Leveraging Hyperspectral Features for Biomass Estimation in Chinese Broccoli: Assessing the Physiological Impact of Iron Dosage

Iron is a crucial micronutrient for the growth and development of leafy vegetable cultivars, such as Chinese broccoli. Iron deficiency can severely affect plant biomass, yield, and nutritional quality. Large-scale, controlled-environment studies are essential to understanding the effects of iron dosing on shoot dry-weight biomass in these cultivars. Hyperspectral imagery is a promising, non-destructive tool for accurately estimating shoot dry-weight biomass by identifying key spectral features. Although hyperspectral imagery captures a wealth of information across multiple spectral bands, current methods have not fully leveraged this data for plant biomass estimation. In response, this study introduces an effective approach to selecting the optimal set of normalized difference spectral features and using them collectively to predict the dry-weight biomass of Chinese broccoli (Brassica oleracea). Moreover, this method shows potential for estimating shoot dry-weight biomass in other cultivars as well.

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Published
2025-08-03
DOI
https://doi.org/10.1109/igarss55030.2025.11242266
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Leveraging Hyperspectral Features for Biomass Estimation in Chinese Broccoli: Assessing the Physiological Impact of Iron Dosage

Lin Qin, Itamar Shenhar, Matan Gavish, Aravind Harikumar et al.
Remote Sensing in Agriculture
article

Leveraging Hyperspectral Features for Biomass Estimation in Chinese Broccoli: Assessing the Physiological Impact of Iron Dosage

Lin Qin, Itamar Shenhar, Matan Gavish, Aravind Harikumar, Kee Woei Ng, Ittai Herrmann, Menachem Moshelion, Jie He, Miguel R. Pebes-Trujillo
article en

Abstract

Iron is a crucial micronutrient for the growth and development of leafy vegetable cultivars, such as Chinese broccoli. Iron deficiency can severely affect plant biomass, yield, and nutritional quality. Large-scale, controlled-environment studies are essential to understanding the effects of iron dosing on shoot dry-weight biomass in these cultivars. Hyperspectral imagery is a promising, non-destructive tool for accurately estimating shoot dry-weight biomass by identifying key spectral features. Although hyperspectral imagery captures a wealth of information across multiple spectral bands, current methods have not fully leveraged this data for plant biomass estimation. In response, this study introduces an effective approach to selecting the optimal set of normalized difference spectral features and using them collectively to predict the dry-weight biomass of Chinese broccoli (Brassica oleracea). Moreover, this method shows potential for estimating shoot dry-weight biomass in other cultivars as well.

Nanyang Technological University (SG), Singapore-HUJ Alliance for Research and Enterprise (SG)
Openalex Percentile: Top 64%
Remote Sensing in Agriculture
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Leveraging Hyperspectral Features for Biomass Estimation in Chinese Broccoli: Assessing the Physiological Impact of Iron Dosage — Lin Qin, Itamar Shenhar, et al. · (2025) | TGRS Research Map | TGRS