Unverified paper record
Characterization of invisible symptoms caused by early phosphorus deficiency in cucumber plants using near-infrared hyperspectral imaging technology.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy · 28 Oct 2021 · 10.1016/j.saa.2021.120540
Abstract
In the early stage of P deficiency in cucumbers, the P deficiency symptoms in leaves are similar to the symptoms in control leaves at the early stage of aging and are difficult to identify with naked eyes or computer image processing techniques. In order to realize the quick diagnosis of P deficiency in plants at the early stage, the NIR hyperspectral images of control leaves and P-deficient leaves were collected, and the feature information of the NIR hyperspectral images was extracted by PCA and ICA respectively. Through PCA and HCA verification, the IC1 component diagram of P-deficient leaves NIR hyperspectral image could effectively characterize the features of invisible water-stained plaques caused by early P-deficient leaves. Region of interest from IC1 was selected to extract spectral information for classification, and the diagnostic rate was remarkably improved. Finally, 240 leaves were diagnosed by using the BP-ANN model with a diagnostic rate of 97.5%. In addition, the experiment verified that it was possible to diagnose whether the plant was in the state of P deficiency 21 days in advance, and timely guidance of top dressing was of great significance to increase yield.
Plant phenotyping relevance
キュウリ葉のNIRハイパースペクトル画像から、目視困難な早期リン欠乏状態を抽出・診断する画像解析手法を開発・検証しており、植物状態の取得方法が研究の中心である。
abstractthe feature information of the NIR hyperspectral images was extracted by PCA and ICA respectively
abstractthe IC1 component diagram of P-deficient leaves NIR hyperspectral image could effectively characterize the features of invisible water-stained plaques
abstractthe BP-ANN model with a diagnostic rate of 97.5%
Code and data availability
公開本文の所在を確認できませんでした。非公開または購読が必要な可能性があります。
No evidence-backed public reproduction asset is currently recorded.
This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.