of a subsoiler that penetrates the soil to any depth between 5 and 40 cm depth, making a trench in the soil, whose bottom is smoothened due to the downward forces acting on the subsoiler. The optical unit is attached to the backside of the subsoiler chisel to acquire soil spectra from the smooth bottom of the trench in diffuse reflectance mode. The subsoiler and the optical unit are attached to a metal frame, which is mounted onto the three-point linkage of a tractor [4]. The metal frame of the sensor has been manufactured in Uludag University using the same design of Mouazen [31] (Figure 1). During field measurement the online sensor was set at 15 cm deep and driven at a moving speed of approximately 3 km h−1.


Online measurement of soil organic carbon as correlated with wheat normalised difference vegetation index in a vertisol field.

Tekin Y, Ulusoy Y, Tümsavaş Z, Mouazen AM - ScientificWorldJournal (2014)

The online visible and near infrared (vis-NIR) soil sensor attached to the three-point linkage of a tractor, simulating the design of Mouazen et al. [31].
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4109388&req=5

fig1: The online visible and near infrared (vis-NIR) soil sensor attached to the three-point linkage of a tractor, simulating the design of Mouazen et al. [31].
Mentions: The online soil sensor consists of a subsoiler that penetrates the soil to any depth between 5 and 40 cm depth, making a trench in the soil, whose bottom is smoothened due to the downward forces acting on the subsoiler. The optical unit is attached to the backside of the subsoiler chisel to acquire soil spectra from the smooth bottom of the trench in diffuse reflectance mode. The subsoiler and the optical unit are attached to a metal frame, which is mounted onto the three-point linkage of a tractor [4]. The metal frame of the sensor has been manufactured in Uludag University using the same design of Mouazen [31] (Figure 1). During field measurement the online sensor was set at 15 cm deep and driven at a moving speed of approximately 3 km h−1.

Bottom Line: Calibration model of SOC in full cross-validation resulted in a good accuracy (R (2) = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81).The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R (2) = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R (2) = 0.60, RMSEP = 0.20%, and RPD = 1.41).Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map.

View Article: PubMed Central - PubMed

Affiliation: Vocational School of Technical Science, Uludag University, 16059 Bursa, Turkey.

ABSTRACT
This study explores the potential of visible and near infrared (vis-NIR) spectroscopy for online measurement of soil organic carbon (SOC). It also attempts to explore correlations and similarities between the spatial distribution of SOC and normalized differential vegetation index (NDVI) of a wheat crop. The online measurement was carried out in a clay vertisol field covering 10 ha of area in Karacabey, Bursa, Turkey. Kappa statistics were carried out between different SOC and NDVI data to investigate potential similarities. Calibration model of SOC in full cross-validation resulted in a good accuracy (R (2) = 0.75, root mean squares error of prediction (RMSEP) = 0.17%, and ratio of prediction deviation (RPD) = 1.81). The validation of the calibration model using laboratory spectra provided comparatively better prediction accuracy (R (2) = 0.70, RMSEP = 0.15%, and RPD = 1.78), as compared to the online measured spectra (R (2) = 0.60, RMSEP = 0.20%, and RPD = 1.41). Although visual similarity was clear, low similarity indicated by a low Kappa value of 0.259 was observed between the online vis-NIR predicted full-point (based on all points measured in the field, e.g., 6486 points) map of SOC and NDVI map.

Show MeSH
Related in: MedlinePlus