Discrimination of nitrogen fertilizer levels of tea plant (<scp><i>Camellia sinensis</i></scp>) based on hyperspectral imaging

Wang, Yujie; Hu, Xin; Hou, Zhiwei; Ning, Jingming; Zhang, Zhengzhu

doi:10.1002/jsfa.8996

Cited by 40 publications

(23 citation statements)

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“…With these, crop monitoring and diagnosis are improved and targeted, once again facilitating the optimum fertilizer application for desirable production outcomes (Zheng et al 2018). Examples of these techniques include hyperspectral imaging, successfully utilized in discriminating N nutritional levels in tea plants (Wang et al 2018b), as well as N, P, K, S, Cu, Zn, Fe and Mn levels in maize and soybean plants (Pandey et al 2017); unmanned aerial vehicle based multispectral imagery applied in the estimation of plant nitrogen concentration and management of N fertilizer application in rice (Zheng et al 2018) and in wheat (Zhu et al 2018a); and reflectance spectroscopy through which authors were able to characterize Fe deficiency symptoms in grapevine and prospect the possibility of detecting in field Fe deficiency conditions (Rustioni et al 2017).…”

Section: Strategies To Preserve the Nutritional Content In Future CLImentioning

confidence: 99%

Preserving the nutritional quality of crop plants under a changing climate: importance and strategies

et al. 2019

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Background Global climate is changing more rapidly than ever, threatening plant growth and productivity while exerting considerable direct and indirect effects on the quality and quantity of plant nutrients. Scope This review focuses on the global impact of climate change on the nutritional value of plant foods. It showcases the existing evidence linking the effects of climate change factors on crop nutrition and the concentration of nutrients in edible plant parts. It focuses on the effect of elevated CO 2 (eCO 2), elevated temperature (eT), salinity, waterlogging and drought stresses, and what is known regarding their direct and indirect influence on nutrient availability. Furthermore, it provides possible strategies to preserve the nutritional composition of plant foods under changing climates. Conclusions Climate change has an impact on the accumulation of minerals and protein in crop plants, with eCO 2 being the underlying factor of most of the reported changes. The effects are clearly dependent on the type, intensity and duration of the imposed stress, plant genotype and developmental stage. Strong interactions (both positive and negative) can be found between individual climatic factors and soil availability of nitrogen (N), potassium (K), iron (Fe) and phosphorous (P). The development of future interventions to ensure that the world's population has access to plentiful, safe and nutritious food may need to rely on breeding for nutrients under the context of climate change, including legumes in cropping systems, better farm management practices and utilization of microbial inoculants that enhance nutrient availability.

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Section: Strategies To Preserve the Nutritional Content In Future CLImentioning

confidence: 99%

Preserving the nutritional quality of crop plants under a changing climate: importance and strategies

et al. 2019

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“…It has been proven that HSI is an effective method for the diagnosis of growth stages, nutritional status, diseases, and insect infections of various plants, i.e. rice, tomato, spinach, cucumber, and tea plant . HSI data provide much complex structural information related to the vibration behavior of combinations of bonds, including the molecular bonds of NH groups, so that the information of nitrogenous compounds with NH groups can be reflected in the spectral data.…”

Section: Introductionmentioning

confidence: 99%

Qualitative and quantitative diagnosis of nitrogen nutrition of tea plants under field condition using hyperspectral imaging coupled with chemometrics

