Estimation models of chlorophyll contents in potato leaves based on hyperspectral vegetation indices

HE Cailian; ZHENG Shunlin; ZHOU Shaomeng; ZHANG Qin; YUAN Jichao; HU Jianjun

doi:10.7671/j.issn.1001-411X.2016.05.008

Journal of South China Agricultural University > 2016 > 37(5): 45-49. > DOI: 10.7671/j.issn.1001-411X.2016.05.008

HE Cailian, ZHENG Shunlin, ZHOU Shaomeng, ZHANG Qin, YUAN Jichao, HU Jianjun. Estimation models of chlorophyll contents in potato leaves based on hyperspectral vegetation indices[J]. Journal of South China Agricultural University, 2016, 37(5): 45-49. DOI: 10.7671/j.issn.1001-411X.2016.05.008

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Estimation models of chlorophyll contents in potato leaves based on hyperspectral vegetation indices

1.
College of Agronomy, Sichuan Agricultural University, Chengdu 611130, China
2.
Crop Research Institute of Sichuan Academy of Agricultural Sciences, Chengdu 610066, China

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Received Date: January 04, 2016
Available Online: May 17, 2023

Graphical Abstract

Abstract

Abstract

Objective
To build models for estimating chlorophyll a and chlorophyll b contents in potato, Solanum tuberosum, leaves by using hyperspectral vegetation indices, and provide a basis for scientific and nondestructive estimation of chlorophyll content in potato leaves.
Method
Leaf spectral reflectance was measured for potato plants at different growth stages under different nitrogen levels by using a portable spectrometer. The hyperspectral vegetation indices were extracted from leaf spectral reflectance. The contents of chlorophyll a and chlorophyll b in potato leaves were measured, and the relationship between hyperspectral vegetation index and chlorophyll content was analyzed.
Result
There were 12 vegetation indices with relatively good correlations with chlorophyll content. Modified normalized difference index(mND₇₀₅), modified simple ratio index(mSR₇₀₅), MERIS terrestrial chlorophyll index(MTCI) and modified chlorophyll absorption reflectance index(MCARI) had the highest correlations with chlorophyll contents among the 12 vegetation indices. Estimation models were established based on above-mentioned four indices. The power model based on MTCI offered the best estimation of chlorophyll a content, and the index model based on MCARI offered the best estimation of chlorophyll b content.
Conclusion
The power model based on MTCI and the index model based on mND₇₀₅ can be respectively used to estimate chlorophyll a and chlorophyll b contents in potato leaves with relatively high accuracy, and indirectly monitor nitrogen deficiency in potato plants.
- hyperspectral technology,
- spectral reflectance,
- Solanum tuberosum,
- vegetation index,
- chlorophyll content,
- inversion model

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References

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