← Papers

Unverified paper record

Detection of Aphid-Infested Mustard Crop Using Ground Spectroscopy

Remote Sensing · 21 Dec 2023 · 10.3390/rs16010047

Abstract

Timely detection of pest infestation in agricultural crops plays a pivotal role in the planning and execution of pest management interventions. In this study, a ground measured electromagnetic spectrum through hyperspectral sensing (400–2500 nm) was conducted in healthy and aphid-infested mustard crops in different regions of the Bharatpur district of Rajasthan state, India. The ground measured hyperspectral reflectance and its derivatives during the mustard aphid infestation period were used to identify the sensitive spectral regions in the electromagnetic spectrum concerning Aphid Infestation Severity Grade (AISG) to discriminate Lipaphis-infested mustard crops from the healthy ones. Further Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were utilized to identify specific spectral bands to differentiate the healthy from aphid-infested crops. The spectral regions of 493–497 nm (blue), 509–515 nm (green), 690–714 nm (red), 717–721 nm (red edge), and 752–756 nm (NIR) showed high correlation with AISG for reflectance, first and second order derivatives. Further analysis of the spectra using PCA and PLSR indicated that spectral bands of 679 nm, 746 nm, and 979 nm had high sensitivity for discriminating aphid-infested crops from the healthy ones. Average reflectance and various spectral indices such as ratio spectral index (RSI), difference spectral index (DSI), and normalized difference spectral index (NDSI) of identified spectral regions and absolute reflectance of identified specific spectral bands were used for predicting AISG. Several regression models, including PCR and PLSR, were examined to predict the AISG. PLSR was found to better predict infestation grade with RMSE of 0.66 and r2 0.71. Our outcomes counseled that hyperspectral reflectance data have the ability to detect aphid-infested severity in mustard.

Plant phenotyping relevance

ハイパースペクトル計測と回帰モデルにより、植物上のアブラムシ被害重症度(AISG)を推定する手法を開発・評価しており、植物状態の取得・抽出が中心である。

abstractThe ground measured hyperspectral reflectance and its derivatives during the mustard aphid infestation period were used to identify the sensitive spectral regions in the electromagnetic spectrum concerning Aphid Infestation Severity Grade (AISG)
abstractSeveral regression models, including PCR and PLSR, were examined to predict the AISG.
abstractPLSR was found to better predict infestation grade with RMSE of 0.66 and r2 0.71.

Code and data availability

The supplied blocks describe ground hyperspectral measurements (ASD FieldSpec 4, 400–2500 nm), AISG ratings, biochemical analyses, and PCA/PLSR modeling for aphid-infested mustard, but contain no data availability statement, no public dataset deposit, no author code/scripts, and no trained model release. All URLs in 's

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.