Aarhus University Seal / Aarhus Universitets segl

Evaluating different non-destructive estimation methods for winter wheat (Triticum aestivum L.) nitrogen status based on canopy spectrum

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Evaluating different non-destructive estimation methods for winter wheat (Triticum aestivum L.) nitrogen status based on canopy spectrum. / Li, Hongjun; Zhang, Yuming; Lei, Yuping; Antoniuk, Vita; Hu, Chunsheng.

In: Remote Sensing, Vol. 12, No. 1, 95, 01.2020.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

APA

CBE

MLA

Vancouver

Author

Li, Hongjun ; Zhang, Yuming ; Lei, Yuping ; Antoniuk, Vita ; Hu, Chunsheng. / Evaluating different non-destructive estimation methods for winter wheat (Triticum aestivum L.) nitrogen status based on canopy spectrum. In: Remote Sensing. 2020 ; Vol. 12, No. 1.

Bibtex

@article{080cc33655ea48a4a140cb899bc5b4fb,
title = "Evaluating different non-destructive estimation methods for winter wheat (Triticum aestivum L.) nitrogen status based on canopy spectrum",
abstract = "Compared to conventional laboratory testing methods, crop nitrogen estimation methods based on canopy spectral characteristics have advantages in terms of timeliness, cost, and practicality. A variety of rapid and non-destructive estimation methods based on the canopy spectrum have been developed on the scale of space, sky, and ground. In order to understand the differences in estimation accuracy and applicability of these methods, as well as for the convenience of users to select the suitable technology, models for estimation of nitrogen status of winter wheat were developed and compared for three methods: drone equipped with a multispectral camera, soil plant analysis development (SPAD) chlorophyll meter, and smartphone photography. Based on the correlations between observed nitrogen status in winter wheat and related vegetation indices, green normalized difference vegetation index (GNDVI) and visible atmospherically resistant index (VARI) were selected as the sensitive vegetation indices for the drone equipped with a multispectral camera and smartphone photography methods, respectively. The correlation coefficients between GNDVI, SPAD, and VARI were 0.92 ** and 0.89 **, and that between SPAD and VARI was 0.90 **, which indicated that three vegetation indices for these three estimation methods were significantly related to each other. The determination coefficients of the 0-90 cm soil nitrate nitrogen content estimation models for the drone equipped with a multispectral camera, SPAD, and smartphone photography methods were 0.63, 0.54, and 0.81, respectively. In the estimation accuracy evaluation, the method of smartphone photography had the smallest root mean square error (RMSE = 9.80 mg/kg). The accuracy of the smartphone photography method was slightly higher than the other two methods. Due to the limitations of these models, it was found that the crop nitrogen estimation methods based on canopy spectrum were not suitable for the crops under severe phosphate deficiency. In addition, in estimation of soil nitrate nitrogen content, there were saturation responses in the estimation indicators of the three methods. In order to introduce these three methods in the precise management of nitrogen fertilizer, it is necessary to further improve their estimation models.",
keywords = "Canopy spectrum, Drone, Multispectral camera, Non-destructive nitrogen status diagnosis, Smartphone photography, SPAD",
author = "Hongjun Li and Yuming Zhang and Yuping Lei and Vita Antoniuk and Chunsheng Hu",
year = "2020",
month = jan,
doi = "10.3390/RS12010095",
language = "English",
volume = "12",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "M D P I AG",
number = "1",

}

RIS

TY - JOUR

T1 - Evaluating different non-destructive estimation methods for winter wheat (Triticum aestivum L.) nitrogen status based on canopy spectrum

