Investigation on the Capability of GreenSeeker Sensor in Predicting Nitrogen Status and Fractional Vegetation Cover of Spinach Crop

Document Type : Research Article- En

Authors

M. Hashemi Jozani ¹

H. Bagherpour ²

J. Hamzei ³

¹ MSc graduated student, Department of Biosystems Engineering, Bu-Ali Sina University, Hamedan, Iran

² Department of Biosystems Engineering, Bu-Ali Sina University, Hamedan, Iran

³ Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran

https://doi.org/10.22067/jam.2021.68387.1013

Abstract

Fractional vegetation cover (FVC) and normalized difference vegetation index (NDVI) are the most important indicators of greenness and have a strong correlation with green biomass. The objective of this study was to evaluate a hand-held GreesnSeeker (GS) active remote sensing instrument to estimate NDVI and FVC in the spinach plant. In this study, the color indices of the G-B index and Excess Green (ExG) were used as color vegetation indices to discriminate leaves from soil background. During 28 to 44 days after emergence (DAG), the results showed good correlations between chlorophyll yield and NDVI (R = 0.61 to 0.91), and the correlation between NDVI of GS and biomass was significant. In addition, in this growth stage, the results showed a good coefficient of correlation between NDVI of GS and FVC (R = 0.67 to 0.82). In assessing the nitrogen rate on the NDVI of GS, the results showed significant differences only at the short period of growth stage (28 to 36 DAG). The results revealed that GreenSeeker performed well for estimation both chlorophyll and biomass yield of spinach crop and it could be used as a suitable instrument for estimation of leaf area index in the middle of the plant growth period.

Keywords

Canopy

Chlorophyll

Optical sensor

Segmentation

20.1001.1.22286829.1401.12.1.8.8

Subjects

• Biological and Biosystems Engineering

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Open Access

©2021 The author(s). This article is licensed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.

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