ArticleScientific reports2024
Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Review
- SENet-SVWF: a spectral vegetation indices and wavelet features fusion method using squeeze and excitation network for predicting the SPAD value of maize leaves.BMC plant biology · 2025Article
- Developing Transferable Fourier Transform Mid-Infrared Spectroscopy Predictive Models for Buffalo Milk: A Spatio-Temporal Application Strategy Analysis Across Dairy Farms.Foods (Basel, Switzerland) · 2025Article
- Remote sensing inversion of nitrogen content in silage maize plants based on feature selection.Frontiers in plant science · 2025Article
- Near-infrared prediction of total phosphorus in leaves content in korla fragrant pear with growth period specificity via spectral modeling.Frontiers in plant science · 2025Article
- Evaluation of the Protein Content and Variability of Olluco (TheScientificWorldJournal · 2025Article
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6 authors.
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Abstract
The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R
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