2023
DOI: 10.1016/j.compag.2023.107745
|View full text |Cite
|
Sign up to set email alerts
|

Hyperspectral proximal sensing of leaf chlorophyll content of spring maize based on a hybrid of physically based modelling and ensemble stacking

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
4
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 26 publications
(5 citation statements)
references
References 72 publications
1
4
0
Order By: Relevance
“…An increase in chlorophyll content indicates a higher level of leaf maturity and increased stability in leaf anatomy. Thus, within the range of 770-900 nm, the spectral reflectance increases with an increase in chlorophyll content, which aligns with the findings of previous studies [13,37,48]. Therefore, estimating the SPAD values of individual cotton leaves using hyperspectral data is feasible.…”
Section: Discussionsupporting
confidence: 88%
See 1 more Smart Citation
“…An increase in chlorophyll content indicates a higher level of leaf maturity and increased stability in leaf anatomy. Thus, within the range of 770-900 nm, the spectral reflectance increases with an increase in chlorophyll content, which aligns with the findings of previous studies [13,37,48]. Therefore, estimating the SPAD values of individual cotton leaves using hyperspectral data is feasible.…”
Section: Discussionsupporting
confidence: 88%
“…Therefore, chlorophyll content is used to measure the photosynthesis capacity, growth status, and status of environmental stress in crops [10,11]. Traditional methods for estimating chlorophyll content not only require destructive sampling but also involve cumbersome processes and long timelines, which are not conducive to large-scale applications [12,13]. The values determined by the soil plant analysis development (SPAD)-520 portable chlorophyll meter exhibit a highly significant correlation with the chlorophyll content of the crop.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, previous studies have often focused on the estimation of SPAD values during the individual growth stages of crops. Compared to single-stage models, models capable of cross-growth stage estimation have higher practicality in agricultural production [68,69]. Surprisingly, the model established for wheat during the cross-growth stage achieved higher accuracy than the best model established during the green-up stage, although slightly lower than the best model established during the jointing stage.…”
Section: The Optimal Inversion Modelsmentioning
confidence: 95%
“…Therefore, many studies utilized feature selection to improve predictive modeling performance, and they can be divided into three categories: filter, wrapper, and embedded [27,28]. For embedding algorithms, variable selection is embedded into the model training process, and is achieved by determining high-importance score contributed to the model, such as LASSO [29], variable importance in projection based on partial least squares (PLS-VIP) [30] and various regression trees [31,32]. The filter-based algorithm, such as Pearson correlation coefficient thresholding, is most commonly used due to its simplicity.…”
Section: Introductionmentioning
confidence: 99%