Wang

Jin

et al. 2019

J Sci Food Agric

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BACKGROUND: Rapid and accurate diagnosis of nitrogen (N) status in field crops is of great significance for site-specific N fertilizer management. This study aimed to evaluate the potential of hyperspectral imaging coupled with chemometrics for the qualitative and quantitative diagnosis of N status in tea plants under field conditions. RESULTS: Hyperspectral data from mature leaves of tea plants with different N application rates were preprocessed by standard normal variate (SNV). Partial least squares discriminative analysis (PLS-DA) and least squares-support vector machines (LS-SVM) were used for the classification of different N status. Furthermore, partial least squares regression (PLSR) was used for the prediction of N content. The results showed that the LS-SVM model yielded better performance with correct classification rates of 82% and 92% in prediction sets for the diagnosis of different N application rates and N status, respectively. The PLSR model for leaf N content (LNC) showed excellent performance, with correlation coefficients of 0.924, root mean square error of 0.209, and residual predictive deviation of 2.686 in the prediction set. In addition, the important wavebands of the PLSR model were interpreted based on regression coefficients. CONCLUSION: Overall, our results suggest that the hyperspectral imaging technique can be an effective and accurate tool for qualitative and quantitative diagnosis of N status in tea plants. RESULTS AND DISCUSSION Statistical analysis of LNCThe N content in the plant leaf is an indicator of soil N status. In general, the richer the N fertilizer in soil, the higher will be the total N content in plants' leaves. Here, the LNC in tea plants treated with different amount of N application was determined by the Kjeldahl method, and the results are shown in Fig. 1. It can be seen that the total N content in the leaves increased significantly with increasing J Sci Food Agric 2020; 100: 161-167

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“…Hyperspectral imaging (HSI) is a novel technology that combines traditional spectroscopic and imaging techniques in one system, to simultaneously acquire two-dimensional spatial information and one-dimensional spectral information from a sample. [15][16][17][18][19][20] As a powerful analytical tool, it has been used as a rapid and non-destructive method to estimate pigment content. Zhang et al 21 combined HSI with chemometrics to predict the Chl and Car content of spinach leaves during storage.…”

Section: Introductionmentioning

confidence: 99%

Rapid prediction of chlorophylls and carotenoids content in tea leaves under different levels of nitrogen application based on hyperspectral imaging

Wang

Jin

et al. 2018

J Sci Food Agric

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BACKGROUND Photosynthetic pigments perform critical physiological functions in tea plants. Their content is an essential indicator of photosynthetic efficiency and nutritional status. The present study aimed to predict chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (total Chl), and carotenoid (Car) content in tea leaves under different levels of nitrogen treatment using hyperspectral imaging (HSI) in combination with variable selection algorithms. RESULTS A total of 150 samples were collected and scanned using the HSI system. The mean spectrum in the region of interest (ROI) was extracted, and the pigment content was measured by traditional chemical methods. Five and seven optimal wavelengths (OWs) were selected using the regression coefficients (RCs) of partial least squares regression (PLSR) and the second‐derivative (2‐Der), respectively. The optimal 2‐Der‐PLSR models for Chl a, Chl b, total Chl, and Car performed remarkably well based on seven OWs with correlation coefficients of prediction (RP) of 0.9337, 0.9322, 0.9333 and 0.9036, root mean square errors in prediction (RMSEP) of 0.1100, 0.0511, 0.1620, and 0.0300 mg g‐1, respectively. CONCLUSION The results of this study revealed that HSI combined with variable selection method can be employed as a rapid and accurate method for predicting the content of pigments in tea plants. © 2018 Society of Chemical Industry

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Discrimination of nitrogen fertilizer levels of tea plant (Camellia sinensis) based on hyperspectral imaging

Abstract: The overall results indicated that visible and near-infrared hyperspectral imaging combined with SVM were effective in discriminating N fertilizer levels of tea plants. © 2018 Society of Chemical Industry.

Cited by 40 publications

References 40 publications

Preserving the nutritional quality of crop plants under a changing climate: importance and strategies

Preserving the nutritional quality of crop plants under a changing climate: importance and strategies

Qualitative and quantitative diagnosis of nitrogen nutrition of tea plants under field condition using hyperspectral imaging coupled with chemometrics

Rapid prediction of chlorophylls and carotenoids content in tea leaves under different levels of nitrogen application based on hyperspectral imaging

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