AU - Li, Hongjun

AU - Zhang, Yuming

AU - Lei, Yuping

AU - Antoniuk, Vita

AU - Hu, Chunsheng

PY - 2020/1

Y1 - 2020/1

N2 - Compared to conventional laboratory testing methods, crop nitrogen estimation methods based on canopy spectral characteristics have advantages in terms of timeliness, cost, and practicality. A variety of rapid and non-destructive estimation methods based on the canopy spectrum have been developed on the scale of space, sky, and ground. In order to understand the differences in estimation accuracy and applicability of these methods, as well as for the convenience of users to select the suitable technology, models for estimation of nitrogen status of winter wheat were developed and compared for three methods: drone equipped with a multispectral camera, soil plant analysis development (SPAD) chlorophyll meter, and smartphone photography. Based on the correlations between observed nitrogen status in winter wheat and related vegetation indices, green normalized difference vegetation index (GNDVI) and visible atmospherically resistant index (VARI) were selected as the sensitive vegetation indices for the drone equipped with a multispectral camera and smartphone photography methods, respectively. The correlation coefficients between GNDVI, SPAD, and VARI were 0.92 ** and 0.89 **, and that between SPAD and VARI was 0.90 **, which indicated that three vegetation indices for these three estimation methods were significantly related to each other. The determination coefficients of the 0-90 cm soil nitrate nitrogen content estimation models for the drone equipped with a multispectral camera, SPAD, and smartphone photography methods were 0.63, 0.54, and 0.81, respectively. In the estimation accuracy evaluation, the method of smartphone photography had the smallest root mean square error (RMSE = 9.80 mg/kg). The accuracy of the smartphone photography method was slightly higher than the other two methods. Due to the limitations of these models, it was found that the crop nitrogen estimation methods based on canopy spectrum were not suitable for the crops under severe phosphate deficiency. In addition, in estimation of soil nitrate nitrogen content, there were saturation responses in the estimation indicators of the three methods. In order to introduce these three methods in the precise management of nitrogen fertilizer, it is necessary to further improve their estimation models.

AB - Compared to conventional laboratory testing methods, crop nitrogen estimation methods based on canopy spectral characteristics have advantages in terms of timeliness, cost, and practicality. A variety of rapid and non-destructive estimation methods based on the canopy spectrum have been developed on the scale of space, sky, and ground. In order to understand the differences in estimation accuracy and applicability of these methods, as well as for the convenience of users to select the suitable technology, models for estimation of nitrogen status of winter wheat were developed and compared for three methods: drone equipped with a multispectral camera, soil plant analysis development (SPAD) chlorophyll meter, and smartphone photography. Based on the correlations between observed nitrogen status in winter wheat and related vegetation indices, green normalized difference vegetation index (GNDVI) and visible atmospherically resistant index (VARI) were selected as the sensitive vegetation indices for the drone equipped with a multispectral camera and smartphone photography methods, respectively. The correlation coefficients between GNDVI, SPAD, and VARI were 0.92 ** and 0.89 **, and that between SPAD and VARI was 0.90 **, which indicated that three vegetation indices for these three estimation methods were significantly related to each other. The determination coefficients of the 0-90 cm soil nitrate nitrogen content estimation models for the drone equipped with a multispectral camera, SPAD, and smartphone photography methods were 0.63, 0.54, and 0.81, respectively. In the estimation accuracy evaluation, the method of smartphone photography had the smallest root mean square error (RMSE = 9.80 mg/kg). The accuracy of the smartphone photography method was slightly higher than the other two methods. Due to the limitations of these models, it was found that the crop nitrogen estimation methods based on canopy spectrum were not suitable for the crops under severe phosphate deficiency. In addition, in estimation of soil nitrate nitrogen content, there were saturation responses in the estimation indicators of the three methods. In order to introduce these three methods in the precise management of nitrogen fertilizer, it is necessary to further improve their estimation models.

KW - Canopy spectrum

KW - Drone

KW - Multispectral camera

KW - Non-destructive nitrogen status diagnosis

KW - Smartphone photography

KW - SPAD

UR - http://www.scopus.com/inward/record.url?scp=85079660296&partnerID=8YFLogxK

U2 - 10.3390/RS12010095

DO - 10.3390/RS12010095

M3 - Journal article

AN - SCOPUS:85079660296

VL - 12

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 1

M1 - 95

ER -