Abstract
Visible/near-infrared (Vis/NIR) hyperspectral imaging was employed to determine the spatial distribution of total nitrogen in pepper plant. Hyperspectral images of samples (leaves, stems, and roots of pepper plants) were acquired and their total nitrogen contents (TNCs) were measured using Dumas combustion method. Mean spectra of all samples were extracted from regions of interest (ROIs) in hyperspectral images. Random frog (RF) algorithm was implemented to select important wavelengths which carried effective information for predicting the TNCs in leaf, stem, root, and whole-plant (leaf-stem-root), respectively. Based on full spectra and the selected important wavelengths, the quantitative relationships between spectral data and the corresponding TNCs in organs (leaf, stem, and root) and whole-plant (leaf-stem-root) were separately developed using partial least-squares regression (PLSR). As a result, the PLSR model built by the important wavelengths for predicting TNCs in whole-plant (leaf-stem-root) offered a promising result of correlation coefficient (R) for prediction (RP = 0.876) and root mean square error (RMSE) for prediction (RMSEP = 0.426%). Finally, the TNC of each pixel within ROI of the sample was estimated to generate the spatial distribution map of TNC in pepper plant. The achievements of the research indicated that hyperspectral imaging is promising and presents a powerful potential to determine nitrogen contents spatial distribution in pepper plant.
Highlights
Pepper (Capsicum annuum L) is one of the popular international spices in cooking [1, 2]
Statistics of the total nitrogen contents (TNCs) measured by Dumas combustion (TNCs-DC)
partial least-squares regression (PLSR) was employed to build the quantitative relationship between the spectral reflectance and TNCs-DC of samples based on full spectra and important wavelengths
Summary
Pepper (Capsicum annuum L) is one of the popular international spices in cooking [1, 2]. World production of pepper is about 19 million tons fresh fruit from 1.5 million ha [3]. Nitrogen (N) is an essential element of vegetative growth, flowering, and fruit bearing of pepper plants [4,5,6,7,8], as well as in all metabolic processes of cellular structure and genetic coding [9]. In order to strengthen and stabilize plant growth and yield production, farmers most of the case will over-apply N fertilizer to ensure enough N for crop requirements. The excessive N fertilizer could result in a series of problems, such as lodging, delayed maturity, diseases, and weed [10, 11]. It is crucial to investigate the N status and obtain the real-time spatial distribution information of N content in crops at different growth stages, so as to improve field management efficiency and economic benefit from agricultural production, as well as contribute to sustainable agriculture [12, 13]
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