A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect

Pan, Yuanyuan; Zhou, Rong; Zhang, Jiayi; Guo, Wanting; Yu, Minglei; Guo, Caili; Yao, Xia; Cheng, Tao; Zhu, Yan; Cao, Weixing; Tian, Yongchao

doi:10.1007/s11119-023-10032-w

Cited by 7 publications

(2 citation statements)

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“…Secondary traits related to the sources such as leaf area index (LAI) ( Bukowiecki et al., 2020 ), chlorophyll content ( Pan et al., 2023 ) and finally biomass ( Yue et al., 2019 ) have been phenotyped using a variety of techniques. Primary traits such as grain yield and quality have been assessed by estimating the mentioned secondary traits during the growth season ( Duan et al., 2017 ; Hassan et al., 2019 ; Vatter et al., 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering

Camenzind,

2024

Front. Plant Sci.

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High throughput field phenotyping techniques employing multispectral cameras allow extracting a variety of variables and features to predict yield and yield related traits, but little is known about which types of multispectral features are optimal to forecast yield potential in the early growth phase. In this study, we aim to identify multispectral features that are able to accurately predict yield and aid in variety classification at different growth stages throughout the season. Furthermore, we hypothesize that texture features (TFs) are more suitable for variety classification than for yield prediction. Throughout 2021 and 2022, a trial involving 19 and 18 European wheat varieties, respectively, was conducted. Multispectral images, encompassing visible, Red-edge, and near-infrared (NIR) bands, were captured at 19 and 22 time points from tillering to harvest using an unmanned aerial vehicle (UAV) in the first and second year of trial. Subsequently, orthomosaic images were generated, and various features were extracted, including single-band reflectances, vegetation indices (VI), and TFs derived from a gray level correlation matrix (GLCM). The performance of these features in predicting yield and classifying varieties at different growth stages was assessed using random forest models. Measurements during the flowering stage demonstrated superior performance for most features. Specifically, Red reflectance achieved a root mean square error (RMSE) of 52.4 g m-2 in the first year and 64.4 g m-2 in the second year. The NDRE VI yielded the most accurate predictions with an RMSE of 49.1 g m-2 and 60.6 g m-2, respectively. Moreover, TFs such as CONTRAST and DISSIMILARITY displayed the best performance in predicting yield, with RMSE values of 55.5 g m-2 and 66.3 g m-2 across the two years of trial. Combining data from different dates enhanced yield prediction and stabilized predictions across dates. TFs exhibited high accuracy in classifying low and high-yielding varieties. The CORRELATION feature achieved an accuracy of 88% in the first year, while the HOMOGENEITY feature reached 92% accuracy in the second year. This study confirms the hypothesis that TFs are more suitable for variety classification than for yield prediction. The results underscore the potential of TFs derived from multispectral images in early yield prediction and varietal classification, offering insights for HTP and precision agriculture alike.

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Section: Introductionmentioning

confidence: 99%

Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering

Camenzind,

2024

Front. Plant Sci.

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“…Secondary traits related to the sources such as leaf area index (LAI) (Bukowiecki et al, 2020), chlorophyll content (Pan et al, 2023) and finally biomass (Yue et al, 2019) have been phenotyped using a variety of techniques. Primary traits such as grain yield and quality have been assessed by estimating the mentioned secondary traits during the growth season Vatter et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain, Volume II

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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A novel approach for estimating fractional cover of crops by correcting angular effect using radiative transfer models and UAV multi-angular spectral data

Pan,

Wu,

et al. 2024

Computers and Electronics in Agriculture

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A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect

Cited by 7 publications

References 50 publications

Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering

Multi temporal multispectral UAV remote sensing allows for yield assessment across European wheat varieties already before flowering

High-Throughput Field Phenotyping to Advance Precision Agriculture and Enhance Genetic Gain, Volume II

A novel approach for estimating fractional cover of crops by correcting angular effect using radiative transfer models and UAV multi-angular spectral data

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